The SPARSEINDEX option controls the type of index algorithm that composites use to load and access their values. The value of SPARSEINDEX at the time a named composite is defined, or an unnamed composite is created, determines the type of algorithm the composite uses by default. When you specify an index algorithm in a DEFINE COMPOSITE statement, this overrides the default specified by the SPARSEINDEX option.
Choosing an index algorithm is important only in regard to performance issues. Any recommendations are for the version of Oracle OLAP that is associated with this documentation. You can test how using different algorithms affect performance by using a CHGDFN statement to change the algorithm for a composite (for example, before loading data).
Data Type
TEXT
Syntax
SPARSEINDEX = {'BTREE'|'HASH'}
Parameters
A standard indexing method that is recommended for composites. Use BTREE unless you are an advanced user. BTREE tends to group similar values together, which results in better locality of access. BTREE is the default algorithm.
A standard indexing method that should only be used when a composite has only two or three base dimensions. HASH is generally not recommended for composites since using HASH results in a very large index table, which can be too large to fit into memory.
Examples
The MAXCHARS function counts the number of characters in the longest line of a multiline text expression. The result returned by MAXCHARS has the same dimensions as the specified expression.
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Tip: When you are using a multibyte character set, you can use the MAXBYTES function instead of the MAXCHARS function. |
Return Value
INTEGER
Syntax
MAXCHARS(text-expression)
Parameters
The text expression whose characters for each line are to be counted. MAXCHARS accepts either a TEXT or NTEXT argument. It does not perform an automatic conversion to either data type. It returns the information that is correct for the data type of the specified argument.
Examples
Example 8-23 Finding the Length of the Longest Line Using Characters
You would like to know the length of the longest line in a text variable called mytext. The following example shows the value of the variable and the result returned by MAXCHARS.
The statement
SHOW mytext
produces the following output.
This is a multiline text variable. The longest line is this one in the middle. The third line is short.
The statement
SHOW MAXCHARS(mytext)
produces the following output.
43
The ERRORTEXT option holds the text of the first error message that occurs when you execute a program or a statement. The name of the error whose message is found in ERRORTEXT is contained in the ERRORNAME option.
Data Type
TEXT
Syntax
ERRORTEXT
Examples
Example 5-35 ERRORTEXT with the SIGNAL Command
In a report program that uses a TRAP command to handle errors, you can use the SIGNAL command to send the appropriate error message to the current outfile.
DEFINE myreport PROGRAM LD Monthly Report PROGRAM TRAP ON CLEANUP NOPRINT PUSH month DECIMALS LSIZE PAGESIZE LIMIT month TO LAST 1 ... POP month DECIMALS LSIZE PAGESIZE RETURN CLEANUP: POP month DECIMALS LSIZE PAGESIZE SIGNAL ERRORNAME ERRORTEXT END
Within an OLAP DML program, the RETURN command terminates execution of a program before its last line. You can optionally specify a value that the program returns when the program is called as a function. The value should have the same data type or dimension that you specified when you defined the program.
Syntax
RETURN [expression]
Parameters
The expression to be returned to the calling program when the called program terminates.
Usage Notes
Return Value Dimensionality
The value returned by a program is a single value, without any dimensions. However, within the context of the statement that calls a user-defined function, the function expression has the dimensions of its arguments. In this case, the program is called once for every combination of the dimension values of the function expression.
Return Value Data Type
When you specify a data type when you define a program, the return value has that data type. When you specify a dimension when you define a program, the return value is a single value in that dimension. When the expression in a RETURN statement does not match the declared data type or dimension, Oracle OLAP converts it to the declared data type.
When you do not specify a data type or dimension in the definition of a program, its return value is treated as worksheet data and Oracle OLAP converts any return value to the data type that is required by the calling context which may lead to unexpected results.
Dimension Location
When the program returns values of a dimension, the dimension must be declared in the same analytic workspace as the program. The program is in the output of the LISTBY program, and OBJ(ISBY) is TRUE for the dimension.
No Return Value
When a program has been invoked as a function, but it does not provide a return value, the value that is returned to the calling program is NA.
Examples
Example 10-106 Terminating a Program Early
In this example, suppose you want a report program that produces a report only when a variable called newfigures is present in the current analytic workspace. In your program, you can use an IF statement to check whether newfigures exists and a RETURN to stop execution when it does not.
DEFINE sales.report PROGRAM
PROGRAM
IF NOT EXISTS('newfigures')
THEN DO
SHOW 'The new data is not yet available.'
RETURN
DOEND
PUSH month
TRAP ON cleanup
LIMIT month TO LAST 3
REPORT ACROSS month: newfigures
cleanup:
POP month
END
Now when you run the program without newfigures in the analytic workspace, the program produces a message and the RETURN statement terminates execution of the program at that point.
Example 10-107 Returning a Value
The following program derives next year's budget figures from the actual variable. It is a temporary calculation. You could call this program in a REPORT statement, thus calculating and reporting the budget figures without storing them in an analytic workspace.
DEFINE budget.growth PROGRAM DECIMAL PROGRAM VARIABLE growth DECIMAL VARIABLE factor DECIMAL growth = TOTAL(actual(year 'Yr97') year) - TOTAL(actual(year - 'Yr96') year) factor = ( 1 + growth ) / TOTAL(actual(year 'Yr96') year) RETURN TOTAL(actual(year 'Yr97') year) * (factor * factor/2) END
OLAP_TABLE is a SQL function that extracts multidimensional data from an analytic workspace and presents it in the two-dimensional format of a relational table.
The OLAP_TABLE function returns multidimensional data in an analytic workspace as a logical table.
The order in which OLAP_TABLE processes information specified in its input parameters is described in "Order of Processing in OLAP_TABLE".
OLAP_TABLE is the fundamental mechanism in the database for querying an analytic workspace. Within a SQL statement, you can specify an OLAP_TABLE function call wherever you would provide the name of a table or view.
OLAP_TABLE returns a table of objects that can be joined to relational tables and views, and to other tables of objects populated by OLAP_TABLE.
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Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
A table type whose rows are objects (ADTs) that identify the selected workspace data. See "Creating Relational Views Using OLAP_TABLE".
Syntax
OLAP_TABLE(
analytic_workspace IN VARCHAR2,
table_object IN VARCHAR2,
olap_command IN VARCHAR2,
limit_map1 IN VARCHAR2,
limit_map2 IN VARCHAR2,
.
.
.
limit_map8 IN VARCHAR2)
RETURN TYPE;
Parameters
Provides the name of the analytic workspace where the source data is stored. It also specifies how long the analytic workspace is attached to your OLAP session, which opens on your first call to OLAP_TABLE.
This parameter is always required by OLAP_TABLE.
The syntax of this parameter is:
'[owner.]aw_name DURATION QUERY | SESSION'
For example:
'olapuser.xademo DURATION SESSION'
owner
Specify owner whenever you are creating views to be accessed by other users. Otherwise, you can omit the owner if you own the analytic workspace. It is required only when you are logged in under a different user name than the owner.
QUERY
Attaches an analytic workspace for the duration of a single query. Use QUERY only when you must see updates to the analytic workspace made in other sessions.
SESSION
Attaches an analytic workspace and keeps it attached after the query. It provides better performance than QUERY because it keeps the OLAP session open. This performance difference is significant when the function is called without either a table_object parameter or AS clauses in the limit map; in this case, the OLAP_TABLE function must determine the appropriate table definition. See "Using OLAP_TABLE With Automatic ADTs".
The name of a predefined table of objects, as described in "Using OLAP_TABLE With Predefined ADTs".
This parameter is optional. Omit this parameter when you are using automatic ADTs.
The syntax of this parameter is:
'table_name'
For example:
'product_dim_tbl'
When you specify the table_name parameter, the column data types for the returned data are predefined. In this case you cannot use AS clauses in the limit map.
When you omit the table_name parameter, the column data types for the returned data are generated at run time. You can either provide the target data types with AS clauses in the limit map, or you can use the default data types described in Table A-1, "Default Data Type Conversions". See "Using OLAP_TABLE With Automatic ADTs".
A single OLAP DML command. To execute multiple commands, create a program in your analytic workspace and call the program in this parameter. The power and flexibility of this parameter comes from its ability to process virtually any data manipulation commands available in the OLAP DML.
The order in which OLAP_TABLE processes the olap_command parameter is specified in "Order of Processing in OLAP_TABLE".
The syntax of this parameter is:
'olap_command'
There are two distinct ways of using the olap_command parameter:
To make changes in the workspace session immediately before the data is fetched (after all the limits have been applied) as described in "Using FETCH in the olap_command Parameter".
To specify the source data directly instead of using a limit map as described in "Using olap_command with a Limit Map".
Maps workspace objects to relational columns and identifies the role of each one. See "Creating Relational Views Using OLAP_TABLE".
The limit map can also specify special instructions to be executed by OLAP_TABLE. For example: It can cause an OLAP DML command to execute before or after the limit map is processed; it can specify a ROW2CELL column for the OLAP_CONDITION and OLAP_EXPRESSION functions. (See "OLAP_CONDITION" and "OLAP_EXPRESSION".)
The order in which OLAP_TABLE processes information in the limit map is specified in "Order of Processing in OLAP_TABLE".
The limit map parameter is generally a required parameter. It can only be omitted when you specify a FETCH command in the olap_command parameter. See the discussion of olap_command.
You can supply the entire text of the limit map as a parameter to OLAP_TABLE, or you can store all or part of the limit map in a text variable in the analytic workspace and reference it using ampersand substitution. For example, the following OLAP_TABLE query uses a limit map stored in a variable called limitmapvar in the MYAW analytic workspace of the MYAW_AW schema.
SELECT * FROM TABLE(OLAP_TABLE(
'myaw_aw.myaw DURATION SESSION',
'',
'',
'&(myaw_aw.myaw!limitmapvar)');
If you supply the limit map as text within the call to OLAP_TABLE, then it has a maximum length of 4,000 characters, which is imposed by PL/SQL. If you store the limit map in the analytic workspace, then the limit map has no maximum length.
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Note: Several analytic workspace objects must be predefined within the workspace to support the mapping of dimension hierarchies in the limit map. For more information, see "Required OLAP DML Objects". |
The syntax of the limit map has numerous clauses, primarily for defining dimension hierarchies. Pay close attention to the presence or absence of commas, since syntax errors prevents your limit map from being parsed.
'[MEASURE column [AS datatype] FROM {measure | AW_EXPR expression}] . . DIMENSION [column [AS datatype] FROM] dimension [WITH [HIERARCHY [column [AS datatype] FROM] parent_relation [(hierarchy_dimension ''hierarchy_name'')] [INHIERARCHY inhierarchy_obj] [GID column [AS datatype] FROM gid_relation] [PARENTGID column [AS datatype] FROM gid_relation] [FAMILYREL column1 [AS datatype], column2 [AS datatype], ... columnn [AS datatype] FROM {expression1, expression2, ... expressionn | family_relation USING level_dimension } [LABEL label_variable]] [HATTRIBUTE column [AS datatype] FROM hier_attribute_variable] . . ] [ATTRIBUTE column [AS datatype] FROM attribute_variable] . . ] [ROW2CELL column] [LOOP loop-clause] [PREDMLCMD olap_command] [POSTDMLCMD olap_command]'
Where:
column is the name of a column in the target table.
datatype is the data type of column.
measure is a variable, formula, or relation in the analytic workspace.
expression is a formula or qualified data reference for objects in the analytic workspace.
dimension is a dimension in the analytic workspace.
parent_relation is a self-relation in the analytic workspace that defines the hierarchies for dimension. See "Parentrel Relation" for more information.
hierarchy_dimension is a dimension in the analytic workspace that contains the names of the hierarchies for dimension. See "Hierlist Dimension" for more information
hierarchy_name is a member of hierarchy_dimension.
inhierarchy_obj is a variable or valueset in the analytic workspace that identifies which dimension members are in each level of the hierarchy. See "Inhier Valueset or Variable" for more information
gid_relation is a relation in the analytic workspace that contains the grouping ID of each dimension member in the hierarchy. See "Gidrel Relation" for more information
family_relation is a self-relation that provides the full parentage of each dimension member in the hierarchy. See "Familyrel Relation" for more information
level_dimension is a dimension in the analytic workspace that contains the names of the levels for the hierarchy. See "Levellist Dimension" for more information
label_variable is a variable in the analytic workspace that contains descriptive text values for dimension.
hier_attribute_variable is a variable in the analytic workspace that contains attribute values for hierarchy_name.
attribute_variable is a variable in the analytic workspace that contains attribute values for dimension.
loop_clause specifies how Oracle OLAP determines how it loops through data values and what rows to create in the relational table. When you exclude a LOOP clause, Oracle OLAP loops through all of the data values that are identified by the dimensions in the DIMENSION clauses in the limit map
For the complete syntax of the LOOP clause see "LOOP Clause".
olap_command is an OLAP DML command.
Detailed syntax for each of the clauses of the limit-map parameter follows.
MEASURE Clause
The MEASURE clause maps a variable, formula, or relation in the analytic workspace to a column in the target table. You can list any number of MEASURE clauses. This clause is optional when, for example, you want to create a dimension view.
The AS subclause specifies the data type of the target column. You can specify an AS subclause when the table of objects has not been predefined. See "Using OLAP_TABLE With Automatic ADTs".
In the FROM subclause, you can either specify the name of a variable, formula, or relation or an OLAP expression that evaluates to one of these objects. For example:
AW_EXPR analytic_cube_sales - analytic_cube_cost
or
AW_EXPR LOGDIF(analytic_cube_sales, 1, time, LEVELREL time.lvlrel)
DIMENSION Clause
The DIMENSION clause identifies a dimension or conjoint in the analytic workspace that dimensions one or more measures or attributes, or provides the dimension members for one or more hierarchies in the limit map.
The column subclause is optional when you do not want the dimension members themselves to be represented in the table. In this case, include a dimension attribute that can be used for data selection.
For a description of the AS subclause, see "MEASURE Clause".
Every limit map should have at least one DIMENSION clause. If the limit map contains MEASURE clauses, then it should also contain a single DIMENSION clause for each dimension of the measures, unless a dimension is being limited to a single value. If the measures are dimensioned by a composite, then you must identify each dimension in the composite with a DIMENSION clause. For the best performance when fetching a large result set, identify the composite in a LOOP clause. See "LOOP Clause".
A dimension can be named in only one DIMENSION clause. Subclauses of the DIMENSION clause identify the dimension hierarchies and attributes.
WITH Subclause for Dimension Hierarchies and Attributes
The WITH subclause introduces a HIERARCHY or ATTRIBUTE subclause. If you do not specify hierarchies or attributes, then omit the WITH keyword. If you specify both hierarchies and attributes, then precede them with a single WITH keyword.
WITH HIERARCHY Subclause
The HIERARCHY subclause identifies the parent self-relation in the analytic workspace that defines the hierarchies for the dimension. See "Parentrel Relation" for more information,
The HIERARCHY subclause is optional when the dimension does not have a hierarchy, or when the status of the dimension has been limited to a single level of the hierarchy. When a dimension has multiple hierarchies, specify a HIERARCHY subclause for each one and specify a hierarchy_dimension phrase. The hierarchy_dimension identifies a dimension in the analytic workspace which holds the names of the hierarchies for this dimension. See "Hierlist Dimension" for more information.
hierarchy_name is a member of hierarchy_dimension. The hierarchy dimension is limited to hierarchy_name for all workspace objects that are referenced in subsequent subclauses for this hierarchy (that is, INHIERARCHY, GID, PARENTGID, FAMILYREL, and HATTRIBUTE).
For a description of the column subclause, see "DIMENSION Clause ".
The keywords in the HIERARCHY subclause are described as follows:
The INHIERARCHY subclause identifies a boolean variable or a valueset in the analytic workspace that identifies the dimension members in each level of the hierarchy. See "Inhier Valueset or Variable" for more information.
It is good practice to include an INHIERARCHY subclause, because OLAP_TABLE saves the status of all dimensions with INHIERARCHY subclauses during the processing of the limit map. It is required when there are members of the dimension that are omitted from the hierarchy.
The GID subclause maps an integer variable in the analytic workspace, which contains the grouping ID for each dimension member, to a column in the target table. The grouping ID variable is populated by the OLAP DML GROUPINGID command command. See "Gidrel Relation" for more information.
The GID subclause is required for Java applications that use the OLAP API.
For a description of the AS subclause, see "MEASURE Clause".
The PARENTGID subclause calculates the grouping IDs for the parent relation using the GID variable in the analytic workspace. The parent GIDs are not stored in an analytic workspace object. Instead, you specify the same GID variable for the PARENTGID clause that you used in the GID clause. The PARENTGID clause is recommended for Java applications that use the OLAP API.
For a description of the AS subclause, see "MEASURE Clause".
The FAMILYREL subclause is used primarily to map a family relation in the analytic workspace to multiple columns in the target table. See "Familyrel Relation" for more information. You can use multiple FAMILYREL clauses for each hierarchy.
List the columns in the order of level_dimension which is a dimension in the analytic workspace that holds the names of all the levels for the dimension. See "Levellist Dimension" for more information.
If you do not want a particular level included, then specify null for the target column. For a description of the AS subclause, see "MEASURE Clause".
The LABEL keyword identifies a text attribute that provides more meaningful names for the dimension members.
The tabular data resulting from a FAMILYREL clause is in rollup form, in which each level of the hierarchy is represented in a separate column, and the full parentage of each dimension member is identified within the row. See Example A-7, "Script for a Rollup View of Products Using OLAP_TABLE".
The HATTRIBUTE subclause maps a hierarchy-specific attribute variable, dimensioned by hierarchy_dimension in the analytic workspace, to a column in the target table.
WITH ATTRIBUTE Subclause
The ATTRIBUTE subclause maps an attribute variable in the analytic workspace to a column in the target table.
If attribute_variable has multiple dimensions, then values are mapped for all members of dimension, but only for the first member in the current status of additional dimensions. For example, if your attributes have a language dimension, then you must set the status of that dimension to a particular language. You can set the status of dimensions in a PREDMLCMD clause.
ROW2CELL Clause
The ROW2CELL clause creates a RAW column, between 16 and 32 characters wide, in the target table and populates it with information that is used by the OLAP expression functions. The OLAP_CONDITION function also uses the ROW2CELL column. Specify a ROW2CELL column when creating a view to be used by these functions. See "Using OLAP DML Expressions in SELECT FROM OLAP_TABLE Statements" and "Adding Calculated Columns to the Relational View".
LOOP Clause
The LOOP clause specifies how Oracle OLAP loops through the data when retrieving values. When you omit a LOOP clause in a limit map, Oracle OLAP loops uses the DIMENSION clauses in that limit map to determine what values that Oracle OLAP loops over. Oracle OLAP loops over only those tuples that identify measure cells that do not contain NA or null.When you include a LOOP clause, you specify one of the following types of subclauses: the optimized_subclause or the union_subclause.
The optimized_subclause specifies that Oracle OLAP automatically create the union_subclause by which it loops through the data. The union_subclause created never includes any DENSE phrases. Consequently, when you specify the optimized_subclause, Oracle OLAP loops over only those tuples that identify measure cells that do not contain NA or null. The optimized_subclause has the following syntax.
OPTIMIZED [MEASURES]
where the optional MEASURES keyword specifies that after identifying the tuples to loop through, Oracle OLAP remove any values that are dimension values that are not dimensions of the objects identified in the MEASURES clauses of the limit map.
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Tip: You can use the$LOOP_AGGMAP, $LOOP_DENSE, and $LOOP_VAR properties, to specify more information as to how OLAP_TABLE loops over a formula. |
The union_subclause specifies exactly how Oracle OLAP determines which base dimensions it uses to identify what data values to loop through. For a successful union to occur, the objects that are referenced in this subclause must have the same base dimensions. The union_subclause has the syntax show below.
[ignore_phrase] [dense_phrase] UNION ({aggmap_phrase | list_phrase }...)]
where:
aggmap_phrase has the following syntax which specifies how Oracle OLAP loops through the values of an aggregated variable.
AGGMAP (ignore_phrase] [dense_phrase] aggmap {variable | dimension_list})
list_phrase has the following syntax which specifies how Oracle OLAP loops through the values of a composite, partition template, or dimension. It has the following syntax.
LIST ([ignore_phrase] [dense_phrase] dimension_list)
ignore_phrase — Specifies the dimension values that you do not want Oracle OLAP to loop over. It has the following syntax.
IGNORE (ignore_list )
For ignore_list you can specify one or more of the following separated by commas.
dimension_name valueset_name COMPLEMENT (valueset_name)
Within a single ignore_list you cannot specify a dimension in multiple ways. In other words, you cannot specify both a dimension and a valueset for that same dimension; you cannot specify two valuesets for the same dimension.
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Note: The result of specifying IGNOR valueset-name is similar to specifying LIMIT REMOVE valueset-name (see LIMIT command). |
dense_phrase — Specifies values that Oracle OLAP loops over even when the measure cells identified by those values contain NA or null. In other words, specifying a dimension in a DENSE phrase is similar to requesting a relational outer join. Typically, you include dimension values in a DENSE phrase to perform time-series processing (for example, to lag over time). A DENSE phrase has the following syntax.
DENSE (dense_list )
For dense_list you can specify one or more of the following separated by commas.
dimension_name valueset_name COMPLEMENT (valueset_name)
Within a single dense_list you cannot specify a dimension in multiple ways. In other words, you cannot specify both a dimension and a valueset for that same dimension; you cannot specify two valuesets for the same dimension.
However, you can have one valueset for a dimension in the outer DENSE phrase and another valueset for the same dimension in an inner DENSE phrase. If a dimension or a valueset of a dimension is specified in both an inner and outer DENSE phrase, Oracle OLAP loops densely over the union of the dense regions. If the dimension, itself, appears in either place, Oracle OLAP loops densely over the whole dimension.
aggmap — The name of an aggmap object. When you specify only the name of an aggmap object, Oracle OLAP uses the values in the PRECOMPUTE phrases of the aggmap to identify the values to loop
variable — The name of the variable aggregated by aggmap_name.
dimension_list — A list of one or more composites, partition templates, or dimensions.
PREDMLCMD Clause
The PREDMLCMD clause specifies an OLAP DML command that is executed before the data is fetched from the analytic workspace into the target table. It can be used, for example, to execute an OLAP model or f orecast whose results will be fetched into the table. The results of the command are in effect during execution of the limit map, and continue into your session after execution of OLAP_TABLE is complete. See "Order of Processing in OLAP_TABLE".
POSTDMLCMD Clause
The POSTDMLCMD clauses specifies an OLAP DML command that is executed after the data is fetched from the analytic workspace into the target table. It can be used, for example, to delete objects or data that were created by commands in the PREDMLCMD clause, or to restore the dimension status that was changed in a PREDMLCMD clause. See "Order of Processing in OLAP_TABLE" .
Usage Notes
Limit Maps
OLAP_TABLE uses a limit map to map dimensions and measures defined in an analytic workspace to columns in a logical table. The limit map combines with the WHERE clause of a SQL SELECT statement to generate a series of OLAP DML LIMIT commands that are executed in the analytic workspace.
OLAP_TABLE can use a limit map with a predefined logical table, or it can use the information in a limit map to dynamically generate a logical table at run time.
Logical Tables
The logical table populated by OLAP_TABLE is actually a table type whose rows are user-defined object types, also known as Abstract Data Types or ADTs.
A user-defined object type is composed of attributes, which are equivalent to the columns of a table. The basic syntax for defining a row is as follows.
CREATE TYPE object_name AS OBJECT ( attribute1 datatype, attribute2 datatype, attributen datatype);
A table type is a collection of object types; this collection is equivalent to the rows of a table. The basic syntax for creating a table type is as follows.
CREATE TYPE table_name AS TABLE OF object_name;
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See Also:
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Using OLAP_TABLE With Predefined ADTs
You can predefine the table of objects or generate it dynamically. When you create the table type in advance, it is available in the database for use by any invocation of OLAP_TABLE. Queries that use predefined objects typically perform better than queries that dynamically generate the objects. See "Using OLAP_TABLE With Predefined ADTs".
Using OLAP_TABLE With Automatic ADTs
If you do not supply the name of a table type as an argument, OLAP_TABLE uses information in the limit map to generate the logical table automatically. In this case, the table type is only available at run time within the context of the calling SQL SELECT statement. See "Using OLAP_TABLE With Automatic ADTs".
When automatically generating ADTs, OLAP_TABLE uses default relational data types for the target columns unless you override them with AS clauses in the limit map. The default data type conversions used by OLAP_TABLE are described in Table A-1.
Table A-1 Default Data Type Conversions
| Analytic Workspace Data Type | SQL Data Type |
|---|---|
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Other |
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Using olap_command with a Limit Map
You may want your application to modify the analytic workspace on the fly during the execution of OLAP_TABLE.
A common use of the olap_command parameter is to limit one or more dimensions. If you limit any of the dimensions that have INHIERARCHY clauses in the limit map, then the status of those dimensions is changed only during execution of this call to OLAP_TABLE; the limits do not affect the rest of your OLAP session. However, other commands (for example, commands that limit dimensions not referenced with INHIERARCHY clauses) can affect your session.
If you want a limit on a dimension in the limit map to stay in effect for the rest of your session, and not just during the command, specify it in the PREDMLCMD clause of the limit map or specify an OLAP_CONDITION function in the SQL SELECT statement.
The following is an example of a LIMIT command in the olap_command parameter.
'LIMIT product TO product_member_levelrel ''L2'''
Using FETCH in the olap_command Parameter
If you specify an OLAP DML FETCH command in the olap_command parameter, OLAP_TABLE uses it, instead of the instructions in the limit map, to fetch the source data for the table object. Because of this usage, the olap_command parameter is sometimes referred to as the data map. In general, do not specify a limit map if you specify a FETCH command.
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Note: Normally, use theFETCH command with OLAP_TABLE only if you are upgrading an Express application that used the FETCH command for SNAPI. If you are upgrading, note that the full syntax is the same in Oracle as in Express 6.3. You can use the same FETCH commands in OLAP_TABLE that you used previously in SNAPI. For the syntax of the FETCH command, see "FETCH". |
FETCH specifies explicitly how analytic workspace data is mapped to a table object. The basic syntax is:
FETCH expression...
Enter one expression for each target column, listing the expressions in the same order they appear in the row definition. Separate expressions with spaces or commas.You must enter the entire statement on one line, without line breaks or continuation marks of any type.
Order of Processing in OLAP_TABLE
The following list identifies the order in which the OLAP_TABLE function processes instructions in the limit map that can change the status of dimensions in the analytic workspace.
Execute any OLAP DML command specified in the PREDMLCMD parameter of the limit map.
Save the current status of all dimensions in the limit map so that it can be restored later (PUSH status).
Keep in status only those dimension members specified by INHIERARCHY subclauses in the limit map (LIMIT KEEP).
Within the status set during step 3, keep only those dimension members that satisfy the WHERE clause of the SQL SELECT statement containing the OLAP_TABLE function (LIMIT KEEP).
Execute any OLAP DML command specified in the olap_command parameter of the OLAP_TABLE function. (If olap_command includes a FETCH, fetch the data.)
Fetch the data (unless an OLAP DML FETCH command was specified in the olap_command parameter).
Restore the status of all dimensions in the limit map (POP status).
Execute any OLAP DML command specified in the POSTDMLCMD parameter of the limit map.
Examples
Because different applications have different requirements, several different formats are commonly used for fetching data into SQL from an analytic workspace. The examples in this section show how to create views using a variety of different formats.
Although these examples are shown as views, the SELECT statements can be extracted from them and used directly to fetch data from an analytic workspace into an application.
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Note: The examples in this section use predefined ADTs. You could modify them to use automatic ADTs. See "Using OLAP_TABLE With Automatic ADTs". |
Example A-5 Script for an Embedded Total Dimension View Using OLAP_TABLE
This example shows the PL/SQL script used to create an embedded total view of the TIME dimension in an analytic workspace named MYAW. This view is similar to the view in Example A-2, "Sample View of the TIME Dimension Using Predefined ADTs", but it specifies both a Calendar and a Fiscal hierarchy, and it includes HATTRIBUTE subclauses for hierarchy-specific End Date attributes.
The INHIERARCHY subclause identifies a valueset in the analytic workspace that lists all the dimension members in each hierarchy of a dimension. OLAP_TABLE saves the status of all dimensions in the limit map that have INHIERARCHY subclauses during the processing of the limit map. See "Order of Processing in OLAP_TABLE".
CREATE TYPE awtime_row AS OBJECT (
awtime_id VARCHAR2(12),
awtime_short_label VARCHAR2(12),
awtime_cal_end_date DATE,
awtime_fis_end_date DATE);
/
CREATE TYPE awtime_table AS TABLE OF awtime_row;
/
CREATE OR REPLACE VIEW awtime_view AS
SELECT awtime_id, awtime_short_label,
awtime_cal_end_date, awtime_fis_end_date
FROM TABLE(OLAP_TABLE(
'myaw DURATION SESSION',
'awtime_table',
'',
'DIMENSION awtime_id FROM time WITH
HIERARCHY time_parentrel
(time_hierlist ''CALENDAR'')
INHIERARCHY time_inhier
HATTRIBUTE awtime_cal_end_date FROM time_cal_end_date
HIERARCHY time_parentrel
(time_hierlist ''FISCAL'')
INHIERARCHY time_inhier
HATTRIBUTE awtime_fis_end_date FROM time_fis_end_date
ATTRIBUTE awtime_short_label FROM time_short_description'));
/
SQL>SELECT * FROM awtime_view;
AWTIME_ID AWTIME_SHORT_LABEL AWTIME_CAL_END_DATE AWTIME_FIS_END_DATE
--------- ------------------ ------------------- -------------------
19 Jan-98 31-JAN-98 31-JAN-98
20 Feb-98 28-FEB-98 28-FEB-98
21 Mar-98 31-MAR-98 31-MAR-98
22 Apr-98 30-APR-98 30-APR-98
23 May-98 31-MAY-98 31-MAY-98
24 Jun-98 30-JUN-98 30-JUN-98
.
.
.
.
98 Q1-03 31-MAR-03 30-SEP-03
99 Q2-03 30-JUN-03 31-DEC-03
1 1998 31-DEC-98 30-JUN-99
102 2003 31-DEC-03 30-JUN-04
119 2004 31-DEC-04 30-JUN-05
2 1999 31-DEC-99 30-JUN-00
3 2000 31-DEC-00 30-JUN-01
4 2001 31-DEC-01 30-JUN-02
85 2002 31-DEC-02 30-JUN-03
Note that you must be sure to verify that you have created the views correctly by issuing SELECT statements against them. Only at that time do any errors in the call to OLAP_TABLE appear.
Example A-6 Creating a View of an Embedded Total Measure Using OLAP_TABLE
In a star schema, a separate measure view is needed with columns that can be joined to each of the dimension views. This example shows the PL/SQL script used to create a measure view with a column populated by a ROW2CELL clause to support custom measures. For information on ROW2CELL, "ROW2CELL Clause".
CREATE TYPE awunits_row AS OBJECT (
awtime VARCHAR2(12),
awcustomer VARCHAR2(30),
awproduct VARCHAR2(30),
awchannel VARCHAR2(30),
awunits NUMBER(16),
r2c RAW(32));
/
CREATE TYPE awunits_table AS TABLE OF awunits_row;
/
CREATE OR REPLACE VIEW awunits_view AS
SELECT awunits,
awtime, awcustomer, awproduct, awchannel, r2c
FROM TABLE(OLAP_TABLE(
'myaw DURATION SESSION',
'awunits_table',
'',
'MEASURE awunits FROM units_cube_units
DIMENSION awtime FROM time WITH
HIERARCHY time_parentrel
DIMENSION awcustomer FROM customer WITH
HIERARCHY customer_parentrel
(customer_hierlist ''MARKET_ROLLUP'')
INHIERARCHY customer_inhier
DIMENSION awproduct FROM product WITH
HIERARCHY product_parentrel
DIMENSION channel WITH
HIERARCHY channel_parentrel
ATTRIBUTE awchannel FROM channel_short_description
ROW2CELL r2c'))
WHERE awunits IS NOT NULL;
SQL>SELECT awchannel, awunits FROM awunits_view
WHERE awproduct = '1'
AND awcustomer = '7'
AND awtime = '4';
AWCHANNEL AWUNITS
--------- -------
All Channels 415392
Direct Sales 43783
Catalog 315737
Internet 55872
Example A-7 Script for a Rollup View of Products Using OLAP_TABLE
Rollup form uses a column for each hierarchy level to show the full parentage of each dimension member. The only difference between the syntax for rollup form and the syntax for embedded total form is the addition of a FAMILYREL clause in the definition of each dimension in the limit map. For information on FAMILYREL, see "WITH HIERARCHY Subclause".
This example shows the PL/SQL script used to create a rollup view of the PRODUCT dimension. It shows a dimension view to highlight the differences in the syntax of the limit map from the one used for the embedded total form, as shown in Example A-5, "Script for an Embedded Total Dimension View Using OLAP_TABLE". Note that the target columns for these levels are listed in the FAMILYREL clause from most aggregate (CLASS) to least aggregate (ITEM), which is the order they are listed in the level list dimension. The family relation returns four columns. The most aggregate level (all products) is omitted from the view by mapping it to null.
Example A-8, "Script Using QDRs in the FAMILYREL Clause of OLAP_TABLE" shows the alternate syntax for the FAMILYREL clause, which uses QDRs to identify exactly which columns are mapped from the family relation.
The limit maps in Example A-7 and Example A-8 generate identical views.
CREATE TYPE awproduct_row AS OBJECT (
class VARCHAR2(50),
family VARCHAR2(50),
item VARCHAR2(50));
/
CREATE TYPE awproduct_table AS TABLE OF awproduct_row;
/
CREATE OR REPLACE VIEW awproduct_view AS
SELECT class, family, item
FROM TABLE(OLAP_TABLE(
'myaw DURATION QUERY',
'awproduct_table',
'',
'DIMENSION product WITH
HIERARCHY product_parentrel
FAMILYREL null, class, family, item
FROM product_familyrel USING product_levellist
LABEL product_short_description'));
SQL> SELECT * FROM awproduct_view
ORDER BY class, family, item;
CLASS FAMILY ITEM
-------------- ---------------- ------------------------
Hardware CD-ROM Envoy External 6X CD-ROM
Hardware CD-ROM Envoy External 8X CD-ROM
Hardware CD-ROM External 6X CD-ROM
Hardware CD-ROM External 8X CD-ROM
Hardware CD-ROM Internal 6X CD-ROM
Hardware CD-ROM Internal 8X CD-ROM
Hardware CD-ROM
Hardware Desktop PCs Sentinel Financial
Hardware Desktop PCs Sentinel Multimedia
.
.
.
Software/Other Operating Systems UNIX/Windows 1-user pack
Software/Other Operating Systems UNIX/Windows 5-user pack
Software/Other Operating Systems
Software/Other
Example A-8 Script Using QDRs in the FAMILYREL Clause of OLAP_TABLE
CREATE OR REPLACE TYPE awproduct_row AS OBJECT (
class VARCHAR2(50),
family VARCHAR2(50),
item VARCHAR2(50));
/
CREATE TYPE awproduct_table AS TABLE OF awproduct_row;
/
CREATE OR REPLACE VIEW awproduct_view AS
SELECT class, family, item
FROM TABLE(OLAP_TABLE(
'myaw DURATION QUERY',
'awproduct_table',
'',
'DIMENSION product WITH
HIERARCHY product_parentrel
FAMILYREL class, family, item FROM
product_familyrel(product_levellist ''CLASS''),
product_familyrel(product_levellist ''FAMILY''),
product_familyrel(product_levellist ''ITEM'')
LABEL product_short_description'));
SQL> SELECT * FROM awproduct_view
ORDER BY by class, family, item;
CLASS FAMILY ITEM
-------------- ---------------- ------------------------
Hardware CD-ROM Envoy External 6X CD-ROM
Hardware CD-ROM Envoy External 8X CD-ROM
Hardware CD-ROM External 6X CD-ROM
Hardware CD-ROM External 8X CD-ROM
Hardware CD-ROM Internal 6X CD-ROM
Hardware CD-ROM Internal 8X CD-ROM
Hardware CD-ROM
Hardware Desktop PCs Sentinel Financial
Hardware Desktop PCs Sentinel Multimedia
.
.
.
Software/Other Operating Systems UNIX/Windows 1-user pack
Software/Other Operating Systems UNIX/Windows 5-user pack
Software/Other Operating Systems
Software/Other
Example A-9 Script Using FETCH with OLAP_TABLE
Oracle Express Server applications that are being revised for use with Oracle Database can use an OLAP DML FETCH command instead of a limit map to map workspace objects to relational columns.
The FETCH command is supplied in the third parameter of OLAP_TABLE, which specifies a single OLAP DML command. See olap_command.
The script that follows fetches data from two variables (SALES and COST) in an analytic workspace named MYAW, and calculates two custom measures (COST_PRIOR_PERIOD and PROFIT). This example also shows the use of OLAP_TABLE directly by an application, without creating a view.
Note that the FETCH statement in the following example is formatted with indentation for readability. In reality, the entire FETCH statement must be entered on one line, without line breaks or continuation characters
CREATE TYPE measure_row AS OBJECT (
time VARCHAR2(20),
geography VARCHAR2(30),
product VARCHAR2(30),
channel VARCHAR2(30),
sales NUMBER(16),
cost NUMBER(16),
cost_prior_period NUMBER(16),
profit NUMBER(16));
/
CREATE TYPE measure_table AS TABLE OF measure_row;
/
SELECT time, geography, product, channel,
sales, cost, cost_prior_period, profit
FROM TABLE(OLAP_TABLE(
'xademo DURATION SESSION',
'measure_table',
'FETCH time, geography, product, channel, analytic_cube_f.sales,
analytic_cube_f.costs,
LAG(analytic_cube_f.costs, 1, time, LEVELREL time_member_levelrel),
analytic_cube_f.sales - analytic_cube_f.costs',
''))
WHERE channel = 'STANDARD_2.TOTALCHANNEL' AND
product = 'L1.TOTALPROD' AND
geography = 'L1.WORLD'
ORDER BY time;
This SQL SELECT statement returns the following result set:
TIME GEOGRAPHY PRODUCT CHANNEL SALES COST COST_PRIOR_PERIOD PROFIT
--------- --------- ------------ ----------------------- --------- --------- ------------------ --------
L1.1996 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 118247112 2490243 115756869
L1.1997 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 46412113 1078031 2490243 45334082
L2.Q1.96 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 26084848 560379 25524469
L2.Q1.97 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 26501765 615399 560379 25886367
L2.Q2.96 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 30468054 649004 615399 29819049
L2.Q2.97 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 19o910347 462632 649004 19447715
L2.Q3.96 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 27781702 582693 462632 27199009
L2.Q4.96 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 33912508 698166 582693 33214342
L3.APR96 L1.WORLD L1.TOTALPROD STANDARD_2.TOTALCHANNEL 8859808 188851 8670957
.
.
.
27 rows selected.
The RESERVED function can provide a list of all the words that are reserved because they are known to the OLAP DML parser, or it can indicate if a word that you specify is known to the OLAP DML parser. Some other words are also reserved as discussed in "Other Reserved Words".
Return Value
Either a multiline text expression or BOOLEAN, depending on whether or not you specify an argument to the function.
Syntax
RESERVED [(word-expression)]
Parameters
A text expression that represents a word that may or may not be reserved in the OLAP DML. When you specify word-expression, the RESERVED function returns a BOOLEAN value indicating if the word is reserved in OLAP DML. When you do not specify an argument, RESERVED returns a TEXT value consisting of all the reserved words in OLAP DML, with each word on a separate line.
Usage Notes
Other Reserved Words
The RESERVED function only recognizes words known to the OLAP DML parser. The RESERVED function des not recognize the names of option objects and some other objects in the EXPRESS analytic workspace. The names of these objects are reserved in Oracle OLAP, but are ignored by the RESERVED function. To identify the names of these objects, issue the following statements.
AW ATTACH EXPRESS LISTNAMES
NA is Reserved
When you specify NA for the argument, the RESERVED function returns NO. When you specify NA, the RESERVED function returns YES.
Case-Sensitivity
The list of reserved words returned by the RESERVED function contains some words in all uppercase and some in mixed case. Words all in uppercase are reserved in their entirety. Words in mixed case can be abbreviated to the uppercase portion. For such words, any subset of the word containing the uppercase portion is reserved. For example, one word in the list returned by RESERVED is CODEVERsion. The following are all reserved: codever, codeversi, codeversio, and codeversion. However, codeve is not reserved.
Examples
The ACROSS command specifies a text expression that contains one or more statements to be executed in a loop. ACROSS temporarily sets status to the values that are in current status for the specified dimensions. After the ACROSS statement executes, dimension status is restored to what it was before the loop, and execution of the program resumes with the next statement. The repetition of the statements in the DO clause statements is controlled by the status of the dimensions and composites specified in the ACROSS statement and by the results of the WHERE clause when included.E
Syntax
ACROSS dimension... DO dml-statements [WHERE boolean-expression]
Parameters
One or more dimensions or composites whose current status controls the repetition of one or more statements, which are contained in dml-statements. The statements are repeated for each combination of the values of the specified dimensions in the current status. When two or more dimensions are specified, the first one varies the slowest.
A multiline text expression that is one or more OLAP DML statements to be executed for each iteration of the loop. You can specify any OALAP DML statement except one that is typically used as part of a multiple-line construct in a program. For example, the IF...THEN...ELSE, WHILE, FOR, or SWITCH commands cannot be executed by an ACROSS statement.
For each iteration of the loop, specifies that the command evaluate boolean-expression before executing dml-statements and, when the result of boolean-expression is either NA or FALSE, to not execute dml-statements for that iteration.
Usage Notes
Code May Change Between Compilation and Execution
Oracle OLAP does not generate the code for the loop body until an ACROSS statement or the program that contains it is executed. Waiting until execution to generate the code allows for the possibility that, because the statements are contained within a text expression, the contents of an ACROSS loop may change between compilation and execution.
Examples
Example 9-4 Using ACROSS to Repeat ROW Commands
In a report program, you want to show the unit sales of tents for each of three months. Use the following ACROSS statement to repeat ROW commands for each value of the month dimension.
LIMIT product TO 'Tents'
LIMIT month TO 'Jan95' to 'Mar95'
ACROSS month DO 'ROW INDENT 5 month WIDTH 6 unit'
Jan95 533363
Feb95 572796
Mar95 707198
The SOUNDEX function returns a character string containing the phonetic representation of a text expression. This function lets you compare words that are spelled differently, but sound alike in English.
|
See: For a discussion of how the phonetic representation is constructed, see the SOUNDEX function in Oracle Database SQL Language Reference |
Return Value
The same data type as text_exp.
Syntax
SOUNDEX(text_exp)
Parameters
The expression for which you want a phonetic representation. It can be any of the text data types.
The STATEQUAL function compares the status lists of a dimension.
Return Value
BOOLEAN
Syntax
STATEQUAL (statlist1, statlist2 [INORDER])
Parameters
The status list of a dimension as specified using the name of the dimension, a valueset dimensioned by the dimension; or a LIMIT or SORT function for the dimension.
The status list of the same dimension as that specified by statlist1. You can specify statlist2 using the name of the dimension, a valueset dimensioned by the dimension; or a LIMIT or SORT function for the dimension.
Specifies that the values must be in the same order.
The MOVINGMAX function (abbreviated MVMAX) returns a series of maximum values of a dimensioned variable or expression over a specified dimension. For each dimension value in status, MOVINGMAX searches the data for the maximum value in the range specified, relative to the current dimension value.
When the variable or expression has only the specified dimension, MOVINGMAX produces a single series of maximum values, one for each dimension value in the status. When the variable or expression has dimensions other than the one specified, MOVINGMAX produces a separate series of maximum values for each combination of values in the status list of the other dimensions
Return Value
DECIMAL when the data type of expression is DECIMAL or SHORT; otherwise, NUMBER.
Syntax
MOVINGMAX(expression, start, stop, step, [dimension [STATUS|limit-clause]])
Parameters
A numeric variable or calculation from whose values you want to find the maximum values; for example, units or sales-expense.
Integer values that specify the range of values over which you want to find the maximum values. The value of start specifies the beginning of the range. The value of stop specifies the end of the range. Specify the values of start and stop relative to the current value of dimension. To specify a negative position for start or stop preceed the value with a comma. Thus, you specify zero (0) for the current dimension value, and -1 for the value preceding the current value. (See also "How the Moving Functions Handle Out-of-Range and NA Values".)
|
Note: By default this function uses the default status list when identifying the range of values to average. You can specify either the STATUS or limit-clause phrase to change this behavior. |
|
Tip: When you want to range to the end of status, for convience and to document your intent, specify the value of stop as OBJ function with the DIMMAX keyword |
A positive whole number that specifies whether to search every value in the range, every other value, every third value, and so on. A value of 1 for step means search every value. A value of 2 means check the first value, the third value, the fifth value, and so on. For example, when the current month is Jun96 and the start and stop values are -3 and 3, a step value of 2 means search the months Mar96, May96, Jul96, and Sep96 and return the maximum value that occurs in one of those four months.
The dimension over which the moving maximum is calculated. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, Quarter, or YEAR.
When expression has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want MOVINGMAX to use that dimension, you can omit the dimension argument.
Specifies that MOVINGMAX uses the values specified by a LIMIT function or those specified with the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
Examples
For an example of calculating maximum sales, see Example 8-31, "Calculating a Moving Average".
The CURRENT_TIMESTAMP function returns the current date and time in the session time zone, as a value of data type TIMESTAMP_TZ. The time zone offset reflects the current local time of the session.
When you want to retrieve the current date and time in the session time zone as a TIMESTAMP value, use the LOCALTIMESTAMP function.
Return Values
TIMESTAMP_TZ
Syntax
CURRENT_TIMESTAMP [ (precision) ]
Parameters
The fractional second precision of the time value returned. When you omit this argument, then the function uses a default value of 6.
Examples
The SIGNAL command produces a user-defined error message from within a program. When Oracle OLAP executes a SIGNAL statement when TRAP is ON, execution branches to the trap label. Any statements following the trap label in the program are then executed.When the program contains an active trap label, execution branches to the label. Without a trap label, execution of the program terminates and, when the program was called by another program, execution control returns to the calling program.
Syntax
SIGNAL {errname [message]|STOP}
Parameters
A TEXT expression that indicates the name of the error message to be produced. When Oracle OLAP executes a SIGNAL statement, it stores the errname in the ERRORNAME option. Normally, the name of the error does not appear in the error message. However, when you omit message, the error name (errname) appears along with a stock message as described in the message argument.
You can use the special name PRGERR to communicate to a calling program that an error has occurred. The statement SIGNAL PRGERR sets ERRORNAME to a blank value and passes an error condition to the calling program without causing another error message to be displayed. For a complete explanation of how to use SIGNAL to pass an error up a chain of nested programs, see the TRAP command.
A TEXT expression that specifies the error message to be produced. When you supply a long line as your error message, you must add your own line breaks to format the text. Type the newline escape sequence (\n) where you want each line to end. You can type up to a limit of 6 lines or 4,000 characters, whichever you reach first. An error occurs when you try to supply a single line longer than 4,000 characters.
When you omit this argument, SIGNAL produces the following message.
ERROR: (errname) Please contact the administrator of your Oracle Oracle OLAP application.
When Oracle OLAP executes a SIGNAL statement, it stores message in the ERRORTEXT option.
Immediately stops execution of all currently running programs. No error message is produced. The error condition is not trapped by an active TRAP label.
Examples
Example 10-123 Signaling an Error
Suppose you have written a program that requires one argument. When no argument is supplied, there is no purpose in running the program. Therefore, the first thing the program does is check if an argument has been passed. When it has not, the program terminates after sending an error message to the current outfile.
The following program lines check for the argument and signal an error when it is not found.
IF ARGS EQ '' THEN SIGNAL msg1 'You must supply an argument.'
SIGNAL sends the following message to the current outfile.
ERROR: You must supply an argument.
Example 10-124 Signaling an Error When an Argument Value is Invalid
Suppose your program produces a report that can present from one to nine months of data. You can signal an error when the program is called with an argument value greater than nine. In this example, nummonths is the name of the argument that must be no greater than nine.
select:
TRAP ON error
PUSH month
LIMIT month TO nummonths
IF STATLEN(month) GT 9
THEN SIGNAL toomany -
'You can specify no more than 9 months.'
REPORT DOWN district W 6 units
finish:
POP month
RETURN
error:
POP month
IF ERRORNAME EQ 'TOOMANY'
THEN SHOW 'No report produced'
The DATEFORMAT option holds the template used for displaying DATE-only data type values and converting DATE-only values to text values. The template can include format specifications for any of the four components of a date (day, month, year, and day of the week). It can also include additional text.
Data Type
TEXT
Syntax
DATEFORMAT = template
Parameters
A TEXT expression that specifies the template for displaying dates. Each component in the template must be preceded by a left angle bracket and followed by a right angle bracket. You can include additional text before, after, or between the components. The default template is '<DD><MTXT><YY>'.
Table 5-2, "DATEFORMAT Templates for Day", Table 5-3, "DATEFORMAT Templates for Week", Table 5-4, "DATEFORMAT Templates for Month", and Table 5-5, "DATEFORMAT Templates for Year" present the valid formats for each component. The tables provide two display examples, one for March 1, 1990 and another for November 12, 2051.
Table 5-2 DATEFORMAT Templates for Day
| Format | Meaning | March 1, 1990 | November 12, 2051 |
|---|---|---|---|
|
|
One digit or two digits |
|
|
|
|
Two digits |
|
|
|
|
Space-padded, two digits |
|
|
|
|
Ordinal, uppercase |
|
|
|
|
Ordinal, lowercase |
|
|
Table 5-3, "DATEFORMAT Templates for Week" presents the valid formats for weeks. The table provides two display examples, one for March 1, 1990 and another for November 12, 2051.
Table 5-3 DATEFORMAT Templates for Week
| Format | Meaning | March 1, 1990 | November 12, 2051 |
|---|---|---|---|
|
|
Numeric |
|
|
|
|
First letter, uppercase |
|
|
|
|
First three letters, uppercase. |
|
|
|
|
First three letters, lowercase |
|
|
|
|
Full name, uppercase |
|
|
|
|
Full name, lowercase |
|
|
Note that when you specify a format of <WTXT>, <WTXTL>, <WTEXT>, or <WTEXTL>, the case in which the value is specified in DAYNAMES affects the displayed value:
When the name in DAYNAMES is entered as all lowercase, the entire name is converted to uppercase. Otherwise, the first letter is converted to uppercase and the second and subsequent letters remain in their original case.
When the name in DAYNAMES is entered as all uppercase, the second and subsequent letters are converted to lowercase. Otherwise, the entire name remains in the case specified in DAYNAMES.
Table 5-4, "DATEFORMAT Templates for Month" presents the valid formats for months. The table provides two display examples, one for March 1, 1990 and another for November 12, 2051.
Table 5-4 DATEFORMAT Templates for Month
| Format | Meaning | March 1, 1990 | November 12, 2051 |
|---|---|---|---|
|
|
One digit or two digits |
1 |
|
|
|
Two digits |
|
|
|
|
Space-padded, two digits |
|
|
|
|
First letter, uppercase |
|
|
|
|
First three letters, uppercase |
|
|
|
|
First three letters, lowercase |
|
|
Note that when you specify a format of <MTXT> or <MTXTL>, the case in which the value is specified in MONTHNAMES affects the displayed value:
When the name in MONTHNAMES is entered as all lowercase, the entire name is converted to uppercase. Otherwise, the first letter is converted to uppercase and the second and subsequent letters remain in their original case.
When the name in MONTHNAMES is entered as all uppercase, the second and subsequent letters are converted to lowercase. Otherwise, the entire name remains in the case specified in MONTHNAMES.
Table 5-5, "DATEFORMAT Templates for Year" presents the valid formats for years. The table provides two display examples, one for March 1, 1990 and another for November 12, 2051.
Usage Notes
Specifying Angle Brackets as Text in a DATEFORMAT Template
To include an angle bracket as additional text in a template, specify two angle brackets for each angle bracket to be included as text (for example, to display the entire date in angle brackets, specify '<<<D><M><YY>>>').
Month and Day Names
The names used in the month component for the MT, MTXT, MTXTL, MTEXT, and MTEXTL formats are drawn from the current setting of the MONTHNAMES option. The names used in the day-of-the-week component for the WT, WTXT, WTXTL, WTEXT, and WTEXTL formats are drawn from the current setting of the DAYNAMES option.
Specifying Abbreviations for Day and Month
You can set the DAYABBRLEN and MONTHABBRLEN options to use abbreviations of different lengths for day and month names.
Out-of-Range Years for DATEFORMAT
When you specify the YY format, and a year outside the range of 1950 to 2049 is to be displayed, the year is displayed in four digits.
Automatic Conversion of DATE-only Values to Text Values
When you use a value with DATE-only data type where a text data type is expected. Oracle OLAP also uses the date template in the DATEFORMAT option to automatically convert the date to a text value. When you want to override the current DATEFORMAT template, you can convert the date result to text by using the CONVERT function with a date-format argument.
Once a DATE-only value is stored in a text variable, the DATEFORMAT template is no longer used to format the display of the value, and subsequent changes to DATEFORMAT have no impact.
DATE-only Dimension Values
The DATEFORMAT option does not how Oracle OLAP displays DATE-only values of DAY, WEEK, MONTH, QUARTER, and YEAR dimensions. How these values are displayed is controlled by a VNF (value name format) attached to the dimension definition, or by default conventions for DAY, WEEK, MONTH, QUARTER, and YEAR dimensions as described in Table 2-5, "Default VNFs for DWMQY Dimensions".
Examples
Example 5-13 Changing the Format of Dates
The following statements define a DATE-only variable and set its value to March 24, 1997, then set the date format to two digits each in the order of day, month, and year, and send the result to the current outfile.
DEFINE datevar VARIABLE DATE datevar = '24Mar97' DATEFORMAT = '<DD>/<MM>/<YY>' SHOW datevar
These statements produce the following output.
24/03/97
The following statements change the date format to month (text), day (two digits), and year (four digits), and send the result to the current outfile.
DATEFORMAT = '<MTEXTL> <D>, <YYYY>' SHOW DATEVAR
These statements produce the following output.
March 24, 1997
The following statements change the date format to day of the week (text), month (text), day (one or two digits), and year (four digits), and send the result to the current outfile.
DATEFORMAT = '<WTEXTL> <MTEXTL> <D>, <YYYY>' SHOW DATEVAR
These statements produce the following output.
Monday March 24, 1997
Example 5-14 Including Text in the Format of a Date
The following statements save and then change the DATEFORMAT option to include extra text for an analytic workspace startup greeting.
PUSH DATEFORMAT DATEFORMAT = 'Hello. Today is <wtextl>, the <dtl> - OF <MTEXTL>.' SHOW TODAY POP DATEFORMAT
When today's date is May 30, 1997, the following output is sent to the current outfile when the program is run.
Hello. Today is Friday, the 30th of May.
The AW_DELETE procedure deletes an existing analytic workspace.
Syntax
AW_DELETE (
awname IN VARCHAR2);
AW_DELETE (
schema IN VARCHAR2,
awname IN VARCHAR2);
Parameters
Table B-14 AW_DELETE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an existing analytic workspace that you want to delete along with all of its contents. You must be the owner of awname or have DBA rights to delete it, and it cannot currently be attached to your session. The AW$awname file is deleted from the database. |
Example
The following command deletes the SALES_DEMO analytic workspace in the user's default schema.
EXECUTE dbms_aw.aw_delete('sales_demo');
The DEFAULTAWSEGSIZE option holds the default maximum segment size for an analytic workspace created in your Database session. The setting is in effect for the duration of your session. For each new session, DEFAULTAWSEGSIZE reverts to the default value.
|
Tip: To change the maximum size for new segments in an existing workspace, use the AW command with the SEGMENTSIZE keyword. To discover the current maximum size for new segments, use the AW function with the SEGMENTSIZE keyword. |
Syntax
DEFAULTAWSEGSIZE = n
Parameters
The number of bytes.
Examples
This chapter provides reference topics for the second set (in alphabetical order) of the OLAP DML commands. There is one topic for each of the OLAP DML commands that begins with the letters H-Z, beginning with HEADING.
Alphabetical and categorical listings of the OLAP DML commands and reference topics for the remaining OLAP DML commands appear in Chapter 9, "OLAP DML Commands: A-G".
For other OLAP DML reference topics, see Chapter 4, "OLAP DML Properties", Chapter 5, "OLAP DML Options", Chapter 7, "OLAP DML Functions: A - K", and Chapter 8, "OLAP DML Functions: L - Z".
|
Tip: Many OLAP DML statements can be coded as a 3-character abbreviation that consists of the first letter of the statement plus the next two consonants. |
Within an OLAP DML program, the IF...THEN...ELSE command executes one or more statements in a program when a specified condition is met. Optionally, it also executes an alternative statement or group of statements when the condition is not met.
|
Note: You can also use IF as a conditional operator in an expression. See "IF...THEN...ELSE expression" |
Syntax
IF boolean-expression
THEN statement1
[ELSE statement2]
Parameters
Any valid Boolean expression that returns either TRUE or FALSE.
Oracle OLAP executes the statement1 argument when the Boolean expression is TRUE. The statement1 must be on the same line as THEN.
Oracle OLAP executes the statement2 argument when the Boolean expression is FALSE. The statement2 must be on the same line as ELSE. When you omit the ELSE phrase, execution continues with the statement after the whole IF...THEN... statement in the program.
Usage Notes
IF with DO
You can use an IF statement for conditional execution of two or more statements by following the THEN or ELSE (or both) keywords with a DO ... DOEND sequence. See Example 10-5, "Using IF...THEN...ELSE".
Single or Multiple Lines
When IF is used as an expression, the THEN and ELSE keywords must be on the same line as IF. When IF is used as a command, THEN and ELSE must be on separate lines.
Examples
Example 10-5 Using IF...THEN...ELSE
The following lines from a program illustrate the use of IF...THEN...ELSE.... When the Boolean expression ANY(DOLLARS LT 200000) is TRUE, the statements following THEN (statement group 1) are executed. When the expression is FALSE, the statements following ELSE (statement group 2) are executed instead.
IF ANY(DOLLARS LT 200000) THEN DO ... " (statement group 1) DOEND ELSE DO ... "(statement group 2) DOEND
Example 10-6 Using IF as a Conditional Operator
In a program that produces a report, you would like to report a previous year's actual expenses or the current year's budget, depending on the year passed to the program as an argument. A conditional expression in a JOINCHARS function produces a heading with the word Actual or Budget. Another conditional expression selects the variable to report. The program would include the following lines.
ARGUMENT cur.year year
LIMIT month TO year cur.year
REPORT -
HEADING JOINCHARS( 'Expenses: ' -
IF cur.year LT 'Yr95' -
THEN 'Actual FOR ' -
ELSE 'Budget FOR ', -
cur.year ) -
IF cur.year LT 'Yr95' THEN actual ELSE budget
The CONTINUE command transfers program control to the end of a FOR or WHILE loop (just before the DO/DOEND statement), allowing the loop to repeat. You can use CONTINUE only within programs and only with FOR or WHILE.
For more information on controlling program execution, see also "Program Flow-of-Control".
Syntax
CONTINUE
Examples
Example 9-73 Skipping Over Code in a FOR Loop
In the following lines from a program, an IF statement is used to test whether total sales for a district exceed 5,000,000. When sales are more this amount, the program goes on to produce a report for that district. However, when a district's sales are less than the amount, the CONTINUE statement is used to transfer control to the end of the FOR loop (just before the DOEND statement). No lines are produced for that district, and the program goes on to test the next district in the status list.
...
FOR district
DO
IF TOTAL(sales, district) LT 5000000
THEN CONTINUE
... "(report statements for districts with total sales above 5,000,000)
DOEND
...
The NUMCHARS function counts the number of characters in a text expression. When the value is a multiline text value, NUMCHARS returns the total number of characters in all the lines. The result returned by NUMCHARS has the same dimensions as the specified expression.
|
Tip: When you are using a multibyte character set, you can use the NULLIF function instead of the NUMCHARS function. |
Return Value
INTEGER
Syntax
NUMCHARS(text-expression)
Parameters
The text expression whose characters are to be counted. NUMCHARS accepts either a TEXT or NTEXT argument. It does not perform an automatic conversion to either data type. It returns the information that is correct for the data type of the specified argument.
Examples
Example 8-43 Counting the Characters in the Longest Name
You would like to know the length of the names of your products so you can specify the appropriate width for the label column in a report. You can use the NUMCHARS function in combination with the LARGEST function to find the length of the longest label. Then use that value to set the column size. The following statements in a program find the longest name and use the character count to format a report.
firstcol = LARGEST(NUMCHARS(name.product))+1
LIMIT month TO FIRST 3
FOR product
DO
ROW WIDTH FIRSTCOL name.product WIDTH 6 ACROSS month -
FIRST 3: units
DOEND
When the program is run, it produces the following output.
3-Person Tents 200 203 269 Aluminum Canoes 347 400 482 Tennis Racquets 992 1,076 1,114 Warm-up Suits 1,096 1,214 1,294 Running Shoes 2,532 2,405 2,775
For output produced by the REPORT and ROW commands, the ZEROROW option suppresses report rows with numeric values that are all NAs or all zeros or would be represented as zeros. When your report includes a small number, such as 0.004, the number of decimal places being shown affects whether ZEROROW treats that number as zero. When you are producing a report with totals, the actual number is used to calculate the total, even when the number is suppressed.
Data Type
BOOLEAN
Syntax
ZEROROW = {YES|NO}
Parameters
Suppresses report rows that contain any numeric values when all the numeric values would be shown either as zeros or NAs.
(Default) Produces all rows of the report, regardless of the values they contain.
Usage Notes
Non-Numeric Data
Even when a row contains non-numeric data, such as TEXT, ID, or BOOLEAN values, along with numeric values, the row is suppressed when ZEROROW is YES and all the numeric values would be shown either as zeros or NAs.
The Effect of NASPELL and ZSPELL
The value of NASPELL does not affect the way ZEROROW handles NA values. The value of ZSPELL does not affect the functioning of ZEROROW; numeric zero values are treated as zeros regardless of their spelling in output.
Examples
Example 5-116 Suppressing Report Rows of All-Zero Data
Suppose you have a variable called worstcase, that is dimensioned by division, month, and line, in which you store the results of calculations to project sales. When you produce a report of the results, you want to suppress any rows for which the value of the worst-case projections is zero for all months in the status. Set ZEROROW to YES, as shown in the following statements.
ZEROROW = YES LIMIT line TO 'Revenue' LIMIT month TO 'Nov95' TO 'Feb96' REPORT WIDTH 8 DOWN division ACROSS month: worstcase
These statements produce the following report.
LINE: REVENUE
-----------------WORSTCASE-----------------
-------------------MONTH-------------------
DIVISION Nov95 Dec95 Jan96 Feb96
-------- ---------- ---------- ---------- ----------
Camping 0.00 0.00 45,500.00 47,400.00
Sporting 0.00 0.00 29,200.00 28,400.00
Clothing 0.00 0.00 15,200.00 14,900.00
In the preceding report, no rows are suppressed, since some months for each division have projected sales. However, when you lay out this report with month down and division across, the rows for Nov95 and Dec95 are suppressed, because these months have no projected sales.
REPORT DOWN month ACROSS division: worstcase
This statement produces the following report.
LINE: REVENUE
-----------WORSTCASE------------
------------DIVISION------------
MONTH Camping Sporting Clothing
-------------- ---------- ---------- ----------
Jan96 45,500.00 29,200.00 15,200.00
Feb96 47,400.00 28,400.00 14,900.00
The COLWIDTH option controls the default width of data columns in report output. For output from the ROW command and HEADING command, COLWIDTH affects all columns except the first column. For output from REPORT, COLWIDTH affects all data columns and the label columns for a composite or a conjoint dimension.
|
Note: For an individual column, the COLWIDTH value is always overridden by a WIDTH attribute in a HEADING, REPORT, or ROW command |
Data Type
INTEGER
Syntax
COLWIDTH = n
Parameters
An INTEGER expression that specifies the desired column width in number of characters. You can set COLWIDTH to any value from 1 to 4,000. The default is 10.
|
Note: The maximum width of a line in a report is 4,000 characters. Therefore, the combined width of all the columns of a report cannot be greater than 4,000 characters. |
Examples
Example 5-9 Setting the Default Column Width in a Report
Suppose you want to look at unit sales for six months. Since the data values are not large, you do not need a width of 10 characters for your data columns. You can set COLWIDTH to provide a narrower default column.
LIMIT district TO 'Atlanta' LIMIT month TO 'Oct95' TO 'Mar96' COLWIDTH = 6 REPORT ACROSS month: units
These statements produce the following output.
DISTRICT: ATLANTA
------------------UNITS------------------
------------------MONTH------------------
PRODUCT Oct95 Nov95 Dec95 Jan96 Feb96 Mar96
-------------- ------ ------ ------ ------ ------ ------
Tents 503 345 259 279 305 356
Canoes 317 282 267 281 309 386
Racquets 1,365 1,270 1,357 1,125 1,304 1,263
Sportswear 3,065 2,327 1,955 2,591 2,829 3,137
Footwear 3,445 3,247 2,831 3,089 3,282 3,475
The ADVISE_DIMENSIONALITY procedure evaluates the information provided by the ADVISE_SPARSITY procedure and generates the OLAP DML commands for defining a composite and a variable in the analytic workspace.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_DIMENSIONALITY (
output OUT CLOB,
cubename IN VARCHAR2,
sparsename IN VARCHAR2 DEFAULT NULL,
dtype IN VARCHAR2 DEFAULT 'NUMBER',
advtable IN VARCHAR2 DEFAULT NULL);
Parameters
Table B-5 ADVISE_DIMENSIONALITY Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of an object (such as a PL/SQL variable) in which the recommendations of the procedure is stored. |
|
|
The same cubename value provided in the call to |
|
|
An object name for the sample composite. The default value is |
|
|
The OLAP DML data type of the sample variable. |
|
|
The name of the table created by the |
Example
The following PL/SQL program fragment defines a variable named DEFS to store the recommended definitions.
DECLARE
defs CLOB;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_aw.advise_dimensionality(defs, 'units_cube_measure_stored',
'units_cube_composite', 'DECIMAL');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The program uses the DBMS_OUTPUT.PUT_LINE and DBMS_AW.PRINTLOG procedures to display the recommended object definitions.
Definitions: DEFINE units_cube.cp COMPOSITE <product customer time> DEFINE units_cube NUMBER VARIABLE <channel units_cube.cp<product customer time>>
In contrast to the Global schema, which is small and dense, the Sales cube in the Sales History sample schema is large and very sparse, and the Sparsity Advisor recommends 11 partitions. The following excerpt shows some additional OLAP DML definitions for defining a partition template and moving the TIME dimension members to the various partitions.
Definitions:
DEFINE sales_cube_composite_p1 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p2 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p3 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p4 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p5 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p6 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p7 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p8 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p9 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p10 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p11 COMPOSITE <channel product promotion customer>
DEFINE sales_cube_pt PARTITION TEMPLATE <time channel product promotion customer> -
PARTITION BY LIST (time) -
(PARTITION p1 VALUES () <sales_cube_composite_p1<>> -
PARTITION p2 VALUES () <sales_cube_composite_p2<>> -
PARTITION p3 VALUES () <sales_cube_composite_p3<>> -
PARTITION p4 VALUES () <sales_cube_composite_p4<>> -
PARTITION p5 VALUES () <sales_cube_composite_p5<>> -
PARTITION p6 VALUES () <sales_cube_composite_p6<>> -
PARTITION p7 VALUES () <sales_cube_composite_p7<>> -
PARTITION p8 VALUES () <sales_cube_composite_p8<>> -
PARTITION p9 VALUES () <sales_cube_composite_p9<>> -
PARTITION p10 VALUES () <sales_cube_composite_p10<>> -
PARTITION p11 VALUES () <time sales_cube_composite_p11<>>)
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'06-JAN-98', '07-JAN-98', '14-JAN-98', '21-JAN-98', -
'24-JAN-98', '28-JAN-98', '06-FEB-98', '07-FEB-98', -
'08-FEB-98', '16-FEB-98', '21-FEB-98', '08-MAR-98', -
'20-MAR-98', '03-JAN-98', '26-JAN-98', '27-JAN-98'
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'31-JAN-98', '11-FEB-98', '12-FEB-98', '13-FEB-98', -
'15-FEB-98', '17-FEB-98', '14-MAR-98', '18-MAR-98', -
'26-MAR-98', '30-MAR-98', '05-JAN-98', '08-JAN-98', -
'10-JAN-98', '16-JAN-98', '23-JAN-98', '01-FEB-98'
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'14-FEB-98', '28-FEB-98', '05-MAR-98', '07-MAR-98', -
'15-MAR-98', '19-MAR-98', '17-JAN-98', '18-JAN-98', -
'22-JAN-98', '25-JAN-98', '03-FEB-98', '10-FEB-98', -
'19-FEB-98', '22-FEB-98', '23-FEB-98', '26-FEB-98'
.
.
.
The LAST_DAY function returns the last day of the month in which a particular date falls.
Return Value
DATETIME
Syntax
LAST_DAY(datetime-expression)
Parameters
An expression that has the DATETIME data type.
Examples
Example 8-5 Calculating Remaining Days in a Month
The following statement calculates how many days remain between today's date and the end of the month.
SHOW JOINCHARS('Days left: ' LAST_DAY(SYSDATE) - SYSDATE)
When today's date is September 8, 2000, then this statement returns the following.
Days left: 22
The NLS_CHARSET_NAME function returns the name of the character set corresponding to a specified character set identification number.
Return Value
When the number is recognized as a valid character, VARCHAR2; otherwise, NA.
Syntax
NSL_CHARSET_NAME (number-exp)
Parameters
A number that is the character set ID.
The AW_TABLESPACE function returns the name of the tablespace in which a particular analytic workspace is stored.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_TABLESPACE (
awname IN VARCHAR2)
RETURN VARCHAR2;
AW_TABLESPACE (
schema IN VARCHAR2,
awname IN VARCHAR2)
RETURN VARCHAR2;
Returns
Name of a tablespace.
Parameters
Table B-17 AW_TABLESPACE Function Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an analytic workspace. |
Example
The following example shows the tablespace in which the GLOBAL analytic workspace is stored.
SET serveroutput ON
EXECUTE dbms_output.put_line('Sales History is stored in tablespace ' ||
dbms_aw.aw_tablespace('sh_aw', 'sales_history'));
This command generates the following statement:
Sales History is stored in tablespace SH_AW
The TO_NUMBER function converts a formatted TEXT or NTEXT expression to a number. This function is typically used to convert the formatted numeric output of one application (which includes currency symbols, decimal markers, thousands group markers, and so forth) so that it can be used as input to another application.
Return Value
NUMBER. Negative return values contain a leading negative sign, and positive values contain a leading space, unless the format model contains the MI, S, or PR format elements.
Syntax
TO_NUMBER(text-exp, [fmt,] [nlsparams])
Parameters
A text expression that contains a number to be converted. The expression can have the TEXT or NTEXT data type. A conversion from NTEXT can result in an incorrect result when the NTEXT value cannot be interpreted as a number.
A text expression that identifies a number format model. This model specifies how the conversion to NUMBER should be performed.
The default number format identifies a period (.) as the decimal marker and does not recognize any other symbol.
A text expression that specifies the thousands group marker, decimal marker, and currency symbols used in text-exp. This expression contains one or more of the following parameters, separated by commas:
NLS_CURRENCY symbol
NLS_ISO_CURRENCY territory
NLS_NUMERIC_CHARACTERS dg
A text expression that specifies the local currency symbol. It can be no more than 10 characters.
A text expression that identifies the territory whose ISO currency symbol is used.
A text expression composed of two different, single-byte characters for the decimal marker (d) and thousands group marker (g).
These parameters override the default values specified by the NLS_CURRENCY, NLS_ISO_CURRENCY, and NLS_NUMERIC_CHARACTERS options. Refer to NLS Options for additional information.
Usage Notes
Default Number Format Values
The values of some formats are determined by the value of NLS_TERRITORY.
Possible Effects of TO_NUMBER Rounding
All number format models cause the number to be rounded to the specified number of significant digits. Table 8-17, "Possible Effects of Rounding" identifies some effects of rounding.
Examples
Example 8-144 Converting Text Data to Decimal Data
The following statements convert a text string to a DECIMAL data type by identifying the local currency symbol (L), the thousands group separator (G) and the decimal marker (D). The NLS_NUMERIC_CHARACTERS option identifies the characters used for the G and D format, since they are different from the current setting for the session.
DEFINE money VARIABLE DECIMAL
money = TO_NUMBER('$94 567,00', 'L999G999D00', NLS_NUMERIC_CHARACTERS ', ')
SHOW money
The output of this statement is:
94,567.00
The FINDBYTES function returns the byte position of the beginning of a specified group of bytes within a text expression.
|
Tip: When you are using a single-byte character set, you can use the FINDCHARS function instead of the FINDBYTES function. |
Return Value
INTEGER
Syntax
FINDBYTES(text-expression, bytes [starting-pos [LINENUM]])
Parameters
The TEXT expression in which you are searching for the specified bytes. The value of text-expression can be a multiline value. In this case, FINDBYTES searches all lines for the specified bytes. The match must be exact, including a match of upper- and lowercase characters.
|
Tip: When you must use this function on NTEXT values, use the CONVERT or TO_CHAR function to convert the NTEXT value to TEXT. |
The group of bytes for which you are searching. When bytes is a multiline value, FINDBYTES ignores all lines except the first one.
When bytes is not found in text-expression, FINDBYTES returns zero. When the group of bytes occurs more than once, FINDBYTES returns the position of its first occurrence.
An INTEGER expression that specifies the byte position where the search in text-expression should start. The default is at position 1 (the first byte) in text-expression.
Specifies that FINDBYTES should return the line number instead of the byte position of the beginning of the specified text.
Examples
Example 7-95 Finding the Starting Position of a Byte Group
This example shows how to find the starting position of various groups of bytes in the literal TEXT value hellotherejoe.
The statement
SHOW FINDBYTES('hellotherejoe', 'joe')
produces the following output.
11
The statement
SHOW FINDBYTES('hellotherejoe', 'al')
produces the following output.
0
The VARCACHE option specifies whether Oracle OLAP stores or caches all variable data that is the result of the execution of an AGGREGATE function or $NATRIGGER property expression.
|
Important: The value of the VARCACHE option is only one factor that Oracle OLAP uses to determine whether variable data computed when the AGGREGATE function or $NATRIGGER property executes is stored or cached. For a discussion of the other factors and their interrelationship, see "How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER" and "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data". |
Syntax
VARCACHE = {VARIABLE | SESSION | NONE}
Parameters
Specifies that Oracle OLAP stores the data in the variable in the Database. When you specify this option, the results of the calculation are permanently stored in the variable when the analytic workspace is updated and committed.
Specifies that Oracle OLAP caches the calculated data in the session cache (See "What is an Oracle OLAP Session Cache?"). When you specify this option, the results of the calculation are ignored during updates and commits and are discarded after the session.
|
Important: When SESSCACHE is set toNO, Oracle OLAP does not cache the data even when you specify SESSION. In this case, specifying SESSION is the same as specifying NONE. |
For data that is calculated on the fly using the AGGREGATE function, specifies that Oracle OLAP calculates the data each time the AGGREGATE function executes; Oracle OLAP does not store or cache the data calculated by the AGGREGATE function
Usage Notes
The VARCACHE Option Can Affect All Variables
When you set the VARCACHE option, its setting can affect all variables. When you have not set the $VARCACHE property on a variable and there is no CACHE statement in the aggmaps that you use with the AGGREGATE function to calculate data on the fly, then it is the VARCACHE option that determines how or if that data is stored.
The LD command adds the description to the current object definition. The description consists of text that you specify to describe the object. You can assign a description to any type of definition.
|
Tip: The current object definition is the definition of the object that has been most recently defined or considered during the current session. To make an object definition the current definition, use a CONSIDER statement. |
Syntax
LD [text]
Parameters
The text of the description you want to assign to the definition. When text is omitted, any existing description for the current definition is deleted.
You can create a multiline description by using a hyphen as a continuation character. However, you cannot create a description with an initial blank line with an LD statement.
Examples
Example 10-13 Adding a Description to the Definition of a Variable
This example changes the description associated with the variable units. First, execute the CONSIDER statement to make units the current definition. Then use a LD statement to assign a new description. The units variable has the following definition.
DEFINE units VARIABLE INTEGER <month product district> LD Actual Unit Shipments
The statements
CONSIDER units ld Actual Unit Shipments for Each Division DESCRIBE units
produce the following definition for units.
DEFINE units VARIABLE INTEGER <month product district> LD Actual Unit Shipments for Each Division
The UNHIDE command makes visible the text of a program that has been made invisible by a HIDE statement. To use UNHIDE, you must know the seed expression that was used with the HIDE statement when the program was hidden.
|
Note: The HIDE command performs simple encoding. For information on using secure encryption and other security features in Oracle, see Oracle Database Security Guide. |
Syntax
UNHIDE prog-name seed-exp
Parameters
The name of a program whose text has been made invisible by using the HIDE statement. Do not enclose the program name in quotes.
The single-line text expression that was used in the HIDE statement when "prog-name" was hidden. The seed expression must be byte-for-byte the same value as you used in the HIDE statement. Also, since the seed expression is case-sensitive, specify uppercase and lowercase characters carefully.
Usage Notes
Forgetting the Seed Expression
When you want to use an UNHIDE statement on a program but you have forgotten the seed expression, you can call Oracle OLAP Products Technical Support for help in solving your problem. Before calling, make a connection to Oracle OLAP from OLAP Worksheet, and in Oracle OLAP, attach the analytic workspace that contains the hidden program.
Examples
The INSCOLS function inserts into the columns of a multiline TEXT value all the columns of another TEXT value. The inserted columns are placed after the column position you specify, and the original columns in each line are moved to the right. The function returns a multiline TEXT value composed of the resulting columns.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
The number of lines in the return value is always the same as the number of lines in text-expression. When the columns TEXT expression has fewer lines, INSCOLS repeats its last line in each subsequent line of the return value.
Syntax
INSCOLS(text-expression columns [after])
Parameters
The expression into which you want to insert columns.
The expression containing one or more columns in each line. All the columns of this expression is inserted into the corresponding lines of text-expression.
An INTEGER between 0 and 4,000 representing the column position after which columns should be inserted. The column position of the first character in each line is 1. When you do not specify after, insertion begins at the end of each line. The total length of a line cannot exceed 4,000 columns of single-byte characters or 2,000 columns of double-byte characters.
When you specify an after column that is to the right of the last character in a given line in text-expression, the corresponding line in the return value has spaces filling in the intervening columns.
Examples
Example 7-121 Inserting Text Columns
In the following example, a color code (stored in the multiline TEXT value itemcolor) is inserted into item identifiers that are stored in the itemid text value. The columns are inserted after Column 3.
itemcolor has the following value.
Blu Red Gre Ora
itemid has the following value.
542-Fra 379-Eng 968-USA 369-Can
The INSCOLS function call
INSCOLS(itemid itemcolor 3)
returns the following.
542Blu-Fra 379Red-Eng 968Gre-USA 369Ora-Can
The ZSPELL option holds the default text that is used for representing numeric zero values in output produced by the HEADING, REPORT, and ROW commands.
Data Type
TEXT
Syntax
ZSPELL = {'text'|'OFF'}
Parameters
The spelling to use as the default spelling for numeric zero values. When you specify an expression rather than a text literal, you can omit the single quotes.
(Default) Shows a zero (0) with the appropriate number of decimal places (determined by a DECIMAL attribute) for each numeric zero value.
Usage Notes
Assigning Zero Values
ZSPELL affects output only; it does not affect the way you assign a zero value. For example, even when you have set ZSPELL to NONE, you still assign a zero value as follows.
var1 = 0
Showing Decimal Places
The default of OFF means that a zero value is shown as 0 (zero), with the number of decimal places indicated by a DECIMAL attribute (for example, 0.00). When you set ZSPELL to the text character 0, zero values are shown as a 0 with no decimal places, regardless of any DECIMAL specification.
Effect of ZSPELL on Values Close to Zero
When your output includes a small number, such as 0.004, the number of decimal places shown affects whether ZSPELL treats the number as zero. See Example 5-118, "Showing Very Small Numbers".
Examples
Example 5-117 Showing Zero Values as NONE
This example changes the value of ZSPELL, so that a zero value in the DECIMAL variable testvar is shown as NONE in report output. When ZSPELL is set to its default value of OFF, the Oracle OLAP statements
testvar = 0.00 ROW testvar
produce the following output.
0.00
In contrast, these OLAP DML statements
ZSPELL = 'NONE' ROW testvar
produce the following output.
NONE
Example 5-118 Showing Very Small Numbers
This example illustrates how the number of decimal places shown in output affects whether ZSPELL treats very small numbers as zeros. When ZSPELL is set to its default value of OFF, these OLAP DML statements
ZSPELL = 'OFF' testvar = 0.004 ROW DECIMAL 3 testvar
produce the following output.
0.004
The following statements set ZSPELL to NONE and specify two decimal places for the output.
ZSPELL = 'NONE' ROW DECIMAL 2 testvar
These statements produce the following output.
NONE
With ZSPELL still set to NONE, the following statement specifies three decimal places for the output.
ROW DECIMAL 3 testvar
This statement produces the following output.
0.004
For expressions dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the ENDOF function returns the last date of a time period that is first in the current status list of the dimension.
ENDOF is particularly useful when the dimension has a phase that differs from the default or when the time periods are formed from multiple weeks or years. For example, when the dimension has four-week time periods, the ENDOF function identifies the final date of a particular four-week period.
Return Value
DATE-only or text
Syntax
ENDOF(dwmqy-dimension)
Parameters
A dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. When you have explicitly defined your own relation between dimensions of this type, you can use the name of this time relation here.
Examples
Example 7-76 Finding the Fiscal Year End Date
The following statements define a year dimension (called taxyear, for a tax year that begins in July), add dimension values for tax years 1998 through 2000, and produce a report showing the last date of each tax year.
DEFINE taxyear DIMENSION YEAR BEGINNING july VNF 'TY<ffb>' MAINTAIN taxyear ADD '01july98' '01july00' REPORT W 14 ENDOF(taxyear)
These statements produce the following output.
TAXYEAR ENDOF(TAXYEAR) -------------- -------------- TY98 30JUN99 TY99 30JUN00 TY00 30JUN01
The COMMIT command executes a SQL COMMIT statement. When you want changes that you have made in an analytic workspace to be committed when you execute the COMMIT command, then you must first update the workspace using an UPDATE statement. UPDATE moves changes from a temporary work area to the database table in which the workspace is stored. Changes that have not been moved to the table are not committed. When you do not use UPDATE and COMMIT statements, changes made to an analytic workspace during your session are discarded when you end your Oracle session.
When you execute a SQL COMMIT statement in your database session, all changes made in your session (including all updated changes in workspaces that you have attached with read/write access) are committed. All committed changes are visible to other users who subsequently attach the workspace. However, another user's UPDATE and COMMIT statements do not affect your view of an already attached workspace.
|
Note: Many users execute DML statements using SQL*Plus® or OLAP Worksheet. Both of these tools automatically execute a COMMIT statement when you end your session |
Syntax
COMMIT
Examples
This chapter contains information about the following:
In the OLAP DML, as in other languages, a data type is a collection of values and the definition of one or more operations on those values.
The Oracle OLAP DML supports the data types outlined in Table 2-1, "Summary of OLAP DML Data Types".
Table 2-1 Summary of OLAP DML Data Types
| Data Type | Abbreviation | Description |
|---|---|---|
|
|
BOOL |
Represents the logical |
|
|
None |
Does not correspond to the SQL data type of the same name; but, instead, is an older data type that is unique to the OLAP DML. Day, month, and year data (but not hour and minute data) between January 1, 1000 A.D. and December 31, 9999 A.D. |
|
|
None |
Corresponds to the SQL Valid date range from January 1, 4712 BC to December 31, 9999 AD. The default format is determined explicitly by the |
|
|
None |
Corresponds to the SQL Year, month, and day values of date, and hour, minute, and second values of time up to a precision of 9 places for the fractional part of the |
|
|
None |
Corresponds to the SQL All values of |
|
|
Corresponds to the SQL All values of
The default format is determined explicitly by the | |
|
|
None |
Corresponds to the SQL Stores a period of time in days, hours, minutes, and seconds. |
|
|
None |
Corresponds to the SQL Stores a period of time in years and months. |
|
|
INT |
A whole number in the range of (-2**31) to (2**31)-1. |
|
|
SHORTINT |
A whole number in the range of (-2**15) to (2**15)-1. |
|
|
LONGINT |
A whole number in the range of (-2**63) to (2**63)-1. |
|
|
DEC |
A decimal number with up to 15 significant digits in the range of -(10**308) to +(10**308). |
|
|
SHORT |
A decimal number with up to 7 significant digits in the range of -(10**38) to +(10**38). |
|
|
None |
A decimal number with up to 38 significant digits in the range of -(10**125) to +(10**125). |
|
|
None |
Up to 4,000 bytes for each line in the Database character set. This data type is equivalent to the |
|
|
None |
Up to 4,000 bytes for each line in UTF-8 character encoding. This data type is equivalent to the |
|
|
None |
Up to 8 single-byte characters for each line in the database character set. ( |
|
|
None |
Raw binary data of length size bytes. Maximum size is 2000 bytes. You must specify size for a RAW value. (Note that when defining a variable of this data type you specify the RANSPACE64 keyword in the DEFINE VARIABLE statement to increase the maximum number of characters for the values of the variable from nearly |
|
|
None. |
Base 64 string representing the unique address of a row in its table. This data type is primarily for values returned by the ROWID pseudocolumn. |
|
|
None |
Base 64 string representing the logical address of a row of an index-organized table. The optional size is the size of a column of type UROWID. The maximum size and default is 4,000 bytes. |
|
|
Specified for arguments and temporary variables in an OLAP DML program when you want to handle arguments without converting values to a specific data type. Use the WKSDATA function to retrieve the data type of an argument with a |
Categories of Data Types
Frequently, these data types are thought of as belonging to the following categories:
Numeric Data Types which are INTEGER, SHORTINTEGER, LONGINTEGER, DECIMAL, SHORTDECIMAL, and NUMBER
Text Data Typeswhich are TEXT, NTEXT and ID.
Datetime and Interval Data Types which includes the datetime data types of DATETIME, TIMESTAMP, TIMESTAMP_TZ, and TIMESTAMP-LTZ and the interval data types of DSINTERVAL and YMINTERVAL.
Date-only Data Type which is the DATE data type that is unique to the OLAP DML.
Boolean Data Type which is BOOLEAN.
Row Identifier Data Types which are ROWID and UROWID.
Which OLAP DML Data Objects Can Have Which Data Type?
Different objects support the use of different data types for their values:
For variables, all of the data types are supported.
For dimensions and surrogates, the INTEGER, NUMBER, TEXT, ID (simple dimensions only), NTEXT, DATETIME, TIMESTAMP, TIMESTAMP_TZ, TIMESTAMP-LTZ, DSINTERVAL, and YMINTERVAL data types are supported. Additionally, when you define a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR using a DEFINE DIMENSION (DWMQY) statement, the data type of the values of that dimension are DATE-only.
The numeric data types described in Table 2-2, "OLAP DML Numeric Data Types" are supported.
Table 2-2 OLAP DML Numeric Data Types
| Data Type | Data Value |
|---|---|
|
|
A whole number in the range of (-2**31) to (2**31)-1. |
|
|
A whole number in the range of (-2**15) to (2**15)-1. |
|
|
A whole number in the range of (-2**63) to (2**63)-1. |
|
|
A decimal number with up to 15 significant digits in the range of -(10**308) to +(10**308). |
|
|
A decimal number with up to 7 significant digits in the range of -(10**38) to +(10**38). |
|
|
A decimal number with up to 38 significant digits in the range of -(10**125) to +(10**125). |
For data entry, a value for any of these data types can begin with a plus (+) or minus (-) sign; it cannot contain commas. Note, however, that a comma is required before a negative number that follows another numeric expression, or the minus sign is interpreted as a subtraction operator. Additionally, a decimal value can contain a decimal point. For data display, thousands and decimal markers are controlled by the NLS_NUMERIC_CHARACTERS option.
Most of the numeric data types return NA when a value is outside its range. However, the LONGINTEGER data type does not have overflow protection and returns an incorrect value when, for example, a calculation produces a number that exceeds its range. Use the NUMBER data type instead of LONGINTEGER when this is likely to be a problem.
When you define a NUMBER variable, you can specify its precision (p) and scale (s) so that it is sufficiently, but not unnecessarily, large. Precision is the number of significant digits. Scale can be positive or negative. Positive scale identifies the number of digits to the right of the decimal point; negative scale identifies the number of digits to the left of the decimal point that can be rounded up or down.
The NUMBER data type is supported by Oracle Database standard libraries and operates the same way as it does in SQL. It is used for dimensions and surrogates when a text or INTEGER data type is not appropriate. It is typically assigned to variables that are not used for calculations (like forecasts and aggregations), and it is used for variables that must match the rounding behavior of the Database or require a high degree of precision. When deciding whether to assign the NUMBER data type to a variable, keep the following facts in mind to maximize performance:
Analytic workspace calculations on NUMBER variables is slower than other numeric data types because NUMBER values are calculated in software (for accuracy) rather than in hardware (for speed).
When data is fetched from an analytic workspace to a relational column that has the NUMBER data type, performance is best when the data has the NUMBER data type in the analytic workspace because a conversion step is not required.
The text data types described in Table 2-3, "OLAP DML Text Data Types" are supported by Oracle OLAP.
Table 2-3 OLAP DML Text Data Types
| Data Type | Data Value |
|---|---|
|
|
Up to 4,000 bytes for each line in the database character set. This data type is equivalent to the |
|
|
Up to 4,000 bytes for each line in UTF-8 character encoding. This data type is equivalent to the |
|
|
Up to 8 single-byte characters for each line in the database character set. ( |
Enclose text literals in single quotes. Oracle OLAP recognizes unquoted alpha-numeric values as object names and double quotes as the beginning of a comment.
You can embed quoted strings within a quoted string, which is necessary when you want to specify the base dimension value of a composite or conjoint dimension or when a value includes an apostrophe. Since a single quotation mark is used in Oracle OLAP to indicate a text string, it is considered a special character when used within such a string. Consequently, to specify the literal value of a single quotation mark within a text string, precede the quotation mark with a backslash.
For example, suppose you want to find out if New York and Apple Sauce are a valid combination of base dimension values in the markprod conjoint dimension. The following statement produces the answer YES or NO.
SHOW ISVALUE(markprod, '<\'New York\' \'Apple Sauce\'>')
When embedded quoted strings have a further level of embedding, you must use backslashes before each special character, such as the apostrophe and the backslash that must precede it in "Joe's Deli," as shown in the following statement.
SHOW ISVALUE(markprod, '<\'Joe\\\'s Deli\' \'Apple Sauce\'>')
Table 2-4, "Recognized Escape Sequences" shows escape sequences that are recognized by Oracle OLAP.
Table 2-4 Recognized Escape Sequences
| Sequence | Meaning |
|---|---|
|
|
Backspace |
|
|
Form feed |
|
|
Line feed |
|
|
Carriage return |
|
|
Horizontal tab |
|
|
Double quote |
|
|
Single quote |
|
|
Backslash |
|
|
Character with ASCII code nnn decimal, where \ |
|
|
Character with ASCII code nn hexadecimal, where |
|
|
Character with Unicode nnnn, where |
The Oracle OLAP DML DATE data type does not correspond to the SQL data type of the same name. It is, instead, is an older data type that is unique to the OLAP DML. The OLAP DML DATE data type is a valid data type for variables and for dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR as discussed in the DEFINE DIMENSION (DWMQY) command topic. It is used to store day, month, and year data (but not hour and minute data) between January 1, 1000 A.D. and December 31, 9999 A.D. Because the OLAP DML DATE data type does not include hour and minute data, it is often referred to as the DATE-only data type.
|
Tip: The Oracle OLAP DML data type that corresponds to the SQL DATE data type is namedDATETIME. See DATETIME Data Type for more information. |
A valid input literal value of type DATE must conform to one of three styles: numeric, packed numeric, or month name. You can mix these styles throughout a session.
|
Tip: To determine whether a text expression (such as an expression with a data type of TEXT or ID) represents a valid DATE-only value, use the ISDATE program |
Numeric style
Specify the day, month, and year as three INTEGER values with one or more separators between them, using these rules:
The day and month components can have one digit or two digits.
For any year, the year component can have four digits (for example, 1997). For years in the range 1950 to 2049, the year component can, alternatively, have two digits (50 represents 1950, and so on).
To separate the components, you can use a space, dash (-), slash (/), colon (:), or comma (,).
Examples: '24/4/97' or '24-04-1997'
Packed numeric style
Specify the day, month, and year as three INTEGER values with no separators between them, using these rules:
The day and month components must have two digits. When the day or month is less than 10, it must be preceded by a zero.
For any year, the year component can have four digits (for example, 1997). For years in the range 1950 to 2049, the year component can, alternatively, have two digits (50 represents 1950, and so on).
You cannot use any separators between the date components.
Examples: '240497' or '04241997'
Month name style
Specify the day and year as INTEGER values and the month as text, using these rules:
The month component must match one name listed in the MONTHNAMES option. You can abbreviate the month name to one letter or more, when you supply enough letters to uniquely match the beginning of a name in MONTHNAMES. The case of the letters in the month component (uppercase or lowercase) does not need to match the case in MONTHNAMES.
The day component can have one digit or two digits.
For any year, the year component can have four digits (for example, 1997). For years in the range 1950 to 2049, the year component can, alternatively, have two digits (50 represents 1950, and so on).
When the day and year components are adjacent, they must have at least one separator between them. As separators, you can use a space, dash (-), slash (/), colon (:), or comma (,). When you want, you can place one or more separators between the day and month or between the year and month.
Examples: '24APR97' or '24 ap 97' or 'April 24, 1997'
The format of a DATE -only value of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR is determined by the value name format (VNF) associated with the object. A VNF is a template that controls the input and display format for DATE -only values. The template can include format specifications for any of the components that identify a time period (day, month, calendar year, fiscal year, and period within a fiscal year). You associate a VNF with an object by adding a VNF statement to its definition. When you do not add a VNF to the definition of an object, the object uses the default VNF shown in Table 2-5, "Default VNFs for DWMQY Dimensions".
Table 2-5 Default VNFs for DWMQY Dimensions
| Type of Dimension | Default VNF | Example |
|---|---|---|
|
DAY |
<DD><MTXT><YY> |
01JAN95 |
|
WEEK |
W<P>.<FF> |
W1.95 |
|
Multiple WEEK |
<NAME><P>.<FF> |
MYWEEK1.95 |
|
MONTH |
<MTXT><YY> |
JAN95 |
|
Multiple MONTH |
<NAME><P>.<FF> |
MYMONTH1.95 |
|
QUARTER |
Q<P>.<FF> |
Q1.95 |
|
YEAR |
YR<YY> |
YR95 |
DATE-only values have independent input and output formats. You can enter DATE-only values in one style and report them in a different style.
When you show a DATE-only variable value in output, the format depends on the DATEFORMAT option. The default format is a 2-digit day, a 3-letter month, and a 2-digit year; for example, 03MAR97. The text for the month names depends on the MONTHNAMES option. To change the order of the month, day, and year components, see the DATEORDER option.
The OLAP DML has data types that correspond to SQL datetime and interval data types. As outlined in Table 2-6, "OLAP DML Datetime and Interval Data Types and the Corresponding SQL Data Types", the names of the data types are different in OLAP DML than they are in SQL.
Table 2-6 OLAP DML Datetime and Interval Data Types and the Corresponding SQL Data Types
| OLAP DML Data Type | Corresponding SQL Data Type |
|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
In the OLAP DML, the datetime data types are DATETIME, TIMESTAMP, TIMESTAMP_TZ, and TIMESTAMP_LTZ. The interval data types are YMINTERVAL and DSINTERVAL. Both datetimes and intervals are made up of fields as discussed in "Datetime and Interval Fields".
Both datetimes and intervals are made up of fields. The values of these fields determine the value of the data type. Table 2-7, "Datetime Fields and Values" lists the datetime fields and their possible values for datetimes and intervals.
|
Tip: To avoid unexpected results in your operations on datetime data, you can verify the Database and session time zones using DBTIMEZONE and SESSIONTIMEZONE If the time zones have not been set manually, Oracle Database uses the operating system time zone by default. If the operating system time zone is not a valid Oracle time zone, then Oracle uses UTC as the default value. |
Table 2-7 Datetime Fields and Values
| Datetime Field | Valid Values for Datetime Data Types | Valid Values for Interval Data Types |
|---|---|---|
|
|
-4712 to 9999 (excluding year 0) |
Any positive or negative integer |
|
|
01 to 12 |
0 to 11 |
|
|
01 to 31 (limited by the values of |
Any positive or negative integer |
|
|
00 to 23 |
0 to 23 |
|
|
00 to 59 |
0 to 59 |
|
|
00 to 59.9(n), where 9(n) is the precision of time fractional seconds. The 9(n) portion is not applicable for |
0 to 59.9(n), where 9(n) is the precision of interval fractional seconds |
|
|
-12 to 14 (This range accommodates daylight saving time changes.) Not applicable for |
Not applicable |
|
(See note at end of table) |
00 to 59. Not applicable for |
Not applicable |
|
|
Query the For a complete listing of all time zone regions, refer to Oracle Database Globalization Support Guide. |
Not applicable |
|
|
Query the |
Not applicable |
Note: TIMEZONE_HOUR and TIMEZONE_MINUTE are specified together and interpreted as an entity in the format +|- hh:mm, with values ranging from -12:59 to +14:00.
A datetime format template is a template that describes the format of datetime data stored in a character string. A format model does not change the internal representation of the value in the Database. When you convert a character string into a date, a format model determines how Oracle Database interprets the string. In OLAP DML statements, you can use a format model as an argument of the TO_CHAR and TO_DATE functions to specify:
The format for Oracle to use to return a value from the Database
The format for a value you have specified for Oracle to store in the Database
You can use datetime format templates in the following functions:
In the TO_* datetime functions to translate a character value that is in a format other than the default format into a datetime value. (The TO_* datetime functions are TO_CHAR, TO_DATE, TO_TIMESTAMP, TO_TIMESTAMP_TZ, TO_YMINTERVAL, and TO_DSINTERVAL.)
In the TO_CHAR function to translate a datetime value that is in a format other than the default format into a string (for example, to print the date from an application)
The default datetime formats are specified either explicitly with the initialization parameter NLS_DATE_FORMAT or implicitly with the initialization parameter NLS_TERRITORY. You can change the default datetime formats for your session with the ALTER SESSION statement. You can override this default and specify a datetime format for use with a particular OLAP DML object by using the DATE_FORMAT command to add a datetime format to the definition of the object.
The following additional formatting rules apply when converting string values to datetime values (unless you have used the FX or FXFM modifiers in the format model to control exact format checking):
You can omit punctuation included in the format string from the date string if all the digits of the numeric format elements, including leading zeros, are specified. In other words, specify 02 and not 2 for two-digit format elements such as MM, DD, and YY.
You can omit time fields found at the end of a format string from the date string.
If a match fails between a datetime format element and the corresponding characters in the date string, then Oracle attempts alternative format elements, as shown in Table 2-8, "Oracle Format Matching".
The OLAP DML DATETIME data type corresponds to the SQL DATE data type. As such, the format and language of DATETIME values are controlled by the settings of the NLS_DATE_FORMAT and NLS_DATE_LANGUAGE options. The DATETIME data type is supported by Oracle Database standard libraries and operates the same way in the OLAP DML as it does the DATE data type in SQL.
You can specify a DATETIME value as a string literal, or you can convert a character or numeric value to a date value with the TO_DATE function.
To specify a DATETIME value as a literal, you must use the Gregorian calendar. You can specify an ANSI literal, as shown in this example:
DATETIME '1998-12-25'
The ANSI date literal contains no time portion, and must be specified in exactly this format ('YYYY-MM-DD').
Alternatively you can specify a DATETIME value us the TO_DATE function and include, as in the following example:
TO_DATE('98-DEC-25 17:30','YY-MON-DD HH24:MI')
The default date format template for an Oracle DATETIME value is specified by the initialization parameter NLS_DATE_FORMAT. This example date format includes a two-digit number for the day of the month, an abbreviation of the month name, the last two digits of the year, and a 24-hour time designation.
Oracle automatically converts character values that are in the default datetime format into datetime values when they are used in datetime expressions.
If you specify a datetime value without a time component, then the default time is midnight (00:00:00 or 12:00:00 for 24-hour and 12-hour clock time, respectively). If you specify a datetime value without a date, then the default date is the first day of the current month.
Values of DATETIME always contain both the date and time fields. Therefore, if you use DATETIME values in an expression, you must either specify the time field in your query or ensure that the time fields in the DATETIME values are set to midnight. Otherwise, Oracle may not return the results you expect. You can use the TRUNC (date) function to set the time field to midnight, or you can include a greater-than or less-than condition in the query instead of an equality or inequality condition. However, if the expression contains DATETIME values other than midnight, then you must filter out the time fields in the query to get the correct result.
The date function SYSDATE returns the current system date and time. The function CURRENT_DATE returns the current session date. For information on SYSDATE, the TO_* datetime functions, and the default date format, see "Datetime functions" and the DATE_FORMAT command.
The TIMESTAMP data type is an extension of the DATETIME data type. It stores the year, month, and day of the DATETIME data type, plus hour, minute, and second values. This data type is useful for storing precise time values.
SHOW SYSDATE
26-JUL-06
DEFINE mytimestamp VARIABLE TIMESTAMP
mytimestamp = SYSDATE
COLWIDTH = 30
REPORT mytimestamp
MYTIMESTAMP
------------------------------
26-JUL-06 10.44.42 AM
The TIMESTAMP data type stores year, month, day, hour, minute, and second, and fractional second values. When you specify TIMESTAMP as a literal, the fractional seconds precision value can be any number of digits up to 9, as follows:
TIMESTAMP '1997-01-31 09:26:50.124'
TIMESTAMP_TZ corresponds to the SQL TIMESTAMP WITH TIMEZONE data type. It is a variant of TIMESTAMP that includes a time zone offset in its value. The time zone offset is the difference (in hours and minutes) between local time and UTC (Coordinated Universal Time—formerly Greenwich Mean Time). This data type is useful for collecting and evaluating date information across geographic regions.
Oracle time zone data is derived from the public domain information available at ftp://elsie.nci.nih.gov/pub/. Oracle time zone data may not reflect the most recent data available at this site.
The TIMESTAMP_TZ data type is a variant of TIMESTAMP that includes a time zone offset. When you specify TIMESTAMP_TZ as a literal, the fractional seconds precision value can be any number of digits up to 9. For example:
TIMESTAMP '1997-01-31 09:26:56.66 +02:00'
Two TIMESTAMP_TZ values are considered identical if they represent the same instant in UTC, regardless of the TIME ZONE offsets stored in the data. For example,
TIMESTAMP '1999-04-15 8:00:00 -8:00'
equals
TIMESTAMP '1999-04-15 11:00:00 -5:00'
That is, 8:00 a.m. Pacific Standard Time equals 11:00 a.m. Eastern Standard Time.
You can replace the UTC offset with the TZR (time zone region) format element. For example, the following example has the same value as the preceding example:
TIMESTAMP '1999-04-15 8:00:00 US/Pacific'
To eliminate the ambiguity of boundary cases when the daylight saving time switches, use both the TZR and a corresponding TZD format element. The following example ensures that the preceding example returns a daylight saving time value:
TIMESTAMP '1999-10-29 01:30:00 US/Pacific PDT'
You can also express the time zone offset using a datetime expression.
If you do not add the TZD format element, and the datetime value is ambiguous, then Oracle returns an error if you have the ERROR_ON_OVERLAP_TIME session parameter set to TRUE. If that parameter is set to FALSE, then Oracle interprets the ambiguous datetime as standard time in the specified region.
TIMESTAMP_LTZ corresponds to the SQL TIMESTAMP WITH LOCAL TIMEZONE data type. It is another variant of TIMESTAMP that includes a time zone offset in its value. It differs from TIMESTAMP_LTZ in that data stored in the Database is normalized to the database time zone, and the time zone offset is not stored as part of the column data. When a user retrieves the data, Oracle returns it in the user's local session time zone. The time zone offset is the difference (in hours and minutes) between local time and UTC (Coordinated Universal Time—formerly Greenwich Mean Time). This data type is useful for displaying date information in the time zone of the client system in a two-tier application.
Oracle time zone data is derived from the public domain information available at ftp://elsie.nci.nih.gov/pub/. Oracle time zone data may not reflect the most recent data available at this site.
The TIMESTAMP_LTZ data type differs from TIMESTAMP_TZ in that data stored in the Database is normalized to the database time zone. The time zone offset is not stored as part of the column data. There is no literal for TIMESTAMP_LTZ. Rather, you represent values of this data type using any of the other valid datetime literals. The table that follows shows some formats you can use to add a TIMESTAMP_LTZ value into object, along with the corresponding value returned by a OLAP DML statement such as a SHOW command.
| Value Specified When Adding Value | Value Returned |
|---|---|
'19-FEB-2004' | 19-FEB-2004.00.00.000000 AM |
SYSTIMESTAMP | 19-FEB-04 02.54.36.497659 PM |
TO_TIMESTAMP('19-FEB-2004', 'DD-MON-YYYY')); | 19-FEB-04 12.00.00.000000 AM |
SYSDATE | 19-FEB-04 02.55.29.000000 PM |
TO_DATE('19-FEB-2004', 'DD-MON-YYYY')); | 19-FEB-04 12.00.00.000000 AM |
TIMESTAMP'2004-02-19 8:00:00 US/Pacific'); | 19-FEB-04 08.00.00.000000 AM |
Notice that if the value specified does not include a time component (either explicitly or implicitly, then the value returned defaults to midnight.
YMINTERVAL corresponds to the SQL INTERVAL YEAR TO MONTH data type. It stores a period of time using the YEAR and MONTH datetime fields. This data type is useful for representing the difference between two datetime values when only the year and month values are significant.
Specify YMINTERVAL interval literals using the following syntax.
INTERVAL 'integer [- integer ]' YEAR|MONTH [(precision) ] [TO YEAR | MONTH ]
where
'integer [-integer]' specifies integer values for the leading and optional trailing field of the literal. If the leading field is YEAR and the trailing field is MONTH, then the range of integer values for the month field is 0 to 11.
precision is the maximum number of digits in the leading field. The valid range of the leading field precision is 0 to 9 and its default value is 2.
If you specify a trailing field, it must be less significant than the leading field. For example, INTERVAL '0-1' MONTH TO YEAR is not valid.
The following YMINTERVAL literal indicates an interval of 123 years, 2 months:
INTERVAL '123-2' YEAR(3) TO MONTH
Examples of the other forms of the literal follow, including some abbreviated versions:
| Form of Interval Literal | Interpretation |
|---|---|
INTERVAL '123-2' YEAR(3) TO MONTH | An interval of 123 years, 2 months. You must specify the leading field precision if it is greater than the default of 2 digits. |
INTERVAL '123' YEAR(3) | An interval of 123 years 0 months. |
INTERVAL '300' MONTH(3) | An interval of 300 months. |
INTERVAL '4' YEAR | Maps to INTERVAL '4-0' YEAR TO MONTH and indicates 4 years. |
INTERVAL '50' MONTH | Maps to INTERVAL '4-2' YEAR TO MONTH and indicates 50 months or 4 years 2 months. |
INTERVAL '123' YEAR | Returns an error, because the default precision is 2, and '123' has 3 digits. |
You can add or subtract one INTERVAL YEAR TO MONTH literal to or from another to yield another INTERVAL YEAR TO MONTH literal. For example:
INTERVAL '5-3' YEAR TO MONTH + INTERVAL'20' MONTH = INTERVAL '6-11' YEAR TO MONTH
DSINTERVAL corresponds to the SQL INTERVAL DAY TO SECOND data type. It stores a period of time in terms of days, hours, minutes, and seconds. This data type is useful for representing the precise difference between two datetime values.
Specify DSINTERVAL interval literals using the following syntax.
INTERVAL 'integer|integer time_expr|time_expr
DAY|HOUR|MINUTE [(leading_precision)] | SECOND [leading_precision[, fractional_seconds_precision ])]
[ TO DAY|HOUR|MINUTE|SECOND [(fractional_seconds_precision) ]]
where
integer specifies the number of days. If this value contains more digits than the number specified by the leading precision, then Oracle returns an error.
time_expr specifies a time in the format HH[:MI[:SS[.n]]] or MI[:SS[.n]] or SS[.n], where n specifies the fractional part of a second. If n contains more digits than the number specified by fractional_seconds_precision, then n is rounded to the number of digits specified by the fractional_seconds_precision value. You can specify time_expr following an integer and a space only if the leading field is DAY.
leading_precision is the number of digits in the leading field. Accepted values are 0 to 9. The default is 2.
fractional_seconds_precision is the number of digits in the fractional part of the SECOND datetime field. Accepted values are 1 to 9. The default is 6.
If you specify a trailing field, it must be less significant than the leading field. For example, INTERVAL MINUTE TO DAY is not valid. Because of this restriction, if SECOND is the leading field, the interval literal cannot have any trailing field.
The valid range of values for the trailing field are as follows:
HOUR: 0 to 23
MINUTE: 0 to 59
SECOND: 0 to 59.999999999
Examples of the various forms of DSINTERVAL literals follow, including some abbreviated versions:
| Form of Interval Literal | Interpretation |
|---|---|
INTERVAL '4 5:12:10.222' DAY TO SECOND(3) | 4 days, 5 hours, 12 minutes, 10 seconds, and 222 thousandths of a second. |
INTERVAL '4 5:12' DAY TO MINUTE | 4 days, 5 hours and 12 minutes. |
INTERVAL '400 5' DAY(3) TO HOUR | 400 days 5 hours. |
INTERVAL '400' DAY(3) | 400 days. |
INTERVAL '11:12:10.2222222' HOUR TO SECOND(7) | 11 hours, 12 minutes, and 10.2222222 seconds. |
INTERVAL '11:20' HOUR TO MINUTE | 11 hours and 20 minutes. |
INTERVAL '10' HOUR | 10 hours. |
INTERVAL '10:22' MINUTE TO SECOND | 10 minutes 22 seconds. |
INTERVAL '10' MINUTE | 10 minutes. |
INTERVAL '4' DAY | 4 days. |
INTERVAL '25' HOUR | 25 hours. |
INTERVAL '40' MINUTE | 40 minutes. |
INTERVAL '120' HOUR(3) | 120 hours. |
INTERVAL '30.12345' SECOND(2,4) | 30.1235 seconds. The fractional second '12345' is rounded to '1235' because the precision is 4. |
You can add or subtract one DAY TO SECOND interval literal from another DAY TO SECOND literal. For example.
INTERVAL'20' DAY - INTERVAL'240' HOUR = INTERVAL'10-0' DAY TO SECOND
A BOOLEAN data type enables you to represent logical values. In code, BOOLEAN values are represented by values for "no" and "yes" (in any combination of uppercase and lowercase characters). The actual values that are recognized in your version of Oracle OLAP are determined by the language identified by the NLS_LANGUAGE option. You can use the read-only NOSPELL and YESSPELL options to obtain the values represent BOOLEAN values. In English language code, you can represent BOOLEAN values, using:
YES, TRUE, ON
NO, FALSE, OFF
Working with BOOLEAN expressions is discussed in "Boolean Expressions".
The RAW data type stores data that is not to be interpreted (that is, not explicitly converted when moving data between different systems) by Oracle Database. The RAW data type is intended for binary data or byte strings.
The syntax for specifying RAW data is as follows:
RAW (size)
where you must specify a size up to the maximum of 2000 bytes
RAW is a variable-length data type, however Oracle Net (which connects user sessions to the instance) and Oracle Database utilities do not perform character conversion when transmitting RAW data.
When Oracle automatically converts RAW data to and from text data, the binary data is represented in hexadecimal form, with one hexadecimal character representing every four bits of RAW data. For example, one byte of RAW data with bits 11001011 is displayed and entered as CB.
The row identifier data types are used to store an address of a row in a relational table. The OLAP DML supports two different data types that you can use to copy this data from a relational table into objects in an analytic workspace:
You can examine a row address of a relational table by querying the pseudocolumn ROWID. Values of this pseudocolumn are strings representing the address of each row. These strings have the data type ROWID.
|
Note: Although you can create relational tables and clusters that contain actual columns having the ROWID data type. Oracle Database does not guarantee that the values of such columns are valid rowids |
The extended ROWID data type stored in a user column includes the data in the restricted rowid plus a data object number. The data object number is an identification number assigned to every database segment. You can retrieve the data object number from the data dictionary views USER_OBJECTS, DBA_OBJECTS, and ALL_OBJECTS. Objects that share the same segment (clustered tables in the same cluster, for example) have the same object number.
Extended rowids are stored as base 64 values that can contain the characters A-Z, a-z, 0-9, and the plus sign (+) and forward slash (/). Extended rowids are not available directly. You can use a supplied package, DBMS_ROWID, to interpret extended rowid contents. The package functions extract and provide information that would be available directly from a restricted rowid as well as information specific to extended rowids.
The rows of some relational tables have addresses that are not physical or permanent or were not generated by Oracle Database. For example, the row addresses of index-organized tables are stored in index leaves, which can move. Rowids of foreign tables (such as DB2 tables accessed through a gateway) are not standard Oracle rowids.
Oracle uses universal rowids (urowids) to store the addresses of index-organized and foreign tables. Index-organized tables have logical urowids and foreign tables have foreign urowids. Both types of urowid are stored in the ROWID pseudocolumn (as are the physical rowids of heap-organized tables).
Oracle creates logical rowids based on the primary key of the table. The logical rowids do not change if the primary key does not change. The ROWID pseudocolumn of an index-organized table has a data type of UROWID. You can access this pseudocolumn as you would the ROWID pseudocolumn of a heap-organized table (that is, using a SELECT ... ROWID statement). To store the rowids of an index-organized table, then define a column of type UROWID for the table and retrieve the value of the ROWID pseudocolumn into that column.
In may cases, Oracle OLAP performs automatic data type conversion for you as discussed in "Automatic Conversion of Textual Data Types" and "Automatic Conversion of Numeric Data Types". Additionally there area number of OLAP DML functions that you can use to convert values from one data type to another.
Oracle OLAP automatically converts NTEXT values to TEXT when they are specified as arguments to OLAP DML statements. This can result in data loss when the NTEXT values cannot be represented in the database character set
Oracle OLAP automatically converts SHORTINTEGER variables and INTEGER variables (with a fixed width of 1 byte to INTEGER (with a width of 4 bytes) for calculations. When you calculate a total of SHORTINTEGER variables, then you can obtain and report a result greater than 32,767 or less than -32,768. When you calculate a total of 1-byte INTEGER variables, then you can obtain and report a result greater than 127 or less than -128. However, when you try to assign the result to a SHORTINTEGER variable or a 1-byte INTEGER variable respectively, then the variable is set to NA.
Oracle OLAP automatically converts numeric data types according to the following rules:
When you use a value with the SHORTINTEGER or SHORTDECIMAL data type in an expression, then the value is converted to its long counterpart before using it. See "Boolean Expressions" for information about problems that can occur when you mix SHORTDECIMAL and DECIMAL data types in a comparison expression.
When you save the results of a calculation as a value with the SHORTINTEGER data type, then NA is stored when the result is outside the range of a SHORTINTEGER (-32768 to 32767).
When you assign the value of a DECIMAL expression to an object with the INTEGER data type, then the value is rounded before storing or using it.
|
Note: When aDECIMAL value is outside the range of an INTEGER, then an NA is stored. |
When you use a decimal value where a value with the INTEGER data type is required, then the value is rounded before storing or using it.
|
Note: When the DECIMAL value is outside the range of an INTEGER, then an NA is stored. |
When you assign the value of a decimal expression to a variable with the SHORTDECIMAL data type, then only the first 7 significant digits are stored.
When you combine NUMBER values with other numeric data types, then all values are converted to NUMBER.
When these conversion are not what you want, then you can use the CONVERT, TO_CHAR, TO_NCHAR, TO_NUMBER, or TO_DATE functions to get different results.
An operator is a symbol that transforms a value or combines it in some way with another value. Table 2-9, "OLAP DML Operators" describes the categories of OLAP DML operators.
Table 2-9 OLAP DML Operators
| Category | Description |
|---|---|
|
Arithmetic |
Operators that you can use in numeric expressions with numeric data to produce a numeric result. You can also use some arithmetic operators in date expressions with a mix of date and numeric data, which returns either a date or numeric result. For a list of arithmetic operators, see "Arithmetic Operators". For more information on numeric expressions, see "Numeric Expressions" |
|
Comparison |
Operators that you can use to compare two values of the same basic type (numeric, text, date, or, in rare cases, Boolean), which returns a |
|
Logical |
The |
|
Assignment |
An operator that you use to assign the results of an expression into an object or to assign a value to an OLAP DML option. For more information on using assignment statements, see the SET, and SET1 commands, and "Assignment Operator". |
|
Conditional |
The |
|
Substitution |
The |
Table 2-10, "Arithmetic Operators" shows the OLAP DML arithmetic operators, their operations, and priority where priority is the order in which that operator is evaluated. Operators of the same priority are evaluated from left to right. When you use two or more operators in a numeric expression, the expression is evaluated according to standard rules of arithmetic. You must code a comma before a negative number that follows another numeric expression, or the minus sign is interpreted as a subtraction operator. For example, intvar,-4
You use comparison and logical operators to make expressions in much the same way as arithmetic operators. Each operator has a priority that determines its order of evaluation. Operators of equal priority are evaluated left to right, unless parentheses change the order of evaluation. However, the evaluation is halted when the truth value is decided.
Table 2-11, "Comparison and Logical Operators" shows the OLAP DML comparison operators and logical operators (AND, OR, and NOT). It lists the operator, the operations, example, and priority where priority is the order in which that operator is evaluated. Operators of the same priority are evaluated from left to right.
Table 2-11 Comparison and Logical Operators
| Operator | Operation | Example | Priority |
|---|---|---|---|
|
|
Returns opposite of |
|
1 |
|
|
Equal to |
|
2 |
|
|
Not equal to |
|
2 |
|
|
Greater than |
|
2 |
|
|
Less than |
|
2 |
|
|
Greater than or equal to |
|
2 |
|
|
Less than or equal to |
|
2 |
|
|
Is a date in a time period? |
|
2 |
|
|
Does a text value match a specified text pattern? |
|
2 |
|
|
Both expressions are true |
|
3 |
|
|
Either expression is true |
|
4 |
In the OLAP DML, as in many other programming languages, the = (equal) sign is used as an assignment operator.
An expression creates temporary data; you can display the resulting values, but these values are not automatically stored in your analytic workspace for future reference during a session. You use an assignment statement to store the result of an expression in an object that has the same data type and dimensions as the expression. If you update and commit the object, then the values are available to you in future sessions.
Like other programming languages, an assignment statement in the OLAP DML sets the value of the target expression equal to the results of the source expression. However, an OLAP DML assignment statement does not work exactly as it does in other programming languages. Like many other OLAP DML statements it does not assign a value to a single cell, instead, when the target-expression is a multidimensional object, Oracle OLAP loops through the cells of the target object setting each one to the results of the source-expression. Additionally, you can use UNRAVEL to copy the values of an expression into the cells of a target object when the dimensions of the expression are different from the dimensions of the target object.
For more information on using assignment statements in the OLAP DML, see SET and SET1.
Expressions represent data values in the syntax of the OLAP DML. This section provides the following information about OLAP DML expressions:
Detailed information about the various types of OLAP DML expressions:
An OLAP DML expression has a data type and can also have dimensions. You can use expressions as arguments in statements. An expression often performs a mathematical or logical operation. It always evaluates to a result in a workspace data type.
An expression can be:
A literal value. For example, 10 or 'East'
An analytic workspace object that contains multiple values. For example, the variable sales
A function that returns one or more values. For example, TOTAL or JOINLINES
Another expression that combines literal values, dimensions, variables, formulas, and functions with operators. For example, inflation*1.02
You can save an expression as a formula as described in "OLAP DML Formulas"
The data type of an expression is the data type of the resulting value. It might not be the same as the data type of the data objects that constitute the expression; it depends on the data and on the operators and functions that are involved.
In addition, a conditional expression that is indicated by an IF... THEN...ELSE operator is supported. A conditional expression returns a value whose data type depends on the expressions in the THEN and ELSE clauses, not on the expression in the IF clause, which must be BOOLEAN.
|
Note: Do not confuse a conditional expression with the IF...THEN...ELSE command in a program, which has similar syntax but a different purpose. TheIF statement does not have a data type and is not evaluated like an expression. |
An expression is dimensioned by a union of the dimensions of all of the variables, dimensions, relations, formulas, qualified data references, and functions in the expression:
Variables, relations, and formulas are dimensioned by the dimensions listed in the definition of the object.
Example 1: When the price variable is dimensioned by month and product, then the expression price * 1.2 is also dimensioned by month and product.
Example 2: When the units variable is dimensioned by month, product, and district, then the expression units * price is dimensioned by month, product, and district (even though the dimensions of the price variable are month and product only).
Qualified data references (QDRs) are dimensioned by all of the dimensions of the associated object, except for the dimensions being qualified. (For more information about qualified data references, see "Limiting a Dimension to a Single Value Without Changing Status".)
The return values of most OLAP DML functions are, in most cases, dimensioned by the union of the dimensions of the input arguments. However, some functions (such as aggregation functions) have fewer dimensions than the input arguments. In these cases, the dimensionality of the return value is documented in the topic for the function in Chapter 7, "OLAP DML Functions: A - K".
|
Note: Unless otherwise noted, when you specify breakout dimensions or relations in an aggregation function, you change the dimensionality of the expression. The first dimension that you specify as a breakout dimension is the slowest varying and the last dimension that you specify is the fastest varying. |
|
Note: You can change the dimensionality of an expression or subexpression using the CHGDIMS function |
You can find out the dimensions of an expression by issuing a PARSE statement, followed by the INFO function. PARSE evaluates the text of an expression; the INFO indicates how the expression is interpreted.
This example illustrates the use of the DIMENSION keyword with the INFO function to retrieve the dimensions of the expression just analyzed by PARSE. Assume that you issue the following statement.
PARSE 'TOTAL(sales region)'
The statement produces the following output.
SHOW INFO(PARSE DIMENSION) REGION
The number of values an expression yields depends on the dimensions of the expression and the status of those dimensions. An expression yields one data value for each combination of dimension values in the current status. For example, when three dimension values are in status for month, and two for product, then the expression price GT 100 results in six values (3 times 2).
Thus, to get the desired results, you must ensure that the dimensions of an expression are limited to the range of data you want to consider. In addition, you must consider any PERMIT statements that might limit access to the dimensions of the data.
When you want to specify a single value without changing the current status you can use a qualified data reference (QDR). Using a QDR, you can qualify a dimension (which enables you to specify one dimension value in an expression) or one or more dimensions of a variable or relation. For more information on dimension status, see "How to Specify the Set of Data that OLAP DML Operations Work Against"; for more information on QDRs, see "Limiting a Dimension to a Single Value Without Changing Status".
You can use an analytic workspace data object in an expression by specifying its name as described in "Syntax for Specifying an Object in an Expression". When calculating the expression, Oracle OLAP uses the data in the specified object as described in "How OLAP DML Data Objects Behave in Expressions".
Table 2-12 summarizes how Oracle OLAP uses the data in an object used as an argument in an expression.
Table 2-12 Objects in Expressions
| Object | Use in Expressions |
|---|---|
|
Variables |
As a one-dimensional or multi-dimensional array of data, depending on its definition. For example, as the target or source expression in an assignment statement. See also: "Using Variables and Relations in Expressions" and "Using Objects in Assignment Statements". |
|
Relations |
As a one-dimensional or multi-dimensional of data, depending on its definition. For example, as the target or source expression in an assignment statement as outlined in "Using Objects in Assignment Statements".
See also: "Using Variables and Relations in Expressions" , "Using Related Dimensions in Expressions". |
|
Dimensions |
As a one-dimensional array of data. When you use a See also: "Specifying a Value of a CONCAT Dimension" and "Using Related Dimensions in Expressions". |
|
Composites |
You can use a composite wherever you can use a dimension. See also: "Specifying a Value of a Composite" . |
|
Valuesets |
As a list of dimension values. See also: "Using Variables and Relations in Expressions" and the DEFINE VALUESET command. |
|
Dimension surrogates |
As a one-dimensional array. A surrogate provides an alternative set of values for a dimension. When you use a Note: You can use a surrogate rather than a dimension in a model, in a LIMIT command, in a qualified data reference, or in data loading with statements such as FILEREAD, FILEVIEW, SQL FETCH, and SQL IMPORT. A surrogate cannot be a participant object in any argument in a DEFINE statement that defines another object. |
|
Formulas |
As a sub-expression or as an expression in a statement. |
|
Programs |
For a program that does not return a value, use the program name as you would an OLAP DML command. For a program that returns a value, invoke the program the same way you invoke an OLAP DML function— use the program name in then expression and enclose the program arguments, if any, in parentheses. |
You can specify an analytic workspace object in an expression using the following syntax.
[[schema-name.]analytic-workspace-name!]object-name
The name of the schema in which the analytic workspace was defined when it was created. By default, an analytic workspace is created in the schema for the database user ID of the user issuing the AW CREATE statement. In almost any DML statement, you can specify the full name of an analytic workspace (for example, Scott.demo).
The name of the workspace that contains the desired object. By specify the analytic workspace name along with the object name you create a qualified object name (QON) for the object. Using a qualified object name for an object is recommended except in those situations described in "When Not to Use Qualified Object Names".
You can specify the value for analytic-workspace-name in any of the following ways:
The name of an analytic workspace. A workspace name is assigned when an analytic workspace is created with an AW CREATE statement.
The alias name of an analytic workspace. An analytic workspace alias is an alternative name for an attached analytic workspace. You can assign or delete an alias with an AW ALIAS LIST statement. An alias is in effect from the time it is assigned to the time that the workspace is detached (or until the alias is deleted). Therefore, each time you attach an unattached workspace, you must reassign its aliases.
One reason for assigning an alias is to have a short way to reference an analytic workspace that belongs to a schema that is not yours. For example, you can use the alias in qualified object names and statements that reference such an analytic workspace. Another reason for assigning an alias is to write generic code that includes a reference to an analytic workspace but does not hard-code its name. With the alias providing a generic reference, you can assign the alias and run the code on different workspaces at different times.
Within an aggregation specification, model, or program, you can use THIS_AW to qualify an object name. When Oracle OLAP compiles an object, it interprets any occurrence of THIS_AW as the name of the workspace in which the object is being compiled. Thus if you have an analytic workspace named myworkspace that contains a program named myprog and a variable named myvar, Oracle OLAP interprets a statement myvar=1 as though it was written myworkspace!myvar=1. Within a program, you can retrieve the value of THIS_AW using the THIS_AW option.
When you do not specify a value for analytic-workspace-name, Oracle OLAP assumes that the specified object is in the current analytic workspace. The current analytic workspace is the first analytic workspace in the list of the active analytic workspaces that you view with an AW LIST statement. You can retrieve the name of the current analytic workspace by using the AW function with the NAME keyword.
|
Note: Your session does not have to have a current analytic workspace. When you start Oracle OLAP without specifying an analytic workspace name, then theEXPRESS analytic workspace is first on the list. However, in this case, the EXPRESS analytic workspace is not current; there is no current analytic workspace until you specify one with the AW command. |
The name of the object unless the object is an unnamed composite. When the object is an unnamed composite, use the following syntax.
SPARSE <basedims....>
For the basedims argument, specify the names of the dimensions, separated by spaces, for which the unnamed composite was created. For an example of using an unnamed composite in an OLAP DML statement, see Example 10-104, "Reporting Data Dimensioned by Composites".
Objects with the same name in different workspaces are treated as completely separate objects, and no similarity or relationship is assumed to exist between them. Any OLAP DML language restrictions that apply between objects in different workspaces apply even when the objects have the same name. For example, you cannot dimension an object in one workspace by a dimension that resides in another workspace, even when both workspaces have dimensions with the same name.
Although the use of qualified object names for objects is typical, there are several considerations to keep in mind:
There are some situations where you cannot use a qualified object name or do not need to use a qualified object name. See "When Not to Use Qualified Object Names" for more information
Before you use ampersand substitution when creating a qualified object name you must understand how and when the substitution occurs. See "Using Ampersand Substitution for Workspace and Object Names" for more information.
Special considerations apply when passing a qualified object name as an argument to a program. See "Passing Qualified Object Names to Programs" for more information.
When Not to Use Qualified Object Names
Generally it is good practice to use a qualified object name in an expression. However, there are some situations where you cannot use a qualified object name or when a qualified object name is not necessary:
The following objects cannot have qualified object names:
An object that is local to a particular program because it was created by an ARGUMENT or VARIABLE statement.
The NAME dimension of any given workspace. When you reference the NAME dimension, Oracle OLAP always uses the NAME dimension of the current workspace.
You do not need to use a qualified object name in the following circumstances:
In the qualifiers of a qualified data reference (QDR). Only the object being qualified needs to be named with a qualified object name. Any unqualified names are assumed to apply to objects in the same workspace as the object being qualified.
In an unnamed composite, when you specify one base dimension as a qualified object name, then all the others are assumed to come from the same workspace.
In a named composite, when the name is a qualified object name then its base dimensions are assumed to come from the same workspace.
In a model, when you specify the solution variable as a qualified object name, then all the dimensions named in DIMENSION statements are assumed to come from the same workspace.
Using Ampersand Substitution for Workspace and Object Names
The workspace name, or the object name, or both can be supplied using ampersand substitution. However, take care when using a qualified object name with ampersand substitution because Oracle OLAP parses the qualified object name (with its exclamation point) before it resolves the ampersand reference. For example, in the expression &awname!objname, the ampersand (&) applies to the entire qualified object name, not just to the workspace name.
Passing Qualified Object Names to Programs
When you pass a qualified object name as an argument to a program and you use an ARGUMENT statement and the ARG, ARGFR, and ARGS functions, the entire qualified object name is considered to be a single argument. Its component parts are not passed separately.
In most cases, you refer to the value of a dimension by specifying the value following the conventions for the data type of the value. For example, assume that you have a TEXT dimension named geog. You can add the value "World" to the dimension by issuing the following statement.
MAINTAIN geog ADD 'World'
Note, however, that when you use a TEXT dimension value in a numeric expression or compare values in a non-numeric dimension, Oracle OLAP uses the INTEGER position number of the value in the array (as based on the default status list) rather than the value itself.
Special considerations apply to specifying the values of composites and concat dimensions.
You can specify a value of a composite in the following ways:
By specifying a set of values of the base dimensions of the composite using the following syntax.
{composite_name | SPARSE} {<base_dimension_name base_dimension_value }, ...>
(Named composites only) By specifying just the values of the composite using the following syntax.
composite_name <base_dimension_value ...>
where base_dimension_value is a set of values of the base dimensions, in the order in which they were defined in the composite, separated by spaces.
Once you have defined a unique CONCAT dimension, you can refer to its values simply by specifying the values of the base dimensions.
However, you must specify a value of a nonunique CONCAT dimension as a concatenation of the name of the base dimension and the base dimension value separated by a colon (:) and a space and enclosed in angle brackets(<>). In an expression, use the following format.
<BASE_DIMENSION_NAME: base_dimension value>
For example, assume that you have defined the base dimensions named city and state and, a CONCAT dimension for them named geog. When you report on the geog dimension, the values of geog include the names of the base dimensions along with the values.
DEFINE city DIMENSION TEXT DEFINE state DIMENSION TEXT DEFINE geog DIMENSION CONCAT(city state) MAINTAIN city ADD 'New York' MAINTAIN state ADD 'New York' REPORT geog GEOG ----------------------------------- <CITY: New York> <STATE: New York>
The syntax of some OLAP DML statements (for example, some variations of the LIMIT command) include two dimension arguments referred to as a dimension, and a related dimension. Other OLAP DML statements (for example, AVERAGE, ANY, COUNT, CUMSUM, NONE, LARGEST, SMALLEST, and TOTAL) allow you to specify the dimensionality of the result in terms of a related dimension. In these contexts, the related dimension is any dimension that shares a relation with another dimension.
Even though the value that you specify for the arguments in these statements is the name of a dimension, in actuality Oracle OLAP uses a relation between the dimensions to perform its calculations. When the two dimensions share only one relation, the behavior is clear. Oracle OLAP performs the calculation based on the values in that relation.
However, when two dimensions share multiple relations, then the behavior is less clear. In some cases, as with a LIMIT using LEVELREL command, you can specify the shared relation you want Oracle OLAP to use. In other cases, the statement syntax does not allow you to specify the name of a relation. In this case, Oracle OLAP chooses among the multiple relations as described in "How Oracle OLAP Chooses Between Multiple Relations".
In expressions, a variable is referenced as an array containing values of the specified data type. A relation is referenced as an array containing values of the specified dimension. In most other respects, variables and relations (both typically multidimensional objects) share the same characteristics.
In most cases, when you use OLAP DML statements with variables that are defined with composites, the statements treat those variables as if they were defined with base dimensions:
You can access a variable that is dimensioned by a composite by requesting any of the base dimension values.
The values of a composite that are in status are determined by the status of the base dimensions of the composite. Composites are not dimensions, and therefore, they do not have any independent status.
When you use a REPORT statement or any other statement that loops over a variable that uses a composite, the default behavior is to evaluate all the combinations of the values of the base dimensions of the composite that are in status. Any combinations that do not exist in the composite display NA for their associated data.
For example, the following statements create a report for the East region that shows the number of coupons issued for sportswear from January through March 2002. Since no coupons were issued in March 2002, the report displays NA in that column.
LIMIT month TO 'Jan02' 'Feb02' 'Mar02'
LIMIT market TO 'East'
LIMIT product TO 'Sportswear'
REPORT coupons
MARKET: EAST
------------COUPONS-------------
-------------MONTH--------------
PRODUCT Jan02 Feb02 Mar02
-------------- ---------- ---------- ----------
Sportswear 1,000 1,000 NA
However, for performance reasons, you can change the default looping behavior for statements such as REPORT, ROW, and the assignment statement (SET) so that they loop over the values in the composite rather than all of the base dimension values.
A qualified data reference (QDR) is a way of limiting one or more dimensions of a data object to a single value. QDRs are useful when you want to specify a single value of a data object without changing the current status. Using a QDR, you can qualify a dimension (which enables you to specify one dimension value in an expression) or one or more dimensions of a variable or relation.
Sometimes the syntax of a QDR is ambiguous and could either be misinterpreted or cause a syntax error. In this case, you can use the QUAL function to explicitly specify a qualified data reference (QDR).
You specify a qualified data reference using the following syntax
expression(dimname1 dimexp1 [, dimname2 dimexp2. . .])
The dimname argument is the name of a dimension or a dimension surrogate of the dimension, of the expression and the dimexp argument is one of the following:
A value of dimname.
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Note: The setting of the LIMITSTRICT option determines how Oracle OLAP behaves when a a QDR specifies a nonexistent value. By default, when you specify a nonexistent value, Oracle OLAP treats the nonexistent value as an invalid value and issues an error. If, instead, you want Oracle OLAP to treat a nonexistent value as anNA value, set the value of LIMITSTRICT to NO |
A text expression whose result is a value of dimname.
A numeric expression whose result is the logical position of a value of dimname.
A relation of dimname.
|
Note: When syntax of a QDR is ambiguous and could either be misinterpreted or cause a syntax error, use the QUAL function to explicitly specify a qualified data reference (QDR). |
You can qualify any or all of a dimensions of a variable using either of the following techniques:
The QDR can temporarily limit a dimension of the variable by selecting one specified value of the dimension. This value can be outside the current status.
The QDR can replace a dimension of the variable with a less aggregate related dimension when you supply the name of an appropriate relation as the qualifier. The dimension is temporarily replaced by the dimension(s) of the relation.
For example, the variable sales has three dimensions, month, product, and district. You might want to compare total sales in Boston to the total sales in all cities. In a single statement, you want district to be limited to two different values:
For the numerator of the expression, you want the status of district to be Boston.
For the denominator of the expression, you want the status of district to be ALL.
The following statement lets you calculate this result by using a QDR.
SHOW sales(district 'Boston')/TOTAL(sales)
You can qualify multiple dimensions of a variable. For example, when you qualify all the dimensions of the sales variable by specifying one dimension value of each dimension, then you narrow sales down to a single–cell value.
To fetch sales for Jun02, Tents, and Seattle, use the following QDR.
SHOW sales(month 'Jun02', product 'Tents', district 'Seattle')
This statement fetches a single value.
You can use a qualified data reference with the target expression of an assignment (SET) statement. This lets you assign a value to a specific cell in a data object.
The following example assigns the value 10200 to the data cell of the sales composite that is specified in the qualified data reference. When the composite named sales does not have a value for the combination Boston and Tents, then this value combination is added to the composite, thus adding the data cell.
sales(market 'Boston' product 'Tents' month 'Jan99')= 10200
When you use a relation as the qualifier in the QDR, you replace a dimension of the variable with the dimension or dimensions of the relation. The relation must be related to the dimension that you are qualifying, and it must be dimensioned by the replacement dimension.
Example 2-1 Replacing a Dimension in a Variable
Suppose you have two variables, sales and quota, which are dimensioned by month, product, and district. A third variable, division.mgr, is dimensioned by month and division. You also have a relation between division and product, called division.product. These objects have the following definitions.
DEFINE sales VARIABLE DECIMAL <month product district> LD Sales Revenue DEFINE quota VARIABLE DECIMAL <month product district> DEFINE division.mgr VARIABLE TEXT <month division> DEFINE division.product RELATION division <product> LD Division for each product
The following statement produces the report following it.
REPORT division.mgr
-------------------DIVISION.MGR----------------------
----------------------MONTH--------------------------
DIVISION JAn02 Feb02 Mar02 Apr02 May02 Jun02
-------- -------- -------- -------- -------- -------- --------
Camping Hawley Hawley Jones Jones Jones Jones
Sporting Carey Carey Carey Carey Carey Musgrave
Clothing Musgrave Musgrave Musgrave Musgrave Musgrave Wong
Suppose you want to obtain a report that shows the fraction by which sales have exceeded quota and you want to include the appropriate division manager for each product. You can show the division manager for each product by using the relation division.product, which is related to division and dimensioned by product, as the qualifier. The QDR replaces the division dimension with product, so that it has the same dimensions as the other expression in the report sales / quota. The following statement produces the report following it.
REPORT DOWN month sales W 6 sales/quota W 8 HEADING -
'MANAGER' division.mgr(division division.product)
DISTRICT: BOSTON
-----------------------------PRODUCT------------------------------------
----TEnts---- ---canoes---- --racquets--- --sportswear-- ---footwear---
Sales/ Sales/ Sales/ Sales/ Sales/
Month Quota Manager Quota Manager Quota Manager Quota Manager Quota Manager
------ ----- ------- ----- ------- ----- ------- ----- -------- ----- --------
Jan02 1.00 Hawley 0.82 Hawley 1.02 Carey 0.91 Musgrave 0.92 Musgrave
Feb02 0.84 Hawley 0.96 Hawley 1.00 Carey 0.80 Musgrave 1.07 Musgrave
Mar02 0.87 Jones 0.95 Jones 0.87 Carey 0.88 Musgrave 0.91 Musgrave
Apr02 0.91 Jones 0.93 Jones 0.99 Carey 0.94 Musgrave 0.95 Musgrave
...
You can also use a QDR to qualify a relation (which is really a special kind of variable).
Suppose the region.district relation is dimensioned by district. When you qualify district with the value Seattle, then the value of the expression is the value of the relation for Seattle. Because the QDR specifies one value of district, the expression has a single–cell result.
The definition of region.district is as follows.
DEFINE region.district RELATION region <district> LD The region for each district
The following statement displays the value WEST.
SHOW region.district(district 'Seattle')
You can use a QDR to qualify the dimension itself, which enables you to specify one dimension value in an expression. The following expression specifies one value of district, the one contained in the single-cell variable mydistrict.
district(district mydistrict)
For a concat dimension, you can use a QDR to qualify the dimension by specifying a value from a base dimension of the concat dimension. The following expression specifies one value of reg.dist.ccdim, a concat dimension that has region and district as its base dimensions. The costs variable is dimensioned by the division and reg.dist.ccdim dimensions.
SHOW reg.dist.ccdim(district 'Boston')
The preceding expression produces the following result.
<DISTRICT: Boston>
An ampersand character (&) at the beginning of an expression substitutes the value of the expression for the expression itself in a statement.When you use an ampersand with a QDR, you must enclose the whole expression in parentheses when you want the variable to be qualified before the substitution is made.
Suppose you have a text variable named myvar that is dimensioned by reptype and that contains the names of variables. Remember that it is myvar that is dimensioned by reptype, not the variables named by myvar. Therefore, you must use parentheses so that myvar is qualified and the resulting value is used in a REPORT statement.
REPORT &(myvar(reptype 'actual'))
When you do not use parentheses and the variable that is specified in myvar is sales, then you get an error message that sales is not dimensioned by reptype.
At any given time, some cells of an analytic workspace data object may be empty. An empty cell occurs when a specific data value has not been assigned to it or when a data value cannot be calculated for the cell. The value of any empty cell in an object is NA. An NA value has no specific data type. Certain functions (for example, the aggregation functions) return an NA values when the information that is requested with the function is not available or cannot be calculated. Similarly, an expression whose value cannot be calculated has NA as its value.
|
Note: To support OLAP DML composite-dimensioned variables that correspond to relational fact tables with null facts, OLAP has a special NA value which is controlled by an NA2 bit. For more information on how Oracle OLAP manages NA values controlled by NA2 bits, see "NA2 Bits and Null Tracking". |
There are cases in which you might specify an operation for which no data is available. For example, there might be no appropriate value for a given cell in a variable, for the return value of a function, or for the value of an expression that includes an arithmetic operator. In these cases, an NA (Not Available) value is automatically supplied.
To set the values of a variable or relation to NA, you can use an assignment statement (SET), as shown in the following example.
sales = NA
Several options and functions control how NA values are treated. For example:
The NA options listed in "Options by Category".
The NAFILL function returns the values of the source expression with any NA values appearing as the specified fill expression. You can include this function in an expression to control the format of its value.
System properties listed in Chapter 4, "OLAP DML Properties".
A numeric expression evaluates to any of the numeric data types. The data in a numeric expression can be any combination of the following:
Numeric literals as discussed in "Numeric Data Types".
Numeric variables or formulas
Dimensions
Functions that yield numeric results
Date literals, variables, formulas, or functions
In addition, you can join any of these expressions with the arithmetic operators for a more complex numeric expression. You use arithmetic operators in numeric expressions with numeric data, which returns a numeric result. You can also use some arithmetic operators in date expressions with a mix of date and numeric data, to retrieve either a date or numeric result.
Several options determine how Oracle OLAP handles numeric expressions.
You can include any type of numeric data in the same numeric expression.
The data type of the result is determined according to the following rules:
When all the data in the expression is INTEGER or SHORTINTEGER, and the only operations are addition, subtraction, and multiplication, then the result is INTEGER.
When any of the data is NUMBER, then the result is NUMBER.
When any of the data is DECIMAL or SHORTDECIMAL, and no data is NUMBER, then the result is DECIMAL.
When you perform any division or exponentiation operations, then the result is DECIMAL.
When you use a dimension with a data type of TEXT in a numeric expression, the dimension value is treated as a position (an INTEGER) and is used as a numeric. The position number is based on the default status list, not on current status.
All decimal data is converted to floating point format, both for storing and for calculations. In floating point format, a number is represented by means of a mantissa and an exponent. The mantissa and the exponent are stored as binary numbers. The mantissa is a binary fraction which, when multiplied by a number equal to 2 raised to the exponent, produces a number that equals or closely approximates the original decimal number.
Because there is not always an exact binary representation for a fractional decimal number, just as there is not an exact representation for the decimal value of 1/3, fractional parts of decimal numbers cannot always be represented exactly as binary fractions. Arithmetic operations on floating point numbers can result in further approximations, and the inaccuracy gradually increases with the number of operations. In addition to the approximation factor, the available number of significant digits affects the exactness of the result.
For all of these reasons, a result computed by the TOTAL, AVERAGE, or other aggregation functions on a DECIMAL or SHORTDECIMAL variable can differ in the least significant digits from a result you compute by hand. Because the SHORTDECIMAL data type provides a maximum of only seven significant digits, you see more of these differences with SHORTDECIMAL data. Therefore, you might want to use the NUMBER data type when accuracy is mor e important than computational speed, such as variables that contain currency amounts.
Another result of the fact that some fractional decimal numbers cannot be exactly represented by binary fractions is that for such numbers, the DECIMAL data type offers a different and closer approximation than the SHORTDECIMAL data type, because it has more significant digits. This can lead to problems when SHORTDECIMAL and DECIMAL data types are mixed in a comparison expression. For information on how to handle such comparisons, see "Boolean Expressions" .
You can control the following types of errors:
Division by zero. When you divide an NA value by zero, then the result is NA; no error occurs. Dividing a non-NA value by zero normally produces an error. When a divide-by-zero error occurs when you are making a calculation on dimensioned data, then you can end up with partial results. When you use REPORT or an assignment statement (SET), values are reported or stored as they are calculated, so the division by zero halts the loop before it has gone through all the values.
When you want to suppress the divide-by-zero error, then you can change the value of the DIVIDEBYZERO option to YES. Consequently, the result of any division by zero is NA and no error occurs. This allows the calculation of the other values of a dimensioned expression to continue.
Root of negative numbers. It is normally an error to try to take the root of a negative number (which includes raising a number to a non-integer power). When you want to suppress the error message and allow the calculation of roots for non-negative values of the expression to continue, then set the ROOTOFNEGATIVE option to YES.
Overflow errors. The DECIMALOVERFLOW option works in a similar manner to DIVIDEBYZERO. It lets you control whether an error is generated when a calculation produces a decimal result larger than it can handle.
A text expression evaluates to data with the TEXT, NTEXT, or ID data type. Text expressions can be any combination of the following:
Text literals. For example, 'Boston' or 'Current Sales Report'
Text dimensions. For example, district or month
Text variables or formulas. For example, product.name
Functions that yield text results. For example, JOINLINES('Product: ' product.name)
Oracle OLAP supports text expressions in all languages that you can identify using the NLS_LANGUAGE option. It also supports multi-language programs and applications using a language dimension.
When you use a DATETIME value where a text value (TEXT, NTEXT, or ID) is expected, or when you store a DATETIME value in a text variable, then the DATETIME value is automatically converted to a text value.
The format of a DATETIME value is controlled by the NLS_DATE_FORMAT option. Once a DATETIME value is stored in a text variable, the NLS_DATE_FORMAT setting has no impact.
TEXT and NTEXT data are interchangeable in most cases. However, implicit conversion can occur, such as when an NTEXT value is assigned to a TEXT variable. When TEXT is converted to NTEXT, no data loss occurs because the UTF-8 character encoding of the NTEXT data type encompasses most other data types. However, when NTEXT is converted to TEXT, data loss occurs when NTEXT characters are not represented in the workspace character set.
When TEXT and NTEXT values are used together, for example in a call to the JOINCHARS function, the TEXT value is converted to NTEXT and an NTEXT value is returned.
As discussed in "Datetime and Interval Data Types", the OLAP DML supports the same datetime and interval data types that are supported by SQL. This section discusses:
A datetime expression yields a value of a datetime data type. A datetime expression has the following syntax.
datetime_value_expr AT LOCAL |
TIME ZONE { ' [ + | - ] hh:mm' | DBTIMEZONE | 'time_zone_name' | expr }
A datetime_value_expr can be a datetime value or a compound expression that yields a datetime value. Datetimes and intervals can be combined according to the rules defined in Table 2-7, "Datetime Fields and Values". The three combinations that yield datetime values are valid in a datetime expression.
If you specify AT LOCAL, Oracle uses the current session time zone.
The settings for AT TIME ZONE are interpreted as follows:
The string '(+|-)HH:MM' specifies a time zone as an offset from UTC.
DBTIMEZONE: Oracle uses the database time zone established (explicitly or by default) during Database creation.
SESSIONTIMEZONE: Oracle uses the session time zone established by default or in the most recent ALTER SESSION statement.
time_zone_name: Oracle returns the datetime_value_expr in the time zone indicated by time_zone_name. For a listing of valid time zone names, query the V$TIMEZONE_NAMES dynamic performance view.
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Note: Timezone region names are needed by the daylight savings feature. The region names are stored in the time zone files underoracore/zoneinfo. The server always uses the large time zone file corresponding to the version number recorded in sys.props$. |
expr: If expr returns a character string with a valid time zone format, Oracle returns the input in that time zone. Otherwise, Oracle returns an error.
An interval expression yields a value of DSNTERVAL or MYINTERVAL where the expression has the following syntax.
interval_value_expr DAY [(leading_field_precision)] TO
SECOND [(fractional_second_precision)]| YEAR [(leading_field_precision)] TO MONTH
The interval_value_expr can be a DSNTERVAL or MYINTERVAL value or a compound expression that yields a DSNTERVAL or MYINTERVAL value. Datetimes and intervals can be combined according to the rules defined in Table 2-7, "Datetime Fields and Values" . The six combinations that yield interval values are valid in an interval expression.
Both leading_field_precision and fractional_second_precision can be any integer from 0 to 9. If you omit the leading_field_precision for either DAY or YEAR, then Oracle Database uses the default value of 2. If you omit the fractional_second_precision for second, then the Database uses the default value of 6. If the value returned by a query contains more digits that the default precision, then Oracle Database returns an error. Therefore, it is good practice to specify a precision that you know is at least as large as any value returned by the query.
You can perform several arithmetic operations on date (DATETIME), timestamp (TIMESTAMP, TIMESTAMP_TZ, and TIMESTAMP_LTZ) and interval (DSINTERVAL and YMINTERVAL) data. Oracle calculates the results based on the following rules:
You can use NUMBER constants in arithmetic operations on date and timestamp values, but not interval values. Oracle internally converts timestamp values to date values and interprets NUMBER constants in arithmetic datetime and interval expressions as numbers of days. For example, SYSDATE + 1 is tomorrow. SYSDATE - 7 is one week ago. SYSDATE + (10/1440) is ten minutes from now. Subtracting the hire_date column of the sample table employees from SYSDATE returns the number of days since each employee was hired. You cannot multiply or divide date or timestamp values.
Oracle implicitly converts BINARY_FLOAT and BINARY_DOUBLE operands to NUMBER.
Each DATETIME value contains a time component, and the result of many date operations include a fraction. This fraction means a portion of one day. For example, 1.5 days is 36 hours. These fractions are also returned by Oracle built-in functions for common operations on DATETIME data. For example, the MONTHS_BETWEEN function returns the number of months between two dates. The fractional portion of the result represents that portion of a 31-day month.
If one operand is a DATETIME value or a numeric value (neither of which contains time zone or fractional seconds components), then:
Oracle implicitly converts the other operand to DATETIME data. (The exception is multiplication of a numeric value times an interval, which returns an interval.)
If the other operand has a time zone value, then Oracle uses the session time zone in the returned value.
If the other operand has a fractional seconds value, then the fractional seconds value is lost.
When you pass a timestamp, interval, or numeric value to a built-in function that was designed only for the DATETIME data type, Oracle implicitly converts the non-DATETIME value to a DATETIME value.
When interval calculations return a datetime value, the result must be an actual datetime value or the Database returns an error.
Oracle performs all timestamp arithmetic in UTC time. For TIMESTAMP_LTZ, Oracle converts the datetime value from the database time zone to UTC and converts back to the database time zone after performing the arithmetic. For TIMESTAMP_TZ, the datetime value is always in UTC, so no conversion is necessary.
Table 2-13, "Matrix of Datetime Arithmetic" is a matrix of datetime arithmetic operations. Dashes represent operations that are not supported.
Table 2-13 Matrix of Datetime Arithmetic
| Operand & Operator | DATETIME | TIMESTAMP | INTERVAL | Numeric |
|---|---|---|---|---|
|
DATETIME |
— |
— |
— |
— |
|
+ |
|
|
|
|
|
- |
|
|
|
|
|
* |
|
|
|
|
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/ |
|
|
|
|
|
TIMESTAMP |
— |
— |
— |
— |
|
+ |
|
|
|
|
|
- |
|
|
|
|
|
* |
|
|
|
|
|
/ |
|
|
|
|
|
INTERVAL |
— |
— |
— |
— |
|
+ |
|
|
|
|
|
- |
|
|
|
|
|
* |
|
|
|
|
|
/ |
|
|
|
|
|
Numeric |
— |
— |
— |
— |
|
+ |
|
|
|
|
|
- |
|
|
|
|
|
* |
|
|
|
|
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/ |
|
|
|
|
Examples You can add an interval value expression to a start time. Consider the sample table oe.orders with a column order_date.
A date-only expression is an expression that evaluates to the OLAP DML DATE data type as discussed in "Date-only Data Type". The expression might be a function that returns a date-only value, a date-only literal, or a more complex expression.
Calculating DATE-only Values
You can add numbers to a DATE value, or subtract numbers from them. Whole numbers are calculated as days, and decimal values are calculated as fractions of a day. For example, SYSDATE+1.5 adds 1 day and 12 hours to the current date and time. You cannot divide or multiply DATE values, and you cannot subtract them from numbers. For example, 1-SYSDATE and 1*SYSDATE return errors.
Using DATE-only Values in Arithmetic Expressions
When you use DATE values in arithmetic expressions, the result can be numeric or it can be a date. The legal operations for dates and the data type of the result are outlined in Table 2-14, "Legal Operations for DATE Values".
Table 2-14 Legal Operations for DATE Values
| Operation | Result |
|---|---|
|
Add or subtract a number from a date |
Future or prior date |
|
Subtract a date from a date |
The number of days between the dates. |
|
Add or subtract a number from a time period. |
The time period at the appropriate interval in the future or the past, similar to the return values of the LEAD or LAG function. The result is NA when there is no dimension value that corresponds to the result. The calculation is made based on the positions of the values in the default status list of the dimension. |
A Boolean expression is a logical statement that is either TRUE or FALSE. Boolean expressions can compare data of any type if both parts of the expression have the same basic data type. You can test data to see if it is equal to, greater than, or less than other data.
A Boolean expression can consist of Boolean data, such as the following:
BOOLEAN values (YES and NO, and their synonyms, ON and OFF, and TRUE and FALSE)
BOOLEAN variables or formulas
Functions that yield BOOLEAN results
BOOLEAN values calculated by comparison operators
For example, assume that your code contains the following Boolean expression.
actual GT 20000
When processing this expression, Oracle OLAP compares each value of the variable actual to the constant 20,000. When the value is greater than 20,000, then the statement is TRUE; when the value is less than or equal to 20,000, then the statement is FALSE.
When you are supplying a Boolean value, you can type either YES, ON, or TRUE for a true value, and NO, OFF, or FALSE for a false value. When the result of a Boolean calculation is produced, the defaults are YES and NO in the language specified by the NLS_LANGUAGE option. The read-only YESSPELL and NOSPELL options record the YES and NO values.
Table 2-11, "Comparison and Logical Operators" shows the comparison and logical operators. Each operator has a priority that determines its order of evaluation. Operators of equal priority are evaluated left to right, unless parentheses change the order of evaluation. However, the evaluation is halted when the truth value is decided. For example, in the following expression, the TOTAL function is never executed because the first phrase determines that the whole expression is true.
yes EQ yes OR TOTAL(sales) GT 20000
A Boolean expression is a three-part clause that consists of two items to be compared, separated by a comparison operator. You can create a more complex Boolean expression by joining any of these three-part expressions with the AND and OR logical operators. Each expression that is connected by AND or OR must be a complete Boolean expression in itself, even when it means specifying the same variable several times.
For example, the following expression is not valid because the second part is incomplete.
sales GT 50000 AND LE 20000
In the next expression, both parts are complete so the expression is valid.
sales GT 50000 AND sales LE 20000
When you combine several Boolean expressions, the whole expression must be valid even when the truth value can be determined by the first part of the expression. The whole expression is compiled before it is evaluated, so when there are undefined variables in the second part of a Boolean expression, you get an error.
Use the NOT operator, with parentheses around the expression, to reverse the sense of a Boolean expression.
The following two expressions are equivalent.
district NE 'BOSTON' NOT(district EQ 'BOSTON')
Example 2-2 Using Boolean Comparisons
The following example shows a report that displays whether sales in Boston for each product were greater than a literal amount.
LIMIT time TO FIRST 2 LIMIT geography TO 'BOSTON' REPORT DOWN product ACROSS time: f.sales GT 7500
This REPORT statement returns the following data.
CHANNEL: TOTALCHANNEL
GEOGRAPHY: BOSTON
---F.SALES GT 7500---
--------TIME---------
PRODUCT Jan02 Feb02
-------------- ---------- ----------
Portaudio NO NO
Audiocomp YES YES
TV NO NO
VCR NO NO
Camcorder YES YES
Audiotape NO NO
Videotape YES YES
When the data you are comparing in a Boolean expression involves an NA value, a YES or NO result is returned when that makes sense. For example, when you test whether an NA value equals a non-NA value, then the result is NO. However, when the result would be misleading, then NA is returned. For example, testing whether an NA value is less than or greater than a non–NA value gives a result of NA.
Table 2-15, "Boolean Expressions with NA Values that Result in non-NA Values" shows the results of Boolean expressions involving NA values, which yield non-NA values.
When you get unexpected results when comparing numeric data, then there are several possible causes to consider:
A number you are comparing might have a small decimal part that does not show in output because of the setting of the DECIMALS option.
You are comparing two floating point numbers and at least one number is the result of an arithmetic operation.
You have mixed SHORTDECIMAL and DECIMAL data types in a comparison.
Oracle recommends that you use the ABS and ROUND functions to do approximate tests for equality and avoid all three causes of unexpected comparison failure. When using ABS or ROUND, you can adjust the absolute difference or the rounding factor to values you feel are appropriate for your application. When speed of calculation is important, then you probably want to use the ABS rather than the ROUND function.
Suppose expense is a decimal variable whose value is set by a calculation. When the result of the calculation is 100.000001 and the number of decimal places is two, then the value appears in output as 100.00. However, the output of the following statement returns NO.
SHOW expense EQ 100.00
You can use the ABS or the ROUND function to ignore these slight differences when making comparisons.
A standard restriction on the use of floating point numbers in a computer language is that you cannot expect exact equality in a comparison of two floating point numbers when either number is the result of an arithmetic operation. For example, on some systems, the following statement returns a NO instead of the expected YES.
SHOW .1 + .2 EQ .3
When you deal with decimal data, do not code direct comparisons. Instead, use the ABS or the ROUND function to allow a tolerance for approximate equality. For example, either of the following two statements produce the desired YES.
SHOW ABS((.1 + .2) - .3) LT .00001 SHOW ROUND(.1 + .2) EQ ROUND(.3, .00001)
You cannot expect exact equality between SHORTDECIMAL and DECIMAL or NUMBER representations of a decimal number with a fractional component, because the DECIMAL and NUMBER data types have more significant digits to approximate fractional components that cannot be represented exactly.
Suppose you define a variable with a SHORTDECIMAL data type and set it to a fractional decimal number, then compare the SHORTDECIMAL number to the fractional decimal number, as shown here.
DEFINE sdvar SHORTDECIMAL sdvar = 1.3 SHOW sdvar EQ 1.3
The comparison is likely to return NO. What happens in this situation is that the literal is automatically typed as DECIMAL and converts the SHORTDECIMAL variable sdvar to DECIMAL, which extends the decimal places with zeros. A bit-by-bit comparison is then performed, which fails. The same comparison using a variable with a DECIMAL or a NUMBER data type is likely to return YES.
There are several ways to avoid this type of comparison failure:
Do not mix the SHORTDECIMAL with DECIMAL or NUMBER types in comparisons. To avoid mixing these two data types, generally avoid defining variables with decimal components as SHORTDECIMAL.
Use the ABS or ROUND function to allow for approximate equality. The following statements both produce YES.
SHOW ABS(sdvar - 1.3) LT .00001 SHOW ROUND(sdvar, .00001) EQ ROUND(.3, .00001)
Values are not compared in the same dimension based on their textual values. Instead, Oracle OLAP compares the positions of the values in the default status of the dimension. This enables you to specify statements like the following statement.
REPORT district LT 'Seattle'
Statements are interpreted such as these using the following process:
The text literal 'Seattle' is converted to its position in the district default status list of the dimension.
That position is compared to the position of all other values in the district dimension.
As shown by the following report, the value YES is returned for districts that are positioned before Seattle in the district default status list of the dimension, and NO for Seattle itself.
REPORT 22 WIDTH district LT 'Seattle' District DISTRICT LT 'Seattle' -------------- ---------------------- Boston YES Atlanta YES Chicago YES Dallas YES Denver YES Seattle NO
A more complex example assigns increasing values to the variable quota based on initial values assigned to the first six months. The comparison depends on the position of the values in the month dimension. Because it is a time dimension, the values are in chronological order.
quota = IF month LE 'Jun02' THEN 100 ELSE LAG(quota, 1, month)* 1.15
However, when you compare values from different dimensions, such as in the expression region lt district, then the only common denominator is TEXT, and text values are compared, not dimension positions.
You can compare two dates with any of the Boolean comparison operators. For dates, "less" means before and "greater" means after. The expressions being compared can include any of the date calculations discussed in Table 2-11, "Comparison and Logical Operators". For example, in a billing application, you can determine whether today is 60 or more days after the billing date to send out a more strongly worded bill.
bill.date + 60 LE SYSDATE
Dates also have a numeric value. You can use the TO_NUMBER and TO_DATE functions to change a value from a DATE to an INTEGER or an INTEGER to a DATE for comparison.
When you compare text data, you must specify the text exactly as it appears, with punctuation, spaces, and uppercase or lowercase letters. A text literal must be enclosed in single quotes. For example, this expression tests whether the first letter of each employee's name is greater than the letter "M."
EXTCHARS(employee.name, 1, 1) GT 'M'
You can compare TEXT and ID values, but they can only be equal when they are the same length. When you test whether a text value is greater or less than another, the ordering is based on the setting of the NLS_SORT option.
You can compare numbers with text by first converting the number to text. Ordering is based on the values of the characters. This can produce unexpected results because the text is evaluated from left to right. For example, the text literal 1234 is greater than 100,999.00 because 2, the second character in the first text literal, is greater than 0, the second character in the second text literal.
Suppose name.label is an ID variable whose value is 3-Person and name.desc is a TEXT variable whose value is 3-Person Tents.
The result of the following SHOW statement is NO.
SHOW name.desc EQ name.label
The result of the following statements is YES.
name.desc = '3-Person' SHOW name.desc EQ name.label
The Boolean operator LIKE is designed for comparing a text value to a text pattern. A text value is like another text value or pattern when corresponding characters match.
Besides literal matching, LIKE lets you use wildcard characters to match multiple characters in a string:
An underscore (_) character in a pattern matches any single character.
A percent (%) character in a pattern matches zero or more characters in the first string.
For example, a pattern of %AT_ matches any text that contains zero or more characters, followed by the characters AT, followed by any other single character. Both DATA and ERRATA return YES when LIKE is used to compare them with the pattern %AT_.
The results of expressions using the LIKE operator are affected by the settings of the LIKECASE and LIKENL options.
No negation operator exists for LIKE. To accomplish negation, you must negate the entire expression. For example, the result of the following statement is NO.
SHOW NOT ('Boston' LIKE 'Bo%')
You can also compare a text literal to a relation. A relation contains values of the related dimension and the text literal is compared to a value of that dimension. For example, region.district holds values of region, so you can do the following comparison.
region.district EQ 'West'
A conditional expression is an expression you can use to select between values based on a condition. You can use conditional expression as part of any other expression if the data type is appropriate. Oracle OLAP supports the use of the following conditional expressions:
An IF expression is an expression you can use to select one of two values based on a Boolean condition.
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Note: Do not confuse the IF expression with the IF...THEN...ELSE command, which has similar syntax but a different purpose, and which must be used in an Oracle OLAP program. The IF...THEN...ELSE command does not have a data type and is not evaluated like an expression. |
An IF expression has the following syntax.
IF Boolean-expression THEN expression1 ELSE expression2
In most cases, expression1 and expression2 must be of the same basic data type (numeric, text, or Boolean) and the data type of the whole expression is determined using the same rules as those for the binary operators. However, when the data type of either expression1 or expression2 is DATE, it is possible for the other expression to have a numeric or text data type. Because Oracle OLAP expects both data types to be DATE, it converts the numeric or text value to a DATE. Also, when the value of one expression is a dimension value then the value of the other expression is converted to a dimension value as it is for QDRs.
You can nest IF expressions; however, in this case, you might want to use a SWITCH expression instead as discussed in "SWITCH Expressions".
An IF expression is processed by first evaluating the Boolean expression; then:
When the result of the Boolean expression is TRUE, then expression1 is evaluated and returns that value.
When the result of the Boolean expression is FALSE, then expression2 is evaluated and returns that value.
The expression1 and expression2 arguments are any valid OLAP DML expressions that evaluate to the same basic data type. However, when the data type of either value is DATE, it is possible for the other value to have a numeric or text data type. Because both data types are expected to be DATE, Oracle OLAP converts the numeric or text value to a DATE. The data type of the whole expression is the same as the two expressions. When the result of the Boolean expression is NA, then NA is returned.
Example 2-3 Using an IF Expression
This example shows a sales bonus report. The bonus is 5 percent of the amount that sales exceeded budget, but when sales in the district are below budget, then the bonus is zero.
LIMIT month TO 'Jan02' TO 'Jun02'
LIMIT product TO 'Tents'
REPORT DOWN district IF sales-sales.plan LT 0 THEN 0
ELSE .05*(sales-sales.plan)
PRODUCT: TENTS
---IF SALES-SALES.PLAN LT 0 THEN 0 ELSE .05*(SALES-SALES.PLAN)---
----------------------MONTH------------------------------
DISTRICT Jan02 Feb02 Mar02 Apr02 May02 Jun02
--------- -------- -------- -------- ------- --------- ----------
Boston 229.53 0.00 0.00 0.00 584.51 749.13
Atlanta 0.00 0.00 0.00 190.34 837.62 1,154.87
Chicago 0.00 0.00 0.00 84.06 504.95 786.81
...
A SWITCH expression consists of a series of CASE expressions. You can use a SWITCH expression as an alternative to a complicated, nested IF ... THEN ... ELSE expression when all the conditions are equality comparisons with a single value.
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Note: Do not confuse the SWTICH expression with the SWITCH command, which has similar syntax but a different purpose, and which must be used in an Oracle OLAP program. The SWITCH command is not evaluated like an expression. |
A SWITCH expression has the following syntax.
SWITCH expression DO { case-label ... exp [,] } ... DOEND
where case-label has the following syntax:
CASE exp: | DEFAULT:
When processing a SWITCH expression, Oracle OLAP compares each CASE expression in succession until it finds a match. When a match is found, it returns the value specified after the last label of the current case group. When no match is found and a DEFAULT label is specified, it returns the value specified for the DEFAULT case; otherwise it returns NA.
Example 2-4 Using a SWITCH Expression Instead of an IF Expression
Assume that you have coded the following OLAP DML statement which includes nested IF...THEN...ELSE statements.
testprogram = IF testtype EQ 0 -
THEN 'program0' -
ELSE IF testtype EQ 1 -
THEN 'program1' -
ELSE IF testtype EQ 2 OR testtype EQ 3 -
THEN 'program2'
ELSE NA
You could, instead, code the same behavior using a SWITCH expression as shown below.
testprogram = SWITCH testtype DO -
CASE 0: 'program0', -
CASE 1: 'program1', -
CASE 2: -
CASE 3: 'program2', -
DEFAULT: NA -
DOEND
You could also code the same behavior using a SWITCH statement that spans fewer lines, omits commas, and omits the DEFAULT case since NA is the default return value when a match is not found.
testprogram = SWITCH testtype DO CASE 0: 'program0' CASE 1: 'program1' -
CASE 2: CASE 3: 'program2' DOEND
To construct a substitution expression, use an ampersand character (&) at the beginning of an expression. Using an ampersand (that is, the substitution operator) this way is also called ampersand substitution. The ampersand specifies that Oracle OLAP evaluates an expression containing a substitution expression as follows:
Evaluate the expression following the ampersand (the substitution expression).
Evaluate the rest of the expression using the result of step 1 (that is, the result of the substitution expression).
Ampersand substitution gives you a level of indirection when you are specifying an expression. For example, when you specify an ampersand followed by a variable that holds the name of another variable, the value of the expression becomes the data in the second variable. Ampersand substitution lets you write more general programs that can operate on data that is chosen when the program is run. Note, however, that, Oracle OLAP does not compile program lines with ampersand substitution; instead these lines are interpreted when the program runs. To avoid ampersand substitution in a program, you can often use an IF or SWITCH command instead.
You cannot use ampersand substitution in model equations.
Example 2-5 Using Ampersand Substitution
Suppose you have a variable called curname that holds the name of a dimension in the analytic workspace (product). When you execute the following statement, then REPORT produces the single value, product, which is the actual value stored in the curname variable.
REPORT curname CURNAME ---------- PRODUCT
However, when you execute the following statement, then REPORT produces the values of the dimension product.
REPORT &curname PRODUCT -------------- Tents Canoes Racquets Sportswear Footwear
Using Ampersand Substitution with QDRs
When you use an ampersand with a QDR, you must enclose the whole expression in parentheses if you want the variable to be qualified before the substitution is made.
Suppose you have a text variable named myvar that is dimensioned by reptype and that contains the names of variables. Remember that it is myvar that is dimensioned by reptype, not the variables named by myvar. Therefore, you must use parentheses so that myvar is qualified and the resulting value is used in a REPORT statement.
REPORT &(myvar(reptype 'actual'))
When you do not use parentheses and the variable that is specified in myvar is sales, then you get an error message that sales is not dimensioned by reptyp
The ZEROTOTAL command resets one or all subtotals of specified report columns to zero. You use the ZEROTOTAL command when you produce reports with the ROW command.
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Note: ZEROTOTAL affects the results returned by the RUNTOTAL and SUBSTR functions. |
Syntax
ZEROTOTAL [{n|ALL} [column1 columnN]]
Parameters
ZEROTOTAL with no arguments resets all subtotals in all columns to zero.
An INTEGER expression that specifies one of the 32 subtotals (1 to 32) Oracle OLAP accumulates for each numeric column in a report. For the specified columns, this subtotal is set to zero.
Sets all 32 subtotals to zero for the specified columns. ALL is the default when there are no arguments. To reset all the subtotals to zero for specific columns, you must include ALL in the statement.
ZEROTOTAL ALL 1 4 7
The column number of a report column. Column number 1 refers to the left-most column in a report, regardless of the type of data it contains. When you do not supply any column number arguments, Oracle OLAP sets the specified subtotal (or all subtotals) to zero for all the columns in the report.
Usage Notes
Initializing Column Subtotals
When you use the ROW command to produce a report, use a ZEROTOTAL statement at the beginning of the report program to initialize all 32 subtotals for all columns to zero. The REPORT statement automatically resets all subtotals to zero before producing output.
Resetting Column Subtotals
You can also use ZEROTOTAL in a report program when you only want to reset some subtotals or when you want to start accumulating new subtotals without inserting the subtotals accumulated so far. A subtotal is automatically reset to zero after it is accessed with the SUBSTR function in its own column. However, a subtotal is not reset to zero after it is accessed with the RUNTOTALRUNTOTAL function.
Examples
Example 10-177 Resetting All Report Column Subtotals
In a report, you want to show a dollar sales total, followed by a detailed summary of unit sales for each district. You also want to show a total for unit sales at the end of the report, but you do not want the dollar sales figures included in that total. After generating the total dollar sales, use ZEROTOTAL to reset all your subtotals to zero. Then when you use SUBTOTAL(1) later in the report, it only totals the unit sales for each district.
Suppose you have these statement lines in your program.
LIMIT product TO 'Footwear' LIMIT month TO 'Jul96' TO 'Sep96' ROW 'Total Dollar Sales' ACROSS month: - DECIMAL 0 TOTAL(sales month) BLANK ROW 'Unit Sales' ZEROTOTAL ALL FOR district ROW INDENT 5 district ACROSS month: units ROW 'Total Unit Sales' ACROSS month: - OVER '-' SUBTOTAL(1)
These statements produce the following output.
Total Dollar Sales 607,552 581,229 658,850
Unit Sales
Boston 3,538 3,369 3,875
Atlanta 4,058 3,866 4,251
Chicago 3,943 3,509 4,058
Dallas 814 824 867
Denver 1,581 1,532 1,667
Seattle 2,053 2,193 2,617
---------- ---------- ----------
Total Unit Sales 15,987.00 15,293.00 17,335.00
The EIFSHORTNAMES option controls the structure of the extension of EIF overflow (extension) file names.
Data Type
BOOLEAN
Syntax
EIFSHORTNAMES = YES|NO
Parameters
Sets the extension of EIF overflow (extension) file names to xx, where each x is an automatically assigned lowercase letter between a and z.
(Default) Sets the extension of EIF overflow (extension) file names have the structure filename.ennn, where nnn is a three-digit number beginning with 001, to distinguish them from workspace extension file names. For example, when an EIF file is named export.eif, the extension files are named export.e001, export.e002, and so on,
Examples
The TEMPSTAT command limits the dimension you are looping over, inside a FOR loop or inside a loop that is generated by a REPORT statement. Status is restored after the statement following TEMPSTAT. When a DO ... DOEND phrase follows TEMPSTAT, status is restored when the matched DOEND or a BREAK or GOTO statement is encountered. You can use TEMPSTAT only within programs.
Syntax
TEMPSTAT dimension...
statement block
Parameters
One or more dimensions whose status you would like to temporarily change inside a FOR loop or an automatic loop that is generated by the REPORT statement.
One or more statements that change the status of the dimension. To execute multiple statements under the temporary status, enclose them between DO ... DOEND brackets.
Usage Notes
Nesting TEMPSTATE Statements
You can nest TEMPSTAT commands, one within another, and you can repeat the same dimension within the nested TEMPSTAT commands.
Placement of TEMPSTAT
When you want to be able to change the status of a dimension while REPORT is looping over it, you must place a TEMPSTAT statement inside that REPORT loop rather than before the REPORT statement. For example, suppose you have written a user-defined function called monthly_sales, which changes the status of month, and monthly_sales is part of a REPORT statement that is looping over month. In this case a TEMPSTAT statement must be inside the monthly_sales function in order for a status change to take place. (TEMPSTATE must be inside of monthly_sales even when the REPORT statement is given within TEMPSTAT DO/DOEND brackets within a FOR loop over MONTH.)
POP and POPLEVEL Commands
Within the DO/DOEND brackets of a TEMPSTAT statement block, you cannot use a POP statement to pop a dimension that is protected by TEMPSTAT on the block -- unless the matching PUSH statement is also within the block.
Similarly, within the DO/DOEND brackets of a TEMPSTAT statement block, you cannot use a POPLEVEL statement to pop a dimension that is protected by TEMPSTAT on the block -- unless one of two conditions is met: the matching PUSHLEVEL statement is also within the block, or the only pushes on the dimension since the PUSHLEVEL statement was given are also within the block.
Use Only LIMIT and CONTEXT Commands
Within the DO/DOEND brackets of a TEMPSTAT statement, the only way to change the status of a dimension within a loop over that dimension is with the LIMIT or CONTEXT APPLY commands. (See the LIMIT command and the CONTEXT command for details.) You cannot change the status of the dimension using POP or POPLEVEL. You also cannot perform any operations that would add values to the dimension, because adding values also changes the status of the dimension to ALL. For example, MAINTAIN ADD, FILEREAD APPEND, and IMPORT (with new values in the EIF file) add values to a dimension.
Examples
TEMPSTAT in a FOR Loop
The following program excerpt uses a TEMPSTAT statement to limit the market dimension within the FOR market loop.
FOR market DO TEMPSTAT market DO LIMIT market TO CHILDREN USING market.market REPORT market DOEND DOEND
The STDHDR program generates the standard Oracle OLAP heading at the top of every page of report output.
The standard running page heading consists of two lines. The first line includes the date and time on the left and the page number on the right. The second line is blank.
The heading output is sent to the current outfile.
Syntax
STDHDR
Usage Notes
Setting LSIZE
LSIZE must be set to a value of at least 29 before you use STDHDR. Otherwise the heading does not look right. A value less than 26 produces an error. The default for LSIZE is 80.
Creating a Custom Heading
When PAGING is set to YES, Oracle OLAP automatically inserts the standard heading at the top of each page of output. To get a different heading you must write a program that produces the heading and set the PAGEPRG option to the name of that program. To return to the standard heading, set PAGEPRG to 'STDHDR'. (See the PAGEPRG option for more information.)
Using STDHDR in a Heading Program
When you use PAGEPRG to specify a heading program, you can still use the standard heading in your custom heading by executing STDHDR as part of your program. Generally, you place STDHDR before the statements that produce your customized heading. See Example 10-152, "Creating a Custom Heading for a Report".
The STDHDR Program
The STDHDR program uses the HEADING and CONVERT commands, as follows.
HEADING L W 8 <CONVERT(TODAY, TEXT,'<DD><MTXTL><YY>') TOD> -
R W LSIZE-25 'Page ' L W 6 D 0 PAGENUM
BLANK
Examples
Example 10-152 Creating a Custom Heading for a Report
Suppose you would like each page of your report to include the standard header and also the customized title "Annual Sales Report." To accomplish this, define a small PAGEPRG program called report.head.
DEFINE report.head PROGRAM PROGRAM CALL STDHDR HEADING WIDTH LSIZE CENTER 'Annual Sales Report' BLANK END
In your report program, set PAGING to YES, and specify the preceding program to execute after every page break by setting the PAGEPRG option to 'REPORT.HEAD' (see the PAGEPRG option for further information). When you run the report, each page contains the following combination of the standard heading and your custom heading.
18Jan97 15:05:16 PAGE 1
Annual Sales Report
The MODEL.COMPRPT program produces a report that shows how model equations are grouped into blocks. For step blocks and for simultaneous blocks with a cross-dimensional dependence, the report lists the dimensions involved in the dependence.
Syntax
MODEL.COMPRPT
Examples
Example 10-62 A Compilation Report for the income.budget Model
The MODEL.COMPRPT program produces a compilation report that shows the block structure of the model that you specify as the program argument and the order of equations within each block. Each equation is identified with the name of the model and its statement number within that model.
The following statements compile the model and invoke MODEL.COMPRPT.
COMPILE income.budget MODEL.COMPRPT income.budget
The MODEL.COMPRPT statement produces the following compilation report.
MODEL INCOME.BUDGET <LINE MONTH>
BLOCK 1 (SIMPLE)
INCOME.BUDGET 4: revenue = lag(revenue, 1, month) * 1.02
INCOME.BUDGET 5: cogs = lag(cogs, 1, month) * 1.01
INCOME.BUDGET 3: gross.margin = revenue - cogs
BLOCK 2 (STEP-FORWARD <MONTH>)
INCOME.BUDGET 6: marketing = lag(opr.income, 1, month) * 0.20
INCOME.BUDGET 2: opr.income = gross.margin - marketing
END BLOCK 2
END BLOCK 1
Example 10-63 A Compilation Report for the income.est Model
The following statement runs the MODEL.COMPRPT program, which produces a compilation report for a model named income.est.
MODEL.COMPRPT income.est
The compilation report contains the following output.
MODEL INCOME.EST <LINE MONTH>
BLOCK 1 (STEP-FORWARD <MONTH>)
INCOME.EST 5: revenue = lag(revenue,1,month)+2*lag(marketing,1,month)
INCOME.EST 4: gross.margin = revenue - cogs
BLOCK 2 (SIMULTANEOUS)
INCOME.EST 2: net.income = opr.income - taxes
INCOME.EST 3: opr.income = gross.margin - marketing - selling - r.d
INCOME.EST 6: marketing = .15 * net.income
INCOME.EST 7: taxes = .3 * opr.income
END BLOCK 2
END BLOCK 1
The LIMIT command sets the current status list of a dimension and its dimension surrogates, or assigns values to a valuesets the current status list of a dimension and its dimension surrogates, or assigns values to a valueset. You use LIMIT to restrict the data values you are working on by temporarily limiting the range of the dimensions of the data. Using LIMIT, you create a current status list for a dimension. The current status list of a dimension is an ordered list of currently accessible values for the dimension. Values that are in the current status list of a dimension are said to be "in status." For more information on dimension status and its importance when working with analytic workspace data, see "How to Specify the Set of Data that OLAP DML Operations Work Against".
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Tip: You set the current status list of one or more base dimensions of a composite, conjoint dimension, concat dimension, or a partition template based on the selected values of that object, see the LIMIT BASEDIMS command. |
Syntax
LIMIT {dimension | valueset } [concat-component] limit-type [limit-clause] [IFNONE label]
where limit-type is one of the following keywords that specify how Oracle OLAP should modify the current status list:
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values.
Specifies the name of the component of the concat dimension whose values are used to determine the limit. When you specify a value for concat-component, the limit sets the status of the specified concat dimension using the values of dimension which is a component of the concat dimension. This limit-clause applies only when dimension is a concat dimension. The status of a concat dimension and of its component dimensions are not shared. Changing the status of a component dimension after you have used that dimension as the limit-clause in setting the status of a concat dimension does not change the status of the concat dimension.
Replaces the status of a dimension or valueset with the values specified by the limit-clause arguments. The TO keyword selects values from the default status of a dimension in the same order as they appear in the LIMIT statement or in the order implied by the valuelist argument. When you use arguments that imply ordering, the ordering of the values is based on their positions in the default status.
Expands the status of a dimension or valueset by adding the values specified by the limit-clause arguments that are not already in status. The ADD keywords selects values from the default status of a dimension in the same order as they appear in the LIMIT statement or in the order implied by the valuelist argument. When you use arguments that imply ordering, the ordering of the values is based on their positions in the default status. ADD adds unique dimension values in the specified order after the current status list or valueset list.
Expands the status of a dimension or valueset by inserting the values specified by the limit-clause arguments in a specified position in the current status. The INSERT keyword selects values from the default status of a dimension in the same order as they appear in the LIMIT statement or in the order implied by the valuelist argument.
When you use arguments that imply ordering (for example,value1 TO value2), the ordering of the values is based on their positions in the default status. INSERT adds values to a specified position in the current status. When an added value is already in status, it is removed from its position in the current status and added in the order in which it appears in the valuelist, preserving the order of the added values.
Inserts the new values before the first value in status.
Inserts new values after the last value in status.
Specifies whether new values Oracle OLAP inserts new values before or after position in the current status.
A dimension value in the current status, a character expression whose value is a dimension value in the current status, or an INTEGER expression whose value represents the position of a dimension value in the default status.
Reduces the status of a dimension or valueset by keeping only the values specified by the limit-clause arguments. Oracle OLAP performs the selection based on the current dimension status. KEEP preserves the current order of values among the values that remain in the status.
Like a simple KEEP, KEEP REORDER reduces the status of a dimension or valueset by keeping only the values specified by the limit-clause arguments. Oracle OLAP performs the selection based on the current dimension status. However, KEEP REORDER orders the result in the order of the selection arguments (that is, the limit-clause arguments) rather than by the current status order.
Reduces the status of a dimension or a valueset by removing the values specified by the limit-clause arguments. Oracle OLAP performs the selection based on the current dimension status. KEEP preserves the current order of values among the values that remain in the status.
Replaces the status of a dimension or valueset with the values that are not specified by the limit-clause arguments. When you do not specify any arguments after COMPLEMENT, status is replaced by all values not now in status. Oracle OLAP performs the selection based on the current dimension status. COMPLEMENT leaves dimension values that remain in their default order. (Abbreviated COMP)
Sorts the values of a dimension or valueset according to the limit-clause arguments. LIMIT creates a temporary list of values based on the limit-clause arguments, and uses this list to sort the current status list. Any values not present in the temporary list are moved to the end of the current status list.
Specifies that NA values are placed first in the sort list rather than last.
Specifies the values to use for the limit. The syntax is quite complex and, consequently, has been divided into the following topics:
(For use only within an OLAP DML program) Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). In either case, the null status is not put into effect when program execution branches. Instead, the original status, before the LIMIT statement was executed, is retained even when OKNULLSTATUS is YES. Within an OLAP DML program, you cannot use both IFNONE and NULL in the same statement.
The name of a label elsewhere in the program constructed following the "Guidelines for Constructing a Label". Execution of the program branches to the line directly following the specified label.
Note that label, as specified in IFNONE, must not be followed by a colon. However, the actual label elsewhere in the program must end with a colon.
Usage Notes
Specifying a Value of a Concat Dimension
To specify a value of a nonunique concat dimension, use the following syntax.
<base-dimension: value>.
Default Status List
When you first attach an analytic workspace, the current status list of each dimension consists of all of the values of the dimension that have read permission, in the order in which the values are stored. This list of values is called the default status list for the dimension.
Unique Values
LIMIT selects only unique values of a dimension. When a value appears more than once in a LIMIT statement, it is placed in status in the order of its first appearance. For example, the following lines.
LIMIT time TO 'Jan97', 'Feb97', 'Jan97' STATUS time
produce this output.
The current status of TIME is: JAN97, FEB97
Nonexistent Values
Oracle OLAP does not signal an error when you try to set the status of a dimension or valueset that has no values, unless you explicitly list values that do not exist. For example, assume that you have not added any values to a newly defined dimension WEEK. In this case, the statement LIMIT week TO FIRST 10 does not cause an error. However, LIMIT week TO 'Pete' causes an error because Pete is not a value. Similarly, LIMIT week TO 20 causes an error because week does not have a value at position 20.
Setting the Status of a Dimension or Valueset to Null
Oracle OLAP allows the status of a dimension or valueset to be set to null (empty status) only when you have explicitly specified that you want null status to be permitted. You can give this permission in either of two ways:
Set the OKNULLSTATUS option to YES. This specification indicates that null status should be allowed whenever it occurs (unless the IFNONE argument is present in a LIMIT statement).
Use the NULL keyword in a LIMIT statement to set the status of a particular dimension or valueset to null. You can do this by specifying TO NULL or KEEP NULL. This specification indicates that null status should be allowed for this LIMIT statement only.
When you have not used either of these two methods to give permission for null status and you execute a LIMIT statement that would result in null status, Oracle OLAP does not change the status to null when it executes the statement. Instead, Oracle OLAP leaves the status as it was before the statement was issued and either signals an error (when IFNONE is not present) or branches to the IFNONE label (when IFNONE is present).
An IFNONE argument indicates that you do not want program execution to take its normal course when a dimension's status were to be set to null. Therefore, when IFNONE is present, Oracle OLAP branches to the IFNONE label and does not set the status to null, even when OKNULLSTATUS is YES. When the NULL keyword is present with IFNONE, Oracle OLAP signals the inconsistency with an error.
IFNONE requires the use of unstructured programming techniques. Oracle OLAP now provides alternative structured techniques, so the use of IFNONE is discouraged. IFNONE has been retained for compatibility with previous versions of Oracle OLAP.
Limiting a Conjoint
To limit a conjoint dimension to a value list, you can use the following constructions:
Specify the actual values, surrounding each combination with angle brackets
LIMIT proddist TO '<Tents, Boston>' - '<Footwear, Denver>'
Use a variable name for the values, surrounding the combination with angle brackets.
prodname = 'Canoes' distname = 'Seattle' LIMIT proddist To <prodname, distname>
Create a multiline list, where each line is a combination surrounded by angle brackets.
namelist = '<Tents Boston>\n<Footwear, - Denver>\n <Canoes, Seattle>' LIMIT proddist TO namelist
Use the implicit relation between a conjoint dimension and its base dimension to limit the conjoint dimension. For example, use the following statement to limit PRODDIST to all conjoint values having "Canoes" as one of its base values.
LIMIT proddist TO product 'Canoes'
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Note: You can use logical position numbers for base dimension values in a conjoint dimension. "Using INSTAT When the Dimension is a Conjoint Dimension" illustrates using logical position numbers |
For an example of how you can limit a conjoint dimension that has a concat base dimension, see Example 10-25, "Limiting a Conjoint Dimension with a Concat Base Dimension".
Limiting a Concat
You can define a concat dimension using simple dimensions, conjoint dimensions, and other concat dimensions as the base dimensions of the concat. The syntax for limiting a concat dimension to one of its values is the following.
LIMIT concatdim TO <base-dim: value>
For example, the concat dimension reg.dist.ccdim has the simple dimensions region and district as its base dimensions. The following statement sets the status of reg.dist.ccdim to two of its values, region: East and district: Atlanta.
LIMIT reg.dist.ccdim TO <region: 'East'> <district: 'Atlanta'>
For other methods of setting the status of a concat dimension, see Example 10-16, "Limiting a Concat Dimension".
Alternative to Branching Using an IFNONE Label
As an alternative to branching to an IFNONE label, you can also handle null status for a dimension with the OKNULLSTATUS option. When you set OKNULLSTATUS to YES, then you are allowed to set the status of a dimension to null. You can then check for null status and execute appropriate commands with an IF...THEN...ELSE command, or you can handle null status as a case in a SWITCH command.
OKNULLSTATUS = YES LIMIT month TO sales GT salesnum IF STATLEN(month) LT 1 THEN GOTO showerr
Examples
Example 10-14 Adding and Removing Values
These lines add values to the status for the month dimension.
LIMIT month TO 'Jan96' TO 'Jun96' LIMIT month ADD 'Jul96' 'Sep96'
Issuing a STATUS month statement produces this output.
The current status of MONTH is: Jan96 TO Jul96, Sep96
This line removes values from the status for the month dimension.
LIMIT month REMOVE 'Jan96' TO 'Mar96'
Now, issuing a STATUS month statement produces this output
The current status of MONTH is: Apr96 TO Jul96, Sep96
Example 10-15 Limiting with a Dimension Surrogate
A dimension and any dimension surrogates for it share the same status.
For example, assume that there is a NUMBER dimension named store_id that has the values 25, 410, 150, 205, 310, and 10. It also uses storepos, an INTEGER dimension surrogate for store_id. The dimension surrogate storepos has the values 1, 2, 3, 4, 5, and 6. A TEXT dimension surrogate for store_id is storename. It has the text values Raoul's - Boston, Poldy's Potpourri, Molly's Emporium, Raoul's - Atlanta, Kinch's Kitchen Supplies, and Raoul's - Chicago. The following statements are equivalent.
LIMIT store_id TO 25 410 150 LIMIT store_id TO storepos 1 2 3 LIMIT storepos TO 1 TO 3 LIMIT storepos TO first 3 LIMIT storename TO first 3 LIMIT storename TO 'Raoul\'s - Boston' TO 'Molly\'s Emporium' LIMIT store_id TO storename storepos 1 2 3 LIMIT storename TO store_id 25 TO 150
The following statements set the status of the store_id dimension by limiting storename, which is a TEXT dimension surrogate for store_id, and report the values of store_id.
LIMIT storename TO 'Raoul\'s Sweets' TO 'Henry\'s Flowers' REPORT store_id
The preceding statement produces the following output.
STORE_ID -------------- 10 20 30
Example 10-16 Limiting a Concat Dimension
In the following examples, the concat dimension reg.dist.ccdim has the simple dimensions region and district as its base dimensions. A concat dimension has an implicit relation to each of its component dimensions.
The following statement sets the status of the concat dimension using the related dimension syntax and specifying the positions of the component (related) dimension.
LIMIT reg.dist.ccdim TO district 1, 4, 5
Issuing a STATUS reg.dist.ccdim statement produces the following output.
The current status of REG.DIST.CCDIM is: <DISTRICT: BOSTON>, <DISTRICT: DALLAS>, <DISTRICT: DENVER>
The following statement limits the concat dimension directly to the values specified by positions of the concat dimension.
LIMIT reg.dist.ccdim TO 1, 4, 5
Issuing a STATUS reg.dist.ccdim statement produces the following output.
The current status of REG.DIST.CCDIM is: <REGION: EAST>, <DISTRICT: BOSTON>, <DISTRICT: ATLANTA>
The following statements set the status of district and then limit reg.dist.ccdim to the status of district.
LIMIT district TO LAST 3 LIMIT reg.dist.ccdim TO district
Issuing a REPORT reg.dist.ccdim statement produces the following output.
REG.DIST.CCDIM ---------------------- <district: Dallas> <district: Denver> <district: Seattle>
In the following statement, the limit-clause argument is a list of values of the concat dimension.
LIMIT reg.dist.ccdim TO <region: 'East'> <district: 'Boston'> <district: 'Atlanta'>
The following statements define a valueset for reg.dist.ccdim, store the current status of the concat dimension in the valueset, reset the status of the concat to ALL, and then limit the concat to the valueset and report the values of the concat in status.
DEFINE regdist.vset VALUESET reg.dist.ccdim LIMIT regdist.vset TO reg.dist.ccdim LIMIT reg.dist.ccdim TO ALL LIMIT reg.dist.ccdim TO regdist.vset RPR W 22 reg.dist.ccdim
The preceding statements produce the following result.
REG.DIST.CCDIM ---------------------- <region: East> <district: Boston> <district: Atlanta>
You can also limit a concat dimension using a valueset of one of its component dimensions:
When the component dimensions contain identical values, you can limit the concat dimension to those values by using a Boolean expression. When the district and region dimensions both have New York as a value, then the following statement limits the reg.dist.ccdim to those values.
LIMIT reg.dist.ccdim TO BASEVAL(reg.dist.ccdim) EQ 'New York'
In the following example, the concat dimension geog has the simple dimension region and the conjoint dimension cityandstate as its base dimensions. The following statement sets the status of the concat dimension by limiting the conjoint base dimension.
LIMIT geog TO cityandstate <'Princeton' 'New Jersey'> - <'Patterson' 'New Jersey'>
Issuing a STATUS geog statement produces the following output.
The current status of GEOG is: <CITYANDSTATE: <PRINCETON, NEW JERSEY>, <CITYANDSTATE: <PATTERSON, NEW JERSEY>>
The following statements sets the status of the concat dimension by limiting the conjoint base dimension by specifying a value of a base dimension of the conjoint dimension.
LIMIT geog TO cityandstate city 'Princeton' RPR W 30 geog
The preceding statement produces the following output.
GEOG ------------------------------ <cityandstate: <Princeton, New Jersey>> <cityandstate: <Princeton, Indiana>>
Example 10-17 Limiting with a Worksheet
This example shows how to limit a dimension to the values that are contained in a column of a worksheet. Here the dimension month is limited to the values that are contained in the first column of the worksheet workitem. The following statements produce a workitem report, which is shown following the statements.
LIMIT month TO ALL
LIMIT wkscol TO 1
LIMIT wksrow TO workitem NE NA
REPORT workitem
-WORKITEM-
--WKSCOL--
WKSROW 1
-------------- ----------
1 Jan96
2 Feb96
3 Mar96
4 Apr96
5 May96
6 Jun96
7 Jul96
8 Aug96
9 Sep96
10 Oct96
11 Nov96
12 Dec96
The following statement limits the month dimension to the values that are listed in the first column of workitem.
LIMIT month TO CHARLIST(workitem)
Issuing a STATUS month statement produces the following output.
The current status of MONTH is: Jan96 TO Dec96
Example 10-18 Using Ampersand Substitution with LIMIT
Assume that you want specify exactly two products for a program named product.rpt. In this cae, you could declare two dimension-value arguments to handle them. But when you want to be able to specify any number of products using LIMIT commands, then you can use a single argument with ampersand substitution.
Suppose you use the following commands in your program.
ARGUMENT natext TEXT
ARGUMENT widthamt INTEGER
ARGUMENT rptprod TEXT
...
LIMIT product TO &rptprod
You can run the program and specify that you want the first three products in the report.
CALL product.rpt ('Missing' 8 'first 3')
The single quotation marks are necessary to indicate that "first 3" should be taken as a single argument, rather than two separate arguments separated by a space. The ampersand causes the LIMIT command to interpret 'first 3' as a keyword expression rather than as a dimension value.
Example 10-19 Branching on Null Status
Your program might try to set or refine the status of the product dimension to include only the products for which unit sales are greater than 500. When no products have unit sales of more than 500, then you can use the IFNONE keyword to specify that execution branch to the novals label.
LIMIT product KEEP units GT 500 IFNONE novals
In the commands following the novals label, you can handle the special situation in which no products have units sales greater than 500.
A LIMIT command with a using values limit clause assigns values to a valueset or sets the current status list of a dimension or dimension surrogates to:
Specified value or values. The values can be any of the following:
Dimension values, expressed as literal values separated by commas, or as a multiline text expression, each line of which is a value of the dimension.
Ranges of dimension values, expressed as value1 TO value2.
Integer values that represent the logical positions of dimension values, expressed as comma-delimited INTEGER values.
Ranges of INTEGER values that represent the logical positions of dimension values, expressed as value1 TO value2.
Valuesets.
Values for which a Boolean expression is TRUE.
The top or bottom performers of a dimension based on a criterion
The top or bottom performers of a dimension, by percentage, based on a criterion represented as an expression
Syntax
LIMIT {dimension | valueset} [concat-component] limit-type -
{inclusive-val-args....| exclusive-val-args} [IFNONE label]
where:
inclusive-val-args is one or more of the following constructs:
exclusive-val-args is one of the following constructs:
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A keyword that specifies how Oracle OLAP should modify the current status list. (See the main entry for LIMIT command for a list and descriptions of these keywords.)
A list of one or more INTEGER values, or the name of a single-cell variable that holds a numeric value. Separate the values with commas (,). Numeric values with decimal places (SHORTDECIMAL or DECIMAL values) are automatically truncated to INTEGER values before being used as dimension values. An INTEGER specifies a dimension value by its logical position in the full set of dimension values. You cannot specify a NUMBER dimension value by an INTEGER position. When the values of the NUMBER dimension are INTEGER values, then you can set the status of the dimension by specifying dimension values, as in intvalue1, intvalue2 and so on.
A multiline text expression, each line of which is a value of dimension.
Specifies a range of dimension values where value1 and value2 can be either INTEGER values or dimension values. Such a range can be increasing (for example, 1 to 10) or decreasing (for example, 10 to 1). When you specify an INTEGER value, that value is the logical position of a value in the default status list for the dimension. When you specify a dimension value, the command convertsthe value to the logical position of the value in the default status list for the dimensioon. The current status of the dimension or valueset is assigned accordingly.
|
Tip: You cannot specify the values of aNUMBER dimension using INTEGER positions. Instead, define an INTEGER dimension surrogate for the NUMBER dimension and limit the dimension by the positions of the surrogate. |
A list of one or more values of dimension. A dimension value can be specified as a text expression whose value is a valid dimension value. For a NUMBER dimension, dimension values are numbers. For dimensions with a type of DAY, WEEK, MONTH, QUARTER, or YEAR, dimension values can also be specified as DATE expressions.
An analytic workspace valueset object that is a saved list that holds the values for the dimension whose status is being set. You cannot define a valueset for a dimension surrogate, therefore you cannot specify a valueset when setting the status of a dimension surrogate. However, when you limit a dimension with a valueset, then you automatically limit to the same set any dimension surrogates of that dimension. You can also specify a LIMIT function.
Specifies that all dimension values in the default status are to be included in the status. The default status is made up of all dimension values for which read permission is granted, in the same order as when the dimension was last maintained. When you start up an analytic workspace, the status for each dimension in your analytic workspace is the default status. Changing the read permission for a dimension with PERMIT or PERMITRESET statement changes the default status for the dimension.
An expression whose TRUE values are used by Oracle OLAP when limiting the dimension or status. The boolean-expression must be dimensioned by the dimension whose status is being set. For a dimension surrogate, the Boolean expression is evaluated over the dimension for which it is a surrogate. The data types of the expressions you are comparing in the Boolean expression must be similar. See the CONVERT function for information on converting data types. To correctly use LIMIT with a Boolean expression you must understand how it works with a Boolean expression that has with multiple dimensions, see "How LIMIT Handles Boolean Expressions With More Than One Dimension" for details.
Specifies that the status of a dimension or valueset is set based on a criterion, where n is the number of values to select and expression is the criterion on which to base the selection. All dimensions of expression other than the one whose status is being set must be limited to a single value. TOP results in the status sorted in descending order, BOTTOM results in the status sorted in ascending order. You cannot use a composite after the BASEDON keyword. When you attempt to do so, an error message is displayed.
Specifies that the status of a dimension or valueset is set by finding the top or bottom performers based on a criterion represented as an expression. This construction sorts values and adds them to the status that is based on their contribution, by percentage, to an expression.
For example, the following statement sorts products in descending order by each product's contribution to TOTAL(sales) and then add values to the status, starting from the top, until the cumulative total of sales by product reaches or exceeds 30 percent of all sales.
LIMIT product TO TOP 30 PERCENTOF TOTAL(sales, product)
|
Important: Do not use a criterion expression that causes a side effect or changes its own value. |
Specifies the first n, last n values in the dimension's full set of values when used with TO, ADD, COMPLEMENT, or INSERT. When used with KEEP or REMOVE, specifies the first n, last n or nth values in the current status.
|
Important: It can happen that the last item in status, based on a PERCENTOF criterion, is one of several dimension values having the same associated criterion value. In this case, LIMIT includes all dimension values with that criterion value in the resulting status, even when that causes the total of the criterion value to far exceed the specified percentage. |
Specifies the n values in the dimension's full set of values when used with TO, ADD, COMPLEMENT, or INSERT. When used with KEEP or REMOVE, specifies the n values in the current status. You can specify any number of values or range of values.
Indicates that there can be up to 2,000 arguments in the LIMIT statement. When there are less than 300 arguments, LONGLIST is not needed.
Specifies that Oracle OLAP use only those dimension members that were created using a MAINTAIN ADD SESSION statement when performing the limit.
Specifies that Oracle OLAP use the values that are presently in status when performing the limit. Specifying this keyword is equivalent to (but more efficient than) using a VALUES (dimname) statement.
Indicates an empty dimension or valueset list. Using this keyword with the TO or KEEP arguments removes all values from the current status, leaving an empty dimension or valueset list, even when OKNULLSTATUS is NO. You cannot use IFNONE and NULL in the same LIMIT statement. ADD, INSERT, and REMOVE NULL leave status unchanged. COMPLEMENT NULL places all values in status.
Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
Usage Notes
Considerations When Specifying Values
Keep the following points in mind when specifying values in limit-clause:
The setting of the LIMITSTRICT option determines how Oracle OLAP behaves when a list of values in a LIMIT command, a LIMIT function, or a QDR contains a nonexistent value. By default, when you specify a nonexistent value, Oracle OLAP treats the nonexistent value as an invalid value and stops executing the limit and issues an error. If, instead, you want Oracle OLAP to treat a nonexistent value as an NA value, set the value of LIMITSTRICT to NO.
You can embed a quoted string within a quoted string, which is necessary when there are special characters in a base dimension value of a composite or conjoint dimension, such as Joe's Deli. See the "Text Literals".
When the dimension has the NTEXT data type and an argument that represents a dimension value has the TEXT data type, LIMIT converts the argument value to NTEXT. Similarly, when the dimension has the TEXT data type and an argument that represents a dimension value has the NTEXT data type, LIMIT converts the argument value to TEXT; however, in this case, the conversion can result in data loss when the NTEXT value cannot be represented in the database character set.
When you specify a value of a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the value can be in the format specified by the VNF (value name format) for the dimension (or in the default VNF for the type of dimension you are limiting when the dimension does not have a VNF) or in a valid input style for DATE values.
You must only provide the date components that are relevant for the type of dimension you are limiting. For a DAY or WEEK dimension, you must supply the day, month, and year components. For a MONTH or QUARTER dimension, you must only supply the month and year (for example, Jun95 or 0695 for June 1995). For a YEAR dimension, you must only specify the year (for example, 95 for 1995). The valid input styles for dates are discussed in DATEORDER.
When you specify a DATE expression or a text value that represents a complete date, you can specify any date that falls within the time period that is represented by the desired dimension value. Oracle OLAP uses the DATEORDER option to resolve any ambiguities.
How LIMIT Handles Boolean Expressions With More Than One Dimension
When you have used this type of LIMIT command (or LIMIT function) to limit only one dimension of a multi-dimensional Boolean expression, you effectively limit that expression to the values of limited dimension and only the current values of the unlimited dimensions.
For example, assume that you you have a sales variable is dimensioned by three dimensions: product, district, and month.
Let's look first at what happens when you explicitly limit district and month dimensions to single values and then limit product using a Boolean expression.
LIMIT month TO 'Jan95' LIMIT district TO 'Boston' LIMIT product TO sales GT 90000 STATUS product
The STATUS statement produces the following output.
The current status of PRODUCT is: Footwear
In this case, the resulting status is all of the products whose sales exceed $90,000 for the month of January 1995 in the Boston district, which is only Footwear.
Now consider the following example in which the MONTH dimension is not limited to a single value.
LIMIT product TO ALL LIMIT month TO 'Jan95' 'Feb95' 'Mar95' LIMIT district TO 'Boston'
When you execute a REPORT sales statement, you can see the BOSTON sales figures for three months.
DISTRICT: BOSTON
-------------SALES--------------
-------------MONTH--------------
PRODUCT Jan95 Feb95 Mar95
-------------- ---------- ---------- ----------
Tents 32,153.52 32,536.30 43,062.75
Canoes 66,013.92 76,083.84 91,748.16
Racquets 52,420.86 56,837.88 58,838.04
Sportswear 53,194.70 58,913.40 62,797.80
Footwear 91,406.82 86,827.32 100,199.46
However, the following LIMIT and STATUS commands produce the output shown following them. Again, only Footwear is in the status for month.
LIMIT product TO sales GT 90000 STATUS product The current status of PRODUCT is: Footwear
In this case, each product has three sales figures, one for each month. For each product, LIMIT evaluates the sales data for only the first month in status. A product is added to the status when its sales data exceeds $90,000 in that month.
When you would like all months evaluated for each product, you can use the EVERY, ANY, or NONE functions. For example, the following LIMIT statement adds a product to the status when any of its months has a sales figure that exceeds $90,000.
LIMIT product TO ANY(sales GT 90000, product)
In this case a STATUS product statement produces the following output.
The current status of product is: Canoes, Footwear
Limiting Using Implicit Relations
Every dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR is related to all other dimensions of this type through an implicit relation. When you limit the values of one DAY, WEEK, MONTH, QUARTER, or YEAR dimension by specifying another DAY, WEEK, MONTH, QUARTER, or YEAR dimension as the related-dimension, Oracle OLAP uses the implicit relation by default. However, when an explicit relation is defined between the two of these types of dimensions, you can override the default by specifying the name of the explicit relation as the related-dimension. For example, you can issue the following statement.
LIMIT month TO quarter year
This statement temporarily limits quarter to year, then limits month to quarter, and finally, restores quarter to its original status.
Examples
Example 10-20 Using LIMIT to Partially Populate Variables
DEFINE GEOG DIMENSION TEXT DEFINE PRODUCTS DIMENSION TEXT DEFINE SALES VARIABLE DECIMAL <PRODUCTS GEOG> DEFINE COSTS VARIABLE DECIMAL <PRODUCTS GEOG>
Assume also as shown by the following reports that you have populated the dimensions but not the variables. All of the elements of the costs and sales variables appear in the report and all have the value of NA.
PRODUCTS
------------
TVs
Radios
Skis
Bikes
GEOG
------------
Boston
Springfield
New Orleans
Baton Rouge
Quebec City
Montreal
Toronto
Norfolk
-------------------SALES-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston NA NA NA NA
Springfield NA NA NA NA
New Orleans NA NA NA NA
Baton Rouge NA NA NA NA
Quebec City NA NA NA NA
Montreal NA NA NA NA
Toronto NA NA NA NA
Norfolk NA NA NA NA
-------------------COSTS-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston NA NA NA NA
Springfield NA NA NA NA
New Orleans NA NA NA NA
Baton Rouge NA NA NA NA
Quebec City NA NA NA NA
Montreal NA NA NA NA
Toronto NA NA NA NA
Norfolk NA NA NA NA
Now you issue the following LIMIT command so that only values indexed by Boston and Springfield values of the geog dimension are accessible to Oracle OLAP.
LIMIT geog TO 'Boston' 'Springfield'
Now you issue new reports for geog, costs, and sales. For the geog dimension only the Boston and Springfield elements values appear. Also, only the elements of the costs and sales variables that are indexed by Boston and Springfield appear in the report.
GEOG
------------
Boston
Springfield
-------------------SALES-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston NA NA NA NA
Springfield NA NA NA NA
-------------------COSTS-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston NA NA NA NA
Springfield NA NA NA NA
Now you issue two assignment statements that use the RANDOM function to populate the costs and sales variables, followed by the LIMIT command that sets the status of the geog dimension to its default status of ALL.
sales = RANDOM (200) costs = RANDOM (100) LIMIT geog to ALL
Now you issue new reports for geog, costs, and sales. All of the values of the geog dimension and all of the elements of the costs and sales variables appear. However, only the elements of the costs and sales variables that are indexed by Boston and Springfield have non-NA values.
GEOG
------------
Boston
Springfield
New Orleans
Baton Rouge
Quebec City
Montreal
Toronto
Norfolk
-------------------SALES-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston 199.97 133.82 10.07 148.17
Springfield 173.94 27.56 32.21 47.40
New Orleans NA NA NA NA
Baton Rouge NA NA NA NA
Quebec City NA NA NA NA
Montreal NA NA NA NA
Toronto NA NA NA NA
Norfolk NA NA NA NA
-------------------COSTS-------------------
-----------------PRODUCTS------------------
GEOG TVs Radios Skis Bikes
------------ ---------- ---------- ---------- ----------
Boston 43.52 25.32 68.68 10.38
Springfield 9.49 27.96 61.76 16.12
New Orleans NA NA NA NA
Baton Rouge NA NA NA NA
Quebec City NA NA NA NA
Montreal NA NA NA NA
Toronto NA NA NA NA
Norfolk NA NA NA NA
Example 10-21 Limiting with a Boolean Expression
You can limit a dimension or valueset according to the values of a Boolean expression. In this example, the values of the TOTALL function are broken out by product and compared to a constant. The LIMIT statement sets the status to all the products whose sales, totaled for all months and districts, are greater than 12 million.
LIMIT product TO TOTAL(sales product) GT 12000000
Example 10-22 Limiting with a Formula
When you use the same criterion frequently to limit a dimension, you can save the expression as a formula and use the name of the formula as the limit expression.
DEFINE criterion FORMULA TOTAL(sales product) GT 12000000 LIMIT product TO criterion
Example 10-23 Limiting with a Valueset
You can save a status list in a valueset and use those values later to limit the status. When it takes several LIMIT commands to produce the status list you want, the valueset keeps you from having to repeat those LIMIT commands each time you need the same list. The following statements limit district to the districts in which sportswear sales exceeded $1,000,000 in 1996. The status is saved in the valueset sports.district, and you can limit district to the same list with one LIMIT statement.
DEFINE sports.district VALUESET district LIMIT product TO 'Sportswear' LIMIT month TO year 'Yr96' LIMIT sports.district TO TOTAL(sales district) GT 1000000 LIMIT district TO sports.district
Issuing a STATUS district statement produces this output.
The current status of DISTRICT is: ATLANTA TO DENVER
Example 10-24 Limiting with a Variable
Here the TOP and BASEDON keywords are used to limit the status of a dimension, using the values of a variable as a criterion. The status list is sorted in descending order according to the values of sales.
LIMIT product TO 'Sportswear' LIMIT month TO 'Jul96' LIMIT district TO TOP 2 BASEDON sales
The following REPORT statement
REPORT DOWN district sales
produces this output, which shows the results of the LIMIT commands.
PRODUCT: SPORTSWEAR
--SALES---
--MONTH---
DISTRICT Jul96
-------------- ----------
Dallas 220,416.81
Atlanta 211,666.14
Example 10-25 Limiting a Conjoint Dimension with a Concat Base Dimension
Assume that your analytic workspace contains a conjoint dimension named prod.regdist that has the product simple dimension and the reg.dist.ccdim concat dimension as its base dimensions. The conjoint dimension prod.regdist has the following values.
Tents <region: East> Tents <region: West> Canoes <region: East> Canoes <region: West> Tents <district: Boston> Tents <district: Atlanta> Tents <district: Denver> Canoes <district: Atlanta> Canoes <district: Seattle>
There are two different ways that you can set the status of a conjoint dimension that has a concat dimension as a base dimension:
By specifying the concat dimension, one of its component dimensions, and a value of the component dimension. The following LIMIT statement sets the status of prod.regdist in this manner.
LIMIT prod.regdist TO reg.proddist.ccdim district 'Atlanta' RPR W 20 prod.regdist
The preceding statement produces the following output.
--------------PROD.REGDIST---------------
PRODUCT REG.DIST.CCDIM
-------------------- --------------------
Tents <district: Atlanta>
Canoes <district: Atlanta>
You can also set the status of the conjoint by specifying its values. The following LIMIT statement sets the status of prod.regdist in this manner.
LIMIT prod.regdist TO <'Tents' '<region: East>'> <'Tents' '<district: Boston>'> RPR W 20 prod.regdist
The preceding statement produces the following output.
--------------PROD.REGDIST---------------
PRODUCT REG.DIST.CCDIM
-------------------- --------------------
Tents <region: East>
Tents <district: Boston>
A LIMIT command that uses only dimension values that are at the same level as the current level of the hierarchical dimension or dimension surrogate when setting status or assigning values to a valueset.
Syntax
LIMIT {dimension | valueset} [concat-component] limit-type-
LEVELREL level-relation-clause [IFNONE label]
where the syntax of level-relation-clause varies depending on the dimensionality of the object you want to specify:
To specify a level relation which is multidimensional you use the following syntax:
RELATION level-relation-name [QUALIFY relation-dimension-name [inclusive-val-args...]...]
(You can also use this syntax when the level relation is one-dimensional.)
To specify a level relation which is one-dimensional, you can use the following simplified syntax:
level-relation-name [valueset2]
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values; or a LIMIT function.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A keyword that specifies how Oracle OLAP should modify the cu rrent status list. (See the main entry for LIMIT command for a list and descriptions of these keywords.)
Sets the status of a hierarchical dimension to all of the values of the hierarchical dimension that are at the same level as the current value of the dimension; or, that limits a hierarchical dimension to those values of the hierarchical dimension that are at the same level as the current value of the dimension and that are also in a specified valueset.
Specifies that Oracle OLAP performs the limit based on the values of the relation specified by level-relation-name. Specify this keyword if level-relation-name is a multidimensional relation.
Specifies the name of a level relation for the hierarchical dimension you want to limit. See "Levelrel Relation" for more information.
Identifies the values by which Oracle OLAP performs the limit.
relation-dimension-name is the name of a dimension of the relation specified by level-relation-name.
inclusive-val-args specifies the values of relation-dimension-name to use when determining the values of level-relation-name by which to perform the limit. You can specify any inclusive valuelist argument as described in the syntax of the inclusive-val-args argument for the valuelist clause for LIMIT command. (See LIMIT (using values) command for detailed syntax.) When you omit this argument, Oracle OLAP uses the current status of the dimension when performing the limit.
Specifies the name of a valueset object is dimensioned by the level dimension for the hierarchical dimension that you want to limit. The result of using this argument is the individual valueset that corresponds to the level value of the current position of the dimensions.
You can also specify aLIMIT function.
Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
Examples
Example 10-26 Limiting to a Single Time Period of a Hierarchical Time Dimension
Assume that you have defined a hierarchical text dimension named time, a level dimension named timelevels that has Month and Year as values, and a relation named timelevelsrel that is dimensioned by time and that has timelevels as a related dimension (that is, for each value of the time dimension, timelevelsre contains a value of either Month or Year) When you want to limit the values of time that are already in status to only those values that are at the same level as Jan99, you can issue the following statement.
LIMIT time TO LEVELREL timelevelsrel
This is equivalent to issuing the following statement
LIMIT time TO RELATION timelevelsrel QUALIFY time CURRENT
A LIMIT command with a related-dimension limit clause that uses the values of a different related dimension to assign values to a valueset or to set the status of a dimension or a dimension surrogate.
Syntax
LIMIT {dimension | valueset} limit-type related-dim-clause [IFNONE label]
where the syntax of related-dim-clause varies depending on the type of object being specified:
When you want to specify a relation, the syntax is:
RELATION relation-name [QUALIFY relation-dimension-name [inclusive-val-args...]...]
When you want to specify a dimension that is related to the dimension being limited, the syntax is:
related-dimension-name [related-dimension-valuelist]
(You can also use this simplified syntax when the object is a a one-dimensional relation.)
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values; or a LIMIT function.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A keyword that specifies how Oracle OLAP should modify the current status list. (See the main entry for LIMIT command for a list and descriptions of these keywords.)
Specifies that Oracle OLAP performs the limit based on the values of the relation specified by relation-name. Specify this keyword if relation-name is a multidimensional relation. Also, when there are multiple relations between the dimension being limited and the dimension specified by related-dimension-name, you can use this phrase to identify which relation Oracle OLAP uses to perform the limit.
Identifies the values by which Oracle OLAP performs the limit, where:
relation-dimension-name is the name of a dimension of the relation specified by relation-name.
inclusive-val-args specifies the values of relation-dimension-name to use when determining the parent values. You can specify any inclusive valuelist argument as described in the syntax of the inclusive-val-args argument for the valuelist clause for LIMIT command. See LIMIT (using values) command for detailed syntax. When you omit this argument, Oracle OLAP uses the current status list of the related dimensions when performing the limit.
Specifies the name of a one-dimensional relation or a dimension that is related to the dimension being limited. For related-dimension-name, you can also specify a dimension surrogate for the dimension you are limiting, or a dimension surrogate of the related dimension. For example, dimsurr is a dimension surrogate of dim2 and dim2 is related to dim1. The dimension surrogate dimsurr has the values Dsv1, Dsv2, Dsv3 and Dsv4. The following statement limits dim1 by specifying values of dimsurr.
LIMIT dim1 TO dimsurr dsv1 dsv3
The values of the related dimension or a dimension surrogate for the related dimension or the dimension specified using the syntax shown in LIMIT command. See LIMIT (using values) command for detailed syntax. When this argument is present in a LIMIT statement, status is obtained by selecting the values of the dimension being limited, which are related to the related-dimension values. When valuelist is omitted, the current status value of related-dimension is used.
Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
Usage Notes
Limiting to a Related Dimension Is a Two-Step Process
When you limit a dimension or valueset to a related dimension, the resulting status is determined in a two-step process:
The dimension values are arranged in the order of the values of the related dimension.
When there are multiple values of the dimension for any value of the related dimension, those values are arranged in the order of their default status.
Suppressing the Sort When Limiting to a Related Dimension
You can suppress the sort that occurs when you limit a dimension or valueset to a related dimension by setting LIMITSORTREL to NO which can significantly improve performance when the dimension you are limiting is large.
|
Note: When LIMIT.SORTREL isNO, printed output of a dimension may not appear in logical order. |
Examples
Example 10-27 Limiting with a Related Dimension
Here the status of a dimension is limited using a related dimension. This statement limits district to Boston and Atlanta, which are in the East region.
LIMIT district TO region 'East'
This statement limits product to Sportswear and Footwear, which are in the division that appears last in the list of division values.
LIMIT product TO division LAST 1
A LIMIT command that uses a parent relation in its limit clause to set the status of a hierarchical dimension or its dimension surrogate, or assigns values to a valueset, based on family relationships within the hierarchy.
Syntax
LIMIT {dimension | valueset} [concat-component] limit-type-
[family-keyword ] USING parent-relation-clause [IFNONE label]
where:
family-keyword has one of the following constructs:
The syntax for parent-relation-clause varies depending on its dimensionality of the object you want to specify:
When the parent relation is multidimensional, use the following syntax:
RELATION parentrel [QUALIFY relation-dimension-name [inclusive-val-args... | CURRENT]...]
(You can also use this syntax when the parent relation is one-dimensional.)
When the parent relation is one-dimensional, you can use the following simplified syntax:
parentrel [inclusive-val-args | CURRENT]
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values; or a LIMIT function.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A keyword that specifies how Oracle OLAP should modify the current status list. (See the main entry for LIMIT command for a list and descriptions of these keywords.)
Finds the parent of each value in valuelist. For a dimension, when there is no valuelist, finds the parent for each value in status. For a valueset, when there is no valuelist, it finds the parent of each value in the valueset. It uses the parent-relation to look up the parent.
Finds the children of each value in valuelist. For a dimension, when there is no valuelist, finds the children for each value in status. For a valueset, when there is no valuelist, it finds the children of each value in the valueset. It uses the parent-relation to look up the children.
When you do not include the DISTANCE phrase:
Finds the ancestors (that is, parents, grandparents, and so on) of each value in valuelist. For a dimension, when there is no valuelist, it finds the ancestors of each value in status.
For a valueset, when there is no valuelist, it finds the ancestors of each value in the valueset. In other words it finds "parents" for the values and the "parents of the parents" until there are no new parents.
When you include the DISTANCE phrase, limits to the ancestors who are members of the generation specified by generation:
For generation, specify 0 for the current generation, 1 for parents, 2 for grandparents, 3 for great grandparents, and so on.
For negative values, the command returns descendant generations (that is -1 returns children, -2 returns grandchildren, and so on).
When you do not include the DISTANCE phrase:
Finds the descendants (that is, children, grandchildren, and so on) of each value in valuelist. For a dimension, when there is no valuelist, it finds descendants for each value in status.
For a valueset, when there is no valuelist, it finds the descendants of each value in the valueset. In other words, it finds the children of the values and the children of the children until there are no new children.
When you include the DISTANCE phrase, limits to the descendants who are members of the generation specified by generation:
For generation, specify 0 for the current generation, 1 for children, 2 for grandchildren, 3 for great grandchildren, and so on.
For negative, the command returns ancestor generations (that is -1 returns parents, -2 returns grandparents, and so on).
Finds all siblings of each value in valuelist, including the valuelist values, themselves. Issuing one LIMIT statement with the SIBLIGS keyword is the same as issuing two consecutive LIMIT statements: 1) LIMIT with PARENTS, 2) LIMIT with CHILDREN. For a dimension, when there is no valuelist, it finds siblings for each value in status. For a valueset, when there is no valuelist, it finds the siblings of each value in the valueset.
(Abbreviated TOPANC) Finds those members that are at the top of the hierarchy; that is, those members that do not have any ancestors which is equivalent to issuing the following two LIMIT commands.
LIMIT dimension to ANCESTORS .... LIMIT dimension REMOVE DESCENDANTS....
(Abbreviated BOTTOMDESC) Finds those members that are at the bottom of the hierarchy; that is, those members that do not have any descendants.
Finds the descendants (that is, children, grandchildren, and so on) based on a particular parent-relation. The difference is the order of the values. DESCENDANTS groups the values by level (all children, then all grandchildren, and so on); HIERARCHY places each group of children next to its parent. HIERARCHY includes the original values (that is, those in status before the LIMIT statement was executed) in status.
Indicates that children should be listed before their parents. By default, children are listed after their parents.
Excludes the original values from the status. The default is to include original values.
Skips n generations for each value in valuelist. For dimensions, when there is no valuelist, it skips n generations for each value in status. For a valueset, when there is no valuelist, it skips n generations for each value in the valueset. This keyword, in combination with DEPTH, is helpful when drilling down; see Example 10-29, "Drilling Down Using SKIP and DEPT".
Includes n generations down from each value of valuelist. For dimensions, when there is no valuelist, it includes n generations for each value in status. For a valueset, when there is no valuelist, it includes n generations of each value in the valueset. The default depth value is 99. This keyword, in combination with SKIP, is helpful when drilling down on values.
Executes a statement, represented as a text expression, every time a group of children is constructed. For example, you can sort each group of children based on information stored in an Oracle OLAP variable. In the following statement, markets are sorted in increasing order based on unit sales every time a group of children is constructed.
LIMIT market TO HIERARCHY RUN 'SORT market a unit.m' USING -
market.market
|
Note: In this example, when you use KEEP or REMOVE instead of TO in your LIMIT statement, the SORT statement would have no effect. |
Specifies the values to use when determining parent values.
Specifies the name of the parent relation for the dimension.
To limit a dimension surrogate, use the parent relation for the dimension for which it is a surrogate.
Identifies the beginning of the parent-relation-clause. You use this keyword when parentrel is a multidimensional relation.
Specifies the name of a dimension of parentrel. The use of this clause varies depending on whether you are coding a LIMIT command or a LIMIT function as described in "Looping Behavior of LIMIT (using parent relation)".
Specifies the values to use when determining the parent values. You can specify any inclusive valuelist argument as described in the syntax of the inclusive-val-args argument for the valuelist clause for LIMIT command. See LIMIT (using values) command for detailed syntax.
Specifies that you want to limit to the values of the children of the current value of the dimension. (This is the same as specifying dimension_name +0.)
Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
Usage Notes
Looping Behavior of LIMIT (using parent relation)
When you do not include a QUALIFY clause, the set of values that this LIMIT puts into status when parentrel is multi-dimensional varies depending on whether or not you are issuing a LIMIT command or a LIMIT function:
LIMIT command. All of the in-status values of the related dimensions of parentrel are included in the set of in-status values. If you only want the current values of the related dimensions of parentrel to be included in the set of in-status values, specify a QUALIFY related-dimension CURRENT clause for each of the related dimensions of parentrel.
LIMIT function. Only the current values of the related dimensions of parentrel are included in the set of in-status values. If you want all of the in-status values of the related dimensions of parentrel to be included in the set of in-status values, specify a QUALIFY related-dimension related-dimension clause for each of the related dimensions of parentrel.
Examples
Example 10-28 A Simple Drill Down
This example drills down on districts from the region level of the market dimension. First, the market dimension, which has embedded totals at the district, region, and total U.S. level, is limited to the region level data. This LIMIT is done using the relation mlv.market, which is a relation between market and market.level.
Issuing a REPORT mlv.market statement produces the following output, which shows the values of mlv.market.
MARKET MLV.MARKET -------------- ---------- Totus Totus East Region Boston District Atlanta District Central Region Chicago District Dallas District West Region Denver District Seattle District
The following LIMIT statement limits the values of MARKET, and the STATUS statement produces the values currently in status. The output of STATUS is shown following the statements.
LIMIT market TO mlv.market 'Region' STATUS market The current status of MARKET is: EAST, CENTRAL, WEST
To drill down on the district level data from the region level, you can use LIMIT with the CHILDREN keyword. The following example uses a parent-relation called market.market to perform the drill down. For each value of the market dimension, this relation contains the name of its parent.
DEFINE market.market RELATION market <market> LD Self-relation for the Market Dimension
A report of market.market produces the following output.
MARKET MARKET.MARKET -------------- ------------- Totus NA East Totus Boston Central Atlanta East Central Totus Chicago Central Dallas Central West Totus Denver West Seattle West
You can limit market to the children of the East, Central, and West regions by using the CHILDREN keyword with LIMIT.
LIMIT market TO mlv.market 'Region' Limit market TO CHILDREN USING market.market
A report of market produces the following output.
MARKET ------------- Boston Atlanta Chicago Dallas Denver Seattle
Example 10-29 Drilling Down Using SKIP and DEPT
Consider the following statement.
LIMIT market TO HIERARCHY DEPTH 2 SKIP 1 USING market.market 'Totus'
Oracle OLAP looks in the child-parent relation (market.market) to find the children and the grandchildren (DEPTH 2) of Totus and it discards the first generation (SKIP 1). The resulting status follows.
Totus Boston Atlanta Chicago Dallas Denver Seattle
Note that Totus is included in status. With HIERARCHY, the original values are included in status.
The LIMIT command sets the current status list of a dimension and its dimension surrogates, or assigns values to a valueset.
A LIMIT command with the NOCONVERT keyword sets the status of one dimension based on the numeric position of values in a different dimension.
Syntax
LIMIT{dimension | valueset} [concat-component] limit-type -
NOCONVERT [{unrelated-dimension|numeric-valueset}] -
[IFNONE label]
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values; or a LIMIT function.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A keyword that specifies how Oracle OLAP should modify the current status list. (See the main entry for LIMIT command for a list and descriptions of these keywords.)
Sets the status of a dimension based on the numeric position of the specified values in the status list of an another dimension.
Specifies the name of a dimension not related to the dimension being limited. Using this argument specifies that the status of a dimension or valueset is set based on the numeric position of each value in status of the unrelated-dimension. Setting status based on in status values in unrelated dimensions is particularly useful when the two dimensions are in different analytic ? workspaces (for example, when a one-to-one correspondence exists between the product dimension in two analytic workspaces).
Specifies a numeric valueset. When you use this argument, NOCONVERT sets the status based on the numeric values in the valueset. The numeric values represent the positions of the values in the default status of the dimension.
(For use only within an OLAP DML program) Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
The LIMIT command sets the current status list of a dimension and its dimension surrogates, or assigns values to a valueset.
A LIMIT command with the POSLIST keyword sets the status of a dimension based on the position of the values within that dimension.
Syntax
LIMIT {dimension | valueset} [concat-component] limit-type -
POSLIST poslist-exp [IFNONE label]
Parameters
The name of the dimension or dimension surrogate for which you are setting status.
The name of the valueset for which you are assigning values; or a LIMIT function.
The name of the component of the concat dimension whose values are used to determine the limit. (See the main entry for LIMIT command for complete description of this argument.)
A standard keyword (documented in the main entry for LIMIT command) that specifies how Oracle OLAP should modify the current status list.
Sets the status of a dimension based on the position of a value within a dimension. poslist-textexp is a text expression, each line of which is a numeric value that evaluates to a numeric position of the dimension being limited.
Specifies that program execution should branch to label when the requested status has null status or is based on a related dimension that turns out to have null status (that is, to have no values). (See the main entry for LIMIT command for complete description of this phrase.)
The MODULO function, like the SQL MOD function, returns the remainder after a number is divided by another; or the number if the divisor is 0 (zero).
Return Values
Numeric.
Oracle determines the argument with the highest numeric precedence, implicitly converts the remaining arguments to that data type, and returns that data type
Syntax
MOD(dividend, divisor)
Parameters
A numeric expression (or an expression that Oracle OLAP can implicitly convert to a numeric expression) that is the number you want to divide.
A numeric expression (or an expression that Oracle OLAP can implicitly convert to a numeric expression) that is the divisor.
Examples
Use the PARSE command to parse a specified group of expressions. When the argument can be parsed, PARSE determines the number of expressions in it and their text, object type, data type, and the number and names of their dimensions. This information is stored internally by Oracle OLAP, but can be obtained with the INFO function.
A PARSE statement is especially useful when you want to accept expressions as arguments to a program.
Syntax
PARSE text-expression
Parameters
A text expression that contains one or more smaller expressions to be parsed. When you are processing program arguments, you can specify an ARGS function as the text expression that contains all the arguments for the program.
Usage Notes
Obtaining Information Produced by a PARSE Statement
See the INFO (PARSE) function for an explanation of how to obtain the information produced by a PARSE statement.
Examples
Example 10-72 Parsing the Arguments to a Program
In a simple report program, you want to specify the data to be reported as an argument to the program. You want to be able to specify an expression and the name of a data variable.
Suppose you want to display each of the arguments with a different column width, which means you must process the arguments individually. The ARGS function can only process them together. So you use PARSE and INFO to parse the arguments and produce individual columns for each of them. Here is a sample program.
DEFINE report1 PROGRAM PROGRAM PUSH month product district DECIMALS DECIMALS = 0 LIMIT month TO FIRST 2 LIMIT product TO ALL LIMIT district TO 'Chicago' PARSE ARGS REPORT ACROSS month WIDTH 8 <&INFO(PARSE FORMULA 1) - WIDTH 13 &INFO(PARSE FORMULA 2)> POP month product district DECIMALS END
When you run the program, you can supply either the names of variables (such as sales) or expressions (such as sales-expense) or one of each as arguments. The following REPORT statement produces the illustrated report.
report1 sales sales-expense
DISTRICT: CHICAGO
--------------------MONTH--------------------
--------JAN95--------- --------FEB95---------
PRODUCT SALES SALES-EXPENSE SALES SALES-EXPENSE
------------ -------- ------------- -------- -------------
Tents 29,099 1,595 29,010 1,505
Canoes 45,278 292 50,596 477
Racquets 54,270 1,400 58,158 1,863
Sportswear 72,123 7,719 80,072 9,333
Footwear 90,288 8,117 96,539 13,847
OLAP_EXPRESSION_DATE is a SQL function that dynamically executes an OLAP DML datetime expression within the context of an OLAP_TABLE function. In addition to returning a custom measure, you can use this function in the WHERE and ORDER BY clauses to modify the result set of the query of the analytic workspace.
OLAP_EXPRESSION_TEXT returns character data. To return numeric, boolean, or text data, use OLAP_EXPRESSION, OLAP_EXPRESSION_BOOL, or OLAP_EXPRESSION_TEXT SQL functions.
Before you use this function, you must specify a ROW2CELL clause in the limit map used by OLAP_TABLE. ROW2CELL identifies a RAW column that OLAP_TABLE populates with information used by the OLAP single-row functions.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
An evaluation of date_expression for each row of the table object returned by the OLAP_TABLE function.
OLAP_EXPRESSION_DATE returns date data. To return numeric, boolean, or text data, use the OLAP_EXPRESSION, OLAP_EXPRESSION_BOOL, or OLAP_EXPRESSION_TEXT functions.
Syntax
OLAP_EXPRESSION_DATE(
r2c IN RAW(32),
date_expression IN VARCHAR2)
RETURN NUMBER;
Parameters
The name of a column specified by a ROW2CELL clause in the limit map. See "ROW2CELL Clause" of OLAP_TABLE
An OLAP DML expression that returns an OLAP DML datetime result.
Examples
Refer to the examples in OLAP_EXPRESSION and OLAP_EXPRESSION_BOOL for examples of OLAP single-row functions.
The AWDESCRIBE program sends information about the current analytic workspace to the current outfile. After a summary page, it provides a report in two parts:
An alphabetic list of analytic workspace objects showing name, type, and description.
A list of object definitions by object type. Each definition includes the information you would see when you used the DESCRIBE statement. It also includes a "Referenced By" list, which indicates any programs or other compilable objects that call or access the object. In addition, compilable objects have a "References To" list, indicating the analytic workspace objects that they call or access.
Syntax
AWDESCRIBE
Usage Notes
Information in Referenced By List
The AWDESCRIBE command does not provide information in the "Referenced By" and "References To" list for implicit references. For example: When a program contains a LIMIT command to limit a dimension by a related dimension, AWDESCRIBE does not list the relation for those dimensions in the "References To" list for that program.
Examples
Example 9-56 Describing an analytic workspace
The following example shows a portion of the output of AWDESCRIBE for an analytic workspace named demo.
DEMO Workspace Listing
=====================
Last updated: 25Jun96 Time: 09:46:50
Print date: 27Aug96 Time: 10:30:11
DEMO contains:
11 DIMENSIONS
19 VARIABLES
1 PROGRAM
4 RELATIONS
2 VALUESETS
This report is in two parts:
- Object Listing: An alphabetic list of workspace objects,
beginning on the next page.
- Object Descriptions: Detailed descriptions of all workspace
objects, sorted by object type and alphabetically by name.
Object List Page 2
Workspace: DEMO Updated: 25Jun96 At: 09:46:50 ACTUAL
NAME TYPE DESCRIPTION
____ ____ ___________
ACTUAL VARIABLE Actual $ Financials
ADVERTISING VARIABLE Total Advertising Dollars
BUDGET VARIABLE Budgeted $ Financials
CHOICE DIMENSION List of choices
CHOICEDESC VARIABLE Description line for the choices
DEMOVER VARIABLE DEMO Workspace Version
DISTRICT DIMENSION
DIVISION DIMENSION Division
DIVISION.PRODUCT RELATION DIVISION for each PRODUCT
EXPENSE VARIABLE Total Production & Distribution Cost
FCST VARIABLE Forecasted $ Financials
INDUSTRY.SALES VARIABLE Total Industry Sales Revenue
LINE DIMENSION Lineitem
MARKET DIMENSION Geography Dim with Embedded Totals
MARKET.MARKET RELATION Self-relation for the Market Dim
MARKETLEVEL DIMENSION Geography Level
MLV.MARKET RELATION
MONTH DIMENSION
NAME.LINE VARIABLE Lineitem Names for Reporting
NAME.PRODUCT VARIABLE Product Names for Reporting Purposes
NATIONAL.SALES VARIABLE Projected Total U.S. Dollar Sales
NOT.IMPLEMENTED PROGRAM
PRICE VARIABLE Wholesale Unit Selling Price
PRODUCT DIMENSION Sporting Goods Products
PRODUCT.MEMO VARIABLE Product Analysis Memo
PRODUCTSET VALUESET Valueset for Sporting Goods Products
QUARTER DIMENSION
QUARTERSET VALUESET
REGION DIMENSION Sales Region
REGION.DISTRICT RELATION REGION for each DISTRICT
SALES VARIABLE Sales Revenue
SALES.FORECAST VARIABLE Forecasted Unit Sales
SALES.PLAN VARIABLE Budgeted Sales Revenue
SHARE VARIABLE Market Share (Based on Dollar Sales)
UNITS VARIABLE Actual Unit Shipments
UNITS.M VARIABLE
YEAR DIMENSION
Description of DIMENSIONS Page 3
Workspace: DEMO Updated: 25Jun96 At: 09:46:50 CHOICE
DEFINE CHOICE DIMENSION TEXT
LD List of choices
Referenced By:
NONE
DEFINE DISTRICT DIMENSION TEXT
Referenced By:
NONE
DEFINE DIVISION DIMENSION TEXT
LD Division
Referenced By:
NONE
...
The INFILE procedure evaluates the OLAP DML commands in the specified file and executes them in the current analytic workspace.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
INFILE (
filename IN VARCHAR2);
Parameters
Table B-23 INFILE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of a file containing OLAP DML commands. The file path must be specified in a current directory object for your OLAP session. Use the OLAP DML CDA command to identify or change the current directory object. |
Example
The following example executes the OLAP DML commands in the finances.inf file. The location of the file is identified by the WORK_DIR database directory.
EXECUTE dbms_aw.infile('work_dir/finances.inf');
The FILESET command sets the paging attributes of a specified fileunit.
Syntax
FILESET fileunit attrib-arg1 exp1 [attrib-argN expN ...]
where attrib-arg is one of the following:
Parameters
A fileunit number that is assigned to a file opened previously using a FILEOPEN statement or by an OUTFILE statement. You can set attributes only for an open file. An attribute argument specifies the file characteristic to change. The attribute must be appropriate for the fileunit specified; otherwise, Oracle OLAP returns an error. You can set several attributes in one FILESET statement by listing the attribute name and its new value in pairs.
Specifies the number of blank lines that constitute the bottom margin.
Specifies the current line number. Resets after each page break when PAGING is on; otherwise, keeps incrementing.
Specifies the maximum line length for text output files, or the record length for binary input files.
Specifies the type of system on which the file was created. The default value of the ORIGIN attribute reflects the system you are currently working on, so you must set ORIGIN when the file originated on a different system. The setting of ORIGIN affects how data reading statements interpret the files. For example, data reading statements use this information to decide whether bytes of binary data have to be reversed, and so forth. Table 9-8, "Values for ORIGIN Clause of FILESET" helps you make the right choice. When your system is not listed, try using PC or HP as the value of ORIGIN. When one value does not work, the other one should.
Table 9-8 Values for ORIGIN Clause of FILESET
| Value | Hardware or Operating System |
|---|---|
|
ALPHA |
Any DEC workstation using an Alpha processor |
|
AVMS |
A DEC Alpha processor running on VM |
|
HP |
HP MPE XL |
|
HPS700 |
HP Series 700 Workstation |
|
HPS800 |
HP Series 800 Workstation |
|
IBMPC |
An Intel processor running DOS, Windows, or Windows N |
|
INTEL5 |
Any Intel5 processor running UNIX |
|
MIPS |
Any MIPS system |
|
MVS |
IBM MVS/TSO |
|
NTALPHA |
A DEC Alpha processor running Windows NT |
|
PC |
An Intel processor running DOS, Windows, or Windows NT |
|
RS6000 |
Any IBM RS6000 processor running IBM AIX |
|
SOLARIS2 |
Any workstation running Solaris2 |
|
SUNOS4 |
Any workstation running SunOS4 |
|
VAX |
VAX VMS (floating point in G format only) |
|
VM |
VM/CMS |
Specifies the current page number.
Specifies the OLAP DML program that produces page titles and headings when output is paged.
Specifies the number of lines on each page.
Specifies if the output is formatted in pages which is equivalent to setting the PAGING option to YES.
Specifies if Oracle OLAP should pause after each page.
Specifies if tab characters should be expanded. When TABEXPAND is zero, tab characters are not expanded. A value greater than 0 indicates the distance, in bytes, between tab stops. The default value of TABEXPAND is 8.
Specifies the number of blank lines that constitute the top margin.
An expression that contains the new value for the attribute being set. The data type of the expression must be the same as the data type of the attribute.
Examples
Example 9-132 Setting Paging for a Report
When you are sending output to a report in a disk file, you might set the following attributes to indicate that the report is organized in pages and that the first page is 1.
DEFINE fil.unit INTEGER
fil.unit = FILEOPEN('REPORT' WRITE)
FILESET fil.unit PAGING YES PAGENUM 1
For dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR, the BEGINDATE function returns the first date of the first time period in dimension status for which the expression has a non-NA value. For example, assume that an expression is dimensioned by month, and that Jan97 is the first dimension value for which the expression has a non-NA value. In this case, BEGINDATE returns the date January 1, 1997.
|
Note: You cannot use this function for time dimensions that are implemented as hierarchical dimensions of type TEXT. |
Return Value
DATE-only or text
When all the values of the expression are NA, BEGINDATE returns NA.
Syntax
BEGINDATE(expression)
Parameters
The expression must have exactly one dimension that has a type of DAY, WEEK, MONTH, QUARTER, or YEAR.
Examples
Example 7-32 Finding the Beginning Date
The following statements limit the values in the month, product, and district dimensions, then send the first date for which the units variable contains a non-NA value for unit sales of tents in the Chicago district to the current outfile.
LIMIT month TO ALL LIMIT product TO 'TENTS' LIMIT district TO 'CHICAGO' SHOW BEGINDATE(units)
These statements produce the following output.
01JAN95
This section identifies the new features of the Oracle Database 11g that relate to the OLAP DML and lists the Oracle OLAP DML statements that were added, changed, renamed, or deleted in Oracle Database 9i and Oracle Database 10g.
In Oracle Database 11g, the following changes were made to the Oracle OLAP DML:
Table Privileges Needed When Working With Analytic Workspaces
Support for OLAP Cubes, Cube Dimensions, and Cube Materialized Views
Also, as outlined in "Changes to the SQL OLAP_TABLE Function", there are several changes in the OLAP_TABLE SQL function which you can use to create relational views of OLAP DML data structures.
In Oracle Database 11g, you must have the correct privileges to create and delete analytic workspaces. For more information, see "Privileges Needed to Create and Delete Analytic Workspaces".
In Oracle Database 11g, the following OLAP DML statements have been added or changed to offer more support for grouping ids:
A new GROUPINGID function
New ROLLUP and GROUPSET keywords in the GROUPINGID command
New $GID_DEPTH, $GID_LIST, and $GID_TYPE system properties
In Oracle Database 11g, the following changes have been made to support explicit looping:
New WHERE clause in the ACROSS command that you can use to specify if the DO loop in that command is executed for an iteration of the loop.
New looping $LOOP_AGGMAP, $LOOP_DENSE, and $LOOP_VAR properties which are used by the OLAP_TABLE SQL function.
Additionally, in the limitmap parameter of the OLAP_TABLE SQL function there is support for a more complex Loop clause and a new Loop optimized clause.
In Oracle Database 11g, the following changes have been made to enhance aggregation:
Aggregation by partition. See AGGREGATE command for details
Clearing variables based on different aggmap objects. See the CLEAR command for details.
Checking to see if there are any changes in an aggmap since the last time a variable was aggregated using that aggmap. See the CHANGEDRELATIONS function for details.
Checking to see any value in a variable has changed (or the number of values that have changed) since the last time a variable was aggregated. See the CHANGEDVALUES function for details.
Checking to see if a variable or one or more of its partitions has values. See the ISEMPTY function for details.
Identifying the depth of a hierarchy. See the HIERDEPTH command for details.
Identifying the shape of a hierarchy. See the HIERSHAPE function for details.
In Oracle Database 11g, the AW command has been modified to support caching which removes the time needed to open an analytic workspace for repeated queries
AW command has new PURGE CACHE keyword.
AW ATTACH command now uses the cached version of an analytic workspace if one is available rather than opening a current version.
AW DETACH command has a new CACHE keyword that specifies that an analytic workspace that is being detached is considered a candidate for caching.
AW TRUNCATE command has been improved
In Oracle Database 11g, the AW command has been modified as follows:
AW command has new FREEZE and THAW keywords
AW ATTACH command has a new THAW keyword.
Additionally, the AW function has been modified to include a FROZEN keyword.
In Oracle Database 11g, the following OLAP DML data types have been added that correspond to SQL built-in data types:
Datetime and interval data types.You can define dimensions and surrogates with datetime data types. You can define variables, formulas, and programs with both datetime and interval data types. For more information, see "Datetime and Interval Data Types", "Datetime and Interval Expressions", and the following OLAP DML statements:
RAW data type. For more information, see "RAW Data Type".
Row identifier data types. more information, see "Row Identifier Data Types".:
The addition of these data types impacted the following OLAP DML statements:
In Oracle11g, the following functions, which are based on SQL functions of the same name, were added to the OLAP DML.
MOD function)Additionally:
The OLAP DML LOG function was modified so that it corresponds more exactly to its SQL counterpart.
The new OLAP DML ISINFINITE and ISNAN functions provide information similar provided by the SQL floating point conditions.
With this release, "logical" OLAP objects (cube and cube dimensions) have been added as first-class Oracle data objects that are defined in the Oracle data dicitionary. These "logical" OLAP objects overlay a number of underlying "physical" OLAP objects that are defined in the analytic workspace itself.
Many of the Oracle Database OLAP features that are new in this release were added to support the use of OLAP cubes and cube materialized views:
The following OLAP DML programs are provided that let you work with OLAP cubes and cube dimensions:
Also, the OBJORG function has been added so that you can use OLAP DML statements that are not cube-aware with OLAP cubes and cube dimensions.
The following changes have been made to the OLAP DML so that it optimally handles OLAP data cells which correspond to relational null facts:
The DEFINE VARIABLE command now has a WITH NULLTRACKING phrase.
Two new functions, NA2 and NAFLAG , return values that Oracle OLAP uses to identify how an OLAP data value corresponds to a relational fact.
The CHGDFN command now includes syntax that adds or removes NA2 bits from a variable.
Typically, these OLAP DML statements are automatically generated during the process of creating a cube materialized view; you do not explicitly write DML code that uses these new features. These changes are documented in this manual so that you can understand the automatically-generated DML statements.
Additionally, the default behavior of the EXPORT (EIF) and IMPORT (EIF) commands is to export and import cube metadata. There is a new keyword (NOAPI) that you can specify when you do not want this behavior.
In earlier releases of the OLAP DML, when you defined a composite using a DEFINE COMPOSITE command, you could specify a composite as a base object of another composite. This functionality was rarely, if ever, used. Beginning, in Oracle Database 11g, the base object of a composite can only be a dimension. If you have any nested composites in an existing analytic workspace, when you convert that analytic workspace into When you import nested composites from earlier versions into an Oracle Database 11g analytic workspace, IMPORT (EIF) automatically unnests the composites.
In some cases there are multiple status lists for a dimension. You can use the new STATCURR function to retrieve a status list value based on from a status list based on the position of that list within the status list stack for the dimension.
OLAP_TABLE is a SQL function that extracts multidimensional data from an analytic workspace and presents it in the two-dimensional format of a relational table. As Oracle OLAP is more tightly integrated into Oracle Database 11g, you no longer must use a MODEL clause in a SELECT FROM OLAP_TABLE statement to enhance performance.
This section contains listings of the OLAP DML statements that were added, changed, renamed, or deleted in Oracle Database 11g:
The following statements have been added to the OLAP DML in Oracle Database 11g. The number in parentheses indicates the specific release in which the statement was added.
SORTCOMPOSITE option
The following statements have been changed in the OLAP DML in Oracle Database 11g. The number in parentheses indicates the most recent release in which the statement was changed.
No statements have been renamed in the OLAP DML in Oracle Database 11g.
This section contains listings of the OLAP DML statements that were added, changed, renamed, or deleted in Oracle Database 10g:
The following statements were added to the OLAP DML in Oracle Database 10g. The number in parentheses indicates the specific release in which the statement was added.
The following statements were deleted from the OLAP DML in Oracle Database 10g. The number in parentheses indicates the specific release in which the statement was deleted.
The following OLAP DML statements were significantly changed in Oracle Database 10g. Examples of significant changes are the addition of a new keyword or a change in a default value. The number in parentheses indicates the last release in which the statement was significantly changed.
No OLAP DML statements have been renamed in Oracle Database 10g.
This section contains listings of the OLAP DML statement changes in Oracle Database 9i.
The following statements were added to the OLAP DML in Oracle Database 9i. The number in parentheses indicates the specific release in which the statement was added.
The following statements were deleted from the OLAP DML in Oracle Database 9i. The number in parentheses indicates the specific release in which the statement was deleted.
The following OLAP DML statements were significantly changed in Oracle Database 9i and have not changed since then. Examples of significant changes are the addition of a new keyword or a change in a default value. The number in parentheses indicates the last release in which the statement was significantly changed. See also "Statements Renamed in Oracle Database 9i" for a list of renamed statements.
The following OLAP DML statements were renamed in Oracle Database 9i. The number in parentheses indicates the specific release in which the statement was renamed.
The MAINTAIN command enters and maintains the values of dimensions, composites, and partition template objects.
|
Note: You can also issue a MAINTAIN statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN object {ADD|DELETE|RENAME|MOVE|MERGE} args
The keywords that you can use with the MAINTAIN command varies by object:
MAINTAIN dimension {ADD|DELETE|RENAME|MOVE|MERGE} args
The keyword that you can use varies by the type of dimension that you want to maintain:
With a non-concat dimension, you can use the ADD, DELETE, RENAME, MOVE, or MERGE keywords to add, delete, rename, move, or merge non-concat dimension values. You can also use the ADD keyword to add temporary calculated members to a dimension.
With a concat dimension, you can only use the MOVE keyword to move concat dimension values.
MAINTAIN composite {ADD|DELETE|MERGE} args
MAINTAIN partition-template {ADD|DELETE|MOVE} args
The specific syntax varies by keyword. Consequently, there are separate topics for each keyword of the MAINTAIN command:
For information that applies to the MAINTAIN command in general, see the Usage Notes in this topic.
Usage Notes
Triggering Program Execution When MAINTAIN Executes
Using the TRIGGER command, you can make the execution of a MAINTAIN statement an event that automatically executes an OLAP DML program. See "Trigger Programs" for more information.
Automatic Status Reset
When you use the ADD, DELETE, MERGE, or MOVE keyword to maintain a dimension or composite whose status is not currently ALL, the MAINTAIN command automatically resets status to ALL before performing the maintenance function. However, when you use the RENAME keyword to maintain a dimension whose status is not currently ALL, the MAINTAIN command does not change the status of the dimension.
Maintain Permission
You cannot perform maintenance on a dimension when a PERMIT MAINTAIN statement denies maintain permission for the dimension. Maintain permission is implicitly denied whenever read permission is restricted for a dimension, even when you specify maintain permission for the dimension. (See the PERMIT command.)
Maintaining Dimensions in Multiwriter Analytic Workspaces
Keep the following points in mind when maintaining dimensions in an analytic workspace that is attached in multiwriter mode:
You cannot update a variable when any of its dimensions have been acquired and modified.
Reverting a dimension after adding dimension values is not recommended since it can result in suboptimal space allocation for variables dimensioned by the dimension.
When an acquired variable is dimensioned by an acquired dimension that has been maintained, you cannot update the variable until the dimension is updated or released.
You do not have to acquire composites in order for them to be maintained, Oracle OLAP automatically performs concurrent dimension maintenance for the composite dimensions.
Also, before you can maintain dimensions in an analytic workspace that is attached in multiwriter mode, you must first acquire the dimension using an ACQUIRE statement.
For example, assume that user A and user B both have to perform what-if computations on both actuals and budget. After performing the what-if computations, user A needs to modify actuals and B needs to modify budget. Finally, both user A and user B have to add a new time dimension value and add data corresponding to that new dimension value to actuals or budget.
User A issues the following OLAP DML statements.
AW ATTACH myworkspace MULTI ...make modifications ACQUIRE actuals ...make more modifications ACQUIRE time MAINTAIN time ADD 'Y2002' actuals (time 'Y2002', ...) = ... UPDATE MULTI actuals, time COMMIT RELEASE actuals, time AW DETACH myworkspace
User B issues the following OLAP DML statements.
AW ATTACH myworkspace MULTI ...make modifications ACQUIRE budget ...make more modifications ACQUIRE time--> failed ACQUIRE RESYNC time WAIT MAINTAIN time ADD 'Y2003' budget (time 'Y2003', ...) = ... UPDATE MULTI budget, time COMMIT RELEASE budget, time AW DETACH myworkspace
MAINTAIN and Dimension Surrogates
You cannot use a MAINTAIN statement on a dimension surrogate. You can only use MAINTAIN to add values to or delete them from a dimension. However, when you add or delete a dimension value, then Oracle OLAP adds or removes a position from surrogates of that dimension. When you add a position to a dimension, the corresponding position in a surrogate for that dimension receives an NA value.
Maintaining a Concat Dimension
A concat dimension contains the values of its component dimensions. You do not directly add, merge, or delete the values of a concat dimension using MAINTAIN statements. Instead, when you add, merge, or delete values from a component dimension of the concat, Oracle OLAP automatically adds or deletes the values from the concat dimension. You can use the MOVE keyword of the MAINTAIN command to change the order of the values of a concat dimension.
The MAINTAIN command with the ADD keyword adds new TEXT, ID, and INTEGER values to a non-concat dimension, composite, or partition; or adds a new temporary calculated member to a dimension.
|
Note: You can also issue a MAINTAIN ADD for TEXT, ID, and INTEGER Values statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program one time for each value; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
The syntax for using the MAINTAIN command with the ADD keyword depends on the type of the object being maintained and whether you are adding a permanent or temporary member.
For this reason, the following separate entries are provided for MAINTAIN ADD:
The MAINTAIN command with the ADD keyword adds new TEXT, ID, or INTEGER values to a non-concat dimension or composite.
|
Note: You can also issue this MAINTAIN ADD statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program one time for each value in valuelist; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN composite|dimension ADD valuelist [FIRST|LAST|BEFORE position|AFTER position]
Parameters
A non-concat dimension, already defined in an attached analytic workspace.
A composite. When the composite is a named composite, it must be defined in an attached analytic workspace. When the composite is unnamed, it must have been used in defining an object in an attached analytic workspace. Use the SPARSE keyword to refer to an unnamed composite (for example, SPARSE <market product>).
Specifies that the values in valuelist are to be added to the dimension or composite:
When you use this argument to add values to a composite or a dimension of type TEXT or ID, the valuelist can be text literals or a TEXT or ID expression. When it is a multiline text expression, each element (line) is treated as a separate value.Do not add null dimension values (empty single quotes) or values that consists of spaces only, because there is no way you can refer to such values in the future.
When dimension is INTEGER, valuelist can be an INTEGER quantity, such as 5 or 100.
Specify the logical position at which dimension values are added. FIRST indicates that the new values are inserted before any existing values. LAST indicates that new values are added after the current values. LAST is the default. When you are adding a certain quantity of INTEGER values to an INTEGER dimension, that quantity of INTEGER values are added before or after any existing INTEGER values (depending on your specification), and all the INTEGER values in the resulting series are automatically adjusted into simple numeric order.
All values specified before the keyword FIRST or LAST are placed in that position, not just the one value immediately preceding the keyword in your statement.
Specify a position before or after which the dimension values are to be added. For position you can specify an existing dimension value, a character expression whose value is an existing dimension value, or an INTEGER expression whose value represents the position of a dimension value. When you are adding a certain quantity of INTEGER values to an INTEGER dimension, that quantity of INTEGER values are added before or after the INTEGER position you specify, and the INTEGER values in the whole of the resulting series are automatically adjusted into simple numeric order.
All values specified before the keywords BEFORE or AFTER are placed in that position, not just the one value immediately preceding the keyword in your statement.
Usage Notes
Performance When Using MAINTAIN ADD BEFORE or AFTER position
The cost performance of using MAINTAIN ADD BEFORE or MAINTAIN MOVE AFTER statements depends on the number of values in the dimension rather than the number of values being added. Consequently, instead of issuing many of these statements one after another:
Add the values using simple MAINTAIN ADD statements
Set the status of the dimension status to the values you are concerned with.
Order the added values, by issuing a single MAINTAIN MOVE dimension value statement
Adding Values to an INTEGER Dimension
When you use MAINTAIN to add values in an INTEGER dimension, the values are renumbered to keep the normal sequence of INTEGER values (1, 2, 3, ...).
Conjoint Dimensions and Composites
Each value of a conjoint dimension or composite is a combination of values from each of the dimensions (and composites, if any) in its dimension list. To add values to a conjoint dimension or composite, specify each value combination enclosed in angle brackets. The values in a given combination must be in the same order as the dimensions and composites in the definition of the conjoint dimension or composite. Each dimension value in the combination must already exist as a value in the corresponding base dimension. However, when a composite value in the combination does not exist, Oracle OLAP automatically adds the value to the appropriate composite.
Examples
Example 10-39 Adding Values to a TEXT Dimension
This statement adds Omaha and Seattle to the end of the dimension values for the city dimension.
MAINTAIN city ADD 'Omaha' 'Seattle'
This statement adds Atlanta at the beginning of the list of cities and inserts Peoria after Omaha.
MAINTAIN city ADD 'Atlanta' FIRST, 'Peoria' AFTER 'Omaha'
Here the value of the TEXT variable textvar is inserted before the fifth dimension value of city. When you assign the value Columbus to textvar, you must make sure it is in mixed case, because you want the dimension value to be in mixed case.
textvar = 'Columbus' MAINTAIN city ADD textvar BEFORE 5
Example 10-40 Adding Values to a Conjoint Dimension
The following is an example of adding values to a conjoint dimension.
DEFINE proddist DIMENSION <product, district> MAINTAIN proddist ADD <'Tents' 'Boston'> <'Footwear' 'Denver'>
You can also assign a value of a base dimension to a text variable and use the name of the variable inside the angle brackets.
prodname = 'Canoes' distname = 'Seattle' MAINTAIN proddist ADD <prodname, distname>
The MAINTAIN command with the ADD keyword adds new values to a dimension of type DAY, WEEK, MONTH, QUARTER, and YEAR.
Syntax
MAINTAIN dimension ADD {valuelist|{n PERIODS FIRST}|{n PERIODS LAST}}
Parameters
A non-concat dimension, already defined in an attached analytic workspace.
Specifies that the values in valuelist are to be added to the dimension. When dimension is of type DAY, WEEK, MONTH, QUARTER, or YEAR, then valuelist can be text constants or a TEXT, ID, or DATE expression. When the values are TEXT, they can be in the format specified by the VNF (value name format) for the dimension (or in the default format for the type of dimension you are maintaining when the dimension does not have a VNF) or in a valid input style for date values. When the values are specified as a TEXT expression, each element or line is treated as a separate value.
When the values are in the format specified by the VNF or in the default format for this type of dimension, each value explicitly indicates the time period you want to add. For example, assume that the VNF for a month dimension is '<MTXT><YY>'. In this case, the value JAN99 represents the month January 1999.
When you specify a value for a DAY, WEEK, MONTH, QUARTER, or YEAR dimension as a date, you must provide only the date components that are relevant for the type of dimension you are maintaining. For a DAY or WEEK dimension, you must supply the day, month, and year components. For a MONTH or QUARTER dimension, you must supply only the month and year (for example, 'JUN98' or '0698' for June 1998). For a YEAR dimension, you must specify only the year (for example, '98' for 1998). For information about the valid input styles for dates, see the DATEORDER option.
When you add a dimension value by specifying a DATE expression or a TEXT value that represents a complete date, you can specify any date that falls within the time period you want to add. For example, to add the month January 1999, you can specify any date from '01JAN99' through '31JAN99'. Oracle OLAP uses the DATEORDER option to resolve any ambiguities.
When adding values to a DAY, WEEK, MONTH, QUARTER, or YEAR dimension that does not yet have values, you must specify only the first and last values you want to add for the dimension. Oracle OLAP automatically fills in the gaps with appropriate values for the intervening time periods.
When a DAY, WEEK, MONTH, QUARTER, or YEAR dimension already has values, you can add values only at the beginning or the end of the existing list. To add values, you must specify only the first or last value you want to add. Oracle OLAP automatically fills in the gap between the existing list and the value you specify.
Specifies the number of periods to add at the beginning or end of an existing list of dimension values.
Examples
Example 10-41 Adding Values to Dimension of Type QUARTER
In this example you define a new QUARTER dimension, called qtr, and you add dimension values for the quarters in 1998 and 1999. You must only add the first and last dimension values you want. Oracle OLAP fills in the intervening values. To add the first and last quarters, you can specify any dates that fall within those quarters.
DEFINE qtr DIMENSION QUARTER MAINTAIN qtr ADD '01jan98' '31dec99'
The MAINTAIN command with the ADD SESSION keywords adds a temporary calculated member to a dimension and applies it to the specified objects; or applies a previously-defined calculated member to the specified objects. The calculated member and its definition do not persist from session to session; both are deleted after the session in which they are created.
Syntax
MAINTAIN dimension ADD SESSION member_name [= calculation] -
[STEP DIMENSION (stepdim...)][apply-to]
where:
calculation is one of the following:
apply-to specifies the basis on which the custom aggregation is added using one of the following phrases:
Parameters
A dimension that is already defined in an attached analytic workspace. You can specify any type of dimension for dimension except a non-unique concat dimension or a base dimension of either a unique or non-unique concat dimension.
ADD SESSION indicates maintenance of a temporary calculated member.
Specifies the name of the temporary calculated member.
Indicates that you are defining a new calculated member.
A text expression that specifies the calculation used as a dynamic model to calculate custom member values. (See the SET command for more information about model equations.)
Indicates that the temporary calculated member is added as a custom aggregation using the specified dimension members. This clause effectively modifies the RELATION statement of aggmap objects that are the aggregation specification for variables dimensioned by dimension. Consequently, a MAINTAIN ADD SESSION statement that contains an AGGREGATION clause must also contain an APPLY WITH RELATION clause.
A text expression that specifies one or more dimension values to be used by the custom aggregation. When using a literal to specify multiple dimension members, separate the values with commas
Indicates that the calculation is a time-series function.
A text expression that specifies the dimension along which the time-series function is calculated. When using a literal to specify multiple dimension names, separate the names with commas.
Indicates that the calculated temporary member is added only to dimensions used by the specified aggmap objects.
A text expression that specifies the name of one or more aggmap objects to which the temporary calculated member is added. When using a literal to specify multiple aggmap objects, separate the names with commas. The temporary calculated member is added to each of the specified aggmap objects.
Indicates that the temporary calculated member is added only to dimensions used by the default aggmap objects for the specified variables.
A text expression that specifies the one or more variable names for which the temporary calculated member is added to. When using a literal to specify multiple variable names, separate the names with commas. The temporary calculated member is added to the default aggmap object of each specified variable.
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Important: When a specified variable does not have a default aggmap, using this clause generates an error. Use AGGMAP SET or $AGGMAP to specify a default aggmap for the variable. |
Indicates that the temporary calculated member is added dimensions used by the aggregation specifications that contain a RELATION statement for the specified relation.
A text expression that specifies the name of the relation for which there must be a RELATION statement in the AGGMAP statement.
Usage Notes
Finding Out Information About Temporary Calculated Members
Once you have added a temporary calculated member using a MAINTAIN statement, you can use AGGMAPINFO to discover the temporary calculated members you have added, the equations used to calculate members, and the dimension members used in the right-hand side of equations used to calculate custom members.
Examples
Example 10-42 Creating Calculated Dimension Members with Aggregated Values
Assume that an analytic workspace has a dimension named letter and a variable named my_quantity with the following definitions and permanent values.
DEFINE letter DIMENSION TEXT DEFINE my_quantity VARIABLE DECIMAL <letter> LETTER MY_QUANTITY -------------- ------------------------------ A 10.00 B 100.00
You can define temporary dimension members for the letter dimension and aggregate data in my_quantity for those members following these steps:
Determine the aggregation that you want to perform and define and populate the necessary supporting objects.
Create an empty child-parent relation for the letter dimension
DEFINE letter.parentrel RELATION letter <letter> LETTER LETTER.PARENTREL -------------- ------------------------------ A NA B NA
Define a simple model to be used to calculate values associated with the letter dimension
DEFINE my_model MODEL MODEL DIMENSION letter END
Define and compile a simple aggmap to be used to calculate my_quantity values associated with the letter dimension
DEFINE my_aggmap AGGMAP AGGMAP RELATION letter.parentrel PRECOMPUTE(NA) MODEL my_model PRECOMPUTE(NA) END COMPILE my_aggmap
Define a variable to contain the definition for the custom aggregation, This new variable is the same as my_quantity except that has my_aggmap as its default aggmap.
DEFINE my_quantity_definition VARIABLE DECIMAL <letter> CONSIDER my_quantity_definition PROPERTY '$AGGMAP' 'my_aggmap' REPORT my_quantity_definition LETTER MY_QUANTITY_DEFINITION -------------- ------------------------------ A NA B NA
Add temporary members to the letter dimension and specify how variable values for those members are to be calculated.
MAINTAIN letter ADD SESSION 'C' = 'A' * 'B'
MAINTAIN letter ADD SESSION 'D' = AGGREGATION('A', 'B') -
APPLY TO AGGMAP my_aggmap
MAINTAIN letter ADD SESSION 'E' = 'C' + 'D' -
APPLY WITH RELATION letter.parentrel
MAINTAIN letter ADD SESSION 'F' = 10 * 'E' -
APPLY FOR VARIABLE my_quantity_definition
A report of the letter dimension shows the new dimension members.
LETTER -------------- A B C D E F
Aggregate my_quantity using the aggmap object named my_aggmap.
REPORT AGGREGATE(my_quantity USING my_aggmap)
AGGREGATE(MY_QUANT ITY USING
LETTER MY_AGGMAP)
-------------- ------------------------------
A 10.00
B 100.00
C 1,000.00
D 110.00
E 1,110.00
F 11,100.00
Assume now that you issue the UPDATE and COMMIT statements to update and commit your analytic workspace. Then you detach the analytic workspace and end your session.
Later you start a new session and attach the same analytic workspace. When you ask for a description of the analytic workspace you can see that all of the objects that were in the analytic workspace when the UPDATE was issued still exist.
DEFINE LETTER DIMENSION TEXT DEFINE LETTER.PARENTREL RELATION LETTER <LETTER> DEFINE MY_QUANTITY VARIABLE DECIMAL <LETTER> DEFINE MY_MODEL MODEL MODEL DIMENSION letter END DEFINE MY_AGGMAP AGGMAP AGGMAP RELATION letter.parentrel PRECOMPUTE(NA) MODEL my_model PRECOMPUTE(NA) END DEFINE MY_QUANTITY_DEFINITION VARIABLE DECIMAL <LETTER>
However, when you report on the letter dimension and the my_quantity variable, the temporary dimension members that you added in the previous session and their related values in the my_quantity variable do not exist.
LETTER
--------------
A
B
REPORT letter.parentrel
LETTER LETTER.PARENTREL
-------------- ------------------------------
A NA
B NA
REPORT my_quantity
LETTER MY_QUANTITY
-------------- ------------------------------
A 10.00
B 100.00
LETTER MY_QUANTITY_DEFINITION
-------------- ------------------------------
A NA
B NA
REPORT AGGREGATE(my_quantity USING my_aggmap)
AGGREGATE(MY_QUANTITY USING
LETTER MY_AGGMAP)
-------------- ------------------------------
A 10.00
B 100.00
The MAINTAIN ADD TO PARTITION statement adds previously-populated dimension or composite values to a partition of a previously-defined partition template object.
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Tip: Use MAINTAIN MOVE TO PARTITION to maintain partition values when you have already populated a partitioned variable. |
Syntax
MAINTAIN partition-template ADD TO PARTITION partition valuelist
Parameters
A text expression that is the name of a previously-defined partition template object.
Specifies that values are to be added to the partition.
A text expression that is the name of a previously-defined partition in the partition template specified by partition-template.
Text literals or a TEXT or ID expression specifying the values to be added. When it is a TEXT expression, each element (line) is treated as a separate value. The values in the expression are added exactly as they are typed.
For a concat dimension, you can specify a value of the concat dimension, or the name of a component dimension and a value or position of that dimension. You can use the values of a dimension surrogate as the values of value.
Note that you cannot partition along an INTEGER dimension.
Indicates a range of values.
Examples
For an example of adding values to a partition, see Example 10-48, "Adding and Deleting Partition Values".
The MAINTAIN command with the DELETE keyword deletes members from non-concat dimensions and composites; or deletes the data of previously-partitioned variables from one partition to another as it changes the dimension or composite values defined for a partition in the partition template which the variables are dimensioned.
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Note: You can also issue a MAINTAIN DELETE statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
The syntax for using the DELETE keyword of the MAINTAIN command to delete members varies depending on the type of object from which you are deleting the members. For this reason, the following separate entries are provided for MAINTAIN DELETE:
The MAINTAIN command with the DELETE keyword deletes dimension members from non-concat dimensions.
|
Note: You can also issue a MAINTAIN DELETE statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN dimension DELETE limit-clause
Parameters
A non-concat dimension, already defined in an attached analytic workspace, whose values are to be deleted.
|
Note: You cannot use a dimension surrogate as the dimension argument of a MAINTAIN DELETE command. However, you can use a dimension surrogate as a value within the limit-clause parameter. |
Specifies the values to delete from the dimension.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
Usage Notes
Deleting Temporary Calculated Members From Dimensions
When you use a MAINTAIN DELETE statement to delete a temporary calculated member, Oracle OLAP:
Deletes the member from the dimension.
Removes the calculation from all aggmap objects that currently contain the corresponding calculation.
Deleting Values in an Integer Dimension
When you use MAINTAIN to delete values in an INTEGER dimension, the values are renumbered to keep the normal sequence of INTEGER values (1, 2, 3, ...).
Examples
Example 10-43 Deleting Dimension Values by Value
This statement deletes Omaha and Newark from the values for city.
MAINTAIN city DELETE 'Omaha' 'Newark'
Example 10-44 Deleting the First Five Values of a Dimension
In this example, you use the INTEGER variable intvar to remove the first five cities from the dimension city.
intvar = 5 MAINTAIN city DELETE FIRST intvar
Example 10-45 Deleting Dimension Values Based on a Boolean Expression
Here you remove from city all those cities with a population of less than 75,000 people. You use the variable population.c, which contains the population for each city.
MAINTAIN city DELETE population.c LT 75000
Example 10-46 Deleting Dimension Values Using Surrogate to Specify Values
Assume that prodid is a NUMBER dimension and prodtype is a TEXT dimension surrogate for prodid. Assume also that the values of prodid are 17, 40, and 56. The values of prodtype are Two-Person Tent, Three-person Tent, and Four-person Tent. The following statement deletes a value from prodid and from its surrogate.
MAINTAIN prodid DELETE prodid(prodtype 'Three-Person Tent')
Example 10-47 Deleting Related MONTH Values
In this example, you use the related dimension quarter to remove values of the dimension month. All months related to the values of quarter currently in the status are deleted.
LIMIT quarter TO FIRST 1
MAINTAIN month DELETE quarter
The MAINTAIN command with the DELETE keyword deletes dimension members from composites.
Syntax
MAINTAIN composite DELETE comp-arg
where comp-arg is one of the following constructs:
Parameters
A composite whose values are to be deleted. When the composite is a named composite, it must be defined in an attached analytic workspace. When the composite is unnamed, it must have been used in defining an object in an attached analytic workspace.
Use the SPARSE keyword to refer to an unnamed composite (for example, SPARSE <market product>).
Specifies one or more values to be deleted from the composite. The valuelist can be text constants or a text expression.
Deletes all composite values, but does not delete the definition of the composite itself.
Deletes the values that include the listed values of a base dimension of the composite. The argument valuelist can be one value, a list of values, or a range of values (using TO to specify an inclusive range). You cannot use position numbers to specify a range of values. When you omit valuelist, Oracle OLAP deletes all values that include base-dim values currently in status.
Deletes all composite values for which the Boolean expression is TRUE. The boolean-expression must be dimensioned by the dimension or the composite from which you the values deleted. When it has additional dimensions, their status must each be limited to one value.
Deletes the top or bottom n values based on the highest (TOP) or lowest (BOTTOM) values in exp. The expression must be dimensioned by the composite from which you the values deleted. When it has additional dimensions, their status must each be limited to one value.
Deletes values by finding the top or bottom performers based on a criterion. This construction sorts values and deletes them based on their contribution, by percentage, to an expression.
Indicates a long list (up to 2,000 values) of individual values to delete. When there are fewer than 300 values, LONGLIST is not needed.
The MAINTAIN DELETE FROM PARTITION command deletes the data of previously-partitioned variables from one partition to another as it changes the dimension or composite values defined for a partition in the partition template which the variables are dimensioned.
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Tip: Use MAINTAIN MOVE TO PARTITION to maintain partition values when you have already populated a partitioned variable. |
Syntax
MAINTAIN partition-template DELETE FROM PARTITION partition { dim-arg| comp-arg}
Parameters
A text expression that is the name of a previously-defined partition template object.
A text expression that is the name of a previously-defined partition in the partition template specified by partition-template.
Specifies that values are to be deleted from the partition and from partitioned variables dimensioned using a partition template that includes the partition.
Specifies the values of a dimension that to use when deleting partitioned variable values and when redefining the values that are in the partition You can use any of the constructs specified for the dim-arg argument in MAINTAIN DELETE dimension.
Specifies the values of a composite to use when deleting partitioned variable values and when redefining the values that are in the partition You can use any of the constructs specified for the comp-arg argument in MAINTAIN DELETE composite.
Examples
Example 10-48 Adding and Deleting Partition Values
Assume that you have defined the following objects in your analytic workspace. on
DEFINE time DIMENSION TEXT
DEFINE time_parentrel RELATION time <time>
DEFINE product DIMENSION TEXT
DEFINE partition_sales_by_year PARTITION TEMPLATE <time product> -
PARTITION BY LIST (time) -
(PARTITION time_2004 VALUES ('2004', 'Dec2004', 'Jan2004', '31Dec2004', -
'01Dec2004', '31Jan2004', '01Jan2004') <TIME PRODUCT> -
PARTITION time_2003 VALUES ('2003', 'Dec2003', 'Jan2003', '31Dec2003', -
'01Dec2003', '31Jan2003', '01Jan2003') <TIME PRODUCT> -
PARTITION time_2002 VALUES ('2002', 'Dec2002', 'Jan2002', '31Dec2002', -
'01Dec2002', '31Jan2002', '01Jan2002') <TIME PRODUCT>)
Assume that instead of having all sales values dimensioned levels by all time values of a year in a partition, you want to have partitions by days and by summary time values (month and year). To change partition_sales_by_year to reflect this new partitioning scheme, you issue the following statements.
"Create the new partition
CHGDFN partition_sales_by_year DEFINE -
(PARTITION partition_month_years VALUES () <time product>)
"Delete the values for months and years from the partitions for years
MAINTAIN partition_sales_by_year DELETE FROM PARTITION time_2004 '2004'-
'Dec2004' 'Jan2004'
MAINTAIN partition_sales_by_year DELETE FROM PARTITION time_2003 '2003'-
'Dec2003''Jan2003'
MAINTAIN partition_sales_by_year DELETE FROM PARTITION time_2002 '2002'-
'Dec2002' 'Jan2002'
"Add the month and year values to the new partition for summary values
MAINTAIN partition_sales_by_year ADD TO PARTITION partition_month_years '2004'-
'Dec2004' 'Jan2004' '2003' 'Dec2003''Jan2003' '2002' 'Dec2002' 'Jan2002'
The partition_sales_by_year partition template object now has the following definition.
DEFINE PARTITION_SALES_BY_YEAR PARTITION TEMPLATE <TIME PRODUCT> -
PARTITION BY LIST (TIME) -
(PARTITION TIME_2004 VALUES ('31Dec2004', '01Dec2004', '31Jan2004', -
'01Jan2004') <TIME PRODUCT> -
PARTITION TIME_2003 VALUES ('31Dec2003', '01Dec2003', '31Jan2003', -
'01Jan2003') <TIME PRODUCT> -
PARTITION TIME_2002 VALUES ('31Dec2002', '01Dec2002', '31Jan2002', -
'01Jan2002') <TIME PRODUCT> -
PARTITION PARTITION_MONTH_YEARS VALUES ('2004', 'Dec2004', 'Jan2004', -
'2003', 'Dec2003', 'Jan2003', '2002', 'Dec2002', 'Jan2002')-
<TIME PRODUCT>)
The MAINTAIN command with the MERGE keyword provides a quick way to make sure all dimension or composite values on a separate list are included in a non-concat dimension or composite. Using the MERGE keyword with the MAINTAIN command automatically adds the new values from the list and ignores the duplicates. This method of entering dimension values can save a significant amount of time when you have a large number of values to enter.
You can use MERGE with dimensions of any data type, including DAY, WEEK, MONTH, QUARTER, and YEAR dimensions. However, since Oracle OLAP provides a quick way of adding values of DAY, WEEK, MONTH, QUARTER, and YEAR dimensions through the ADD keyword, the MERGE keyword may not be as useful with DAY, WEEK, MONTH, QUARTER, and YEAR dimensions as it is with TEXT or ID dimensions.
At the same time as you are merging values into a dimension, you can also update a relation that involves that dimension.
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Note: You can also issue this MAINTAIN MERGE statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program one time for each value in exp; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN dimension|composite MERGE exp [RELATE relation]
A non-concat dimension, already defined in an attached analytic workspace, whose values are to be entered or changed.
A composite whose values are to be added, deleted, or merged. When the composite is a named composite, it must be defined in an attached analytic workspace. When the composite is unnamed, it must have been used in defining an object in an attached analytic workspace. Use the SPARSE keyword to refer to an unnamed composite (for example, SPARSE <market product>).
Specifies an expression whose values are to be merged with dimension; for example, the name of a dimensioned text variable that contains dimension values, or a single-cell text variable whose value is a multiline list of dimension values. MAINTAIN MERGE ignores any NAs in exp. When dimension is an INTEGER dimension, then exp specifies the number of values that you want in the dimension. When the actual total is less, MAINTAIN MERGE adds enough values to reach the specified total. For example, when an INTEGER dimension has 10 positions, MERGE 5 has no effect; but MERGE 15 would add 5 values.
Specifies a relation to be updated as new values from exp are merged into dimension. At least one dimension of exp must also appear in the definition of relation. When exp is a single-cell value, you cannot use the RELATE phrase.
Examples
Example 10-49 Using the MERGE Keyword with Composites
Suppose you want to define a composite that is made up of all combinations of the first three values of the product dimension and the first five values of the district dimension. You can efficiently include all 15 values with the following statements.
DEFINE comp_proddist COMPOSITE <product district> LIMIT product TO FIRST 3 LIMIT district TO FIRST 5 MAINTAIN comp_proddist MERGE <product district>
This method works with conjoint dimensions as well.
A MAINTAIN command with the MOVE keyword has different effects depending on the object on which it operates:
When maintaining a dimension, MAINTAIN MOVE changes the position of one or more values in a non-concat dimension or a dimension of type TEXT, ID, or INTEGER or adds previously-populated dimension or composite values to a partition
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Note: You can also issue a MAINTAIN MOVE dimension value statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
When maintaining a partition, MAINTAIN MOVE moves the data of a previously-partitioned variables from one partition to another as it changes the dimension or composite values defined for a partition in the partition template which the variables are dimensioned.
Syntax
The syntax for using the MAINTAIN command with the MOVE keyword depends on the type of the object being maintained.
For this reason, the following separate entries are provided for MAINTAIN MOVE:
A simple MAINTAIN MOVE statement changes the position of one or more values in a non-concat dimension or a dimension of type TEXT, ID, or INTEGER. You cannot use the MOVE keyword of the MAINTAIN command with composites or with dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR.
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Note: You can also issue a MAINTAIN MOVE statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN dimension MOVE limit-clause
Parameters
A non-concat dimension, already defined in an attached analytic workspace, whose values are to be entered or changed. The dimension must be of type TEXT, ID, or INTEGER. You cannot specify a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR.
Specifies the values you want to move.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLI*#ST).
Usage Notes
What Effects Performance of MAINTAIN MOVE
The performance cost of issuing a MAINTAIN MOVE command is dependent on the length of the dimension, not on the number of values being moved. Consequently, when moving values in a large dimension, do not issue several MAINTAIN MOVE statements one after another; instead, set up the dimension status to what you want and then issue a single MAINTAIN MOVE command.
Reordering or Sorting Values within a Dimension
When you want to reorder or sort dimension values using a MAINTAIN MOVE statement, to specify that you want to use all of the dimension values that are in status, use the STATUS keyword of the limit-clause argument of LIMIT (using values) command rather than a VALUES command.
Examples
Example 10-50 Moving a Dimension Value to a Specific Position
This statement moves the position of the city Houston to the position following the fifth dimension value.
MAINTAIN city MOVE 'Houston' AFTER 5
Example 10-51 Moving a Dimension Value to the End of the Status List
In this example, you use the TEXT variable textvar to move Seattle to the end of the list of cities.
textvar = 'Seattle' MAINTAIN city MOVE textvar LAST
Example 10-52 Moving Values of Concat Dimensions
The following statement moves the reg.dist.ccdim concat dimension value <district: 'Denver'> after the concat dimension value <region: 'West'>.
MAINTAIN reg.dist.ccdim MOVE <district: 'Denver'> AFTER <region: 'West'>
The following statement moves the concat dimension value <district: 'Denver'> after the position that corresponds to the first value of the component district dimension. If the first value in the status of district is Atlanta, then <district: 'Denver'> moves after the value <district: 'Atlanta'> in the concat dimension.
MAINTAIN reg.dist.ccdim MOVE <district: 'Denver'> AFTER <district: 1>
The following statement moves the concat dimension value <district: 'Dallas'> after the third value of the concat dimension.
MAINTAIN reg.dist.ccdim MOVE <district: 'Dallas'> AFTER 3
A MAINTAIN MOVE TO PARTITION statement combines both add and move capabilities. You can use a MAINTAIN MOVE TO PARTITION statement to:
Add previously-populated dimension or composite values to a partition in the same manner as MAINTAIN ADD TO PARTITION
Change the dimension or composite values defined for a partition in the partition template by which the variables are dimensioned and, at the same time, move the data of a previously-partitioned variables dimensioned by those dimensions and composites from one partition to another.
Syntax
MAINTAIN partition-template MOVE TO PARTITION partition value [TO value]
Parameters
A text expression that is the name of a previously-defined partition template object.
Specifies that values are to be added to the partition or moved from one partition to another.
A text expression that is the name of a previously-defined partition in the partition template specified by partition-template.
Specifies one or more values of a previously-populated dimension or composite. You can specify these values as:
A literal value.
An expression whose value is a dimension value.
For all dimensions except NUMBER dimensions, an INTEGER expression whose value represents the position of a dimension value.
A valueset; or a LIMIT function.
For a concat dimension, you can specify a value of the concat dimension, or the name of a component dimension and a value or position of that dimension. You can use the values of a dimension surrogate as the values of value.
Indicates a range of values.
Examples
Example 10-53 Specifying the Values of a Partition Using Valuesets
Assume that you have defined a partition template object with the following definition that does not specify the actual dimension values for each partition.
DEFINE PARTITION_SALES_BY_YEAR PARTITION TEMPLATE <TIME PRODUCT> -
PARTITION BY LIST (TIME) -
(PARTITION TIME_2004 VALUES () <TIME PRODUCT> -
PARTITION TIME_2003 VALUES () <TIME PRODUCT> -
PARTITION TIME_2002 VALUES () <TIME PRODUCT>)
To specify the values of each partition using valuesets, you take the following steps:
Define a valueset for each year's values.
DEFINE vs_2004 VALUESET time
LIMIT vs_2004 to '01Dec2004' '31Dec2004' '01Jan2004''31Jan2004' -
'Jan2004' 'Dec2004' '2004'
DEFINE vs_2003 VALUESET time
LIMIT vs_2003 to '01Dec2003' '31Dec2003' '01Jan2003''31Jan2003' -
'Jan2003' 'Dec2003' '2003'
DEFINE vs_2002 VALUESET time
LIMIT vs_2002 to '01Dec2002' '31Dec2002' '01Jan2002''31Jan2002' -
'Jan2002' 'Dec2002' '2002'
Using MAINTAIN MOVE statements, specify values for the partitions of the partition template.
MAINTAIN partition_sales_by_year MOVE TO PARTITION time_2004 vs_2004 MAINTAIN partition_sales_by_year MOVE TO PARTITION time_2003 vs_2003 MAINTAIN partition_sales_by_year MOVE TO PARTITION time_2002 vs_2002
When you issue a DESCRIBE statement, you can see that the description of the partition_sales_by_year partition template now includes the appropriate values of time in each partition definition.
DEFINE PARTITION_SALES_BY_YEAR PARTITION TEMPLATE <TIME PRODUCT> -
PARTITION BY LIST (TIME) -
(PARTITION TIME_2004 VALUES -
('2004','Dec2004','Jan2004', 31Dec2004',01Dec2004','31Jan2004','01Jan2004')-
PARTITION TIME_2003 VALUES -
('2003','Dec2003','Jan2003', 31Dec2003',01Dec2003','31Jan2003','01Jan2003')-
PARTITION TIME_2002 VALUES -
('2002','Dec2002','Jan2002', 31Dec2002',01Dec2002','31Jan2002','01Jan2002'))
The MAINTAIN command with the RENAME keyword changes the spelling of one or more dimension values. You cannot use RENAME keyword with a composite or with dimensions of type INTEGER, DAY, WEEK, MONTH, QUARTER, or YEAR.
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Note: You can also issue a MAINTAIN RENAME statement for a surrogate dimension that has a Maintain trigger. In this case, Oracle OLAP only executes the Maintain trigger program; no other action occurs. See "Trigger Programs" for more information for more information. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. |
Syntax
MAINTAIN dimension RENAME {value new-value}...
Parameters
A non-concat dimension of type TEXT or ID that is already defined in an attached analytic workspace and whose values are to be renamed. You cannot specify a dimension of type INTEGER, DAY, WEEK, MONTH, QUARTER, or YEAR.
Specifies an existing dimension value to be renamed. You can specify a dimension value, a character expression whose value is a dimension value, or an INTEGER expression whose value represents the position of a dimension value.
A text constant or a TEXT or ID expression that is the new spelling for the dimension value.
Examples
Example 10-54 Renaming Values of a TEXT Dimension
This statement changes the spelling of the cities Chic and Bost to Chicago and Boston.
MAINTAIN city RENAME 'Chic' 'Chicago' 'Bost' 'Boston'
In this example you use the TEXT variable textvar to change the second city to Atlanta.
textvar = 'Atlanta' MAINTAIN city RENAME 2 textvar
The MODDAMP option specifies a weighting factor that damps out oscillations between iterations when you use the Gauss-Seidel method for solving simultaneous equations in a model. MODDAMP can allow the solution of models that would otherwise never converge because the oscillation between equations is stable. In these cases, the oscillations never decay without damping.
With the Gauss-Seidel method, Oracle OLAP tests each model equation for convergence or divergence in each iteration over a block of simultaneous equations. The tests are made by comparing the results of the current iteration to the results from the previous iteration. When MODDAMP specifies a weighting factor that is greater than zero, the value that Oracle OLAP tests and stores after each iteration is a weighted average of the current and previous results. For equations that oscillate between iterations, you can therefore use MODDAMP to damp out the oscillations and either prevent divergence or speed up the convergence of the equations.
Data Type
DECIMAL
Syntax
MODDAMP = {n|0.00}
Parameters
A decimal value, greater than or equal to zero and less than one, that specifies the weighting factor. The closer MODDAMP is to 0.00, the more weight is given to the value from the current iteration. The default value is 0.00, which gives full weight to the current iteration.
When MODDAMP is greater than zero, Oracle OLAP calculates the weighted average for the current iteration as follows.
calcvalue * (1 - MODDAMP) + weightavg
where:
calcvalue is the value calculated from the model equation in the current iteration.
weightavg is the weighted average calculated in the previous iteration.
Usage Notes
Specifying the Solution Method
The MODDAMP option is used only with the Gauss-Seidel method for solving simultaneous equations. The MODSIMULTYPE option determines the solution method that is being used. The possible settings for MODSIMULTYPE are GAUSS, for the Gauss-Seidel method, and AITKENS, for the Aitkens delta-squared method.
Effect of MODDAMP on Convergence Speed
MODDAMP is used in calculating the results of all model equations in every simultaneous block, whether they oscillate between iterations or not. For equations that do not oscillate, convergence is slowed down when the value of MODDAMP is greater than zero. Therefore, when your model contains some equations that oscillate and some that do not, you might be able to speed up overall convergence by setting MODDAMP to a small nonzero value, such as 0.20. A small nonzero value slows down the convergence of non-oscillating equations only slightly, while speeding up the convergence of oscillating equations.
Stored Weighted Average
When the model equation does not converge or diverge on the current iteration, the weighted average calculated in the current iteration is stored. In the next iteration, Oracle OLAP uses this stored average as weightavg (that is, the weighted average calculated in the previous iteration) in the formula for the weighted average.
In the first iteration over a block, Oracle OLAP uses the starting value of the target variable (or dimension value) as the weightavg (that is, the weighted average calculated in the previous iteration).
Iteration Results Compared
In tests for convergence and divergence in each iteration, Oracle OLAP compares the results of the current iteration to the results from the previous iteration. When MODDAMP is greater than zero, Oracle OLAP tests a comparison value that is calculated as follows.
(weightavg - weightavg) / (weightavg PLUS MODGAMMA)
where weightavg is the weighted average calculated in the previous iteration
For an explanation of the test for convergence, see the MODTOLERANCE option. For an explanation of the test for divergence, see the MODOVERFLOW option.
Options to Control the Solution of Simultaneous Blocks
Altering the value of MODDAMP is just one step you can take in attempting to speed up or attain convergence of a simultaneous block. MODEL lists additional options that you can use to control the solution of simultaneous blocks and provides information on running and debugging models.
Examples
Example 5-50 Using the Default MODDAMP Value
The following statements trace a model called income.bud, specify that the Gauss-Seidel method should be used for solving simultaneous blocks, limit a dimension, and run the income.bud model.
MODTRACE = YES MODSIMULTYPE = 'GAUSS' LIMIT division TO 'Camping' income.bud budget
These statements produce the following output.
(MOD= INCOME.BUD) BLOCK 1: SIMULTANEOUS (MOD= INCOME.BUD) ITERATION 1: EVALUATION (MOD= INCOME.BUD) revenue = marketing * 300 - cogs ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 35) = 368.650399101 ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 36) = 369.209604252 ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 37) = 368.718556135 ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 38) = 369.149674626 ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 39) = 368.771110244 ... (MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 40) = 369.103479583 (MOD= INCOME.BUD) END BLOCK 1
The MODDAMP option is set to its default value of 0.00. The equation for the Revenue line item converged in 40 iterations over a block of simultaneous equations. In the trace lines, you can see the results that were calculated for the Revenue line item in the final 6 iterations.
Example 5-51 Setting MODDAMP to Speed Up the Convergence of a Model
The following statements change the value of MODDAMP and run the income.bud model.
MODDAMP = 0.2 income.bud budget
These statements produce the following output.
(MOD= INCOME.BUD) BLOCK 1: SIMULTANEOUS
(MOD= INCOME.BUD) ITERATION 1: EVALUATION
(MOD= INCOME.BUD) revenue = marketing * 300 - cogs
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 1) = 276.200000000
...
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 2) = 416.187139753
...
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 3) = 368.021098186
...
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 4) = 367.209906847
...
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 5) = 369.271224267
...
(MOD= INCOME.BUD) BUDGET (LINE REVENUE MONTH 'JAN97' ITER 6) = 368.965397407
(MOD= INCOME.BUD) END BLOCK 1
In "Using the Default MODDAMP Value", the equation for the Revenue line item converged in 40 iterations. With MODDAMP set to 0.2 in the current example, the same equation converged in just 6 iterations.
The MODMAXITERS option determines the maximum number of iterations Oracle OLAP performs in attempting to solve a block of simultaneous equations in a model.
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See also: "Model Options" for descriptions of all of the options that control the solution of simultaneous blocks, and |
Data Type
INTEGER
Syntax
MODMAXITERS = {n|50}
Parameters
A positive INTEGER value that indicates the maximum number of iterations Oracle OLAP should perform in attempting to solve a simultaneous block. The default is 50.
Usage Notes
Reporting Model Execution Results
When any equation in a simultaneous block diverges or fails to converge within the number of iterations specified by MODMAXITERS, the solution of the block fails and an error occurs. You can use the MODEL.XEQRPT program to produce a report on the results of the model's execution. The report indicates whether a simultaneous block diverged or failed to converge. When a block failed to converge, you can experiment with increasing the value of MODMAXITERS to see if convergence can be attained.
Examples
The PAGEPRG option holds the name of a program or the text of a statement to be executed at the beginning of each page of output. You can use this program or statement to create titles and column headings on multiple pages of a report. A program can also contain other statements appropriate for execution at the start of every page. Normally, you set the value of PAGEPRG in the initialization section of a report program.
The PAGEPRG option is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and LISTNAMES.
Data Type
TEXT
Syntax
PAGEPRG = {'program'|'statement'|'NONE'|'STDHDR'}
Parameters
The name of a program to be executed after every page break. When you specify the program name as a text expression, you can omit the single quotes.
The text of a statement to be executed after every page break. When you specify the statement as a text expression, you can omit the single quotes.
Indicates that no statement or program is executed automatically after a page break.
(Default) Makes STDHDR the program name that PAGEPRG stores. You can also set PAGEPRG to 'DEFAULT' to make STDHDR the program name that PAGEPRG stores. STDHDR produces a heading with the date and time on the left and the page number on the right.
Usage Notes
Using a STDHDR Program in a PAGPRG Program
When you create a PAGEPRG program, you can include the STDHDR program as a line in the program. Generally, you place STDHDR before the other statements that produces the custom heading. See Example 5-85, "Creating a Custom Heading".
Keeping Header Information Current
You can use Oracle OLAP functions such as TODAY, TOD, and PAGENUM in a program that is specified by the PAGEPRG option. You can also have a header program that accepts arguments, such as the title for a particular report. In this case you would set the PAGEPRG option to a text expression that invokes the report header program with arguments. See Example 5-86, "Using Program Arguments".
Setting PAGEPRG for a File
To set PAGEPRG for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set PAGEPRG to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, PAGEPRG returns to its default value of 'STDHDR' for the file.
When you set PAGEPRG for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE commands that send output to a file. That is, the value of PAGEPRG is automatically saved for the default outfile.
Examples
Example 5-85 Creating a Custom Heading
Suppose you want each page of a report to include both the standard running page heading and the title "Annual Sales Report." To accomplish this, create a program called report.head.
DEFINE report.head PROGRAM PROGRAM STDHDR BLANK HEADING WIDTH LSIZE CENTER 'Annual Sales Report' BLANK IF PAGENUM GT 1 THEN HEADING WIDTH LSIZE CENTER '(Continued)' BLANK END
Specify this program to execute after every page break by setting the PAGEPRG option in the report program. You can include PUSH and POP commands to save the PAGEPRG setting that is active.
PUSH PAGEPRG PAGING
PAGEPRG = 'report.head'
PAGING = YES
... (body of report program)
POP PAGEPRG PAGING
When you run the report, each page contains the following heading.
15JAN98 15:05:16 Page 1
Annual Sales Report
Each page after the first page also contains the subheading "(Continued)" because of the PAGENUM test in the IF statement.
Example 5-86 Using Program Arguments
As an alternative to specifying the report name in the report.head program, you can pass the report name to the report.head program from your report program. You can do this by setting the PAGEPRG option to a text expression that invokes the report.head program with the report name as an argument. Suppose your report program contains the following statement.
PAGEPRG = 'CALL report.head(\'Annual Sales Report\')'
Then you can change the first few lines of the report.head program to the following.
ARGUMENT titlevar TEXT STDHDR BLANK HEADING WIDTH LSIZE CENTER titlevar
The EXTLINES function extracts lines from a multiline text expression.
Return Value
TEXT or NTEXT
Syntax
EXTLINES(text-expression [start [numlines]])
Parameters
A multiline TEXT or NTEXT expression from whose values one or more lines are to be extracted.
An INTEGER that represents the line number at which to begin extracting. The position of the first line in text-expression is 1. When you omit this argument, EXTLINES begins with line 1.
An INTEGER representing the number of lines to be extracted. When you do not specify numlines, or when you specify a number greater than the number of lines from start to the end of text-expression, all the lines from start to the end of text-expression are copied.
Examples
Example 7-85 Extracting One Text Line
This example shows how to extract the second line from a multiline text value in a variable called mktglist. The mktglist variable has the following values.
Salespeople Products Services
The statement
SHOW EXTLINES(mktglist 2 1)
produces the following output.
Products
The EQ command specifies a new expression for an already defined formula. To use EQ to assign an expression to a formula definition, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER command to make it the current definition.
An alternative to the EQ command is the EDIT FORMULA command, which is available only in OLAP Worksheet. The EDIT FORMULA command opens an Edit window in which you can add, delete, or change the expression to be calculated for a formula.
Be sure to distinguish between the EQ command described here and the EQ operator used to compare values of the same type.
Syntax
EQ [expression]
Parameters
The calculation that is performed to produce values when you use the formula. When you do not specify an expression, the EQ command sets the expression to NA. The formula text is not converted to uppercase.
Usage Notes
Data Type and Dimensions
Typically, the data type and dimensions of the new expression match the specified data type and dimensions in the definition of the formula. When they do not, the resulting values are converted to the formula's data type and the results are forced into the formula's dimensionality. The DESCRIBE command shows the formula's data type and dimensions. You can find out the data type and dimensions of the new expression by parsing it. See Example 9-115, "Using PARSE with EQ".
You cannot use the EQ command to change the data type or dimensions of a formula. To make changes in these, you must delete the formula and redefine it.
Examples
Example 9-114 Adding an EQ
This example specifies a new expression for the f1 formula with the following definition.
DEFINE f1 FORMULA INTEGER <month line division> EQ actual * 2
The statements
CONSIDER f1 EQ actual * 3 DESCRIBE f1
produce the following definition of the formula with a new EQ.
DEFINE F1 FORMULA INTEGER <MONTH LINE DIVISION> EQ actual * 3
Example 9-115 Using PARSE with EQ
The following example supposes that your workspace already has a formula named line.totals. The PARSE and SHOW INFO statements check the dimensionality and data type of an expression. The CONSIDER and EQ statements assign the expression to the line.totals formula. The line.totals formulas has the following definition.
DEFINE line.totals FORMULA DECIMAL <year line>
The statements
PARSE 'total(actual line year)' SHOW INFO(PARSE DIMENSION)
produce the following output.
YEAR LINE
The statement
SHOW INFO(PARSE DATA)
produces the following output.
DECIMAL
The output from INFO(PARSE) shows that the expression has the same dimensionality and data type as the line.totals formula. The statements
CONSIDER line.totals EQ TOTAL(actual line year) DESCRIBE line.totals
show the definition of line.totals with its new EQ.
DEFINE LINE.TOTALS FORMULA DECIMAL <YEAR LINE> EQ total(actual line year)
The SHOW command shows a single value of an expression. Normally, you would use SHOW to show the value of a single-cell variable or to show a message. SHOW is useful in programs when you want to generate an error-like message without creating an error condition. The output from SHOW is sent to the current outfile.
Syntax
SHOW expression [NONL]
Parameters
The value you want to show. When expression is dimensioned, only the first value of the expression is shown, based on the current status of its dimensions. When you are showing a text literal, you must enclose the value in single quotes.
Indicates that a new line sequence should not be appended to the end of the value. By default, SHOW appends a new line sequence.
Usage Notes
Concatenating Output Lines
The NONL argument to SHOW is useful in programs. Using this argument you can concatenate several values into a single line of output. To accomplish this, include one or more SHOW commands with the NONL argument, followed by a single SHOW statement without the NONL argument. The values from all the SHOW commands are concatenated into a single output value, in the order specified. Depending on the length of the line, this value might actually produce multiple lines of output.
Generating Error Messages
SHOW can be used as an alternative to SIGNAL when you want to generate an error message from a program. Unlike SIGNAL, SHOW produces a message without signaling an error condition and thus halting execution of the program. Your error message may be most useful when you send it to a debugging file. When you use a DBGOUTFILE statement to direct messages to a debugging file, the output from SHOW is sent to the debugging file and to your current outfile.
Showing Values of Composites
When SHOW is used with a named or unnamed composite, an NA value is shown when the composite does not have a value that corresponds to the first values in the status for its base dimensions. For example, the statement
SHOW SPARSE <market product>
produces an NA value when the combination of the current values of market and product does not exist in the composite.
Breaking Lines of Text
To break a text expression into two or more lines of output text, insert newline delimiters (\n) at the appropriate places in the text.
Using SHOW With NTEXT Values
The SHOW command converts NTEXT values to the character set of the outfile. When an NTEXT value cannot be represented in the outfile character set, the character is not displayed correctly.
Examples
Example 10-119 Showing the Value of an Option
This example uses SHOW to report the current value of the DECIMALS option. The OLAP DML statement
SHOW DECIMALS
produces the following output.
2
Example 10-120 Showing a Data Value
When you use SHOW to report the value of a dimensioned variable, only the first value of the variable, based on the current status of its dimensions, is shown. The OLAP DML statement
SHOW JOINCHARS('Actual = ' actual)
produces the following output.
Actual = 533,362,88
Example 10-121 Creating Error Messages Using SHOW
When you want to produce a warning message without branching to an error label, then you can use a SHOW statement.
select:
LIMIT month TO nummonths
IF STATLEN(month) GT 9
THEN DO
SHOW 'You can select no more than 9 months.'
GOTO finish
DOEND
REPORT DOWN district W 6 units
finish:
POP month
RETURN
The CONVERT procedure converts an analytic workspace in 9i storage format to to 10g storage format. Note that you cannot execute this procedure from within the OLAP Worksheet; you must execute if in a SQL tool such as SQL*Plus.
|
Note: Issuing thedbms_aw.convert procedure is only one small step in upgrading Oracle 9i analytic workspaces to Oracle 10g workspaces. For the complete procedure for upgrading Oracle 9i analytic workspaces, see Oracle OLAP Application Developer's Guide, 10g Release 2 (10.2). |
|
See: For information on converting an analytic workspace to Oracle 11g storage format, see Oracle OLAP User's Guide. |
Syntax
CONVERT (
original_aw IN VARCHAR2);
CONVERT (
original_aw IN VARCHAR2,
converted_aw IN VARCHAR2,
tablespace IN NUMBER DEFAULT);
Parameters
Table B-19 CONVERT Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The analytic workspace you want to convert. |
|
|
The converted analytic workspace. |
|
|
The name of a tablespace in which the converted workspace is stored. If this parameter is omitted, then the analytic workspace is created in the user's default tablespace. |
Example
This example performs the conversion in a single step, using the analytic workspace as both the source and the target of the conversion.
EXECUTE dbms_aw.convert('global');
The next example performs the conversion in several steps. The converted workspace must have the same name as the original workspace, because the fully qualified names of objects in the workspace include the workspace name.
EXECUTE dbms_aw.rename('global', 'global_temp');
EXECUTE dbms_aw.convert('global_temp', 'global');
EXECUTE dbms_aw.delete('global_temp');
The FCCLOSE command closes a forecasting context. When Oracle OLAP closes a forecasting context, only data in the variables specified in the FCEXEC command remain available to applications. Oracle OLAP purges all other data, including temporary pages, associated with the forecast.
You must use the FCCLOSE command in combination with other OLAP DML statements as outlined in "Forecasting Programs".
Syntax
FCCLOSE handle-expression
Parameters
An INTEGER expression that is the handle to forecast context previously opened using the FCOPEN function.
Examples
For an example of a forecasting program, see Example 9-119, "A Forecasting Program".
The ROWIDTONCHAR function converts a value of the ROWID data type to a value of the NCHAR data type. The result of this conversion is always in the national character set and is 18 characters long.
Return Value
NCHAR
The result of this conversion is always in the national character set and is 18 characters long.
Syntax
ROWIDTONCHAR (rowid)
Parameters
The value of type ROWID to convert.
Examples
See Example 8-91, "Converting ROWID Data to TEXT or NTEXT Data".
(Read-only) The SECONDS option holds the number of seconds since January 1, 1970. As an aid to enhancing a program's speed, SECONDS can be used to determine how many real seconds elapse while the program is running.
Data Type
INTEGER
Syntax
SECONDS
Examples
Example 5-97 Timing a Program Using SECONDS
The following program puts the value of SECONDS at the start of the program in a variable called t1, then displays the difference between t1 and the value of SECONDS after the program executes.
DEFINE prodsummary PROGRAM PROGRAM VARIABLE t1 INTEGER t1 = seconds LIMIT product TO ALL BLANK FOR product DO ROW WIDTH 16 name.product ACROSS month Jun96: DECIMAL 0 LSET - '$'WIDTH 18 <RSET ' (actual)' sales RSET ' (plan)' sales.plan> DOEND BLANK ROW WIDTH 35 LSET 'the program took ' RSET ' SECOND(s).' - (SECONDS-t1) END
Running this program produces the following results.
3-Person Tents $95,121 (actual) $80,138 (plan)
Aluminum Canoes $157,762 (actual) $132,931 (plan)
Tennis Racquets $97,174 (actual) $84,758 (plan)
Warm-up Suits $79,630 (actual) $73,569 (plan)
Running Shoes $153,688 (actual) $109,219 (plan)
The program took 2 second(s).
The ADVISE_CUBE procedure helps you determine how to preaggregate a cube in an analytic workspace. When you specify a percentage of the cube's data to preaggregate, ADVISE_CUBE recommends a set of members to preaggregate from each of the cube's dimensions.
The ADVISE_CUBE procedure takes an aggmap and a precompute percentage as input. The aggmap must have a precompute clause in each of its RELATION statements. The precompute clause must consist of a valueset. Based on the precompute percentage that you specify, ADVISE_CUBE returns a set of dimension members in each valueset.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_CUBE (
aggmap_name IN VARCHAR2,
precompute_percentage IN INTEGER DEFAULT 20,
compressed IN BOOLEAN DEFAULT FALSE);
Parameters
Table B-3 ADVISE_CUBE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of an aggmap associated with the cube. Each |
|
|
A percentage of the cube's data to preaggregate. The default is 20%. |
|
|
Controls whether the advice is for a regular composite ( |
Example
This example illustrates the ADVISE_CUBE procedure with a cube called UNITS dimensioned by PRODUCT and TIME. ADVISE_CUBE returns the dimension combinations to include if you want to preaggregate 40% of the cube's data.
SET SERVEROUTPUT ON
--- View valuesets
EXECUTE dbms_aw.execute('describe prodvals');
DEFINE PRODVALS VALUESET PRODUCT
EXECUTE dbms_aw.execute('describe timevals');
DEFINE TIMEVALS VALUESET TIME
--- View aggmap
EXECUTE dbms_aw.execute ('describe units_agg');
DEFINE UNITS_AGG AGGMAP
RELATION product_parentrel PRECOMPUTE (prodvals)
RELATION time_parentrel PRECOMPUTE (timevals)
EXECUTE dbms_aw.advise_cube ('units_agg', 40);
---- The results are returned in the prodvals and timevals valuesets
The CHANGECHARS function changes one or more occurrences of a specified string in a text expression to another string.
Return Value
When all arguments are TEXT values, the return value is TEXT. When all arguments are NTEXT values, the return value is NTEXT. When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
CHANGECHARS(text-expression oldtext newtext [number] [UPCASE])
Parameters
The TEXT or NTEXT expression in which characters are to be changed. When text-expression is a multiline text value, CHANGECHARS preserves the line breaks in the returned value.
A TEXT or NTEXT expression that contains one or more characters to be changed.
A TEXT or NTEXT expression that contains one or more characters to replace oldtext.
An INTEGER that represents the number of times oldtext should be replaced with newtext when oldtext appears more than once in text-expression. The default is to change all occurrences of oldtext.
Specifies that CHANGECHARS should uppercase text-expression and oldtext before trying to find a match. CHANGECHARS does not uppercase the return value.
Examples
The AW_DETACH procedure detaches an analytic workspace from your session so that its contents are no longer accessible. All changes that you have made since the last update are discarded. Refer to "AW_UPDATE Procedure" for information about saving changes to an analytic workspace.
Syntax
AW_DETACH (
awname IN VARCHAR2);
AW_DETACH (
schema IN VARCHAR2,
awname IN VARCHAR2);
Parameters
Table B-15 AW_DETACH Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an attached analytic workspace that you want to detach from your session. |
Example
The following command detaches the GLOBAL_FINANCE analytic workspace.
EXECUTE dbms_aw.aw_detach('global_finance');
The next command detaches the SALES_HISTORY analytic workspace in the SH_AW schema.
EXECUTE dbms_aw.aw_detach('sh_aw', 'sales_history');
The $AGGMAP property specifies that Oracle OLAP use the identified aggmap to automatically aggregate non-precomputed data to substitute for NA values that are in the dimensioned variable, but not in the session cache for the variable (if any). Consequently, you do not need to explicitly use the AGGREGATE function to aggregate non-precomputed data in a variable that has an $AGGMAP property.
Additionally, the aggmap specified in a variable's $AGGMAP property, is the aggmap that Oracle OLAP uses when the variable is the target of an AGGREGATE command that does not include a USING phrase.
Syntax
You add or delete an $AGGMAP property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$AGGMAP' agggmap-name
To delete the property, issue the following statement.
PROPERTY DELETE '$AGGMAP'
Parameters
A TEXT expression that is the name of a previously defined aggmap object.
Examples
Example 4-1 Using $AGGMAP To Dynamically Aggregate Data
Assume that you have a hierarchical dimension named geog,a simple dimension named year, and the following variable named sales which is dimensioned by both and which has data only at the detail level.
Assume that you want to explicitly specify the value of 8000 for the sales cell for Connecticut in 2005. To do this you issue the following assignment statement and a report of sales shows the value.
sales (geog 'Connecticut' year '2005') = 8000
REPORT sales;
-----------SALES-----------
-----------YEAR------------
GEOG 2004 2005 2006 2007
-------------- ------ ------ ------ ------
Toronto 1,000 1,333 1,954 1,260
Norfolk 1,131 1,867 1,843 1,767
Montreal 1,571 1,754 1,316 1,905
Quebec City 1,914 1,728 1,386 1,847
Hartford 1,870 1,943 1,085 1,335
New Haven 1,684 1,330 1,458 1,402
Springfield 1,630 1,116 1,897 1,690
Boston 1,780 1,310 1,368 1,581
Ontario NA NA NA NA
Quebec NA NA NA NA
Connecticut NA 8,000 NA NA
Massachusetts NA NA NA NA
Canada NA NA NA NA
USA NA NA NA NA
All Geog NA NA NA NA
Now assume that you define an aggmap for sales. The aggmap has the following definition which specifies that only the upper-level data for Canada and the top level (All Geog) be aggregated by the AGGREGATE command.
DEFINE MYAGGMAP AGGMAP
AGGMAP
RELATION geogParentrel PRECOMPUTE ('Quebec' 'Ontario' 'Canada' 'All Geog')
END
Now assume you issue the following statements:
CONSIDER sales PROPERTY '$AGGMAP' 'Myaggmap'
As a result of using the $AGGMAP property to make myaggmap as the default aggmap for sales, a simple REPORT statement for sales causes Oracle OLAP to aggregate all of the data for the USA. (Note that only those values that were not specified as PRECOMPUTE and that previously had NA values are calculated. The 8,000 value for Connecticut in 2005 that was specifically assigned is not recalculated.)
REPORT sales
-----------SALES-----------
-----------YEAR------------
GEOG 2004 2005 2006 2007
-------------- ------ ------ ------ ------
Toronto 1,000 1,333 1,954 1,260
Norfolk 1,131 1,867 1,843 1,767
Montreal 1,571 1,754 1,316 1,905
Quebec City 1,914 1,728 1,386 1,847
Hartford 1,870 1,943 1,085 1,335
New Haven 1,684 1,330 1,458 1,402
Springfield 1,630 1,116 1,897 1,690
Boston 1,780 1,310 1,368 1,581
Ontario NA NA NA NA
Quebec NA NA NA NA
Connecticut 3,554 8,000 2,543 2,737
Massachusetts 3,410 2,426 3,265 3,271
Canada NA NA NA NA
USA 6,964 5,699 5,808 6,008
All Geog NA NA NA NA
Once you aggregate sales using the AGGREGATE command, Oracle OLAP aggregates values for all of the PRECOMPUTE cells in sales.
REPORT sales
-----------SALES-----------
-----------YEAR------------
GEOG 2004 2005 2006 2007
-------------- ------ ------ ------ ------
Toronto 1,000 1,333 1,954 1,260
Norfolk 1,131 1,867 1,843 1,767
Montreal 1,571 1,754 1,316 1,905
Quebec City 1,914 1,728 1,386 1,847
Hartford 1,870 1,943 1,085 1,335
New Haven 1,684 1,330 1,458 1,402
Springfield 1,630 1,116 1,897 1,690
Boston 1,780 1,310 1,368 1,581
Ontario 2,131 3,200 3,797 3,027
Quebec 3,485 3,482 2,702 3,752
Connecticut 3,554 8,000 2,543 2,737
Massachusetts 3,410 2,426 3,265 3,271
Canada 5,616 6,682 6,499 6,779
USA 6,964 5,699 5,808 6,008
All Geog 12,580 12,381 12,307 12,787
Example 4-2 The $AGGMAP Property Effect on an AGGREGATE Command
Example 4-3, "Using the $AGGREGATE_FROM Property" illustrates how the AGGREGATE command shown in Example 9-13, "Using a CACHE Statement in an Aggregation Specification" can be simplified to the following statement.
AGGREGATE sales_by_revenue USING revenue_aggmap
You can further simplify the AGGREGATE command if you place an $AGGMAP property on the sales_by_revenue variable. To define an $AGGMAP property on the sales_by_revenue variable, issue the following statements.
CONSIDER sales_by_revenue PROPERTY '$AGGMAP' 'revenue_aggmap'
Now you can aggregate the data by issuing the following AGGREGATE command that does not include a USING clause.
AGGREGATE sales_by_revenue
The NAFILL function returns the values of the source expression with any NA values replaced with the specified fill expression.
Return Value
The value returned is the same data type as source-expression. When the fill and source expressions do not have the same data type, Oracle OLAP converts the fill expression to the data type of the source expression when possible. Otherwise, an error is produced. When both the source and fill expressions equal NA, then NAFILL returns NA.
Syntax
NAFILL(source-expression fill-expression)
Parameters
The expression being evaluated. For values of source-expression that do not equal NA, NAFILL returns the corresponding values of source-expression. Source-expression determines the dimensions and data type of the result.
The expression to be substituted in the return value. Fill-expression must have the same data type as source-expression. Fill-expression is only evaluated for values of source-expression that equal NA.
Usage Notes
Functions in the Fill Expression
You can use any functions in the fill expression if they return the same data type as the source expression.
NATRIGGER Takes Precedence Over NAFILL
Oracle OLAP evaluates an $NATRIGGER property expression before applying the NAFILL function. When the $NATRIGGER expression is NA, then the NAFILL function has an effect.
Examples
Example 8-32 Filling NA Values with Zeros
Suppose you have NA values in the variable sales and you want to calculate an average that counts those values as zeros. Ordinarily, AVERAGE ignores NA values and does not count them in the number of values being averaged. You can use NAFILL inside the AVERAGE function to temporarily treat those values as zeros so the NA values count in calculating the average.
REPORT AVERAGE(NAFILL(sales 0.0))
The NUMLINES function counts the number of lines in each value of a text expression. The result returned by NUMLINES has the same dimensions as the specified expression.
NUMLINES accepts either a TEXT or NTEXT argument. It does not perform an automatic conversion to either data type.
Return Value
INTEGER
Syntax
NUMLINES(text-expression)
Parameters
The text expression whose lines are to be counted.
Examples
The NONE function returns YES when none of the values of a Boolean expression are TRUE. It returns NO when any value of the expression is TRUE.
Return Value
BOOLEAN or NA if all the values of the expression are NA
Syntax
NONE(boolean-expression [CACHE] [dimension...])
Parameters
The Boolean expression to be evaluated.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of boolean-expression and another dimension that you want as a dimension of the result.
By default, NONE returns a single YES or NO value. When you indicate one or more dimensions for the result, NONE tests for TRUE values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of boolean-expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of boolean-expression, but, instead, is dimension that is related to a dimension of boolean-expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
The Effect of NASKIP on NONE
NONE is affected by the NASKIP option. When NASKIP is set to YES (the default), and all of the values in the expression are NA NONE returns NA; if even one value is not NA, NONE ignores all of the NA values in the expression. When NASKIP is set to NO, NONE returns NA when any value of the expression is NA.
Examples
Example 8-37 Testing for No True Values by District
Suppose you want to find out which districts had no months in which sales fell below $50,000. Use the NONE function to determine whether the Boolean expression (SALES LT 50000) is TRUE for no months. To have the results dimensioned by district, specify district as the second argument to NONE.
LIMIT product TO 'Sportswear' REPORT NONE(sales LT 50000, district)
The preceding statements produce the following output.
NONE(SALES
LT 50000,
DISTRICT DISTRICT)
-------------- ----------
Boston NO
Atlanta YES
Chicago YES
Dallas YES
Denver YES
Seattle NO
Example 8-38 Testing for No True Values by Region
You might also want to find out which regions had no months in which no districts had sportswear sales of less than $50,000. Since the region dimension is related to the district dimension, you can specify region instead of district as a dimension for the results of ANY.
REPORT NONE(sales LT 50000, region)
The preceding statement produces the following output.
NONE(SALES
LT 50000,
REGION REGION)
-------------- ----------
East NO
Central YES
West NO
The LCOLWIDTH option controls the default width of the label column in reports. For output from ROW command and HEADING, LCOLWIDTH affects the first column. For output from REPORT, LCOLWIDTH affects the first column unless the first column is a data column or part of a set of columns that represent the base dimensions of a composite or a conjoint dimension.
|
Note: For an individual column, the LCOLWIDTH value is always overridden by a WIDTH attribute in a HEADING, REPORT, or ROW command |
Data Type
INTEGER
Syntax
LCOLWIDTH = n
Parameters
An INTEGER expression that specifies the desired column width in number of characters. You can set LCOLWIDTH to any value from 1 to 4000. The default is 14.
|
Note: The maximum width of a line in a report is 4,000 characters. Therefore, the combined width of all the columns of a report cannot be greater than 4,000 characters |
Examples
Example 5-38 Setting Default Column Widths
Suppose you want to look at unit sales for six months. Since the longest product name is 10 characters, you do not need the default width of 14 for your label column. Also, since the sales figures are not large, you do not need a width of 10 characters for your data columns. You can set LCOLWIDTH and COLWIDTH to give smaller default column widths.
LIMIT district TO 'Atlanta' LIMIT month TO 'Oct95' TO 'Mar96' LCOLWIDTH = 10 COLWIDTH = 6 REPORT ACROSS month: units
These statements produce the following output.
DISTRICT: ATLANTA
------------------UNITS------------------
------------------MONTH------------------
PRODUCT Oct95 Nov95 Dec95 Jan96 Feb96 Mar96
---------- ------ ------ ------ ------ ------ ------
Tents 503 345 259 279 305 356
Canoes 317 282 267 281 309 386
Racquets 1,365 1,270 1,357 1,125 1,304 1,263
Sportswear 3,065 2,327 1,955 2,591 2,829 3,137
Footwear 3,445 3,247 2,831 3,089 3,282 3,475
The INSCHARS function inserts one or more characters into a text expression.
When you are using a multibyte character set, you can use the INSBYTES function instead of the INSCHARS function.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
INSCHARS(text-expression characters [after])
Parameters
The expression into which the characters are to be inserted. When text-expression is a multiline TEXT value, INSCHARS preserves the line breaks in the returned value.
One or more characters that you insert into text-expression.
An INTEGER that represents the character position after which the specified characters are to be inserted. The position of the first character in text-expression is 1. To insert characters at the beginning of the text, specify 0 for after. When you omit this argument, INSCHARS inserts the characters after the last character in text-expression.
When you specify a value for after that is greater than the length of text-expression, INSCHARS adds blanks to the last line of text-expression. The number of inserted blanks is the difference between the value of after and the length of text-expression. For example, INSCHARS('abc' 'def' 4) inserts one blank before adding 'def' to 'abc', resulting in.
abc def
Examples
The ADD_MONTHS function returns the date that is n months after the specified date.
Return Value
DATETIME
Syntax
ADD_MONTHS(start_datetime, n)
Parameters
A DATETIME expression that identifies the starting date. When the day component of start_datetime is the last day of the month or when the returned month has fewer days, then the returned day component is the last day of the month. Otherwise, the day component of the returned date is the same as the day component of start_datetime. See Example 7-2, "End-of-Month Calculation".
An INTEGER that identifies the number of months to be added to start_datetime.
Examples
The FULLDSC program produces a report that lists the definition of one or more workspace objects, including the properties and triggers of the object(s).
Syntax
FULLDSC [names]
Parameters
The names of one or more workspace objects, separated by spaces or commas. FULLDSC shows the full definition of each object specified. When you omit this argument, FULLDSC shows the definition of all objects in the current status of the NAME dimension.
Usage Notes
Output of FULLDSC
The FULLDSC program is an extension to the DESCRIBE command. That is, the object definition that you list with FULLDSC includes the definition components that are listed by the DESCRIBE command, followed by any properties that are assigned to the object. Each property is listed on its own line with the word PROPERTY, the name of the property, and its value.
Limiting the Objects Described
Normally, the status of NAME is ALL, so FULLDSC with no argument produces a report that includes the definitions of all objects in your current workspace. However, you can use the LIMIT command in combination with FULLDSC to report the definitions of a particular group of objects in your workspace. Use LIMIT first to limit the status of the NAME dimension to the names of the objects whose definitions you want to see. Then execute a FULLDSC statement with no arguments to list the definitions.
Paginated Output
You can produce paginated output with a FULLDSC statement by setting PAGING to YES before using FULLDSC.
Creating Objects with FULLDSC Output
You can use the output from a FULLDSC statement to create objects in other workspaces, because each line of the output is a valid statement. For example, you can execute an OUTFILE statement to send subsequent output to a file, and then execute a FULLDSC statement. You can then access another workspace, and use an INFILE statement to read the FULLDSC output. The same object is created in that workspace.
The output produced by FULLDSC might not exactly reproduce the original PROPERTY statements that created the properties of the object because the original name and value expressions are not saved. In addition, FULLDSC sets the DECIMALS option to 255, which drops trailing zeros. See "Listing the Properties of a Variable".
Examples
Example 9-143 Listing the Properties of a Variable
This example produces a report of the full definition of the actual variable, to which the properties DECPLACE and REPPRG have been added. The statement
FULLDSC actual
produces the following output.
DEFINE ACTUAL VARIABLE DECIMAL <LINE DIVISION MONTH> LD Actual $ Financials PROPERTY 'DECPLACE' 4 PROPERTY 'REPPRG' 'qtrrep'
Suppose the DECPLACE property had been specified with the following statement, where PRPNAME is a variable whose value is DECPLACE.
PROPERTY prpname 4.00
The output from FULLDSC would be the same as that shown in the preceding example; the value 4.00 would be shown as 4. Therefore, when you created an object using the INFILE technique with the FULLDSC output, the newly created property value would have a type of INTEGER (based on the value 4) even though the original property value had a type of DECIMAL (based on the value 4.00). In most cases, this difference is immaterial, because the appropriate conversions are performed when the property values are used.
The STATLIST function returns a list of all values in the current status list of a dimension or dimension surrogate, or in a valueset. You can format the list to a specified width. The STATLIST function is employed by the STATUS command, which summarizes the status of a dimension. Use STATLIST rather than STATUS when you want to control the width or placement of the display.
Return Value
STATLIST returns a list of TEXT values that contains either the dimension or dimension surrogate values themselves (for example, Jan95) or numbers (for example, 6) that represent the positions of the values in the default status list.
The returned values are in the form value TO value, for example, Jan96 TO Jun96. When default status is in effect, it displays ALL. When the current status list or the valueset is empty, it displays NULL.
Syntax
STATLIST(dimension [keyword] [width])
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
A keyword from Table 8-14, "Keywords for STATLIST". The keywords allow you to specify the form in which you want the values in the current status list to appear.
Table 8-14 Keywords for STATLIST
| Keyword | Description |
|---|---|
|
INTEGER |
Specifies that STATLIST should return the list of values in the current status of a dimension in the form of the |
|
TEXT |
(Default) Specifies that STATLIST should return the list of values in the current status of a dimension in the form of the value names of those values. |
An optional INTEGER expression that specifies the width of the list in characters. When no width is specified, STATLIST uses the current value of the LSIZE option. LSIZE has a default value of 80.
Examples
Example 8-111 Producing a Status List with ROW
This example lists months in which total sales exceed $3,000,000.
These statements
LIMIT month TO TOTAL(sales, month) GE 3000000 ROW W 40 'Months with total sales over $3,000,000: '- W 40 STATLIST(month, 40)
produce the following output.
Months with total sales over $3,000,000: Jun95 TO Sep95, May96 TO Sep96
Example 8-112 Producing a Status List with SHOW
The following STATLIST statement formats dimension values to a 20-character width.
LIMIT month TO 'Jan95' 'Mar95' 'May95' 'Jul96' 'Sep96' 'Nov96' SHOW STATLIST(month 20)
These statements produce this output.
Jan95, Mar95, May95, Jul96, Sep96, Nov96
This statement lists dimension positions.
SHOW STATLIST(month INTEGER 20)
This is the output.
1, 3, 5, 19, 21, 23
The EIFNAMES option holds a list of the names of all the objects imported by the most recent IMPORT (EIF) command.
Data Type
TEXT
Syntax
EIFNAMES
Examples
Checking What You Have Imported
Suppose you have exported the units variable and the productset valueset from the demo analytic workspace to a file called myfile.eif. After importing the contents of the file into a new workspace, you can use the EIFNAMES option to see the names of the objects you have just imported.
The following statements
AW CREATE mytest IMPORT ALL FROM EIF FILE 'myfile.eif' SHOW EIFNAMES
produce this output.
DISTRICT PRODUCT MONTH UNITS PRODUCTSET
(Read-only) After the Database reports an error and SQLCODE has a nonzero value, the SQLERRM option usually contains text that explains the problem.
Data Type
TEXT
Syntax
SQLERRM
Usage Notes
Oracle Relational Manager
You can set the SQLMESSAGES option to YES to send the value of SQLERRM to the current output file automatically.
Examples
The TRACE command specifies whether or not information about the entry, exit, and execution of individual programs, models, and formulas is recorded in the current outfile during execution:
For programs and and models, it traces the entry, exit, and execution of individual lines of code and produces output similar to the output produced when the PRGTRACE or MODTRACE option is set to YES.
For formulas, it outputs the name and dimension value on entry and the return value on exit.
Syntax
TRACE [?|{object-name|*} [OFF] [begin-arguments] [end-arguments] [ TRACELINES | NOTRACELINES]]
where:
begin-arguments requires the following syntax:
IN [ARGS | NOARGS]
end-arguments requires the following syntax:
OUT [VALUE | NOVALUE]
Parameters
A ? (question mark) displays the current TRACE list, which includes the name of each program, model, and formula that will be traced when executed. In addition, if there is a global trace, TRACE ALL is listed. For each program, model, and formula, and for TRACE ALL, the list displays the current TRACE settings (the values of begin-arguments and end-arguments).
The unqualified name of the program, model, or formula that you want to trace. You can specify the name of a program, model, or formula even if it does not exist in an attached database. Without the OFF keyword, this argument turns on an object-specific trace, in which TRACE traces the execution of the named program, model, or formula whenever you run it. In order to change the TRACE settings of a program, model, or formula, you can turn on its object-specific trace several times. With the OFF keyword, this argument turns off the object-specific trace.
An* (asterisk) is only used with programs and models:
Without the OFF keyword, an * (asterisk) adds TRACE ALL to the TRACE list and turns on a global trace. This means that TRACe traces the execution of every program and model that you run, including programs such as LISTNAMES that are part of express.db. If you have both an object-specific trace and a global trace specified, the settings for the object-specific trace take precedence when you run the given program or model.
With the OFF keyword, an * (asterisk), turns off the gloabl trace by deleting all program names, model names, and TRACE ALL from the TRACE list, leaving the list empty.
ARGS and NOARGS are used only with programs and formulas. These keywords indicate whether TRACE should display the values of arguments when entering a program or the dimension values of formulas. The default is ARGS.
VALUE and NOVALUE are used only with programs. These keywords indicate whether the return value of the program is displayed after executing its last line. If the program does not have a return value, no value is displayed. The default is VALUE.
TRACELINES and NOTRACELINES are used only with programs and models. These keywords indicate whether the program or model lines are printed. The default is TRACELINES.
Usage Notes
Nested Programs and Models
If you execute nested programs (in which one program calls another), and if you trace all the nested programs, TRACE will keep track of the nested levels. If one of the programs calls a model, you can also trace the model, and TRACE will keep track of the model within the stack of nested programs.
Changing TRACE Settings
You can change a TRACE setting for a program or model by executing a new TRACE command. If you only change one of the settings, the others remain set to the values they had before.
Tracing a Model
If a block of simultaneous equations in a model cannot be solved within a specified number of iterations, an error occurs. The value of the MODERROR option determines the action that TRACE takes in this event.
The $LOOP_DENSE property is used to determine how to loop the formula on which it is assigned when a OLAP_TABLE SQL function with the LOOP OPTIMIZED clause is executed. It specifies that Oracle OLAP loops densely over the formula (that is, that it loop over every tuple of the formula—even those member cells that do not have values).
Syntax
You add or delete a $LOOP_DENSE property to the most recently defined or considered formula (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$LOOP_DENSE' dimension_list
To delete the property, issue the following statement.
PROPERTY DELETE '$LOOP_DENSE'
Parameters
One or more names of the dimensions of the formula separated by commas.
The FINTSCHED function calculates the interest portion of the payments on a series of fixed-rate installment loans that are paid off over a specified number of time periods. For each time period, you specify the amount of the loans incurred during that time period and a single interest rate that applies to those loans over their lifetime.
FINTSCHED calculates the result for a given time period as the sum of the interest due on each loan that is incurred or outstanding in that period.
Return Value
DECIMAL
The result returned by the FINTSCHED function is dimensioned by the union of all the dimensions of loans, rates, n, and the dimension used as the time-dimension argument.
Syntax
FINTSCHED(loans, rates, n, [time-dimension] [STATUS])
Parameters
A numeric expression that contains the initial amounts of the loans. When loans does not have a time dimension, or when loans is dimensioned by multiple time dimensions, the time-dimension argument is required.
A numeric expression that contains the interest rates charged for loans. When rates is a dimensioned variable, it can be dimensioned by any dimension, including a different time dimension. When rates is dimensioned by a time dimension, you specify the interest rate in each time period that applies to the loans incurred in that period. The interest rate for the time period in which a loan is incurred applies throughout the lifetime of that loan. The rates are expressed as decimal values; for example, a 5 percent rate is expressed as.05.
A numeric expression that specifies the number of payments required to pay off the loans in the series. The n expression can be a dimensioned variable, but it cannot be dimensioned by the time dimension argument. One payment is made in each time period of the time dimension by which loans is dimensioned or in each time period of the dimension specified in the time-dimension argument. For example, one payment is made each month when loans is dimensioned by MONTH.
The name of the dimension along which the interest payments are calculated. When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional, unless loans has multiple time dimensions.
Specifies that FINTSCHED should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the interest portion of the payments. By default FINTSCHED uses the default status list.
Usage Notes
FINTSCHED and NA Values
When loans has a value other than NA and the corresponding value of rates is NA, an error occurs.
FINTSCHED is affected by the NASKIP option. When NASKIP is set to YES (the default), and a loan value is NA for the affected time period, the result returned by FINTSCHED depends on whether the corresponding interest rate has a value of NA or a value other than NA. Table 7-11, "Effect of NASKIP When Loan or Rate Values are NA for a Time Period" illustrates how NASKIP affects the results when a loan or rate value is NA for a given time period.
Table 7-11 Effect of NASKIP When Loan or Rate Values are NA for a Time Period
| Loan Value | Rate Value | Result When NASKIP = YES | Result When NASKIP = NO |
|---|---|---|---|
|
Non- |
|
Error |
Error |
|
|
Non- |
Interest values ( |
|
|
|
|
|
|
As an example, suppose a loan expression and a corresponding interest expression both have NA values for 1997 but both have values other than NA for succeeding years. When the number of payments is 3, FINTSCHED returns NA for 1997, 1998, and 1999. For 2000, FINTSCHED returns the interest portion of the payment due for loans incurred in 1998, 1999, and 2000.
FINTSCHED Ignores the Status of the Time Dimension
The FINTSCHED calculation begins with the first time dimension value, regardless of how the status of that dimension may be limited. For example, suppose loans is dimensioned by year, and the values of year range from Yr95 to Yr99. The calculation always begins with Yr95, even when you limit the status of year so that it does not include Yr95.
However, when loans is not dimensioned by the time dimension, the FINTSCHED calculation begins with the first value in the current status of the time dimension. For example, suppose loans is not dimensioned by year, but year is specified as time-dimension. When the status of year is limited to Yr97 to Yr99, the calculation begins with Yr97 instead of Yr95.
Examples
Example 7-98 Calculating Interest
The following statements create two variables called loans and rates.
DEFINE loans DECIMAL <year> DEFINE rates DECIMAL <year>
Suppose you assign the following values to the variables loans and rates.
YEAR LOANS RATES -------------- ---------- ---------- Yr95 100.00 0.05 Yr96 200.00 0.06 Yr97 300.00 0.07 Yr98 0.00 0.00 Yr99 0.00 0.00
For each year, loans contains the initial value of the fixed-rate loan incurred during that year. For each year, the value of rates is the interest rate that is charged for any loans incurred in that year; for those loans, this same rate is charged each year until the loans are paid off.
The following statement specifies that each loan is to be paid off in three payments, calculates the interest portion of the payments on the loans,
REPORT W 20 HEADING 'Payment' FINTSCHED(loans, rates, 3, year)
and produces the following report.
YEAR Payment -------------- -------------------- Yr95 5.00 Yr96 15.41 Yr97 30.98 Yr98 18.70 Yr99 7.48
The interest payment for 1995 is interest on the loan of $100 incurred in 1995, at 5 percent. The interest payment for 1996 is the sum of the interest on the remaining principal of the 1995 loan, at 5 percent, plus interest on the loan of $200 incurred in 1996, at 6 percent. The 1997 interest payment is the sum of the interest on the remaining principal of the 1995 loan, at 5 percent; interest on the remaining principal of the 1996 loan, at 6 percent; and interest on the loan of $300 incurred in 1997, at 7 percent. Since the 1995 loan is paid off in 1997, the payment for 1998 represents interest on the remaining principal of the 1996 and 1997 loans. In 1999, the interest payment is on the remaining principal of the 1997 loan.
The NVL2 function returns one value when the value of a specified expression is not NA or an empty string, or another value when the value of the specified expression is an empty string or NA.
To replace a NA value or an empty string with a string, use NVL.
Return Value
The data type of the return value is always the data type of expr2 (that is, the expression whose value is returned when the value of expr1 is not NA).
Syntax
NVL2 (expr1 , expr2 , expr3)
Parameters
The expression whose value this function evaluates.
An expression whose value is returned when the value of expr1 is not an empty string or NA.
An expression whose value is returned when the value of expr1 is NA.
Usage Notes
Comparing Values of Different Data Types
When the data types of expr2 and expr3 are different, then the function converts expr3 to the data type of expr2 before comparing them.
Examples
The TALLY function counts the number of values of a dimension that correspond to each value of one or more related dimensions.
Return Value
INTEGER
Syntax
TALLY(dimension [related-dimensions])
Parameters
A dimension whose values are to be counted. When you specify related-dimensions, TALLY counts the number of values of dimension that correspond to each value of a single related dimension, or to each combination of values of two or more related dimensions. When you do not specify related-dimensions, TALLY counts the number of values in the dimension. Only values in the current status of dimension are counted.
One or more related dimensions for the results. These must be related to dimension. Alternatively, you can specify the name of the relation instead of the dimension name which enables you to choose which relation is used when there are multiple relations between dimensions. When no related-dimensions are specified, TALLY returns the total number of values in the current status of dimension.
Usage Notes
TALLY with NA
TALLY returns NA for any related-dimension position that has no dimension values corresponding to it.
TALLY with DWMQY Dimensions
When expression is dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR as a related-dimension. Oracle OLAP uses the implicit relation between the dimensions. To control the mapping of one DAY, WEEK, MONTH, QUARTER, or YEAR dimension to another (for example, from weeks to months), you can define an explicit relation between the two dimensions and specify the name of the relation as the related-dimension argument to the TALLY function.
For each time period in the related dimension, Oracle OLAP tallies all the source time periods that end in the target time period. This method is used regardless of which dimension has the more aggregate time periods.
Examples
Example 8-130 Breaking Out TALLY Results
Here you use TALLY to determine how many products are produced by each division. The division.product relation records the division to which each product belongs. The following is a report of division.product.
PRODUCT DIVISION.PRODUCT --------------------------------- Tents Camping Canoes Camping Racquets Sporting Sportswear Clothing Footwear Clothing
The following statement includes TALLY to present the number of products produced by each division.
REPORT HEADING 'Products' TALLY(product, division)
The statement produces this report.
DIVISION Products ------------------------- Camping 2 Sporting 1 Clothing 2
The FCEXEC command executes a forecast based on the parameters options specified by the FCSET command for the forecast. The FCEXEC command implicitly loops over all the dimensions of the expression other than the time dimension.
You must use the FCEXEC command in combination with other OLAP DML statements as outlined in "Forecasting Programs".
Syntax
FCEXEC handle-expression [choice] time-series-expression
where choice is one or more of the following:
Parameters
An INTEGER expression that specifies the handle to a forecasting context previously opened using the FCOPEN function.
The name of the time dimension. You do not have to specify this parameter when one dimension of the time-series-expression is of type DAY, WEEK, MONTH, QUARTER, or YEAR.
An INTEGER expression that specifies the number of business days in the unit of time of the time data type (that is, DAY, WEEK, MONTH, or YEAR) of the time-series-expression. By default the value is the total number of days in the unit of time.
The name of the Oracle OLAP variable in which the forecasting engine stores the forecast data. This variable must be dimensioned by the time dimension and any other dimensions of the time-series-expression that have multiple values in status. (This variable can have additional dimensions. However, in this case, when Oracle OLAP executes the forecast, it limits each of these additional dimensions to the first value in the dimension's status list.).
|
Important: When you do not specify INTO and the time-series-expression names an Oracle OLAP variable, the forecasting engine populates the input variable with the output data of the forecast, thus overwriting the original data. |
The name of the variable that the forecasting engine populates with the data that represents seasonal factors.The forecasting engine produces only one cycle of factors and stores these values into this variable beginning with the first time period in status. This variable must be dimensioned by the time dimension and any other dimensions of the time-series-expression that have multiple values in status. (This variable can have additional dimensions. However, in this case, when the forecasting engine executes the forecast, Oracle OLAP limits each of these additional dimensions to the first value in the dimension's status list.)
The name of the variable that the forecasting engine populates with the data that represents smoothed seasonal factors. The forecasting engine produces only one cycle of factors and stores these values into this variable beginning with the first time period in status; all other values are set to NA. This variable must be dimensioned by the time dimension and any other dimensions of the time-series-expression that have multiple values in status. (This variable can have additional dimensions. However, in this case, when the forecasting engine executes the forecast, Oracle OLAP limits each of these additional dimensions to the first value in the dimension's status list.)
The BACKCAST keyword specifies that the forecasting engine returns fitted historical data. Typically this data is available only for a subset of the historical periods (sometimes called the "fit window"). The forecasting engine sets the value of the data that corresponds to the historical time periods that are outside of the fit window to NA.
|
Important: When you specify a value for BACKCAST and do not specify a value for INTO variable, the forecasting engine populates the source variable with the backcasted data, thus overwriting the original data. |
An expression that specifies the data from which FCEXEC calculates values. The time-series-expression must be a numeric expression that is dimensioned by time-dimension. The time-series-expression may also be dimensioned by other dimensions. In this case, FCEXEC implicitly loops over all the dimensions of the expression other than the time dimension. The maximum status length of the time-series-expression is 5000.
Usage Notes
Forecasting a Single Value
The FCEXEC command implicitly loops over all the dimensions of the time-series expression other than the time dimension. When you want to forecast only one value of a multidimensional time-series expression, then you must limit the status of all non-time dimensions to a single value before you execute the FCEXEC command.
Examples
Example 9-119 A Forecasting Program
Suppose you define a program named autofcst to perform a forecast from the data that is in an input variable named fcin1. The fcin1 variable is dimensioned by a time dimension named timedim. Assume that you have defined a program named autofcst with the following definition and specification.
DEFINE autofcst PROGRAM
PROGRAM
" Using the Automatic forecasting method
" Suppose you want to create a forecast from the data in
" an input variable named fcin1 that is dimensionsed by
" a time dimension named timedim.
"
" Open a forecasting context
hndl = FCOPEN('MyForecast')
" Initialize the target variables
fcout1 = NA
fcseas1 = NA
fcsmseas1 = NA
" Specify that the forecast be of the AUTOMATIC type
fcset hndl method 'automatic'
" Execute the forecast
FCEXEC hndl time timedim INTO fcout1 -
seasonal fcseas1 smseasonal fcsmseas1 backcast fcin1
" Create a report showing the input and output of the forecast
REPORT DOWN timedim fcin1 fcout1 fcseas1 fcsmseas1
" Run a program named queryall to retrieve the characteristics
" of the forecasting trials
QUERYALL
" Close the forecasting context
FCCLOSE hndl
END
The autofcst program opens a forecasting context, sets the option of the forecast to AUTOMATIC, reports on the forecasted data, and queries and reports the characteristics of the various trials that Oracle OLAP performed to determine the method to use, and closes the forecasting context.
The autofcst program contains the following report command that displays a report of the input to and the output from the forecast.
REPORT DOWN timedim fcin1 fcout1 fcseas1 fcsmseas1
The sample report created by this statement follows.
TIMEDIM FCIN1 FCOUT1 FCSEAS1 FCSMSEAS1 -------------- ---------- ---------- ---------- ---------- Jan97 NA NA 1.06725482 1.02926773 Feb97 NA NA .978607917 .945762221 Mar97 NA NA 1.12699278 .860505188 Apr97 NA NA .576219022 .905284834 May97 NA NA .920601317 .907019312 Jun97 NA NA 0.91118344 1.0580697 Jul97 NA NA 1.07886483 1.05597234 Aug97 NA NA 1.08101034 1.054612 Sep97 NA NA 1.08077427 1.05361672 Oct97 2,914 NA 1.08351799 1.05380407 Nov97 2,500 NA 1.01126778 1.04504316 Dec97 2,504 NA 1.08370549 1.03104272 Jan98 3,333 NA NA NA Feb98 2,512 NA NA NA Mar98 2,888 NA NA NA ... ... ... ... ... Jan01 NA 3,371.7631 NA NA Feb01 NA 2,736.4811 NA NA Mar01 NA 3,408.3656 NA NA Apr01 NA 714.277175 NA NA May01 NA 2,502.9315 NA NA Jun01 NA 3,195.3626 NA NA Jul01 NA 3,911.6058 NA NA Aug01 NA 4,000.651 NA NA Sep01 NA 4,220.2658 NA NA Oct01 NA 3,416.0208 NA NA Nov01 NA 2,827.3943 NA NA Dec01 NA 2,990.8629 NA NA
The queryall program and a sample report created from its output is shown in Example 7-87, "Querying a Forecast".
The AGGREGATE function calculates the data in the variable that is not specified as PRECOMPUTE in the specified aggmap. (For information about specifying precompute data, see PRECOMPUTE statement and the PRECOMPUTE clause of the RELATION (for aggregation) statement.) The aggregation is limited to those values that are currently in status.
|
Note: When the variable you want to aggregate has an $AGGMAP property, you do not have to explicitly use the AGGREGATE function to aggregate nonprecomted data in that variable. |
Return Value
The same data type as the aggregated variable.
Syntax
AGGREGATE (var ... [USING aggmap] -
[FROM fromspec|FROMVAR textvar] [FORCECALC FORCEORDER] [COUNTVAR countvar])
Parameters
The name of the variable whose data is calculated (if necessary) and returned.
This keyword indicates that the aggregation is performed using the specified aggmap.
The name of a previously-defined aggmap that specifies how the data is aggregated. For information about aggmaps, see DEFINE AGGMAP.
This keyword indicates that the detail data is obtained from a different object. A FROM clause is only one way in which you can specify the variable from which detail data should be obtained when performing aggregation. See "Ways of Specifying Where to Obtain Detail Data for Aggregation".
An arbitrarily dimensioned variable, formula, or relation from which the detail data for the aggregation is obtained.
This keyword indicates that the detail data is obtained from different objects to perform a capstone aggregation. A FROMVAR clause is only one way in which you can specify the variable from which detail data should be obtained when performing aggregation. See "Ways of Specifying Where to Obtain Detail Data for Aggregation".
An arbitrarily dimensioned variable used to resolve any leaf nodes. Specify NA to indicate that a node does not need detail data to calculate the value.
Specifies that any value that is not specified in a PRECOMPUTE clause of a RELATION statement that are in the aggmap should be recalculated, even when there is a value stored in the desired cell. Use the FORCECALC keyword when you want users to be able to change detail data cells and see the changed values reflected in dynamically-computed aggregate cells.
|
Note: You can also set an $AGGREGATE_FORCECALC property on a variable to specify this behavior as the default aggregation behavior. In this case, you do not have to include the FORCECALC keyword with the AGGREGATE function. |
Specifies that the calculation must be performed in the order in which the RELATION statements are listed in the aggmap. Use this option when you have changed some values calculated by the AGGREGATE command. Otherwise, the optimization methods used by the AGGREGATE function may cause the modified values to be ignored. FORCEORDER slows performance.
|
Note: You can also set an $AGGREGATE_FORCEORDER property on a variable to specify this behavior as the default aggregation behavior. In this case, you do not have to include the FORCEORDER keyword with the AGGREGATE function. |
Indicates that Oracle OLAP should use the user-defined variable specified by countvar to store the non-NA counts of the number of leaf nodes that contributed to aggregate values calculated for RELATION (for aggregation) statements that have an AVERAGE, HAVERAGE, HWAVERAGE, or WAVERAGE operator.
|
Note: Typically, you do not use a user-defined Countvar variable to store the counts for average aggregations. Instead, you use an Oracle OLAP-created Aggcount variable. You must use an Aggcount variable when the aggregation specification includes a RELATION (for aggregation) statement with an average operator that is for a compressed composite.For more information on Aggcount variables, see "Aggcount Variables". |
The countvar variable must be an INTEGER variable with the same dimensions in the same order as the dimensions of the variable specified by var. When you aggregate several variables together, you must define an INTEGER variable for each one to record the results.
Usage Notes
Steps for Supporting Run-Time Calculations
Follow these steps when combining pre-aggregation with run-time aggregation:
Create an aggmap that limits the amount of data to be precalculated.
Execute the AGGREGATE command with the FUNCDATA argument.
When you have made any changes after executing the AGGREGATE command (see "Compiling the Aggmap"), recompile the aggmap with a COMPILE statement.
Add an $AGGREGATE_FROM property to the data variables (see "Using NA Values to Trigger Run-Time Calculations").
UPDATE and COMMIT the analytic workspace.
Compiling the Aggmap
Be sure to compile the aggmap at the time you load data, either with an explicit COMPILE statement or with the FUNCDATA argument to the AGGREGATE command. Otherwise, the aggmap is recompiled at run time for each session in which the AGGREGATE function is used. Perform other calculations (such as calculating models) before you compile the aggmap.
You must recompile the aggmap after maintaining any of the dimensions in the aggmap definition or any of the relations that are included in the text of the aggmap.
Run-Time Changes to Data Values
When users are able to change data values at run time, then the data may get out of synchronization. You can prevent this problem in the following ways:
Use an ALLOCATE statement to distribute the data in a new aggregate to the contributing values lower in the hierarchy.
Do not precalculate the data that is subject to run-time changes, since the stored aggregates cannot be altered to reflect changes made at run time to the contributing values.
Using NA Values to Trigger Run-Time Calculations
By adding an $NATRIGGER property to a variable, you can implicitly call the AGGREGATE function each time the data is queried. The following statements cause sales data to be aggregated using the sales.aggmap aggmap.
CONSIDER sales PROPERTY '$NATRIGGER' 'AGGREGATE(sales USING sales.aggmap)'
From now on, a statement such as REPORT SALES executes the AGGREGATE function, so that computed values are returned instead of NAs.
Using the AGGREGATE Function after Partial Rollups
When your batch window is not sufficiently long to preaggregate all of the data to generate, you can perform the aggregation in stages on consecutive days and use the AGGREGATE function to calculate the balance. For each stage, you must do the following:
Change the PRECOMPUTE phrase of the RELATION statement in the aggmap so that new data is aggregated.
Execute the AGGREGATE command with the FUNCDATA keyword.
Verify that the $NATRIGGER property is set on the variables so that the AGGREGATE function calculates the balance of the data.
Using Multiple Aggmaps
Whenever possible, use only one aggmap to rollup a variable. However, in some situations, a variable requires multiple aggmaps to roll up the data in the desired manner. When a variable requires multiple aggmaps to rollup data problems are created when some data is calculated on the fly, because the metadata retained for the AGGREGATE function corresponds to the last aggmap. The AGGREGATE function needs metadata that is the union of all of the aggmaps used by the AGGREGATE command. The solution is to create an additional aggmap for use by the AGGREGATE function that correctly identifies the NA values. Be sure to compile this aggmap.
Do not use the AGGREGATE function with multiple aggmaps unless you feel comfortable answering the following question:
When you cannot answer "yes" to this question with confidence, do not use the AGGREGATE function with multiple aggmaps.
Examples
This section contains several examples of using the AGGREGATE function. For additional aggregation examples, see the examples for the AGGMAP command.
Example 7-5 Using the AGGREGATE Function as the Formula of an Expression
Example 9-32, "Capstone Aggregation" illustrates performing the final capstone aggregation using an AGGREGATE command. You could also perform the capstone aggregation at run time as the expression of a formula.
Assume that your analytic workspace contains the following object definitions.
DEFINE GEOG.D DIMENSION TEXT DEFINE GEOG.PARENTREL RELATION GEOG.D <GEOG.D> DEFINE TIME.D DIMENSION TEXT DEFINE TIME.PARENTREL RELATION TIME.D <TIME.D> DEFINE SALES_JAN76 VARIABLE INTEGER <GEOG.D> DEFINE SALES_FEB76 VARIABLE INTEGER <GEOG.D> DEFINE SALES_MAR76 VARIABLE INTEGER <GEOG.D> DEFINE SALES_CAPSTONE76 VARIABLE INTEGER <GEOG.D TIME.D> DEFINE CAPSTONE_SOURCE VARIABLE TEXT <TIME.D>
Now you create two aggmap objects with the following definitions. Note that in this case the capstone_aggmap consists of a RELATION statement with a PRECOMPUTE NA clause.
DEFINE LEAF_AGGMAP AGGMAP AGGMAP RELATION geog.parentrel OPERATOR SUM END DEFINE CAPSTONE_AGGMAP AGGMAP AGGMAP RELATION time.parentrel OPERATOR SUM PRECOMPUTE (NA) END
In Example 9-32, "Capstone Aggregation", the final capstone aggregation is performed using an AGGREGATE command. In this example, the capstone aggregation is defined as a formula named f_sales_capstone76 that has an AGGREGATE function as the expression of the formula.
DEFINE F_SALES_CAPSTONE76 FORMULA INTEGER <GEOG.D TIME.D> EQ AGGREGATE ( sales_capstone76 USING capstone_aggmap fromvar capstone_source)
When you report on the unaggregated variables and formulas in your analytic workspace, you see the following results.
GEOG.D SALES_JAN76 SALES_FEB76 SALES_MAR76
-------------- -------------- -------------- --------------
Boston 1,000 2,000 3,000
Medford 2,000 4,000 6,000
San Diego 3,000 6,000 9,000
Sunnydale 4,000 8,000 12,000
Massachusetts NA NA NA
California NA NA NA
United States NA NA NA
--------------------F_SALES_CAPSTONE76---------------------
--------------------------TIME.D---------------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- -------------- -------------- -------------- --------------
Boston 1,000 2,000 3,000 6,000
Medford 2,000 4,000 6,000 12,000
San Diego 3,000 6,000 9,000 18,000
Sunnydale 4,000 8,000 12,000 24,000
Massachusetts NA NA NA NA
California NA NA NA NA
United States NA NA NA NA
---------------------SALES_CAPSTONE76----------------------
--------------------------TIME.D---------------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- -------------- -------------- -------------- --------------
Boston 1,000 2,000 3,000 NA
Medford 2,000 4,000 6,000 NA
San Diego 3,000 6,000 9,000 NA
Sunnydale 4,000 8,000 12,000 NA
Massachusetts NA NA NA NA
California NA NA NA NA
United States NA NA NA NA
Now you aggregate the leaf variables using the following AGGREGATE statement.
AGGREGATE sales_jan76 sales_feb76 sales_mar76 USING leaf_aggmap
A report of the leaf variables shows that they are aggregated.
GEOG.D SALES_JAN76 SALES_FEB76 SALES_MAR76 -------------- -------------- -------------- -------------- Boston 1,000 2,000 3,000 Medford 2,000 4,000 6,000 San Diego 3,000 6,000 9,000 Sunnydale 4,000 8,000 12,000 Massachusetts 3,000 6,000 9,000 California 7,000 14,000 21,000 United States 10,000 20,000 30,000
A report of the f_sales_capstone76 formula shows the aggregated values for 76Q1.
--------------------F_SALES_CAPSTONE76---------------------
--------------------------TIME.D---------------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- -------------- -------------- -------------- --------------
Boston 1,000 2,000 3,000 6,000
Medford 2,000 4,000 6,000 12,000
San Diego 3,000 6,000 9,000 18,000
Sunnydale 4,000 8,000 12,000 24,000
Massachusetts 3,000 6,000 9,000 18,000
California 7,000 14,000 21,000 42,000
United States 10,000 20,000 30,000 60,000
While a report of the sales_capstone76 variable does not show the aggregated values for 76Q1 since they are not stored in the variable.
---------------------SALES_CAPSTONE76----------------------
--------------------------TIME.D---------------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- -------------- -------------- -------------- --------------
Boston 1,000 2,000 3,000 NA
Medford 2,000 4,000 6,000 NA
San Diego 3,000 6,000 9,000 NA
Sunnydale 4,000 8,000 12,000 NA
Massachusetts 3,000 6,000 9,000 NA
California 7,000 14,000 21,000 NA
United States 10,000 20,000 30,000 NA
Example 7-6 Aggregating Data on the Fly for a Report
The units variable is aggregated entirely on the fly using the tp.agg aggmap.
This is the object definitions for the variable units.
DEFINE units VARIABLE INTEGER <time product>
The parent relation for time contains these values.
---TIME.PARENTREL----
--TIME.HIERARCHIES---
TIME STANDARD YTD
---------- ---------- ----------
Jan01 Q1.01 Last.Ytd
Feb01 Q1.01 Last.Ytd
Mar01 Q1.01 Last.Ytd
Q1.01 2001 NA
The parent relation for the product dimension contains these values.
PRODUCT.PA
PRODUCT RENTREL
---------- ----------
Food Na
Snacks Food
Drinks Food
Popcorn Snacks
Cookies Snacks
Cakes Snacks
Soda Drinks
Juice Drinks
In the units variable, data is stored only at the lowest level of each dimension hierarchy.
-------------------UNITS------------------- -------------------TIME-------------------- PRODUCT Jan01 Feb01 Mar01 Q1.01 ----------- ---------- ---------- ---------- ---------- Food NA NA NA NA Snacks NA NA NA NA Drinks NA NA NA NA Popcorn 2 2 4 NA Cookies 3 6 3 NA Cakes 4 4 2 NA Soda 7 3 9 NA Juice 1 3 2 NA
The aggmap specifies that all data is calculated on the fly.
DEFINE tp.agg AGGMAP LD <time product> Aggmap AGGMAP RELATION time.parentrel PRECOMPUTE (NA) RELATION product.parentrel PRECOMPUTE (NA) END
The following REPORT statement uses the AGGREGATE function to calculate the data.
REPORT aggregate(units USING tp.agg) -------AGGREGATE(UNITS USING TP.AGG)------- -------------------TIME-------------------- PRODUCT Jan01 Feb01 Mar01 Q1.01 ----------- ---------- ---------- ---------- ---------- Food 17 18 20 55 Snacks 9 12 9 30 Drinks 8 6 11 25 Popcorn 2 2 4 8 Cookies 3 6 3 12 Cakes 4 4 2 10 Soda 7 3 9 19 Juice 1 3 2 6
Example 7-7 Using $NATRIGGER to Aggregate Data
When the AGGREGATE function is added to units in the $NATRIGGER property, a simple REPORT statement displays aggregated results.
CONSIDER units PROPERTY '$NATRIGGER' 'AGGREGATE(units USING tp.agg)' REPORT units -------------------UNITS------------------- -------------------TIME-------------------- PRODUCT Jan01 Feb01 Mar01 Q1.01 ----------- ---------- ---------- ---------- ---------- Food 17 18 20 55 Snacks 9 12 9 30
Example 7-8 Calculating all but one Value on the Fly
The AGGREGATE function calculates the complement of the data specified in the PRECOMPUTE clause of the RELATION statement. It returns those values that are currently in status.
For example, when you are using an aggmap that contains this RELATION statement.
RELATION letter.letter PRECOMPUTE ('AA')
Then the AGGREGATE function calculates all aggregations except AA, as shown here.
REPORT AGGREGATE(units USING letter.aggmap)
AGGREGATE(UNITS
LETTER USING LETTER.AGGMAP)
-------------- --------------------
A 3
AA NA
AB 3
AAB 2
ABA 1
ABB 2
AAAA 1
AABA 2
ABAA 1
ABBB 1
ABBA 1
...
The OUTFILE command lets you redirect the text output of statements to a file.
Syntax
OUTFILE {EOF | TRACEFILE | [APPEND] file-name [NOCACHE] [NLS_CHARSET charset-exp]}
Parameters
The current outfile is closed and output is redirected to the default outfile.
Specifies that the output should be directed the Oracle trace file, which is identified by the TRACEFILEUNIT option.
Specifies that the output should be added to the end of an existing disk file. When you omit this argument, the new output replaces the current contents of the file.
A text expression that is the name of the file to which output should be written. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Specifies that Oracle OLAP should write lines to the outfile as they are generated. Without this keyword, Oracle OLAP reduces file I/O activity by saving text and writing it periodically to the file. The NOCACHE keyword slows performance significantly, but it ensures that every line is immediately recorded in the outfile. This argument must be specified after file-name
Specifies the character set that Oracle OLAP uses when writing data to the file specified by file-name which allows Oracle OLAP to convert the data accurately into that character set. This argument must be specified after file-name. When this argument is omitted, then Oracle OLAP writes the data to the file in the database character set, which is recorded in the NLS_LANG option.
Usage Notes
Outfiling a PERMIT_READ or PERMIT_WRITE Program
The contents of a PERMIT_READ or a PERMIT_WRITE program is emptied when outfiled. To successfully copy the contents of these programs to and from analytic workspaces, rename them before using OUTFILE; and then, after using INFILE to copy them into an analytic workspace, name them back to PERMIT_READ or PERMIT_WRITE.
Current Outfile Identifier
As a first step, every OUTFILE statement closes the current outfile. When OUTFILE opens a new outfile on disk, it automatically assigns to it an arbitrary INTEGER as its file unit number. The current file unit number is held in the OUTFILEUNIT option.
Appending to an Outfile
When you send output to a file and then send output to a second file, the first file does not remain open. To resume sending output to the first file, you must execute another OUTFILE statement and include the APPEND file-name phrase.
Automatic Closing of Outfile
When you use OUTFILE file-name to direct output to a disk file, OUTFILE closes any outfile currently open. OUTFILE issues a close even when the new file is not actually opened (as when you specify an invalid file-name in an OUTFILE statement).
Paging Options and Redirected Output
The paging options control the organization of text output in pages. Examples are: BMARGIN, LINENUM, LINELEFT, PAGESIZE, PAGENUM, PAGEPRG, PAGING, TMARGIN, and LSIZE. The paging options have a separate value for each separate outfile. When you set a paging option to control output to a disk file, the new value remains in effect until you use an OUTFILE statement again to redirect output. At this point, the paging option returns to its default value. Therefore, when you want a paging option to have a particular value for a disk file, you generally have set it after you execute an OUTFILE statement.
Maximum Line Length
The maximum line length in Oracle OLAP is 4,000 characters.
Current and Default Outfiles
The current outfile is the destination for the output of statements, such as REPORT and DESCRIBE, that produce text. When you have not used an OUTFILE statement to send output to a file, Oracle OLAP uses your default outfile.
Examples
Example 10-68 Sending a Report to an Output File
In this example, you want to send the output of a REPORT statement to an output file.
OUTFILE 'budget.rpt' REPORT budget OUTFILE EOF
Example 10-69 Directing Output to a File
Suppose you have a program called year.end.sales, and you want to save the report it creates in a file. Type the following commands to write a file of the report. In this example, userfiles is a directory object and yearend.txt is the name of the file.
OUTFILE 'userfiles/yearend.txt' year.end.sales OUTFILE EOF
Now the file contains the year.end.sales report. You can add more reports to the same file with the APPEND keyword for OUTFILE. Suppose you have another program called year.end.expenses. Add its report to the file with the following commands. Remember that without APPEND, an OUTFILE statement overwrites the expense report.
OUTFILE APPEND 'userfiles/yearend.txt' year.end.expenses OUTFILE EOF
The DAYOF function returns an INTEGER in the range of 1 through 7, giving the day of the week on which a specified date falls. A result of 1 refers to Sunday. The result has the same dimensions as the specified DATE expression.
Return Value
INTEGER
Syntax
DAYOF(date-expression)
Parameters
An expression that has the DATE data type, or a text expression that specifies a date. Instead of a DATE expression, you can specify a text expression that has values that conform to a valid input style for dates. DAYOF automatically converts the values of the text expression to DATE values, using the current setting of the DATEORDER option to resolve any ambiguity.
Examples
The RECNO function reports the current record number of a file opened for reading. It returns NA when Oracle OLAP has reached the end of the file.
Return Value
INTEGER
Syntax
RECNO(fileunit)
Parameters
A file unit number assigned to a file opened for reading in a previous call to the FILEOPEN function.
Usage Notes
Opening Files
Before you can use the RECNO function, you must open the file for reading. When the file unit number is not associated with an open file or the file has been opened for writing, RECNO returns an error.
Using RECNO with FILEGET
RECNO is usually used with FILEREAD or FILENEXT, which read whole records. When you are reading data from a file with the FILEGET function, which can read partial records, RECNO returns the number of times you have read data from the file, not the number of actual records.
LINENUM Option
See also the LINENUM option, which holds the current line number of output.
Records in Text Files
When the file is a text file, a record is delimited by a newline character. When the file is a binary file, you must set the file's LSIZE attribute to the record length with a FILESET statement. TEXT is the default file type.
Examples
Example 8-66 Using RECNO with FILEREAD
In the following example code, a FILEREAD statement maintains the INTEGER dimension, adding each record number associated with filename. The text associated with each record number becomes each value of the variable textvar.
DEFINE dim1 INTEGER DIMENSION
DEFINE textvar TEXT <dim1>
x = FILEOPEN('filename' R)
FILEREAD x APPEND dim1 = RECNO(x) W 8 TEXTVAR
The ARCTAN function calculates the angle value (in radians) of a specified tangent.
To retrieve a full-range (0 - 2 pi) numeric value indicating the arc tangent of a given ratio, use ARCTAN2.
Return Value
NUMBER
Syntax
ARCTAN(expression)
Parameters
An expression that contains the decimal value of a tangent.
Examples
The ERRORNAME option holds the name of the first error that occurs when you execute a program or when you execute an OLAP DML statement.
Data Type
TEXT
Syntax
ERRORNAME
Usage Notes
ERRORNAME and SIGNAL
You can create your own error conditions in a program with the SIGNAL command. SIGNAL sets ERRORNAME and ERRORTEXT to the values you specify.
You can use the special name PRGERR with the SIGNAL command to communicate to a calling program that an error has occurred. The command SIGNAL PRGERR sets ERRORNAME to a blank value and passes an error condition to the calling program without causing another error message to be displayed. For information on using SIGNAL to pass an Oracle OLAP error up a chain of nested programs, see the TRAP command.
Examples
Example 5-34 Using ERRORNAME with TRAP
In a report program that uses a TRAP command to handle errors, you can use the SIGNAL command to send the appropriate error name to the current outfile.
DEFINE myreport PROGRAM LD Monthly Report PROGRAM TRAP ON CLEANUP NOPRINT PUSH month DECIMALS LSIZE PAGESIZE LIMIT month TO LAST 1 ... POP month DECIMALS LSIZE PAGESIZE RETURN CLEANUP: POP month DECIMALS LSIZE PAGESIZE SIGNAL ERRORNAME ERRORTEXT END
The HIERHEIGHT command populates a previously-defined relation with the values of a specified hierarchical dimension by level. Typically, you use the HIERHEIGHT command when you are preparing an analytic workspace for access using the OLAP_TABLE function.
To retrieve the value of a node (by level) for the value of a hierarchical dimension, use the HIERHEIGHT function.
Syntax
HIERHEIGHT parentrelation [(qdrlist)] INTO{familyrel-
[USING level-relation | A | D] [INHIERARCHY { inh-variable | inh-valueset}]
Parameters
A child-parent self-relation for the hierarchical dimension. See "Parentrel Relation" for more information.
A list of QDRs that limits the values of parentrel. Specify the QDRs as described in "Syntax of a Qualified Data Reference". When you do not specify a value for qdrlist, HIERHEIGHT uses the values of parentrel that are in current status.
A previously -defined relation that the HIERHEIGHT command populates when it executes. This relation can have multiple dimensions; however, it must be dimensioned by the dimensions of parentrel and one other dimension that represents the levels of the hierarchical dimension. The actual construct of the dimension that represents the levels of the hierarchical dimension varies depending on whether or not the HIERHEIGHT statement includes the USING phrase:
When the statement includes the USING phrase, the dimension that represents the levels of the hierarchical dimension is a dimension that contains the names of the levels.
When the statement does not include the USING phrase, the dimension that represents the levels of the hierarchical dimension is an INTEGER dimension that has as values the depth of the level.
When familyrel is populated before a HIERHEIGHT statement executes, the HIERHEIGHT statement depopulates it before computing new values.
Specifies that the relation is populated using the specified levelrel. See "Levelrel Relation" for more information.
Specifies that the relation is populated in ascending order.
(Default) Specifies that the relation is populated in descending order.
A BOOLEAN variable that is dimensioned by the hierarchical dimension and, when the hierarchical dimension is a multi-hierarchical dimension, by a dimension that is the names of the hierarchies. The values of the variable are TRUE when the dimension value is in a hierarchy and FALSE when it is not.
The name of a valueset object whose values are the hierarchical dimension values to be considered when creating grouping ids. Values not included in the valueset are ignored. See "Inhier Valueset or Variable" for more information.
Usage Notes
HIERHEIGHT with the OLAP_TABLE Function
Typically, you use a HIERHEIGHT statement when you are preparing an analytic workspace for access using the OLAP_TABLE function.
Examples
Example 10-4 Creating a Relational Representation of a Geography Hierarchy
Assume that there is an analytic workspace named myaw that has a Geography hierarchy defined with analytic objects with the following definitions.
DEFINE geog.hierdim DIMENSION TEXT LD Hierarchy names for Geography hierarchies DEFINE geog.leveldim DIMENSION TEXT LD List of levels for GEOGRAPHY hierarchies DEFINE geography DIMENSION TEXT WIDTH 12 LD Values for the Geography hierarchies DEFINE geog.levelrel RELATION geog.leveldim <geography geog.hierdim> LD Level of each value in the Geography hierarchies DEFINE geog.parent RELATION geography <geography geog.hierdim> LD Child-parent relation for the Geography hierarchies DEFINE geog.familyrel RELATION geography <geography geog.leveldim geog.hierdim> LD Geography values by level and hierarchy
These objects have the following structures.
GEOGRAPHY
------------------
World
Americas
Canada
USA
Toronto
Montreal
Boston
LosAngeles
GEOG.HIERDIM
------------------
Standard
Consolidated
GEOG.LEVELDIM
------------------
World
Continent
Country
City
Consolidated
Continent
Consolidated
Country
------------GEOG.LEVELREL------------
------------GEOG.HIERDIM-------------
GEOGRAPHY Standard Consolidated
------------------ ------------------ ------------------
World World NA
Americas Continent Consolidated
Continent
Canada Country Consolidated
Country
USA Country Consolidated
Country
Toronto City NA
Montreal City NA
Boston City NA
LosAngeles City NA
-------------GEOG.PARENT-------------
------------GEOG.HIERDIM-------------
GEOGRAPHY Standard Consolidated
------------------ ------------------ ------------------
World NA NA
Americas World NA
Canada Americas Americas
USA Americas Americas
Toronto Canada NA
Montreal Canada NA
Boston USA NA
LosAngeles USA NA
To create a family relation of the Geography hierarchy you define an analytic workspace object with the following definition.
DEFINE geog.familyrel RELATION geography <geography geog.leveldim geog.hierdim> LD Geography values by level and hierarchy
Then you use a HIERHEIGHT statement as illustrated in the following statement to populate the object.
HIERHEIGHT geog.parent INTO geog.familyrel USING geog.levelrel
By issuing a REPORT statement, you can display the relational representations of both the Standard and Consolidated hierarchies of the geography dimension.
REPORT DOWN geography geog.familyrel
GEOG.HIERDIM: Standard
-------------------------------GEOG.FAMILYREL--------------------------------
--------------------------------GEOG.LEVELDIM--------------------------------
Consolidated Consolidated
GEOGRAPHY World Continent Country City Continent Country
------------ ------------ ------------ ------------ ------------ ------------ ------------
World World NA NA NA NA NA
Americas World Americas NA NA NA NA
Canada World Americas Canada NA NA NA
USA World Americas USA NA NA NA
Toronto World Americas Canada Toronto NA NA
Montreal World Americas Canada Montreal NA NA
Boston World Americas USA Boston NA NA
LosAngeles World Americas USA LosAngeles NA NA
GEOG.HIERDIM: Consolidated
-------------------------------GEOG.FAMILYREL--------------------------------
--------------------------------GEOG.LEVELDIM--------------------------------
Consolidated Consolidated
GEOGRAPHY World Continent Country City Continent Country
------------ ------------ ------------ ------------ ------------ ------------ ------------
World NA NA NA NA NA NA
Americas NA NA NA NA Americas NA
Canada NA NA NA NA Americas Canada
USA NA NA NA NA Americas USA
Toronto NA NA NA NA NA NA
Montreal NA NA NA NA NA NA
Boston NA NA NA NA NA NA
LosAngeles NA NA NA NA NA NA
DML Reference
11g Release 2 (11.2)
E17122-07
May 2011
Oracle OLAP DML Reference, 11g Release 2 (11.2)
E17122-07
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The BLANKSTRIP function removes leading or trailing blank spaces from text values. BLANKSTRIP is useful for such purposes as removing unwanted blank spaces from imported fixed-length fields.
Return Value
TEXT or NTEXT
Syntax
BLANKSTRIP(text-expression [TRAILING|LEADING|BOTH])
Parameters
A text expression from which to remove blank spaces. When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
Removes blank spaces at the end of the text.
Removes blank spaces at the beginning of the text.
Removes both leading and trailing spaces.
Examples
Use the FORECAST command to forecast data by one of three methods: straight-line trend, exponential growth, or Holt-Winters extrapolation. FORECAST performs the calculation according to the method you specify and optionally stores the result in a variable in your analytic workspace.
You can then execute FORECAST.REPORT to produce a standard report of the forecast. You can also use the INFO function to obtain portions of the results for use in your own customized reports or for further analysis.
|
Tip: Most applications forecast data using a forecasting context rather than using a FORECAST statement. See "Forecasting Programs" for more information. |
Syntax
FORECAST [LENGTH n] -
[METHOD {TREND|EXPONENTIAL|WINTERS PERIODICITY p [argument...]}] -
[TIME dimension] [FCNAME name] time-series
where argument is one or more of the following clauses that specify the characteristics of the forecast:
Parameters
Specifies the number of periods to forecast. The default is zero. When you supply a LENGTH, you must also supply the FCNAME option.
(Default) Specifies that the forecasting technique is a straight-line extrapolation of historical data.
Specifies that the forecasting technique is an extrapolation of historical data using a constant period-to-period percentage growth.
Specifies that the forecasting technique is the Holt-Winters method, an extrapolation method that allows for both a linear trend and seasonal fluctuations in the data. Oracle OLAP first constructs three statistically related series for each time period of the historical data. (See "Holt-Winters Constructed Series".) Then, Oracle OLAP produces a forecast from the three series for the specified number of periods into the future.
You can supply several arguments that affect the results of the Holt-Winters forecast. The only required one is PERIODICITY. For the others, Oracle OLAP chooses a reasonable value based on the data available.
The length of the seasonal cycle, where p is an expression that specifies an INTEGER greater than or equal to 2. For example, when the data you are analyzing has monthly values, then p is 12.
PERIODICITY is required when you use the METHOD WINTERS keyword.
Smoothing constants for the first three series calculated for the Holt-Winters forecast (See "Holt-Winters Constructed Series"). ALPHA is for the smoothed data series; BETA is for the seasonal index series; and GAMMA is for the trend series. The value n is a decimal expression greater than 0 and less than or equal to 1. Each value is optional. When you omit one, Oracle OLAP calculates an optimal smoothing constant for that series that minimizes the Mean Absolute Percent Error of the one-period-ahead forecasts in the historical time periods.
STSMOOTHED specifies the starting value of the smoothed data series (See "Holt-Winters Constructed Series"). The value n is a decimal expression greater than 0. When you specify STSMOOTHED, you must also specify STSEASONAL and STTREND. When you omit it, Oracle OLAP calculates a starting value.
STSEASONAL specifies the starting values for the seasonal index series (See "Holt-Winters Constructed Series"). N-series is an array of decimal values, one for each period in a seasonal cycle. The number of values needed equals the number specified for PERIODICITY (See "Holt-Winters Starting Values"). When you specify STSEASONAL, you must also specify STSMOOTHED and STTREND. When you omit it, Oracle OLAP calculates the starting values.
STTREND specifies the starting value of the trend series (See "Holt-Winters Constructed Series"). N is a decimal value. When you specify STTREND, you must also specify STSMOOTHED and STSEASONAL. When you omit it, Oracle OLAP calculates a starting value.
Numeric variables in which Oracle OLAP can store the data calculated for the smoothed data series, the seasonal index series, and the trend series (See "Holt-Winters Constructed Series"). The variable specified by name must have the TIME dimension as one of its dimensions. The series calculations produce DECIMAL results, but Oracle OLAP converts the values to the data type of name before storing them. You can save any or all of the preliminary series. When you do not save a series, Oracle OLAP discards the values after completing the forecast.
The name of the dimension considered to be the time dimension. The current status of dimension determines the number of periods of historical data used to calculate the forecast. The status of the time dimension must be an increasing, consecutive range of values. LENGTH specifies how many values immediately beyond this range is forecast.
When time-series has only one dimension, the time dimension defaults to that. When time-series has multiple dimensions and one dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, then the time dimension defaults to that type. Otherwise, you must specify the time dimension, even when the additional dimensions are limited to a single value. FORECAST only uses the first value in the status for dimensions other than the time dimension.
The name of a numeric variable in which to store the values calculated by FORECAST. Name must be dimensioned by the time dimension; it can have other dimensions as well. When the data type of name is not decimal, FORECAST converts the values to the appropriate data type.
Fitted values, which correspond to the historical data, are stored in name for the current status of the time dimension. Forecasted values are stored in name for the number of periods specified by LENGTH. These forecasted periods immediately follow the current status of the time dimension.
For the Holt-Winters method, the fitted values are one-period-ahead forecasts calculated at the previous period. The final forecasted values are extrapolated from the fitted data.
For the TREND and EXPONENTIAL methods, FORECAST obtains the fitted values by evaluating the regression equation over the current status of the time dimension.
An expression that specifies the time series to be forecast. Time-series must be a numeric expression that is dimensioned by the time dimension. When time-series has other dimensions, FORECAST uses the first value only in their current status. The time-series is the historical data from which FORECAST calculates fitted and forecasted values. (See the explanation for FCNAME.)
Usage Notes
Forecasting Multidimensional Expressions
When you want to forecast all the values of a multidimensional expression, you can use a program that puts a FORECAST statement inside one or more FOR loops to loop over all the remaining dimensions of the expression.
Obtaining Portions of Results
YOu can obtain portions of the results of FORECAST for your own reports or further analysis, using an INFO statement.
Order of Arguments
You can specify the arguments for FORECAST in any order, except that time-series, the expression specifying the data to be forecast, must be last.
Time-series Data Handling
Each method has its own criteria for handling the input data specified in time-series.
TREND -- Requires at least two values that are not NA; accepts zero and negative values; ignores NA values
EXPONENTIAL -- Requires at least two positive values; ignores zero, negative, and NA values
WINTERS -- Accepts zero and negative values; fills in NA values by calculating a weighted moving average
Zero Values
All methods allow zero values in the historical data, specified by time-series, but those time periods are excluded from the Mean Absolute Percent Error (MAPE) calculation.
Holt-Winters Constructed Series
The Holt-Winters forecasting method constructs three statistically related series, which are used to make the actual forecast. These series are:
The smoothed data series, which is the original data with seasonal effects and random error removed.
The seasonal index series, which is the seasonal effect for each period. A value greater than one represents a seasonal increase in the data for that period, and a value less than one is a seasonal decrease in the data. The Holt-Winters method allows seasonal effects to vary over time, so there is a seasonal index value for every historical period.
The trend series, which is the change in the data for each period with the seasonal effects and random error removed. The Holt-Winters method allows the trend effect to vary over time, so there is a trend value for every historical period.
Holt-Winters Omitted Arguments
For the Holt-Winters method, when you omit the STSMOOTHED, STTREND, and STSEASONAL phrases, Oracle OLAP calculates the necessary starting values using an algorithm from Statistical Methods for Forecasting by Abraham and Ledolter. Let Oracle OLAP calculate the starting values when you have little experience with Holt-Winters forecasting.
Holt-Winters Starting Values
When you specify starting values, Oracle OLAP obtains the STSEASONAL starting values by unraveling the values to make a list. The list must have at least the number of values as specified by PERIODICITY. Any more values are ignored; fewer values cause an error. The STSEASONAL expression can be multidimensional and does not have to have the same dimensions as the historical data. (For information about the order of the list when a dimensioned expression is unraveled, see the UNRAVEL function.)
Getting Calculated Values
You can find out the values that Oracle OLAP calculates for ALPHA, BETA, and GAMMA and for STSMOOTHED, STSEASONAL, and STTREND by using the INFO function.
Getting a Report of the Forecast
The FORECAST.REPORT program produces a standard report of a forecast created using the FORECAST command.
The report shows the parameters of the forecast, including the forecast formula and Mean Absolute Percent Error, followed by a display of the forecasted values. To produce this report, type the following.
FORECAST.REPORT
Examples
Example 9-139 Using the EXPONENTIAL Method
The following statements create a variable called fcst.sales, limit the dimensions of the sales variable, use the EXPONENTIAL method to forecast sportswear sales for the Chicago district for 1997, and store the results of the calculation in fcst.sales.
DEFINE fcst.sales DECIMAL <month> LIMIT product TO 'Sportswear' LIMIT district TO 'Chicago' LIMIT month TO 'Jan95' TO 'Dec96' FORECAST LENGTH 12 METHOD EXPONENTIAL FCNAME fcst.sales - time month sales
You can now execute FORECAST.REPORT to see the values that have been generated. Running the FORECAST.REPORT program for that forecast produces the following report.
Forecasting Analysis
====================
Variable to Forecast: SALES
Forecast dimension: MONTH
Forecast method: EXPONENTIAL
Mean absolute percent error: 16.64%
Forecast Equation: SALES = 87718.0009541883 *
(1.00553383457899 ** MONTH)
MONTH Actual Value Fitted Value
-------------------- ------------ ------------
Jan95 72,123.47 88,203.42
Feb95 80,071.75 88,691.52
Mar95 78,812.69 89,182.33
Apr95 97,413.26 89,675.85
May95 94,406.65 90,172.10
... ... ...
Dec96 72,095.02 100,140.38
... ... ...
Example 9-140 Using the WINTERS Method
The following statements limit the month dimension, then calculate a forecast that takes into account seasonal influences, using the WINTERS method.
DEFINE fcst.sales DECIMAL <montH> LIMIT month TO year 'Yr95' 'Yr96' FORECAST LENGTH 12 METHOD WINTERS - PERIODICITY 12, ALPHA .5, BETA .5, GAMMA .5 - time month, FCNAME fcst.sales, sales
You can now execute FORECAST.REPORT to see the values that have been generated. Running the FORECAST.REPORT program for that forecast produces the following report.
Forecasting Analysis
====================
Variable to Forecast: SALES
Forecast dimension: MONTH
Forecast method: WINTERS
Alpha: 0.50
Beta: 0.50
Gamma: 0.50
Periodicity: 12
Mean absolute percent error: 0.20%
MONTH Actual Value Fitted Value
-------------------- ------------ ------------
Jan95 72,123.47 72,154.67
Feb95 80,071.75 80,027.51
Mar95 78,812.69 79,171.08
Apr95 97,413.26 97,200.81
May95 94,406.65 94,464.71
.... ... ...
Dec97 77,867.23
The REEDIT command edits a statement that you entered earlier in your session. The statement is retrieved from the command log, which is a list of up to 256 statements that you have entered most recently during the current session. REEDIT enables you to change the statement without executing it, so you can edit it sequentially.
The REDO command is similar to REEDIT, except that the statement is executed after you edit it.
|
Note: REEDIT statements themselves are not included in the command log; however the statements re-executed by REEDIT are included. |
Syntax
REEDIT [number|index] 'original' 'replacement' [specifier]
Parameters
A positive INTEGER that indicates the number of the statement to be edited. You can display the statements, with their numbers, using a RECAP statement.
A negative INTEGER or 0 (zero) that indicates the position of the statement to be edited relative to the end of the command log. The most recent statement is 0, the one before that is -1, and so on. The default is 0.
A text literal that is part of the statement to be edited.
A text literal that should replace original when the statement is edited.
A specifier listed in Table 10-3, "Valid Values for REEDIT specifier". Each specifier indicates where text replacement should occur in the edited statement.
Table 10-3 Valid Values for REEDIT specifier
| Specifier | Meaning |
|---|---|
|
|
Indicates that only the first occurrence of original should be changed to replacement. |
|
|
Indicates that only the last occurrence of original should be changed to replacement. |
|
n |
A number indicating which occurrence of original should be changed to replacement. For example, |
|
|
Indicates that all occurrences of original should be changed to replacement |
|
|
Indicates that all occurrences of original should be changed to replacement. |
The default is ALL. When you do not provide a specifier, all occurrences of original are changed to replacement.
Usage Notes
REEDIT with No number or index Argument
When you type REEDIT without number or index, the most recent statement is edited.
Case-Sensitivity
When matching original with the text of the statement to be edited, REEDIT ignores case differences. For example, assume you specify AT as original, REEDIT matches it with at, At, aT, or AT in the statement.
When replacing original with replacement, REEDIT retains the case of all characters in replacement. For example, assume you specify ShOw as replacement, that is exactly how it appears in the edited statement.
Examples
Example 10-90 Editing Multiple Values in a LIMIT Command
The following example illustrates why it could be helpful to use a REEDIT statement to edit a statement several times before executing it. With REEDIT commands, you can edit multiple values in a LIMIT command before executing it. When you enter a REDO statement, the LIMIT command is executed.
The following output is the result of a recap 1 statement.
COMMAND LOG
6: limit mydim to 1 to 10, 15 to 20, 24 to 28, 33 to 40
The statement
REEDIT 6 '1' '2' FIRST
produces the following output.
7: limit mydim to 2 to 10 , 15 to 20, 24 to 28, 33 to 40
The statement
REEDIT 7 '15' '18'
produces the following output.
8: limit mydim to 2 to 10 , 18 to 20, 24 to 28, 33 to 40
The statement
REDO 8 '40' '41'
makes one more change and re-executes the LIMIT command with the new values. It also produces the following output.
9: limit mydim to 2 to 10 , 18 to 20, 24 to 28, 33 to 41
The VINTSCHED function calculates the interest portion of the payments on a series of variable-rate installment loans that are paid off over a specified number of time periods. VINTSCHED calculates the result for a given time period as the sum of the interest due on each loan that is incurred or outstanding in that period. For each time period, you specify the initial amount of the loans incurred in that time period and the interest rate that is charged in that time period for each new or outstanding loan.
Return Value
DECIMAL
The result returned by the VINTSCHED function is dimensioned by the union of all the dimensions of loans and rates and the dimension that is used as the time-dimension argument.
Syntax
VINTSCHED(loans, rates, n, [time-dimension] [STATUS])
Parameters
A numeric expression that contains the initial amounts of the loans. When loans does not have a time dimension, or when loans is dimensioned by multiple time dimensions, the time-dimension argument is required.
A numeric expression that contains the interest rates charged for loans. When rates is a dimensioned variable, it can be dimensioned by any dimension, including a different time dimension. When rates is dimensioned by a time dimension, you specify the interest rate in each time period that applies to the loans incurred or outstanding in that period. The interest rates are expressed as decimal values; for example, a 5 percent rate is expressed as .05.
A numeric expression that specifies the number of payments required to pay off the loans in the series. The n expression can be dimensioned, but it cannot be dimensioned by the time dimension argument. One payment is made in each time period of the time dimension by which loans is dimensioned or in each time period of the dimension specified in the time-dimension argument. For example, one payment a month is made when loans is dimensioned by month.
The name of the dimension along which the interest payments are calculated. When loans has a dimension of type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional, unless loans has multiple dimensions of these types.
Specifies that VINTSCHED should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the interest portion of the payments. By default VINTSCHED uses the default status list.
Usage Notes
VINTSCHED and NA Values
When loans has a value other than NA and the corresponding value of rates is NA, an error occurs.
VINTSCHED is affected by the NASKIP option. When NASKIP is set to YES (the default), and a loan value is NA for the affected time period, the result returned by VINTSCHED depends on whether the corresponding interest rate has a value of NA or a value other than NA. Table 8-21, "How NASKIP Affects the Results When a Loan or Rate Value is NA for a Given Time Period" illustrates how NASKIP affects the results when a loan or rate value is NA for a given time period.
Table 8-21 How NASKIP Affects the Results When a Loan or Rate Value is NA for a Given Time Period
| Loan Value | Rate Value | Result when NASKIP = YES | Result when NASKIP = NO |
|---|---|---|---|
|
Non- |
|
Error |
Error |
|
|
Non- |
Interest values ( |
|
|
|
|
|
|
As an example, suppose a loan expression and a corresponding interest expression both have NA values for 1997, but both have values other than NA for succeeding years. When the number of payments is 3, VINTSCHED returns NA for 1997, 1996, and 1995. For 1997, VINTSCHED returns the interest portion of the payment due for loans incurred in 1995, 1996, and 1997.
VINTSCHED Ignores the Status of a Time Dimension
The VINTSCHED calculation begins with the first value of the time dimension, regardless of how the status of that dimension may be limited. For example, suppose loans is dimensioned by year, and the values of year range from Yr95 to Yr99. The calculation always begins with Yr95, even when you limit the status of year so that it does not include Yr95.
However, when loans is not dimensioned by the time dimension, the VINTSCHED calculation begins with the first value in the current status of the time dimension. For example, suppose loans is not dimensioned by year, but year is specified as time-dimension. When the status of year is limited to Yr97 to Yr99, the calculation begins with Yr97 instead of Yr95.
Examples
Example 8-164 Using VINTSCHED
The following statements create two variables called loans and rates.
DEFINE loans DECIMAL <year> DEFINE rates DECIMAL <year>
Suppose you assign the following values to the variables loans and rates.
YEAR LOANS RATES -------------- ---------- ---------- Yr95 100.00 0.05 Yr96 200.00 0.06 Yr97 300.00 0.07 Yr98 0.00 0.07 Yr99 0.00 0.07
For each year, loans contains the initial value of the variable-rate loan incurred during that year. For each year, the value of rates is the interest rate that is charged for that year on any loans incurred or outstanding in that year.
The following statement specifies that each loan is to be paid off in three payments, calculates the interest portion of the payments on the loans,
REPORT W 20 HEADING 'Payment' VINTSCHED(loans, rates, 3, year)
and produces the following report.
YEAR Payment -------------- -------------------- Yr95 5.00 Yr96 16.10 Yr97 33.06 Yr98 19.43 Yr99 7.48
The interest payment for 1995 is interest on the loan of $100 incurred in 1995, at 5 percent. The interest payment for 1996 is the sum of the interest on the remaining principal of the 1995 loan, plus interest on the loan of $200 incurred in 1996; the interest rate for both loans is 6 percent. The 1997 interest payment is the sum of the interest on the remaining principal of the 1995 loan, interest on the remaining principal of the 1996 loan, and interest on the loan of $300 incurred in 1997; the interest rate for all three loans is 7 percent. Since the 1995 loan is paid off in 1997, the payment for 1998 represents 7 percent interest on the remaining principal of the 1996 and 1997 loans. In 1999, the interest payment is on the remaining principal of the 1997 loan.
The DDOF function returns an INTEGER in the range of 1 through 31, giving the day of the month on which a specified date falls. The result returned by DDOF has the same dimensions as the specified DATE expression.
Return Value
INTEGER
Syntax
DDOF(date-expression)
Parameters
An expression that has the DATE data type, or a text expression that specifies a date. See "Date-only Input Values" for valid formats for a text expression.
Examples
The STATCURR function returns the values of a specified status list for a dimension
Return Value
The data type of the returned value varies depending on the data type of the dimension.
Syntax
STATCURR (dimension, integer)
Parameters
The name of the dimension for which the function searches for status lists.
Specifies the position in the status list stack of the status list the function returns.
| Value | Specifies |
|---|---|
0 | The current value of the dimension. |
-1 | Returns the current value of status for the previous status list in the status list stack for the dimension. |
1 | Returns the current value of the status list on the bottom of the status list stack for the dimension. |
The $GID_LIST property contains the names of the levels used to create the grouping ids in a relation created when the GROUPINGID command with either the ROLLUP or GROUPSET keyword executes.
Syntax
You cannot explicitly define a $GID_LIST property. Oracle OLAP automatically creates a $GID_LIST property on a grouping id relation when the execution of a GROUPIONGID command with either the ROLLUP or GROUPSET keyword creates the relation.
$GID_LIST = levels
Parameters
A TEXT expression which is the levels, separated by hyphens (-), of the hierarchies of the dimension for which grouping ids were created.
The BACK function returns the names of all currently executing programs, listed one name on each line in a multiline text value. When multiple programs are executing, one program has called another in a series of nested executions.
The first name in the return value is that of the program containing the call to BACK. The last name is that of the initial program, which made the first call to another program.
BACK can only be used in a program.
Return Value
TEXT
Syntax
BACK
Examples
Example 7-27 Debugging a Program Using the BACK Function
The following example uses three programs. program1 calls program2, and program2 calls program3.
DEFINE program1 PROGRAM PROGRAM SHOW 'This is program number 1' CALL program2 END DEFINE program2 PROGRAM PROGRAM SHOW 'This is program number 2' CALL program3 END DEFINE program3 PROGRAM PROGRAM SHOW 'This is program number 3' SHOW 'These programs are currently executing:' SHOW BACK END
Executing program1 produces the following output.
This is program number 1 This is program number 2 This is program number 3 These programs are currently executing: PROGRAM3 PROGRAM2 PROGRAM1
The COALESCE function returns the first non-NA expression in a list of expressions, or NA when all of the expressions evaluate to NA.
Return Value
Data type of the first argument.
Syntax
COALESCE (expr [, expr]...)
Parameters
An expression.
Examples
Example 7-45 Using COALESCE to Determine the Sales Price of a Product
Assume that you have defined the following objects in your analytic workspace. (Note that the sale formula uses the COALESCE function for its calculations.)
DEFINE product_id DIMENSION TEXT DEFINE supplier_id DIMENSION TEXT DEFINE list_price VARIABLE DECIMAL <product_id supplier_id> DEFINE min_price VARIABLE DECIMAL <product_id supplier_id> DEFINE sale FORMULA DECIMAL <Product_id supplier_id> EQ COALESCE(0.9*list_price, min_price, 5)
The following code illustrates limiting supplier_id to a single value and displaying a report that shows the list price, minimum price, and sale price for the products provided by that supplier.
LIMIT supplier_id TO '102050'
REPORT DOWN product_id list_price min_price sale
----------SUPPLIER_ID-----------
-------------102050-------------
PRODUCT_ID LIST_PRICE MIN_PRICE SALE
-------------- ---------- ---------- ----------
2382 850.00 731.00 765.00
3355 NA NA 5.00
1770 NA 73.00 73.00
2378 305.00 247.00 274.50
1769 48.00 NA 43.20
1660 16.45 16.45 14.80
The $AGGREGATE_FORCEORDER property specifies the same behavior as that specified by the FORCEORDER keyword in an AGGREGATE command or an AGGREGATE function. By adding an $AGGREGATE_FORCEORDER property to a variable you can ensure this behavior when the variable is aggregated — even when it is aggregated by an AGGREGATE statement does not include the FORCEORDER keyword.
The behavior specified by both the $AGGREGATE_ORDER property and the FORCEORDER keyword is that the calculations must be performed in the order in which the RELATION (for aggregation) statements are listed in the aggmap used for the aggregation. Typically, you want this behavior when some values calculated through aggregation have changed because, otherwise, the optimization methods used by AGGREGATE may cause the modified values to be ignored. (Note, however, that forcing the order of execution can slow performance.)
Syntax
You add or delete an $AGGREGATE_FORCEORDER property to the most recently defined or considered object (see DEFINE and CONSIDER commands) by issuing a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$AGGREGATE_FORCEORDER'
To delete the property, issue the following statement.
PROPERTY DELETE '$AGGREGATE_FORCEORDER'
The MODOVERFLOW option is used in testing whether any equation in a simultaneous block of a model has diverged. MODOVERFLOW determines how dissimilar the results of an equation must be in successive iterations for the equation to be considered to have diverged.
|
See: "Model Options" for a list of all of the options that control the solution of simultaneous blocks. |
Data Type
INTEGER
Syntax
MODOVERFLOW = {n|3}
Parameters
An INTEGER value to use in testing for divergence. As Oracle OLAP calculates each equation in a simultaneous block, it constructs a comparison value that is based on the results of the equation for the current iteration and the previous iteration. When the comparison value meets a divergence test, the equation is considered to have diverged.
The comparison value that is tested is as follows.
(thisResult - prevResult) / (prevResult + MODGAMMA)
where thisResult is the result of this iteration and prevResult is the result of the previous iteration
In the preceding calculation, MODGAMMA is an INTEGER option that controls the degree to which the comparison value represents the absolute amount of change between iterations versus the proportional change. The default value of MODGAMMA is 1.
In the divergence test, Oracle OLAP tests whether the comparison value is greater than 10 to the power of MODOVERFLOW. The calculation for this test is as follows.
Comparison value > 10**MODOVERFLOW
For the equation to be considered to have diverged, the comparison value must meet the test described earlier. The default value of MODOVERFLOW is 3. With this default, the comparison value meets the test when it is greater than 1000.
Usage Notes
Equation Divergence
When an equation diverges, an error occurs. The MODERROR option controls the action that Oracle OLAP takes when an error occurs.
Faster Divergence During Development
While you are developing a model, you can sometimes save time by using a small value for MODOVERFLOW. When Oracle OLAP is performing many iterations over a particular simultaneous block, a smaller value of MODOVERFLOW can cause rapid divergence of that block. When you set the MODOVERFLOW option to CONTINUE, execution of the model continues when the divergence occurs, and you can concentrate on debugging the other blocks in the model. After you have debugged the model, you can use a larger value for MODOVERFLOW.
Examples
Example 5-58 Using the Default MODOVERFLOW Value
The following statements specify a trace for a model called income.est, limit a dimension, and run the model.
MODTRACE = YES LIMIT division TO 'Camping' income.est budget
These statements produce the following output.
(MOD= INCOME.EST) BLOCK 1: SIMULTANEOUS (MOD= INCOME.EST) ITERATION 1: EVALUATION (MOD= INCOME.EST) selling = marketing * 3 (MOD= INCOME.EST) BUDGET (LINE SELLING MONTH 'JAN97' ITER 1) = 3 ... (MOD= INCOME.EST) BUDGET (LINE SELLING MONTH 'JAN97' ITER 2) = -997 ... (MOD= INCOME.EST) BUDGET (LINE SELLING MONTH 'JAN97' ITER 3) = 6.00902708124 ... (MOD= INCOME.EST) BUDGET (LINE SELLING MONTH 'JAN97' ITER 49) = 34.2715693388 ... (MOD= INCOME.EST) BUDGET (LINE SELLING MONTH 'JAN97' ITER 50) = -7.22300601861
In the trace, you can see the results that were calculated for the Selling line item in the first three iterations and the forty-ninth and fiftieth iterations over a block of simultaneous equations. The block failed to converge after 50 iterations.
The value of MODOVERFLOW is its default value of 3. Consequently, for an equation to meet the divergence test, its comparison value must be greater than 1000.
Example 5-59 Speeding Up the Divergence
The following statements change the MODOVERFLOW setting and run the income.est model.
MODOVERFLOW = 2 income.est budget
With MODOVERFLOW set to 2, any comparison value of more than 100 meets the test for divergence. In this example, the equation for Selling meets the test in the second iteration. In the second iteration, Oracle OLAP calculates the comparison value for Selling as follows.
(-997 - 3) / (3 + 1) = 250
Since this comparison value is greater than 100, the equation for Selling diverges in the second iteration.
The MAKEDATE function returns the DATE value that corresponds to specified INTEGER values for a year, month, and day.
Return Value
DATE or text
Syntax
MAKEDATE(year month day)
Parameters
An INTEGER expression that represents the year of the test date. For any year, you can specify the year as a four-digit number in the range 1000 to 9999. For years in the range 1950 to 2049 (the default) or some other range (as set through the YRABSTART option), you have the alternative of specifying a two-digit number that represents the last two digits of the year (96 represents 1996, for example).
Any INTEGER expression, normally in the range 1 to 12. When you specify an INTEGER less than 1 or greater than 12, MAKEDATE returns a date in a year before or after the year specified by the INTEGER expression for year.
For example, if the arguments to MAKEDATE are (97 14 21), MAKEDATE returns the date February 21, 1998 since, in effect, February 1998 is the fourteenth month of 1997.
An INTEGER expression in the range 1 to 31.
Usage Notes
Format of the Result Returned by MAKEDATE
When you display the result returned by MAKEDATE, the date is formatted according to the date template in the DATEFORMAT option. When the day of the week or the name of the month is used in the date template, the day names specified in the DAYNAMES option and the month names specified in the MONTHNAMES option are used. You can use the result returned by MAKEDATE anywhere that a DATE value is expected.
Invalid Dates
When the arguments to MAKEDATE do not represent a valid date between January 1, 1000, and December 31, 9999, MAKEDATE returns an NA value.
Examples
Example 8-19 Converting Integers to a Date
The following statements specify the date format and send the output to the current outfile.
DATEFORMAT = '<mtextl> <d>, <yyyy>' SHOW MAKEDATE(97 11 14)
These statements produce the following output.
November 14, 1997
Example 8-20 Calculating a Date Using YYOR, MMOF, and DDOF Functions
The following statement calculates the date one year from today, and sends the output to the current outfile. The TODAY function returns today's date. The INTEGER functions YYOF, MMOF, and DDOF return the INTEGER values that correspond to the year, month, and day of today's date.
SHOW MAKEDATE(YYOF(TODAY) + 1 MMOF(TODAY) DDOF(TODAY))
When today's date is January 15, 1995, this statement produces the following output.
January 15, 1996
The NPV function computes the net present value of a series of cash flow values.
Return Value
DECIMAL
The result returned by the NPV function is dimensioned by all the dimensions of cashflows except its time dimension. When cashflows is dimensioned only by the time dimension, NPV returns a single value.
Syntax
NPV(cashflows, discount-rate, [time-dimension])
Parameters
A numeric expression that is dimensioned by time-dimension and specifies the series of cash flow values.
|
Note: All cash flows are assumed to occur at the beginning of the time period with which they are associated. The cash flows are discounted back to the beginning of the earliest time period that appears in the current status of the time dimension. NPV ignores cash flows that corresponds to out-of-status dimension positions. |
A numeric expression that specifies the interest rate for each period to be used to discount the cash flow values. It can either be a single value or an array of values with one or more non-time dimensions. Express the discount rate as a decimal quantity; for example, 8.25 percent as .0825.
NPV accepts any positive discount rate, and it also accepts a negative discount rate when the rate is greater than minus one (that is, rate > -1). When you supply a negative rate, you must precede it with a comma.
A name that specifies the time dimension. When cashflows has a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, NPV automatically uses that dimension, and you can omit the time-dimension argument.
Usage Notes
NA Discount Rate
When the discount rate used to compute a result value equals NA, then that result value is NA.
Cash Flow Timing
Different assumptions about the intra-period timing of the cash flows, or the base time point for the present value calculations, can be accommodated by multiplying the result of the NPV function by the following quantity: one plus the discount rate, raised to an appropriate positive or negative power.
Examples
Example 8-40 Computing the Net Present Value
The following statements create a dimension called project, add values to it, and create a variable called cflow, which is dimensioned by year and project.
DEFINE project DIMENSION TEXT MAINTAIN project ADD 'a' 'b' 'c' 'd' 'e' DEFINE cflow VARIABLE DECIMAL <project year>
When you assign the following values to CFLOW,
------------------------CFLOW----------------------
-----------------------PROJECT---------------------
YEAR a b c d e
------------ ---------- ---------- ---------- ---------- -------
Yr95 -200.00 -200.00 -300.00 -100.00 -200.00
Yr96 100.00 150.00 200.00 25.00 25.00
Yr97 100.00 400.00 200.00 100.00 200.00
then the following statement
REPORT NPV(cflow, .08, year)
uses a discount rate of 8 percent to create the following report of the net present value of the cflow data.
NPV(CFLOW,
PROJECT .08, YEAR)
-------------- ----------
a -21.67
b 281.82
c 56.65
d 8.88
e -5.38
The REMCOLS function removes specified columns from every line of a multiline TEXT value. The function returns a multiline text value that includes only the remaining columns.
Columns refer to the character positions in each line of a multiline TEXT value. The first character in each line is in column one, the second is in column two, and so on.
Return Value
TEXT or NTEXT
REMCOLS always returns a TEXT value that has the same number of lines as text-expression, though some lines may be empty.
Syntax
REMCOLS(text-expression start [length])
Parameters
The text expression from which the specified columns should be removed. When text-expression is a multiline TEXT value, the characters in the specified columns are removed from each one of its lines.
When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
An INTEGER, between 1 and 4,000, representing the column position at which to begin removing columns. The column position of the first character in each line of text-expression is 1. When you specify a starting column that is to the right of the last character in a given line in text expression, the corresponding line in the return value is identical to the given line.
An INTEGER representing the number of columns to be removed. When you do not specify length, REMCOLS removes only the starting column. When you specify a length that exceeds the number of characters that follow the starting position in a given line in text expression, the corresponding line in the return value includes only the characters that precede the starting column.
Examples
Example 8-74 Removing Text Columns
In the following example, four columns are removed from each line of CITYLIST, starting from the second column.
DEFINE citylist VARIABLE TEXT CITYLIST = 'Boston\nHouston\nChicago\nDenver'
The statement
SHOW citylist
produces the following output.
Boston Houston Chicago Denver
The statement
SHOW REMCOLS(citylist 2 4)
produces the following output.
Bn Hon Cgo Dr
The LEAST function returns the smallest expression in a list of expressions. All expressions after the first are implicitly converted to the data type of the first expression before the comparison.
To retrieve the largest expression in a list of expressions, use GREATEST.
Return Value
The data type of the first expression.
Syntax
LEAST (expr [, expr]...)
Parameters
An expression.
Examples
The $NATRIGGER property specifies values for Oracle OLAP to substitute for NA values that are in a dimensioned variable, but not in the session cache for the variable (if any). To calculate the values, Oracle OLAP takes the steps described in "How Oracle OLAP Calculates Data for a Variable with NA Values". The results of the calculation are either stored in the variable or cached in the session cache for the variable as described in "How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER".
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Note: When you want to trigger the aggregation of a variable, you can use the $AGGMAP property rather than the $NATRIGGER property. |
Syntax
You add or delete a $NATRIGGER property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$NATRIGGER' value
To delete the property, issue the following statement.
PROPERTY DELETE '$NATRIGGER'
Parameters
A TEXT expression that is the value of the property. The text can be any expression that is valid for defining a formula
Usage Notes
How Oracle OLAP Calculates Data for a Variable with NA Values
When calculating the data for a dimensioned variable, Oracle OLAP takes the following steps for each cell in the variable:
Is there is a session cache for the variable.
Yes. Go to step 2.
No. Go to step 3.
Does that cell in the session cache for the variable have an NA value.
Yes. Go to step 3.
No. Go to step 7.
Does that cell in variable storage have an NA value.
Yes. Go to step 4.
No. Go to step 7.
Does the variable have an $AGGMAP property?
Yes. Aggregate the variable using the aggmap specified for the $AGGMAP property and, then, go to step 5.
No. Go to step 6.
What is the value of the cell after aggregating the variable?
NA, go to step 6.
Non-NA, go to step 7.
Does the variable have a $NATRIGGER property?
Yes. Execute the expression specified for the $NATRIGGER property and, then, go to step 7.
No. Go to step 7.
Calculate the data.
Apply the NAFILL function or the NASKIP, NASKIP2, or NASPELL options, as appropriate.
Making NA Triggers Recursive or Mutually Recursive
You can make NA triggers recursive or mutually recursive by including triggered objects within the value expression. You must set the RECURSIVE option to YES before a formula, program, or other $NATRIGGER expression can invoke a trigger expression again while it is executing. For limiting the number of triggers that can execute simultaneously, see the TRIGGERMAXDEPTH option.
Using $NATRIGGER with Composites
You can set an $NATRIGGER expression on a variable that is dimensioned by a composite, but Oracle OLAP evaluates the $NATRIGGER expression only for the dimension-value combinations that exist in the composite.
$NATRIGGER Ignored by EXPORT and AGGREGATE
The AGGREGATE command and the AGGREGATE function ignore the $NATRIGGER property setting for a variable during an aggregation operation. The statements fetch the stored value only, and do not invoke the $NATRIGGER expression. The $NATRIGGER property remains in effect for other operations.
In executing an EXPORT (EIF) statement, Oracle OLAP does not evaluate the $NATRIGGER property expression on a variable when it simply exports the variable. However, Oracle OLAP does evaluate the $NATRIGGER property expression when the variable is part of an expression that Oracle OLAP calculates during the export operation.
Examples
Example 4-11 Adding an $NATRIGGER Property to a Variable
The following statements define a dimension with three values and define a variable that is dimensioned by the dimension. They add the $NATRIGGER property to the variable, then put a value in one cell of the variable and leave the other cells empty so their values are NA. Finally, they report the values in the cells of the variable.
DEFINE d1 INTEGER DIMENSION MAINTAIN d1 ADD 3 DEFINE v1 DECIMAL <d1> PROPERTY '$NATRIGGER' '500.0' v1(d1 1) = 333.3 REPORT v1
The preceding statements produce the following output.
D1 V1
--------- ----------
1 333.3
2 500.0
3 500.0
The MOVE command moves an object name to a new position in the NAME dimension of an analytic workspace. The reorganizing effect of the MOVE command on the workspace is cosmetic. That is, no physical changes take place in workspace storage. Users often reorganize workspace objects so the output from DESCRIBE is easier to read.
Syntax
MOVE name... {FIRST|LAST|{BEFORE|AFTER} name2} [AW workspace]
Parameters
The names of one or more objects to move. You can specify the names individually, or use one of the following forms to specify a group of names:
You can specify a qualified object name to indicate the attached workspace in which the object resides. As an alternative, you can use the AW argument to specify the workspace. Do not use both.
When you do not use a qualified object name or the AW argument to specify an analytic workspace, Oracle OLAP looks for the object in the current workspace.
The logical position in the NAME dimension to which Oracle OLAP moves the objects specified by the name argument. Specifying FIRST moves the objects to the beginning of the NAME dimension. Specifying LAST (the default) moves the names to the end of the NAME dimension.
The position before or after a particular object (name2) to which Oracle OLAP moves the objects specified by the name argument.
The name of an attached workspace in which you want to move the object. When you do not use a qualified object name or the AW argument to specify an analytic workspace, objects are moved in the current workspace.
Usage Notes
Alphabetizing Your Objects
You can arrange your workspace objects alphabetically with the following statements, which work on the NAME dimension.
SORT NAME A NAME MOVE CHARLIST(NAME) FIRST
Examples
Example 10-67 Moving a Relation
This example shows how to move the relation desc.product after product. The OLAP DML statement
SHOW CHARLIST(NAME)
produces the following list (annotation has been added).
product <--- Position of product district division line region marketlevel market month year quarter desc.product <--- Old position of desc.product region.district division.product ...
The following statements
MOVE desc.product AFTER product SHOW CHARLIST(NAME)
change the workspace order and produce the following list (annotation has been added).
product <--- Position of product desc.product <--- New position of desc.product district division line region marketlevel market month year quarter region.district division.product ...
The LAGDIF function returns the difference between the value of a dimensioned variable or expression at a specified offset of a dimension before the current value of that dimension and the current value of the dimensioned variable or expression.
Return Value
DECIMAL or NA when you try to lag before the first period of a time dimension.
Syntax
LAGDIF(variable, n, dimension, [STATUS|NOSTATUS|limit-clause] )
Parameters
A variable or expression that is dimensioned by dimension.
The offset (that is, the number of dimension values) to lag. LAGDIF uses this value to determine the number of values that LAGDIF should go back in dimension to retrieve the value of variable. Typically, n is a positive INTEGER that indicates the number of time periods (or dimension values) before the current one. When you specify a negative value for n, it indicates the number of time periods after the current one. In this case, LAGDIF compares the current value of the time series with a subsequent value.
The dimension along which the lag occurs. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR.
When variable has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want LAGDIF to use that dimension, you can omit the dimension argument.
Specifies that LAGDIF should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the lag.
(Default) Specifies that LAGDIF should use the default status (that is, a list all the dimension values in their original order) when computing the lag.
Specifies that LAGDIF should use the default status limited by limit-clause when computing the lag.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
To specify that LAG should use the current status limited by limit-clause when computing the lag, specify a LIMIT function for limit-clause.
Examples
For an example of using LAGDIF, see Example 8-2, "Using LAGDIF and LAGABSPCT".
The INF_STOP_ON_ERROR option specifies the behavior of Oracle OLAP when an error occurs during the execution of an INFILE statement.
Syntax
INF_STOP_ON_ERROR = {YES|NO}
Parameters
When an error occurs, report the error and stop reading from the file.
When an error occurs, report the error and continue reading from the file.
Examples
Example 5-37 Using INF_STOP_ON_ERROR with DBMS_EXECUTE
Assume that you have an file named attachmyaw.inf that includes the following OLAP DML statement that detaches an analytic workspace named myaw
AW DETACH myaw
Assume that the myaw workspace is not attached when a SQL application issues the DBMS_AW.EXECUTE statement with an OLAP DML INFILE statement to read the attachmyaw.infinfile file.
When the INF_STOP_ON_ERR option is set to NO then the error Analytic workspace MYAW is not attached is reported, Oracle OLAP continues to read the file, and the DBMS_AW.EXECUTE procedure completes successfully.
DBMS_AW.EXECUTE('INF_STOP_ON_ERR = NO ');
DBMS_AW.EXECUTE('INFILE attachmyaw.inf');
The current directory is MYDIR.
ERROR: (ORA-34344) Analytic workspace MYAW is not attached.
ERROR: (ORA-34344) Analytic workspace MYAW is not attached.
PL/SQL procedure successfully completed.
When the INF_STOP_ON_ERR option is set to YES then the error Analytic workspace MYAW is not attached is reported, Oracle OLAP stops reading the file, and the DBMS_AW.EXECUTE procedure aborts.
DBMS_AW.EXECUTE('INF_STOP_ON_ERR = YES ');
DBMS_AW.EXECUTE('INFILE attachmyaw.inf');
The current directory is MYSPL.
DECLARE
*
ERROR at line 1:
ORA-35166: (ORA-34344) Analytic workspace MYAW is not attached.
ORA-06512: at "SYS.DBMS_AW", line 27
ORA-06512: at "SYS.DBMS_AW", line 115
ORA-06512: at line 8
The TRIM function enables you to trim leading or trailing characters (or both) from a character string.
You can also trim leading characters using LTRIM and trailing characters using RTRIM.
Return Value
The data type of the string you are trimming (that is, trim-source).
Syntax
TRIM ([{{LEADING|TRAILING|BOTH} [trim_characters])|trim_character} FROM] trim_source)
Parameters
An expression that specifies the character values to be trimmed. This text expression can be any of the text data types.
When you specify multiple characters in trim-characters, the function searches for each character in trim_source, in turn, removing characters from trim_source until it encounters a character in trim_source that is not in trim-characters.
When you do not specify a value, then the default value is a blank space and the function removes leading and trailing blank spaces.
Specifies that the function removes any leading characters from trim_source that are equal to trim_characters.
Specifies that the function removes any trailing characters from trim_source that are equal to trim_characters.
Specifies that the function removes leading and trailing characters from trim_source that are equal to trim_characters.
An expression that is the string value to be trimmed. This text expression can be any of the text data types.
The SQLMESSAGES option controls whether error messages are sent to the current output file.
Data Type
BOOLEAN
Syntax
SQLMESSAGES = {YES|NO}
Parameters
Error messages are sent to the current output file.
(Default) Error messages are only stored as values of SQLERRM.
Usage Notes
Typical Usage
You want to set SQLMESSAGES to YES while you are developing an application so that you can diagnose errors quickly. When your application is in use, you probably want it to capture and handle errors in a different manner with SQLMESSAGES set to NO.
The STATALL function indicates whether default status is currently in effect for a given dimension. That is, STATALL returns YES when STATLIST would return ALL. Otherwise, STATALL returns NO.
Return Value
BOOLEAN
Syntax
STATALL(dimension)
Parameters
A text expression whose value is the name of a dimension or dimension surrogate.
Usage Notes
STATALL Compared to STATLIST
STATALL provides an alternative to running the STATLIST program to determine if the status of a specified dimension is ALL.
Examples
(Read-only) The DSECONDS option returns the elapsed time as a DECIMAL value. When Oracle is installed on UNIX, the DSECONDS option is the elapsed number of seconds since Oracle was started. When Oracle is installed on Windows, the DSECONDS option is the elapsed number of seconds since the computer on which Oracle is installed was rebooted. As an aid to enhancing a program's speed, DSECONDS can be used to determine how much time elapses while the program is running.
Data Type
DECIMAL
Syntax
DSECONDS
Examples
Example 5-25 Timing a Program Using DSECONDS
The following program puts the value of DSECONDS at the start of the program in a variable called t1 and then displays the difference between t1 and the value of DSECONDS after the program executes.
DEFINE prodsummary PROGRAM PROGRAM VARIABLE t1 DECIMAL t1 = dseconds LIMIT product TO ALL BLANK FOR product DO ROW WIDTH 16 name.product ACROSS month Jun96: DECIMAL 0 LSET - '$'WIDTH 18 <RSET ' (Actual)' sales rset ' (Plan)' sales.plan> DOEND BLANK ROW WIDTH 35 LSET 'The program took ' rset ' seconds.' - (dseconds - t1) END
Running this program produces the following results.
3-Person Tents $95,121 (actual) $80,138 (plan)
Aluminum Canoes $157,762 (actual) $132,931 (plan)
Tennis Racquets $97,174 (actual) $84,758 (plan)
Warm-up Suits $79,630 (actual) $73,569 (plan)
Running Shoes $153,688 (actual) $109,219 (plan)
The program took .20 seconds.
The ALLOCATE command calculates lower-level data from upper-level data by allocating variable data down a hierarchical dimension. Frequently you allocate data for budgeting, forecasting, and profitability analysis.
Syntax
ALLOCATE source [SOURCE conjoint] [BASIS basisname [ACROSS dimname]] - [TARGET targetname [TARGETLOG targetlogname]] - [USING aggmap] [ERRORLOG errorlogfileunit]
Parameters
A variable or formula that provides the values to allocate. When the source object is a formula, you must also specify a variable with the TARGET keyword. When you specify a variable as source and you do not specify a target variable or a basisname variable, then ALLOCATE uses source as the basis and the target.
Specifies a conjoint dimension that contains a list of cells the user has changed. The ALLOCATE command uses this list to produce the smallest target status needed to allocate all of the changed source cells.
Specifies a variable, relation, or formula that provides the data on which the allocation is based. That data determines which cells of the target receive allocated values and, in an even or proportional operation, the amount of the source allocated to a target cell.
When the OPERATOR specified by a RELATION (for allocation) statement in aggmap is a COPY operator (COPY, MIN, MAX, FIRST, LAST), the basis tells the ALLOCATE command which target cells to update. When the OPERATOR specified is EVEN, then ALLOCATE derives the counts that it uses for allocation from the basis. When the OPERATOR specified is the PROPORTIONAL, then ALLOCATE uses the basis data to determine the amount to allocate to each target cell. When the OPERATOR is HCOPY, HFIRST, HLAST, or HEVEN, then ALLOCATE does not use a BASIS object. Instead, it allocates the source data to all of the target cells in the dimension hierarchy that is specified by the relation named in the RELATION statement.
When you specify the same variable as both the basis and the target, the current values of the target cells determine the allocation. When you do not specify a basis, then the ALLOCATE command uses the source as the basis.
Specifies a dimension, which can be a named composite, that the ALLOCATE command loops over to discover the cells in a basis. Because a basis can be a formula, you can realize a significant performance advantage by supplying a looping dimension that eliminates the sparsity from the basis loop.
Specifies a variable to hold the allocated values. When the source object is a formula, then you must specify a target. When the source object is a variable and you do not specify a target, then ALLOCATE uses the source variable as the target.
Specifies a variable (identically dimensioned to the targetname variable), or a relation that specifies such a variable, to which ALLOCATE assigns a copy of the allocation. For instance, when ALLOCATE assigns the value of 100 to the cell of the costs variable that is specified by the time and product dimension values Jan01 and TV, and the targetlog relation specifies the cell of the costacct variable that is specified by the same dimension values, then ALLOCATE assigns the value of 100 to the specified costacct cell, also.
Specifies the name of a previously-defined aggmap to use for the allocation. When you do not include this phrase, the command uses the default allocation specification for the variable as previously specified using the $ALLOCMAP property.
Specifies a file unit that ALLOCATE uses for logging allocation deadlocks, errors, or other information. When the allocation does not generate any deadlocks or errors, ALLOCATE sets errorlogname to NA. When the allocation produces one or more deadlocks or errors, the events are sent to the specified file. ALLOCATE writes one line in the file for each allocation source that remains unallocated.
When you do not specify a file unit with ERRORLOG, ALLOCATE sends the information to the standard output device.
Usage Notes
Preserving Original Basis Values
Often the source, basis, and target objects are the same variable and therefore the original values in the cells of the target variable determine the proportions of the allocation. The allocation overwrites those original values in the target cells with the allocated values. To preserve original values in a variable, specify the original variable as the basis object and save the allocated values to a new variable as the target object. Using different basis and target objects makes it possible for you to preview the allocated data. When you then want to store the allocated values in the same variable as the basis, you can perform the allocation again with the same object as the basis and the target. Another example of using different basis and target objects is using an actuals variable as the basis of the allocation and a budget variable as the target.
Using a Formula as a Source or Basis
Source and basis objects can be formulas, which makes it possible for you to make complex computations and have the results be the source or basis object. For example, when you want to see the sales of individual products that would be necessary to produce a thirty percent increase in sales for the next year, you could express the increase in the following formula.
DEFINE actualsWanted DECIMAL FORMULA <time, product> EQ LAG(actuals, 1, time) * 1.3
You would then use ACTUALSWANTED as the source object with the ALLOCATE command. In this example, you would use the ACTUALS variable as the basis.
Tracking Multiple Allocations
When you specify a variable with the TARGETLOG argument, you can store an allocated value in that variable and in the target variable. This double entry allocation makes it possible for you to track multiple allocations to the same target cell. For example, when you allocate a series of different costs to the same costs centers, then each allocation increases the values in the target cells. You can keep track of the individual allocations by specifying a different targetlogname variable for each allocation.
Logging Allocation Errors
When you specify a file with the ERRORLOG argument, you can record errors that result from locks and NA basis values. The log can provide feedback to an application about which source values remain unallocated. You can use the information to modify the allocation, for example by using a hierarchical operator such as HEVEN in a RELATION statement in the aggmap. You can use the ALLOCERRLOGHEADER and ALLOCERRLOGFORMAT options to format the error log. Within an allocation specification, you can specify other aspects of the error log using the ERRORLOG and ERRORMASK statements.
Logging the Progress of an Allocation
When you specify a file with the POUTFILEUNIT option, then you can record and monitor the progress of an allocation. You can use the file to get feedback during a lengthy allocation and to gain information that might be useful for optimizing the allocation in the future.
Examples
Example 9-34 Direct Even Allocation
This example allocates a value specified at one level of the time dimension hierarchy directly to the variable target cells that are specified by lower level values in the hierarchy without allocating values to an intermediate level. The timemonthyear relation specifies the hierarchical relationship of the time values. The source, basis, and target of the allocation are all the same variable, PROJBUDGET, which is dimensioned by division, time, and line. The time dimension is a nonunique concat dimension that has as its base dimensions year, quarter, and month. The time dimension is limited to <year: Yr02>, <quarter: Q1.02>, <quarter: q1.02>, and <month: Jan02> to <month: Jun02>. The following statements define the projbudget variable, set the value of a cell in to 6000 and then report the variable.
DEFINE projbudget VARIABLE DECIMAL <division time line> projbudget(division 'CAMPING' time '<YEAR: YR02>' line 'MARKETING') = 6000 REPORT projbudget
The preceding statement produces the following results.
LINE: MARKETING
-PROJBUDGET--
--DIVISION---
TIME CAMPING
---------------- -------------
<year: Yr02> 6,000.00
<quarter: Q1.02> NA
<quarter: Q2.02> NA
<month: Jan02> NA
<month: Feb02> NA
<month: Mar02> NA
<month: Apr02> NA
<month: May02> NA
<month: Jun02> NA
The following statements define a self-relation on the time dimension, relate the month values directly to the year values, and report the values of the relation.
DEFINE timemonthyear RELATION time <time> LIMIT month TO 'JAN02' TO 'JUN02' timemonthyear(time month) = '<YEAR: YR02>' REPORT timemonthyear
The preceding statement produces the following results.
TIME TIMEMONTHYEAR ---------------- ------------- <year: Yr02> NA <quarter: Q1.02> NA <quarter: Q2.02> NA <month: Jan02> <year: Yr02> <month: Feb02> <year: Yr02> <month: Mar02> <year: Yr02> <month: Apr02> <year: Yr02> <month: May02> <year: Yr02> <month: Jun02> <year: Yr02>
The following statements define an aggmap and enter statements into the allocation specification. They allocate the value that is specified by <year: Yr02> from projbudget to the cells of the same variable that are specified by the month dimension values, and then report projbudget. The target cells of the variable have NA values so the RELATION statement in the allocation specification specifies the HEVEN operator. The ALLOCATE command specifies only one variable, projbudget, so that variable is the source and target of the allocation. No basis object is required because the allocation is an HEVEN operation. The allocation is directly from the year source value to the month target values because that is the hierarchy specified by the relation in the allocation specification.
DEFINE projbudgmap AGGMAP ALLOCMAP RELATION timemonthyear OPERATOR HEVEN END ALLOCATE projbudget USING projbudgmap REPORT projbudget
The preceding statement produces the following results.
LINE: MARKETING
-PROJBUDGET--
--DIVISION---
TIME CAMPING
---------------- -------------
<YEAR: YR02> 6,000.00
<QUARTER: Q1.02> NA
<QUARTER: Q2.02> NA
<MONTH: JAN02> 1,000.00
...
<MONTH: JUN02> 1,000.00
Example 9-35 Recursive Even Allocation with a Lock
This example allocates a value specified at one level of the time dimension hierarchy first to the target cells at an intermediate level in a variable and then to the cells that are specified by the lowest level values in the hierarchy. The timeparent relation specifies the hierarchical relationship of the time values. The source, basis, and target of the allocation are projbudget. The status of the division, time, and line dimensions are the same as the direct allocation example. At the beginning of this example, the projbudget variable again has just the single value, 6000, in the cell specified by <year: Yr02>.
DEFINE timeparent RELATION time <time> LIMIT quarter TO 'Q1.02' 'Q2.02' timeparent(time quarter) = '<YEAR: YR02>' LIMIT month TO 'JAN02' TO 'MAR02' timeparent(time month) = '<QUARTER: Q1.02>' LIMIT month TO 'APR02' TO 'JUN02' timeparent(time month) = '<QUARTER: Q1.02>' REPORT timeparent
The preceding statement produces the following results.
TIME TIMEPARENT ---------------- ------------- <year: Yr02> NA <quarter: Q1.02> <year: Yr02> <quarter: Q2.02> <year: Yr02> <month: Jan02> <quarter: Q1.02> <month: Feb02> <quarter: Q1.02> <month: Mar02> <quarter: Q1.02> <month: Apr02> <quarter: Q2.02> <month: May02> <quarter: Q2.02> <month: Jun02> <quarter: Q2.02>
This example demonstrates locking a cell so that it does not participate in the allocation. Locking a cell requires a valueset, so the following statements define one, limit the time dimension to the desired value, assign a value to the valueset, and then reset the status of the time dimension.
DEFINE timeval TO '<QUARTER: Q2.02>' LIMIT time TO '<Year: YR02>' '<Quarter: Q1.02>' '<Quarter: Q2.02>' - '<month: Jan02>' '<month: Feb02>' '<month: Mar02>' - '<month: Apr02>' '<month: May02>' '<month: Jun02>
The following statements revise the specification of the aggmap named projbudgmap. This time the RELATION statement in the allocation specification specifies the timeparent relation, the HEVEN operator, and the PROTECT argument. The READWRITE keyword specifies that the children of the locked cell also do not participate in the allocation. The NONORMALIZE keyword specifies that the value of the locked cell is not subtracted from the source value before it is allocated to the target cells. The statements then allocate the source value and report the results.
CONSIDER projbudgmap ALLOCMAP RELATION timeparent OPERATOR HEVEN ARGS PROTECT NONORMALIZE READWRITE timeval END ALLOCATE projbudget USING projbudgmap REPORT projbudget
The preceding statement produces the following results.
LINE: MARKETING
-PROJBUDGET--
--DIVISION---
TIME CAMPING
---------------- -------------
<year: Yr02> 6,000.00
<quarter: Q1.02> 6,000.00
<quarter: Q2.02> NA
<month: Jan02> 2,000.00
<month: Feb02> 2,000.00
<month: Mar02> 2,000.00
<month: Apr02> NA
<month: May02> NA
<month: Jun02> NA
Example 9-36 Recursive Proportional Allocation
This example uses the same relation as the recursive even allocation but it uses the PROPORTIONAL operator and it does not lock any cells. Because a proportional allocation uses the values of the basis object to calculate the values to assign to the target cells, the projbudget variable has values assigned to each of its cells. The value of the <year: Yr02> cell is 6000., which was assigned to that cell. It is not the value an aggregation of the lower levels. A report of projbudget before the allocation produces the following results.
LINE: MARKETING
-PROJBUDGET--
--DIVISION---
TIME CAMPING
---------------- -------------
<year: Yr02> 6,000.00
<quarter: Q1.02> 1,000.00
<quarter: Q2.02> 2,000.00
<month: Jan02> 300.00
<month: Feb02> 100.00
<month: Mar02> 600.00
<month: Apr02> 400.00
<month: May02> 800.00
<month: Jun02> 800.00
The following statements replace the previous specification of the aggmap with the new RELATION statement, which specifies the PROPORTIONAL operator. The allocation specification includes a SOURCEVAL ZERO statement, which specifies that the source value is replace with a zero value after the allocation (see the SOURCEVAL statement of the ALLOCMAP command for more information). The statements then allocate the source value and report the result.
CONSIDER projbudgmap
ALLOCMAP JOINLINES('RELATION timeparent OPERATOR PROPORTIONAL timeval' -
'SOURCEVAL ZERO' -
'END')
ALLOCATE projbudget USING projbudgmap
REPORT projbudget
The preceding statement produces the following results.
TIME TIMEPARENT
LINE: MARKETING
-PROJBUDGET--
--DIVISION---
TIME CAMPING
---------------- -------------
<year: Yr02> 0
<quarter: Q1.02> 2,000.00
<quarter: Q2.02> 4,000.00
<month: Jan02> 600.00
<month: Feb02> 200.00
<month: Mar02> 1,200.00
<month: Apr02> 800.00
<month: May02> 1,600.00
<month: Jun02> 1,600.00
The FROM_TZ function converts a timestamp value and a time zone to a TIMESTAMP_TZ value.
Return Values
TIMESTAMP_TZ
Syntax
FROM_TZ (timestamp_value , time_zone_value)
Parameters
A text expression with a TIMESTAMP data type.
A text expression that returns a string in the format TZH:TZM or in TZR with optional TZD format.
Examples
Example 7-102 Creating a TIMESTAMP_TZ Value from a Timestamp Value and a Time Zone
DEFINE mytimestamp VARIABLE TIMESTAMP DEFINE mytimezone VARIABLE TEXT DEFINE mytimestamptz VARIABLE TIMESTAMP_TZ mytimestamp = '26-MAR-06' mytimezone = '-04:00' mytimestamptz = FROM_TZ (mytimestamp mytimezone) REPORT mytimestamptz MYTIMESTAMPTZ ------------------------------ 26-MAR-06 12.00.00 AM -04:00
The MODEL.XEQRPT program produces a report about the execution of the model. The report specifies the block where the solution failed and shows the values of the model options that were used in solving simultaneous blocks.
Syntax
MODEL.XEQRPT
Usage Notes
Running MODEL.XEQRPT
Before you can run the MODEL.XEQRPT program, you must
Set the MODERROR option to STOP or CONTINUE.
Execute the model.
When the model halts because of an error, run the MODEL.XEQRPT program.
Effect of MODERROR on MODEL.XEQRPT
The results returned by MODEL.XEQRPT vary depending on the setting of the MODERROR option:
When MODERROR is set to STOP and execution of the model halts because of an error, you can run the MODEL.XEQRPT program to produce a report about the execution of the model. The report specifies the block where the solution failed and shows the values of the model options that were used in solving simultaneous blocks.
When MODERROR is set to CONTINUE and one block in the model is a simultaneous block that either diverges or fails to converge, Oracle OLAP executes any remaining blocks in the model.
Moreover, Oracle OLAP executes the model for the remaining values in the status of any additional dimensions of the solution variable that are not dimensions of the model. In this case, when you run the MODEL.XEQRPT program when Oracle OLAP finishes executing the model, a report on the solution for the final values of the additional dimensions is produced.
When the simultaneous blocks in the model converged when the model was executed for the final values of the additional dimensions, then MODEL.XEQRPT reports that the blocks were solved, even though an earlier execution of the model for another dimension value might have failed. When you want to see the MODEL.XEQRPT for the dimension values where the failure occurred, you can set MODERROR to STOP and rerun the model.
Examples
Example 10-65 Producing an Execution Report for the income.est Model
After running the income.est model, you can use the MODEL.XEQRPT program to produce a report on the execution of the model.
The following statement runs the MODEL.XEQRPT program, which produces an execution report for the model.
MODEL.XEQRPT income.est
The execution report contains the following output.
MODEL INCOME.EST <LINE MONTH> Solution status: SOLVED Model options in use: MODSIMULTYPE: AITKENS MODMAXITERS: 50 MODTOLERANCE: 3 MODOVERFLOW: 3 MODGAMMA: 1 BLOCK 1 (STEP-FORWARD <MONTH>) Solution status: SOLVED BLOCK 2 (SIMULTANEOUS) Solution status: SOLVED Iterations: 15
The report shows the values of the model options that were used in solving the simultaneous blocks and indicates whether each block was solved.
The JOINCHARS function joins two or more non-NA expressions as a single line text. JOINCHARS removes line breaks from the text it joins. (Use INSCHARS to preserve line breaks.)
When the length of the joined line exceeds 4,000 bytes, JOINCHARS automatically breaks the line and puts the remaining characters on the next line. When the line break would occur between the two bytes of a double-byte character, JOINCHARS does not split the double-byte character; instead, it puts both bytes of the double-byte character on the next line.
|
Tip: When you are using a multibyte character set, you can use the JOINBYTES function instead of the JOINCHARS function. |
Return Value
TEXT or NTEXT
The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
JOINCHARS(first-expression, next-expression...)
Parameters
An expression to which JOINCHARS joins next-expression. When the first-expression has a data type other than TEXT or NTEXT, JOINCHARS converts it to TEXT.
One or more expressions to join with first-expression. When an expression you want to concatenate has a data type other than TEXT or NTEXT, JOINCHARS converts it to TEXT.
Examples
Example 7-136 Using JOINCHARS to Concatenate Values
This example shows how you can use JOINCHARS to combine text with the current values of the two variables name.product and price. The variable price has a data type of DECIMAL; however, JOINCHARS automatically converts its value to TEXT to join it with the other text values.
LIMIT product TO 'Canoes' LIMIT month TO 'Dec96'
The JOINCHARS function
JOINCHARS('Current Price for ' name.product ' is: $' price)
returns the following value.
Current Price for Aluminum Canoes is: $200.03
The GREATEST function returns the largest expression in a list of expressions. All expressions after the first are implicitly converted to the data type of the first expression before the comparison.
To retrieve the smallest expression in a list of expressions, use LEAST.
Return Value
The data type of the first expression.
Syntax
GREATEST (expr [, expr]...)
Parameters
An expression.
Examples
OLAP_EXPRESSION_BOOL is a SQL function that dynamically executes an OLAP DML boolean expression within the context of an OLAP_TABLE function. In addition to returning a custom measure, you can use this function in the WHERE and ORDER BY clauses to modify the result set of the query of the analytic workspace.
OLAP_EXPRESSION_TEXT returns character data. To return numeric, text, or date data, use OLAP_EXPRESSION, OLAP_EXPRESSION_TEXT, or OLAP_EXPRESSION_DATE SQL functions.
Before you use this function, you must specify a ROW2CELL clause in the limit map used by OLAP_TABLE. ROW2CELL identifies a RAW column that OLAP_TABLE populates with information used by the OLAP single-row functions.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
An evaluation of boolean_expression for each row of the table object returned by the OLAP_TABLE function.
OLAP_EXPRESSION_BOOL returns boolean data. To return numeric, date, or text data, use the OLAP_EXPRESSION, OLAP_EXPRESSION_DATE, or OLAP_EXPRESSION_TEXT functions.
Syntax
OLAP_EXPRESSION_BOOL(
r2c IN RAW(32),
boolean_expression IN VARCHAR2)
RETURN NUMBER;
Parameters
The name of a column specified by a ROW2CELL clause in the limit map. See "ROW2CELL Clause" of OLAP_TABLE
An OLAP DML expression that returns a Boolean result.
Examples
The following script was used to create the view awunits_view, which is used in Example A-14 to illustrate the use of OLAP_EXPRESSION_BOOL.
Sample View: MYAW_AW.AWUNITS_VIEW
-- Create the logical row
CREATE TYPE awunits_row AS OBJECT (
awtime VARCHAR2(12),
awcustomer VARCHAR2(30),
awproduct VARCHAR2(30),
awchannel VARCHAR2(30),
awunits NUMBER(16),
r2c RAW(32));
/
-- Create the logical table
CREATE TYPE awunits_table AS TABLE OF awunits_row;
/
-- Create the view
CREATE OR REPLACE VIEW awunits_view AS
SELECT awunits,
awtime, awcustomer, awproduct, awchannel, r2c
FROM TABLE(OLAP_TABLE(
'myaw_aw.myawaw DURATION SESSION',
'awunits_table',
'',
'MEASURE awunits FROM units_cube_aw_units_aw
DIMENSION awtime FROM time_aw WITH
HIERARCHY time_aw_parentrel
DIMENSION awcustomer FROM customer_aw WITH
HIERARCHY customer_aw_parentrel
(customer_aw_hierlist ''MARKET_ROLLUP_AW'')
INHIERARCHY customer_aw_inhier
DIMENSION awproduct FROM product_aw WITH
HIERARCHY product_aw_parentrel
DIMENSION channel_aw WITH
HIERARCHY channel_aw_parentrel
ATTRIBUTE awchannel FROM channel_aw_short_description
ROW2CELL r2c'))
WHERE awunits IS NOT NULL;
/
The following query shows some aggregate data in the view. For all products in all markets during the year 2001, it shows the number of units sold through each channel.
SQL> SELECT awchannel, awunits FROM awunits_view
WHERE awproduct = '1'
AND awcustomer = '7'
AND awtime = '4';
AWCHANNEL AWUNITS
--------- -------
All Channels 415392
Direct Sales 43783
Catalog 315737
Internet 55872
The following statements show the descriptions of the Product, Customer, and Time dimension members used in the query.
SQL>execute dbms_aw.execute('limit product_aw to ''1''');
SQL>execute dbms_aw.execute('rpr product_aw_short_description');
PRODUCT_AW PRODUCT_AW_SHORT_DESCRIPTION
--------------- --------------------------------------------------
1 Total Product
SQL>execute dbms_aw.execute('limit customer_aw to ''7''');
SQL>execute dbms_aw.execute('rpr customer_aw_short_description');
CUSTOMER_AW CUSTOMER_AW_SHORT_DESCRIPTION
--------------- --------------------------------------------------
7 Total Market
SQL>execute dbms_aw.execute('limit time_aw to ''4''');
SQL>execute dbms_aw.execute('rpr time_aw_short_description');
TIME_AW TIME_AW_SHORT_DESCRIPTION
--------------- --------------------------------------------------
4 2001
Example A-14 OLAP_EXPRESSION_BOOL Function in a SELECT List
This example uses the view described in "Sample View: MYAW_AW.AWUNITS_VIEW". The following SELECT statement calculates an expression with an alias of lowest_units, which indicates whether or not the number of units of each product was less than 500.
SQL>SELECT awproduct products,
olap_expression_bool(r2c, 'units_cube_aw_units_aw le 500') lowest_units
FROM awunits_view
WHERE awproduct > 39
AND awproduct < 46
AND awcustomer = '7'
AND awchannel = 'Internet'
AND awtime = '4';
PRODUCTS LOWEST_UNITS
--------------- ------------
40 0
41 1
42 1
43 1
44 1
45 0
This query shows that products 41-44 all had less than 500 units. These products are the documentation sets in German, French, Spanish, and Italian. The selected products are shown as follows.
SQL>execute dbms_aw.execute
('limit product_aw to product_aw gt 39 and product_aw lt 46');
SQL>execute dbms_aw.execute('rpr product_aw_short_description');
PRODUCT_AW PRODUCT_AW_SHORT_DESCRIPTION
--------------- --------------------------------------------------
40 O/S Documentation Set - English
41 O/S Documentation Set - German
42 O/S Documentation Set - French
43 O/S Documentation Set - Spanish
44 O/S Documentation Set - Italian
45 O/S Documentation Set - Kanji
The MOVINGTOTAL function (abbreviated MVTOT) computes a series of totals for the values of a dimensioned variable or expression over a specified dimension. For each dimension value in status, MOVINGTOTAL computes the total of the data in the range specified, relative to the current dimension value.
When the variable or expression has only the specified dimension, MOVINGTOTAL produces a single series of totals, one for each dimension value in the status. When the variable or expression has dimensions other than the one specified, MOVINGTOTAL produces a separate series of totals for each combination of values in the status list of the other dimensions.
Return Value
DECIMAL when the data type of expression is DECIMAL or SHORT; otherwise, NUMBER.
Syntax
MOVINGTOTAL(expression, start, stop, step, [dimension [STATUS|limit-clause]])
Parameters
A numeric variable or calculation whose values you want to total; for example, UNITS or SALES-EXPENSE.
Integer values that specify the range of values over which you want to total. The value of start specifies the beginning of the range. The value of stop specifies the end of the range. Specify the values of start and stop relative to the current value of dimension. To specify a negative position for start or stop preceed the value with a comma. Thus, you specify zero (0) for the current dimension value, and -1 for the value preceding the current value. (See also "How the Moving Functions Handle Out-of-Range and NA Values".)
|
Note: By default this function uses the default status list when identifying the range of values to average. You can specify either the STATUS or limit-clause phrase to change this behavior. |
|
Tip: When you want to range to the end of status, for convience and to document your intent, specify the value of stop as OBJ function with the DIMMAX keyword |
A positive whole number that specifies whether to total over every value in the range, every other value, every third value, and so on. A value of 1 for step means total over every value. A value of 2 means total over the first value, the third value, the fifth value, and so on. When the current month is Jun96 and the start and stop values are -3 and 3, a step value of 2 means total over Mar96, May96, Jul96, and Sep96.
The dimension over which the moving total is calculated. While this can be any dimension, it is typically a time dimension.
When expression has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want MOVINGTOTAL to use that dimension, you can omit the dimension argument.
Specifies that MOVINGTOTAL should use the current status list (that is, only the dimension values currently in status in their current status order) when calculating the moving total.
Specifies that MOVINGTOTAL uses the values specified by a LIMIT function or those specified with the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
Examples
For an example of calculating a moving total sales, see Example 8-31, "Calculating a Moving Average".
(Read-only) The SESSION_NLS_LANGUAGE option is an OLAP session-wide, option that holds the value of NLS_LANGUAGE when the value of STATIC_SESSION_LANGUAGE is NO; or, when the value of STATIC_SESSION_LANGUAGE is YES, the value of NLS_LANGUAGE the last time that the value of STATIC_SESSION_LANGUAGE was NO.
Data Type
TEXT
Syntax
SESSION_NLS_LANGUAGE
Examples
For examples of retrieving how the value of SESSION_NLS_LANGUAGE is impacted by changes in the value of NLS_LANGUAGE and STATIC_SESSION_LANGUAGE, see Example 4-9, "Changing NLS_LANGUAGE" and Example 5-104, "Changing NLS_LANGUAGE Without Changing the Language of the OLAP Session".
Example 5-98 SESSION_NLS_LANGUAGE is a Session-Wide Option
Assume that you have two analytic workspace, one named myaw3 and another named myaw4. Assume also, as shown in the following code, that they both have language dimensions named mylangs and that the languages for mylangs in myaw3are American and French and that the languages for mylangs in myaw4 are American and German.
REPORT myaw3!mylangs MYLANGS -------------- AMERICAN FRENCH REPORT myaw4!mylangs MYLANGS -------------- AMERICAN GERMAN
Now assume that you attach both of these analytic workspaces while NLS_LANGUAGE and SESSION_NLS_LANGUAGE are set to American. As shown in the following code, Oracle OLAP limits mylangs in both analytic workspace to American.
REPORT myaw3!mylangs MYLANGS -------------- AMERICAN REPORT myaw4!mylangs MYLANGS -------------- AMERICAN
The MONTHS_BETWEEN function calculates the number of months between two dates. When the two dates have the same day component or are both the last day of the month, then the return value is a whole number. Otherwise, the return value includes a fraction that considers the difference in the days based on a 31-day month. The return value is positive when the first date is later than the second date, and negative when the first date is earlier than the second date.
Return Value
NUMBER
Syntax
MONTHS_BETWEEN(datetime_expression1, datetime_expression2)
Parameters
One expression that has the DATETIME data type, or a text expression that specifies a date.
A second expression that has the DATETIME data type, or a text expression that specifies a date.
Examples
Within an OLAP DML program, the DO and DOEND commands bracket a group of one or more statements in a program. DO and DOEND are normally used to bracket one of the following:
A group of statements that are to be executed under a condition specified by an IF command
A group of statements in a repeating loop introduced by FOR or WHILE
The CASE labels for a SWITCH command.
You can put one DO statement inside another to nest groups of statements. You can nest as many groups as you want, if each DO statement has a corresponding DOEND to indicate the end of its statement group.
Syntax
DO
statement1
...
statementN
DOEND
Parameters
One or more OLAP DML statements, user-defined programs, or both.
Usage Notes
TEMPSTAT Statement and DOEND Statement
Within a FOR loop of a program, when a DO/DOEND phrase follows TEMPSTAT, status is restored when the DOEND, BREAK, or GOTO is encountered.
Examples
Example 9-111 DO and DOEND with the FOR Statement
Suppose you want to use the ROW command to produce a report that shows the unit sales of tents for each of 2 months. Use DO ... DOEND to bracket the ROW and BLANK statements you want to execute repeatedly for each value of the month dimension. You might write the following program.
LIMIT month TO 'Jan96' to 'Feb96'
ROW district
ROW UNDER '-' VALONLY name.product
FOR month
DO
ROW INDENT 5 month WIDTH 6 UNITS
BLANK
DOEND
The program produces the following output.
BOSTON
3-Person Tents
--------------
Jan96 307
Feb96 209
The VALSPERPAGE program calculates the maximum number of values for a variable of a given width that fits on one page. Pages are units of storage in the workspace.
Return Value
INTEGER
Syntax
VALSPERPAGE(n)
Parameters
An INTEGER expression specifying the width of a variable in bytes. This value should be between 1 and 4000. When you specify a value greater than 4000 or less than 1, the result is NA.
Usage Notes
Large Variables
Oracle OLAP lets you create very large, multidimensional variables. Theoretically, a variable can contain up to 2**63 cells, although this maximum is subject to memory constraints and other factors specific to your system.
Examples
Example 8-159 Calculating the Number of Cells in a Page
The following statement calculates the maximum number of cells available in a single page for a variable with an INTEGER data type. The default width of an INTEGER value in Oracle OLAP is 4 bytes.
SHOW VALSPERPAGE(4)
The output of this statement is
992
The NLS_CURRENCY option specifies the local currency symbol for the L number format element for the session. (See the TO_NUMBER function for a description of number format elements.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_CURRENCY = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
The LSIZE option defines the line size within which the STDHDR program centers the standard header. LSIZE can be set in the initialization section of a report program.
Data Type
INTEGER
Syntax
LSIZE = n
Parameters
An INTEGER expression that specifies the line size within which the STDHDR program centers the standard header, or the maximum line size for output from a HEADING statement. The default is 80 characters for a line.
The maximum width of any line in a report, including a heading line, is 4,000 characters. Therefore, it generally makes sense to set LSIZE to a value of 4000 or less
Usage Notes
Centering Report Segments
Since STDHDR centers the running page heading within the width of LSIZE, you can use it with LSIZE to center parts of your report. (Start by setting LSIZE to the width of the longest line in your report.)
Creating Centered Headings
You can use LSIZE in centering your own headings for each page or at the beginning of a section. Start by setting LSIZE to the width of your line. Then use a HEADING statement with a WIDTH of LSIZE and the keyword CENTER before the text of your heading. See Example 5-49, "Centering a Heading".
Setting LSIZE for a File
To set LSIZE for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set LSIZE to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, LSIZE returns to its default value of 80 for the file.
When you set LSIZE for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE commands that send output to a file. That is, the value of LSIZE is automatically saved for the default outfile.
Examples
Example 5-49 Centering a Heading
Suppose you design a quarterly sales report to have a short line width of 50 characters so that readers have plenty of room to make notes in the margins. To center your headings, include the following lines near the beginning of your report program.
PAGEPRG = 'stdhdr' LSIZE = 50 PAGING = YES PAGE HEADING WIDTH LSIZE CENTER 'Quarterly Sales'
The following output is produced at the beginning of the report.
96/05/13 15:05:16 PAGE 1
Quarterly Sales
The RUNTOTAL function returns the running total of an expression. You can use the RUNTOTAL function in a ROW command, ROW function, or REPORT command to generate a running total of the value of an expression.
Return Value
DECIMAL
Syntax
RUNTOTAL(n)
Parameters
One of the 32 subtotals (1 to 32) that Oracle OLAP accumulates for the current column of a report. RUNTOTAL returns the value of this subtotal for the specified column, but does not reset the value of the subtotal to zero.
The numbers by which the 32 subtotals are referenced (1 to 32) have no intrinsic significance; all the subtotals are the same until you reference them.
Usage Notes
How RUNTOTAL Works
Unlike the SUBSTR function, RUNTOTAL does not reset the indicated subtotal to zero, nor does it add the value returned by RUNTOTAL to the indicated subtotal. However, the value returned by RUNTOTAL is added to the other 31 accumulating totals for the current column.
Accessing Data from Another Column
You can obtain a running total of an expression shown in another column of a report by adding that expression to RUNTOTAL. You can use the COALESCE function to refer to the values in the other column. For example, to show the sales for each month in the first data column of a row, and a cumulative total of sales in the second data column, you could use this statement.
ROW month sales COLVAL(-1) + RUNTOTAL(1)
Resetting Subtotals
When you use a ROW statement to produce a report, you can use a ZEROTOTAL statement to reset any subtotal of any column to zero. Typically, use ZEROTOTAL at the beginning of a report program to make sure all totals begin at zero. A REPORT statement automatically resets all subtotals to zero before producing output.
NA Values and RUNTOTAL
RUNTOTAL ignores NA values unless all values are NA. When all values are NA, the total is NA.
Examples
Example 8-94 Calculating a Running Total in a Report
In a report, suppose you want column 2 to contain a running total of the values in column 1.
Assume that you issue the following OLAP DML statements
ZEROTOTAL ALL ROW W 4 R 2 RUNTOTAL(1) + COLVAL(1) ROW W 4 R 5 RUNTOTAL(1) + COLVAL(1) ROW W 4 R 3 RUNTOTAL(1) + COLVAL(1)
These statements produce the following output.
2 2.00 5 7.00 3 10.00
Example 8-95 Calculating a Running Total over Two Districts
In this example, you want your report to contain the unit sales of tents for two districts for the first six months of 1996. Along with the monthly sales figures, you want to see a running total of tent sales for these two districts for the year to date. To produce this cumulative total, use the RUNTOTAL function.
LIMIT product TO 'Tents' LIMIT month TO 'Jan96' TO 'Jun96' LIMIT district TO 'Boston' 'Chicago' REPORT ACROSS district: units - DECIMAL 0 TOTAL(units, month)+RUNTOTAL(1)
These statements produce the following output.
PRODUCT: TENTS
--------UNITS--------
------DISTRICT-------
TOTAL(UNIT
S,
MONTH)+RUN
MONTH Boston Chicago TOTAL(1)
-------------- ---------- ---------- ----------
Jan96 307 189 496
Feb96 209 190 895
Mar96 277 257 1,429
Apr96 372 318 2,119
May96 525 433 3,077
Jun96 576 466 4,119
The RANDOM.SEED.1 and RANDOM.SEED.2 options specify values used by RANDOM when computing random numbers. To compute the number, RANDOM uses the values of the options RANDOM.SEED.1 and RANDOM.SEED.2, and then changes the values for the next time.
When you want to reproduce the same sequence of random numbers when you are developing and debugging your application programs set RANDOM.SEED.1 and RANDOM.SEED.2 to some specific values just before using RANDOM.
Data Type
INTEGER
Syntax
RANDOM.SEED.1|RANDOM.SEED.2 = n
Parameters
An INTEGER expression that specifies the value to use when generating random numbers. The default is for RANDOM.SEED.1 is 12345 and RANDOM.SEED.2 is 1073.
Usage Notes
Reproducing a Random Sequence
As illustrated in Example 8-64, "Producing Random Numbers", when you want to reproduce the same sequence of random numbers when you are developing and debugging your application programs, set RANDOM.SEED.1 and RANDOM.SEED.2 to some specific values just before using RANDOM. To duplicate the sequence, set these options to the same values just before using RANDOM again. Then changes in the behavior of your programs are caused by your changes to the programs and not by differing sequences of random numbers.
Examples
Example 5-94 Explicitly Seeding RANDOM for a Test
Assume that you have the following dimension and variable in your analytic workspace
DEFINE id DIMENSION TEXT DEFINE myvar VARIABLE INTEGER <id>
As shown in the following code, when you use RANDOM to populate myvar without seeding it first. Oracle OLAP populates myvar with different values each time the RANDOM executes.
myvar = 0 myvar = RANDOM (10, 20) REPORT myvar ID MYVAR -------------- ---------- a1 11 a2 19 a3 14 myvar = 0 myvar = RANDOM (10, 20) REPORT myvar ID MYVAR -------------- ---------- a1 16 a2 13 a3 12
Now, assume that you want to write a test that uses RANDOM to create predictable values for myvar. As the following code illustrates, to ensure that the results of RANDOM are the same from time to time, you must set the values of RANDOM.SEED.1 and RANDOM.SEED.2 right before the execution of RANDOM.
myvar = 0
RANDOM.SEED.1 = 5
RANDOM.SEED.2 = 3
myvar = RANDOM (10, 20)
REPORT myvar
ID MYVAR
-------------- ----------
a1 10
a2 16
a3 13
myvar = 0
RANDOM.SEED.1 = 5
RANDOM.SEED.2 = 3
myvar = RANDOM (10, 20)
REPORT myvar
ID MYVAR
-------------- ----------
a1 10
a2 16
a3 13
The values that you set for RANDOM.SEED.1 and RANDOM.SEED.2 do not stay the same throughout a session. As the following code illustrates, when you do not reseed with the same values before each execution, the values produced by RANDOM are not the same.
myvar = 0RANDOM.SEED.1 = 5
RANDOM.SEED.2 = 3
myvar = RANDOM (10, 20)
REPORT myvar
ID MYVAR
-------------- ----------
a1 10
a2 16
a3 13
myvar = 0
myvar = RANDOM (10, 20)
REPORT myvar
ID MYVAR
-------------- ----------
a1 11
a2 16
a3 20
The BITAND function computes a logical AND operation on the bits of two nonnegative values. This function is commonly used with the DECODE function.
An AND operation compares two bit values. When the values are the same, the operator returns 1. When the values are different, the operator returns 0. Only significant bits are compared. For example, an AND operation on the integers 5 (binary 101) and 1 (binary 001 or 1) compares only the rightmost bit, and results in a value of 1 (binary 1).
Return Value
INTEGER
Syntax
BITAND (argument1 , argument2)
Parameters
A nonnegative INTEGER expression.
A nonnegative INTEGER expression.
Examples
The REMCHARS function removes one or more characters from a text expression and returns the value that remains.
|
Tip: When you are using a multibyte character set, you can use the REMBYTES function instead of the REMCHARS function. |
Return Value
TEXT or NTEXT
Syntax
REMCHARS(text-expression start [length])
Parameters
The expression from which REMCHARS removes characters. When the characters to remove from text-expression contain embedded line breaks, these breaks are also removed. Other line breaks are preserved. Removed line breaks are not counted toward the total number of characters removed.
When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
An INTEGER that represents the character position at which to begin removing characters. The position of the first character in text-expression is 1. When the value of start is greater than the length of text-expression, REMCHARS simply returns text-expression.
An INTEGER that represents the number of characters to be removed. When length is not specified, only the character at start is removed.
Examples
This chapter provides reference topics for the second set (in alphabetical order) of the OLAP DML functions. There is one topic for each of the OLAP DML functions that begins with the letters L-Z, beginning with LAG.
Alphabetical and categorical listings of the OLAP DML functions and reference topics for the remaining OLAP DML functions appear in Chapter 7, "OLAP DML Functions: A - K".
For other OLAP DML reference topics, see Chapter 4, "OLAP DML Properties", Chapter 5, "OLAP DML Options", Chapter 9, "OLAP DML Commands: A-G", and Chapter 10, "OLAP DML Commands: H-Z".
|
Tip: Many OLAP DML statements can be coded as a 3-character abbreviation that consists of the first letter of the statement plus the next two consonants. |
The EXPTRACE option controls whether OLAP DML programs in the analytic workspace named EXPRESS are traced when the PRGTRACE option is set to YES. The EXPRESS analytic workspace is always attached and contains, among other things, OLAP DML programs documented as OLAP DML statements and other "helper" OLAP DML programs.
Data Type
BOOLEAN
Syntax
EXPTRACE = {YES|NO}
Parameters
All programs are traced, including OLAP DML programs provided as OLAP DML statements.
(Default) OLAP DML programs provided as OLAP DML statements are not traced. Only other types of programs are traced.
Usage Notes
How to Identify OLAP DML Programs Provided as OLAP DML Statements
Some OLAP DML statements are implemented as OLAP DML programs. These programs are affected by EXPTRACE. To send to the current outfile a list of these programs, issue the following statement.
SHOW AW(PROGRAM 'express')
Examples
The FINDLINES function determines the position of one or more lines in a multiline text expression.
Return Value
INTEGER
Syntax
FINDLINES(text-expression, lines)
Parameters
A text expression within whose values you want to locate a certain line or group of lines. FINDLINES searches text-expression for the specified lines. The match must be exact, including a match of uppercase and lowercase characters. Also, when you specify two or more lines, FINDLINES searches for all the specified lines as a single continuous block in text-expression. When all the lines occur in text-expression, but are not in a continuous block, FINDLINES returns 0 (not found).
FINDLINES accepts TEXT values and NTEXT values as arguments. When only one argument is NTEXT, then FINDLINES automatically converts the other argument to NTEXT before performing the function operation.
Note that when the value of text-expression is NA, FINDLINES returns NA.
A second text expression containing the line(s) for which you are searching. When lines is not found in text-expression, FINDLINES returns 0. When lines occurs more than once, FINDLINES returns the line number of its first occurrence.
Examples
Example 7-97 Finding Two Sequential Lines
This example shows how to find the location of the two lines "products" and "services" in a multiline value in a TEXT variable called newlist. The newlist variable has the following values.
salespeople products services regions priorities
The characters "\n" in the lines argument to the following FINDLINES function call indicates a line break to show that "product" and "services" are separate lines.
SHOW FINDLINES(newlist, 'products\nservices')
The result of this statement is
2
The UPDATE_ATTRIBUTE_VALUE program modifies the attributes of an OLAP cube dimension member.
This program is especially useful when updating the following kinds of attributes:
For attributes with an underlying relation or indexed dimension, you need only to provide the dimension member and value. The indexed dimension is maintained along with setting the value in the relation.
For spread attributes, if you set an attribute value on an attribute spanning all levels, then the values are spread down to lower levels on compile.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL UPDATE_ATTRIBUTE_MEMBER(dim_member_id, attribute_name, attribute_value -
[, auto_compile ])
Parameters
Since UPDATE_ATTRIBURE_VALUE is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the value of the cube dimension member that you want to modify the attributes of.
A text expression that is the Oracle data dictionary name of the cube dimension of which dim_member_id is a member.
A text expression that is the Oracle data dictionary name of the attribute.
A text expression that specifies the value of attribute_name.
A Boolean expression that specifies whether or not you want related analytic workspace objects to be updated immediately.
The default value is TRUE in which case all of the changes to the analytic workspace that are needed to update the attribute of the cube dimension member happen now.
Specify FALSE only when, for performance reasons, you want to make a bulk set of changes before issuing a compile. In this case, you need to explicitly compile the cube dimension before the values of the analytic workspace objects take effect as described in "Explicitly Compiling a Cube Dimension".
|
Note: Regardless of the value that you specify for this argument, the attribute of the dimension member is always immediately updated -- even when an error is signaled during compilation. |
Examples
Example 10-169 Updating the Attributes of an OLAP Cube Dimension
This example uses the UPDATE_ATTRIBUTE_VALUE program provided with the OLAP DML to update attributes of the my_time cube dimension for the L1-2 and the descendants of L1-2. The calls to the UPDATE_ATTRIBUTE_VALUE program provided with the OLAP DML are within a user-written OLAP DML program named ADD_L1_2_DATE.
Issue the following PL/SQL statement to execute the user-written OLAP DML program named ADD_L1_2_DATE to set time attribute values for L1_2 and its descendants
exec dbms_aw.execute('call my_util_aw!add_l1_2_dates');
The definition of the user-written ADD_L1_2_DATE OLAP DML program is shown below. Notice the calls to the UPDATE_ATTRIBUTE_VALUE program provided with the OLAP DML.
DEFINE ADD_L1_2_DATES PROGRAM
PROGRAM
VARIABLE _aw_dim text
VARIABLE _start_date text
VARIABLE _timespan text
_aw_dim = OBJORG(DIM 'my_time')
_start_date = OBJORG(ATTRIBUTE 'my_time' 'start_date')
_timespan = OBJORG(ATTRIBUTE 'MY_TIME' 'timespan')
" Updates the time attribute of L1_2, L2_3, L3_6, but does not compile
CALL UPDATE_ATTRIBUTE_VALUE('L1_2', 'my_time', 'start_date', -
&_start_date(&_aw_dim 'L1_1')+365, NO)
CALL UPDATE_ATTRIBUTE_VALUE('L1_2', 'my_time', 'timespan', -
&_timespan(&_aw_dim 'L1_1'), NO)
CALL UPDATE_ATTRIBUTE_VALUE('L2_3', 'my_time', 'start_date', -
&_start_date(&_aw_dim 'L1_2'), NO)
CALL UPDATE_ATTRIBUTE_VALUE('L2_3', 'my_time', 'timespan', -
&_timespan(&_aw_dim 'L2_1'), NO)
CALL UPDATE_ATTRIBUTE_VALUE('L3_6', 'my_time', 'start_date', -
&_start_date(&_aw_dim 'L1_2'), NO)
CALL UPDATE_ATTRIBUTE_VALUE('L3_6', 'my_time', 'timespan', -
&_timespan(&_aw_dim 'L3_1'), NO)
UPDATE
COMMIT
END
Issue the following SQL statement to see what the attributes of the my_time cube dimension are.
select dim_key||' '||start_date||' '||lpad(timespan, 3)
from my_time_view
order by dim_key asc;
DIM_KEY||''||START_DATE||''||LPAD(TIMESPAN,3)
----------------------------------------------------------------------------
L1_0 01-JAN-09 365
L1_1 01-JAN-10 365
L1_2 01-JAN-11 365
L2_1 01-JAN-10 90
L2_2 01-APR-10 61
L2_3 01-JAN-11 90
L3_1 01-JAN-10 31
L3_2 01-FEB-10 28
L3_3 01-MAR-10 31
L3_4 01-APR-10 30
L3_5 01-MAY-10 31
L3_6 01-JAN-11 31
12 rows selected.
Issue the following SQL statement to report the values of the sales and moving_sales measures before the my_time cube dimension is compiled. Note that the calculation for the measures does not consider the new attributes of the my_time cube dimension.
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2) from my_cube_view order by my_time asc; MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2) -------------------------------------------------------------------- L1_0 24 27 L1_1 14 38 L1_2 3 3 L2_1 2 5 L2_2 12 14 L2_3 3 3 L3_1 1 4 L3_2 1 2 L3_3 10 11 L3_4 1 11 L3_5 1 2 L3_6 3 3 12 rows selected.
Issue the following SQL statement to compile the my_time cube dimension.
exec dbms_cube.build('MY_TIME USING (COMPILE)');
Issue the following SQL statement to report the values of the sales and moving_sales measures after the my_time cube dimension is compiled. Note that now the calculation for the measures considers the new attributes of the my_time cube dimension
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2)
from my_cube_view
order by my_time asc;
MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2)
--------------------------------------------------------------------
L1_0 24 24
L1_1 14 38
L1_2 3 17
L2_1 2 2
L2_2 12 14
L2_3 3 15
L3_1 1 1
L3_2 1 2
L3_3 10 11
L3_4 1 11
L3_5 1 2
L3_6 3 4
12 rows selected.
The STATIC_SESSION_LANGUAGE option is a read/write option that controls if Oracle OLAP keeps the value of the SESSION_NLS_LANGUAGE option synchronized with the value of the NLS_LANGUAGE option.
Data Type
BOOLEAN
Syntax
STATIC_SESSION_LANGUAGE = NO | YES
Parameters
Specifies that whenever the value of the NLS_LANGUAGE option changes, Oracle OLAP changes the value of SESSION_NLS_LANGUAGE to the value of the NLS_LANGUAGE option. (Default)
Specifies that the value of SESSION_NLS_LANGUAGE does not change when the value of NLS_LANGUAGE changes.
Examples
Example 5-104 Changing NLS_LANGUAGE Without Changing the Language of the OLAP Session
Example 4-9, "Changing NLS_LANGUAGE" illustrates how changing the NLS_LANGUAGE value can change the language of the OLAP session. This example illustrates how you can keep the language of the OLAP session the same even as the value of the NLS_LANGUAGE option changes.
Assume that you attach your analytic workspace while the NLS_LANGUAGE is American. As the following code illustrates by changing the value of the STATIC_SESSION_LANGUAGE to Yes, you can insure that even as the value of the NLS_LANGUAGE option is changed to French, the value of the SESSION_NLS_LANGUAGE stays American which means that Oracle OLAP limits the language dimension (mylangs) to American.
SHOW NLS_LANGUAGEFRENCH
AMERICAN
" Make the session language static
STATIC_SESSION_LANGUAGE = yes
"Change the value of NLS_LANGUAGE to FRENCH
SET NLS_LANGUAGE= 'FRENCH'
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
AMERICAN
SHOW NLS_LANGUAGE
FRENCH
SHOW SESSION_NLS_LANGUAGE
AMERICAN
SHOW LOCK_LANGUAGE_DIMS
oui
SHOW STATIC_SESSION_LANGUAGE
oui
REPORT mylangs
MYLANGS
--------------
AMERICAN
REPORT prod_desc
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
AMERICAN Trousers Skirts
The GET function requests input from the current input stream. The input may be a single item of data, a dimension value, an analytic workspace object, or simply the next item in the input stream. The simplest form of the GET function requests a value of a certain data type.
GET(datatype)
GET also provides several arguments that verify the input.
Because GET is a function, it must be used in an OLAP DML command. It also may be used in an assignment statement to store the input in a variable for later use, or in a LIMIT command to set the status of a dimension. GET can be used in programs to request information necessary for the completion of the program.
Return Value
The return value depends on the input that you request, as described in the syntax.
Syntax
GET({RAW TEXT|[NEW|VALID|POSLIST] input} -
[VERIFY condition-exp [IFNOT result-exp]])
where input is one of the following:
Parameters
A text expression specifying the name of a dimension. When you specify dim-name, GET requests a value of this dimension as input and verifies that the input is a valid value of the dimension.
Specifies that GET should return the next item in the input stream exactly as it is entered. See "GET with RAW TEXT".
The NEW keyword with the dim-name argument causes GET to request a new value for the dimension. When requesting a dimension value with NEW, GET verifies that the input is not already a value of the dimension.
The VALID keyword with the dim-name argument causes GET to request either a new value or an existing value of the dimension. When requesting a dimension value with VALID, GET verifies that the input is either an existing dimension value or a valid new dimension value.
The POSLIST keyword with the dim-name argument causes GET to request a dimension value identified by its position in the dimension. When requesting a dimension value with POSLIST, GET verifies that the input is an existing position number in the dimension. See "GET with POSLIST".
Indicates that GET is requesting the name of an object in the current analytic workspace. When you specify NAME, GET verifies that the input is an object that exists in the current analytic workspace. The object name must not be enclosed in single quotes, and it must follow the rules for valid object names explained in the main DEFINE entry. GET automatically converts the object name to uppercase.
The NEW NAME keywords cause GET to request a name for a new analytic workspace object. When requesting an analytic workspace object name with NEW, GET verifies that the input is not already the name of an object in any attached analytic workspace (including EXPRESS.DB).
The VALID NAME keywords cause GET to request a name for an analytic workspace object. When requesting an analytic workspace object name with VALID, GET verifies that the input follows the rules for valid object names, even when there is no current analytic workspace and regardless of whether the name exists.
The POSLIST NAME keywords cause GET to request an analytic workspace object name identified by its position in the NAME dimension. When requesting an analytic workspace object name with POSLIST, GET verifies that the input is an existing position number in the NAME dimension.
Specifies the type of data being requested by GET which can be any of the Oracle OLAP data types: INTEGER, SHORTINTEGER, DECIMAL, SHORTDECIMAL, BOOLEAN, ID, TEXT, or DATE. GET accepts a value of NA when requesting any data type.
With VERIFY, you can specify a Boolean condition that must be satisfied by the input to GET. The keyword VALUE may be used in condition-exp to test the input before any assignment is made. For example, when requesting a value of LSIZE, the Boolean condition might be as follows.
VALUE NE NA AND VALUE GE 1 AND VALUE LE 80
The IFNOT clause specifies a text expression to provide for occasions when the input does not satisfy condition-exp. For example, you might jump to an error-handling routine in your program. When you do not use IFNOT and an error occurs, GET produces an error message and then resumes waiting for input.
Usage Notes
Current Input Stream
Oracle OLAP obtains statements for processing from the current input stream. You can override your default input stream with an INFILE statement. INFILE causes Oracle OLAP to read input from a file. Each line of the infile must contain a single statement.
Input from INFILE
When the GET function is in an infile, Oracle OLAP considers the next line in the infile to be the input to GET. You must be sure you supply the expected input for GET in the line or lines following the statement that invokes the GET function.
For example, suppose your infile contains a line invoking a report program that calls GET to obtain the number of decimal places to use. The infile then continues with other statements. When you do not put the desired number of decimal places on the line following the program call, GET examines line after line in the infile looking for the expected numeric response, rather than executing those lines as statements. See "Using GET to Obtain Textual Value".
INTEGER Dimension Values
When GET requests a value of an INTEGER dimension, the input should usually be in the form of a dimension-value position number
Non-INTEGER Dimension Values
Non-integer dimension values must be entered in uppercase and enclosed in single quotes.
Entering Values for DWMQY Dimensions
Values of DAY, WEEK, MONTH, QUARTER, or YEAR dimensions may be entered in the format of the dimension's VNF (or in the format of the default VNF when the dimension does not have a VNF of its own) or as a date. See the VNF command for an explanation of how to enter values in a VNF format. See "Date-only Input Values" for an explanation the valid input styles for entering values as dates.
Whether you use the VNF format or specify the value as a date, you must specify only the date components that are relevant for this type of time dimension. For example, for a MONTH dimension, you must supply only the month and year.
TEXT or ID Values
TEXT and ID values provided as input to GET retain the case in which they were entered. You do not have to enclose TEXT and ID values in quotes unless they begin with single or double quotes, or contain embedded blanks or escape sequences, such as \dnnn or \n. (Remember to precede any single quote in the value with a backslash (\') so Oracle OLAP interprets it literally.)
DATE-only Values
When GET requests a DATE value, you can provide the input in any of the valid styles for dates, as explained in "Date-only Input Values". Oracle OLAP uses the current value of the DATEORDER option to resolve any ambiguity in the DATE-only value.
Numeric Values
GET rounds a SHORTDECIMAL or DECIMAL value when converting it into an INTEGER value. When GET requests an INTEGER or SHORTINTEGER value and the input is a number beyond the range for that data type, GET produces an error message and resumes waiting for input.
GET with RAW TEXT
When GET requests RAW TEXT input and no input is provided, GET returns a null string (''). For any type of information other than RAW TEXT, GET waits until input is provided.
GET with POSLIST
When you use the POSLIST keyword with the GET function, Oracle OLAP requires that you enter a position value to identify the dimension value rather than the dimension name. The syntax for the POSLIST keyword depends on whether you are using the GET function with either an assignment statement created using an assignment statement or the LIMIT command. When you want to set a variable equal to the result of a GET function, use the following syntax.
expression = GET(POSLIST dimension)
When you want to limit a dimension to a value returned by a GET function, you specify the POSLIST keyword twice, as shown in the following syntax.
LIMIT dimension TO POSLIST GET(POSLIST dimension)
Examples
This chapter provides an overview information on how to create OLAP DML programs. It includes the following topics:
The OLAP DML provides a number of programs that you can use to work with OLAP cubes and cube dimensions as previously defined in the Oracle data dictionary. These programs are listed in "Cube-Aware OLAP DML Statements".
It also provides the following programs that work directly on the analyhtic workspace:
ALLCOMPILE which uses the COMPILE command to compile every compilable object in your current analytic workspace, one at a time.
ALLSTAT sets the status of all dimensions in the current analytic workspace to the default status list of the dimension.
AWDESCRIBE sends information about the current analytic workspace to the current outfile. After a summary page, it provides a report in two parts: An alphabetic list of analytic workspace objects showing name, type, and description; and a DESCRIBE of each object by object type.
COPYDFN defines a new object in the analytical workspace by copying the definition from a already-defined object in the current workspace or in an attached workspace.
FORECAST.REPORT produces a standard report of a forecast created using the FORECAST command. The report shows the parameters of the forecast, including the forecast formula and Mean Absolute Percent Error, followed by a display of the forecasted values.
FULLDSC produces a report that lists the definition of one or more workspace objects, including the properties and triggers of the object(s).
ISDATE determines whether a text expression to see if it can be converted to a DATE value It returns YES when the text expression represents a valid date; NO when it does not. (Note that, ISDATE does not actually make the conversion. You must use CONVERT to make the conversion.)
LISTBY produces a report of the names of all objects in an analytic workspace that are dimensioned by or related to one or more specified dimensions or composites. You can use LISTBY with a dimension or composite in any attached workspace.
LISTNAMES produces a report that lists the names of the objects in an analytic workspace. You can limit the list to particular types of objects, and you can have the names for each type of object listed in alphabetical order.
MODEL.COMPRPT produces a report that shows how model equations are grouped into blocks. For step blocks and for simultaneous blocks with a cross-dimensional dependence, the report lists the dimensions involved in the dependence.
MODEL.DEPRT produces a report that lists the variables and dimension values on which each model equation depends. When a dependence is dimensional, the report gives the name of the dimension.
MODEL.XEQRPT produces a report about the execution of the model. The report specifies the block where the solution failed and shows the values of the model options that were used in solving simultaneous blocks.
PAGE, commonly used in report programs or with LISTNAMES, forces a page break in output when PAGING is set to YES. An optional argument to PAGE specifies a conditional page break based on how many lines are left on the page.
REGRESS.REPORT produces a standard report of a regression performed using the REGRESS command.
STATUS sends to the current outfile the status of one or more dimensions, dimension surrogates, or valuesets, or the status of all dimensions in an analytic workspace.
STDHDR generates the standard Oracle OLAP heading at the top of every page of report output.
VALSPERPAGE calculates the maximum number of values for a variable of a specified width that fits on one page. Pages are units of storage in the workspace.
Since the ISDATE and VALSPERPAGE programs are like simple functions because they return a single value, they are documented in alphabetical sequence along with OLAP DML functions in Chapter 7, "OLAP DML Functions: A - K" and Chapter 8, "OLAP DML Functions: L - Z". The other programs provided with the OLAP DML, are documented in alphabetical sequence along with the OLAP DML commands in Chapter 9, "OLAP DML Commands: A-G" and Chapter 10, "OLAP DML Commands: H-Z".
An OLAP DML program is written in the OLAP DML. It acts on data in the analytic workspace and helps you accomplish some workspace management or analysis task. You can write OLAP DML programs to perform tasks that you must do repeatedly in the analytic workspace, or you can write them as part of an application that you are developing.
To create an OLAP DML program, take the following steps:
Issue a DEFINE PROGRAM statement to define the program object. When the program that you are defining is used is a function, include the datatype or the dimension argument.
Add contents to the program that specify the processing that you want performed as described in "Specifying Program Contents".
Compile the program as described in "Compiling Programs".
Test and debug the program as described in "Testing and Debugging Programs".
Execute the program as described in "Executing Programs".
The content of a program consists of the following OLAP DML statements:
A PROGRAM statement that indicates the beginning of the program contents. (Omit when coding the specification in an Edit window of the OLAP Worksheet.)
(Optional) VARIABLE statements that define any local variables.
(Optional) ARGUMENT statements that declare arguments. (See "Passing Arguments" for more information.)
Additional OLAP DML statements that specify the processing you want performed. You can use almost any of the OLAP DML statements in a program. There are also some OLAP DML statements, such as flow-of-control statements, that are only used in programs.
Use the following formatting guidelines as you add lines to your program:
Each line of code can have a maximum of 4,000 bytes.
To continue a single statement on the next line, place a hyphen (-) at the end of the line to be broken. The hyphen is called a continuation character.
You cannot use a continuation character in the middle of a text literal.
To write multiple statements on a single line, separate the statements with semicolon (;).
Enclose literal text in single quotation marks ('). To include a single quotation mark within literal text, precede it with a backslash (\). To specify escape sequences, see "Escape Sequences".
Precede comments with double quotation marks ("). You can place a comment, preceded by double quotation marks, either at the beginning of a line or at the end of a line, after some statements.
A final END statement that indicates the end of the contents of the program. (Omit when coding the specification in an Edit window of the OLAP Worksheet.)
One type of program that is commonly written is a user-define function that you can use in OLAP DML statements in much the same way as you use an OLAP DML function. A user-defined function is simply an OLAP DML program that returns a value. For an example of a user-defined function, see Example 9-44, "Passing an Argument to a User-Defined Function".
When you create a user-defined function, you use a DEFINE PROGRAM statement that includes the datatype and dimension arguments. Within the program, you include a RETURN statement that returns a value. The return expression in the program should match the data type that is specified in its definition. When the data type of the return value does not match the data type that is specified in its definition, then the value is converted to the data type in the definition.
User-defined functions can accept arguments. A user-defined function returns only a single value. However, when you supply an argument to a user-defined function in a context that loops over a dimension (for example, in a REPORT statement), then the function returns results with the same dimensions as its argument.
You must declare the arguments using an ARGUMENT statement within the program, and you must specify the arguments in parentheses following the name of the program.
Use ARGUMENT statements to declare both simple and complex arguments (such as expressions). ARGUMENT statement also make it convenient to pass arguments from one program to another, or to create your own user-defined functions since using these statements you can declare an argument of any data type, dimension, or valueset. Any ARGUMENT statements must precede the first executable line in the program. When you run the program, these declared arguments are initialized with the values you provided as arguments to the program. The program can then use these arguments in the same way it would use local variables.
A program can declare as many arguments as needed. When the program is executed with arguments specified, the arguments are matched positionally with the declared arguments in the program. When you run the program, you must separate arguments with spaces rather than with commas or other punctuation. Punctuation is treated as part of the arguments. For an example of passing multiple arguments, see Example 9-45, "Passing Multiple Arguments".
Sometimes you want your OLAP DML program to be able to handle arguments without converting values to a specific data type. In this case, you can specify a data type of WORKSHEET in the ARGUMENT and VARIABLE statements that define the arguments and temporary variables for the program. You can use WKSDATA to determine the actual data type of the argument or variable.
It is very common to pass a simple text argument to a program. However, there are some situations in which you might want to write more general programs or pass a more complicated text argument, such as an argument that is all of the data in an analytic workspace object or the results of an expression. In these cases, you can pass the argument using a substitution expression. Passing an argument in this way is called ampersand substitution.
For the following types of arguments, you must always use an ampersand to make the appropriate substitution:
Names of workspace objects, such as units or product
Statement keywords, such as COMMA or NOCOMMA in the REPORT statement, or A or D in the SORT command
When you use ampersand substitution to pass the names of workspace objects to a program (rather than their values), the program has access to the objects themselves because the names are known to the program which is useful when the program must manipulate the objects in several operations.
|
Note: You cannot compile and save any program line that contains an ampersand. Instead, the line is evaluated at run time, which can reduce the speed of your programs. Therefore, to maximize performance, avoid using ampersand substitution when another technique is available. |
For an example of using ampersand substitution to pass multiple dimension values, see Example 10-18, "Using Ampersand Substitution with LIMIT". For an example of using ampersand substitution to pass the text of an expression, see Example 9-47, "Passing the Text of an Expression". For an example of using ampersand substitution to pass object names and keywords, see Example 9-48, "Passing Workspace Object Names and Keywords".
Like most programming languages, the OLAP DML has several statements that you can use to determine the flow-of-control within a program. However, you must code explicit loops less frequently in an OLAP DML program because of the intrinsic looping nature of many OLAP DML statements.
Table 6-1, "Statements For Determining Flow-of-Control" lists OLAP DML flow-of-control statements. The looping characteristic of OLAP DML statements is discussed in "OLAP DML Statements Apply to All of the Values of a Data Object".
The OLAP DML contains the flow-of-control statements typically found in a programming language. Table 6-1, "Statements For Determining Flow-of-Control" lists these statements.
Table 6-1 Statements For Determining Flow-of-Control
| Statement | Description |
|---|---|
|
|
Transfers program control from within a SWITCH, FOR, or WHILE statement to the statement immediately following the DOEND associated with SWITCH, FOR, or WHILE. |
|
|
Transfers program control to the end of a FOR or WHILE loop (just before the DO/DOEND statement), allowing the loop to repeat. You can use CONTINUE only within programs and only with FOR or WHILE. |
|
|
Brackets a group of one or more statements. DO and DOEND are normally used to bracket a group of statements that are to be executed under a condition specified by an IF statement, a group of statements in a repeating loop introduced by FOR or WHILE, or the CASE labels for a SWITCH statement. |
|
|
Specifies one or more dimensions whose status controls the repetition of one or more statements. |
|
|
Alters the sequence of statement execution within the program by indicating the next program statement to execute. |
|
|
Executes one or more statements in a program if a specified condition is met. Optionally, it also executes an alternative statement or group of statements when the condition is not met. |
|
|
An option that determines whether you can limit the dimension you are looping over within an explicit FOR loop. |
|
|
Terminates execution of a program before its last line. You can optionally specify a value that the program returns. |
|
|
Produces an error message and halts normal execution of the program. When the program contains an active trap label, execution branches to the label. Without a trap label, execution of the program terminates and, if the program was called by another program, execution control returns to the calling program. |
|
|
Provides a multipath branch in a program. The specific path taken during program execution depends on the value of the control expression that is specified with SWITCH. |
|
|
Limits the dimension you are looping over, inside a FOR loop or inside a loop that is generated by a REPORT statement. Status is restored after the statement following TEMPSTAT. If a DO ... DOEND phrase follows TEMPSTAT, status is restored when the matched DOEND or a BREAK or GOTO statement is encountered. |
|
|
Causes program execution to branch to a label when an error occurs in a program or when the user interrupts the program. When execution branches to the trap label, that label is deactivated. |
|
|
Repeatedly executes a statement while the value of a Boolean expression remains TRUE. |
There are two types of environments:
Session environment. The dimension status, option values, and output destination that are in effect before a program is run constitute the session environment.
Program environment. The dimension status, option values, and output destination that you use in a program constitute the program environment.
To perform a task within a program, you often must change the output destination or some dimension and option values. For example, you might run a monthly sales report that always shows the last six months of sales data. You might want to show the data without decimal places, include the text "No Sales" where the sales figure is zero, and send the report to a file. To set up this program environment, you can use the following statements in your program.
LIMIT month TO LAST 6 DECIMALS = 0 ZSPELL = 'No Sales' OUTFILE monsales.txt
To avoid disrupting the session environment, the initialization section of a program should save the values of the dimensions and options that are set in the program. After the program executes, you can restore the saved environment, so that other programs do not need to be concerned about whether any values have been changed. In addition, when you have sent output to a file, then the exit sections should return the output destination to the default outfile.
The following suggestions let you save the environment of a program or a session:
When you want to save the current status or value of a dimension, a valueset, an option, or a single-cell variable that is changed in the current program, then use PUSHLEVEL and PUSH statements. You can restore the current status values using POPLEVEL and POP statements.
When you want to save, access, or update the current status or value of a dimension, a valueset, an option, a single-cell variable, or a single-cell relation for use in the current session, then use a named context. Use the CONTEXT command to define the context.
Contexts are the most sophisticated way to save object values for use during a session. With contexts, you can access, update, and commit the saved object values. In contrast, PUSH and POP simply allow you to save and restore values. Typically, you use PUSH and POP statements within a program to make changes that apply only during the execution of the program.
A PUSH statement saves the current status of a dimension, the value of an option, or the value of a single-cell variable. For example, to save the current value of the DECIMALS option so you can set it to a different value for the duration of the program, use the following statement in the initialization section.
PUSH DECIMALS
You do not need to know the original value of the option to save it or to restore it later. You can restore the saved value with a POP statement.
POP DECIMALS
You must make sure a POP statement is executed when errors cause abnormal termination of the program and when the program ends normally. Therefore, place the POP statement in the normal and abnormal exit sections of the program.
You can save the status of one or more dimensions and the values of any number of options and variables in a single PUSH statement, and you can restore the values with a single POP statement, as shown in the following example.
PUSH month DECIMALS ZSPELL
...
POP month DECIMALS ZSPELL
When you are saving the values of several dimensions and options, then PUSHLEVEL and POPLEVEL statements provide a convenient way to save and restore the session environment.
You first use a PUSHLEVEL statement to establish a level marker. Once the level marker is established, you use a PUSH statement to save the status of dimensions and the values of options or single-cell variables.
When you place multiple PUSH statements between the PUSHLEVEL and POPLEVEL statements, then all the objects that are specified in those PUSH statements are restored with a single POPLEVEL statement.
By using PUSHLEVEL and POPLEVEL, you save some typing as you write your program because you must only type the list of objects once. You also reduce the risk of omitting an object from the list or misspelling the name of an object.
For an example of creating level markers, see Example 10-85, "Creating Level Markers". Example 10-86, "Nesting PUSHLEVEL and POPLEVEL Commands" illustrates nesting PUSHLEVEL and POPLEVEL statements.
As an alternative to using PUSHLEVEL and POPLEVEL, you can use the CONTEXT command. After you create a context, you can save the current status of dimensions and the values of options, single-cell variables, valuesets, and single-cell relations in the context. You can then restore some or all of the object values from the context. The CONTEXT function returns information about objects in a context.
When an error occurs anywhere in a program, Oracle OLAP performs the following actions:
< ol>Stores the name of the error in the ERRORNAME option, and the text of the error message in the ERRORTEXT option.
|
Note: When the ERRNAMES option is set to the default value ofYES, the ERRORTEXT option contains the name of the error (that is, the value of the ERRORNAME option) and the text of the error message. |
When ECHOPROMPT is YES, then Oracle OLAP echoes input lines, error messages, and output lines, to the current outfile. When you use the OUTFILE or DBGOUTFILE statement, you can capture the error messages in a file. See Example 10-69, "Directing Output to a File" for an example of directing output to a file.
When error trapping is off, then the execution of the program is halted. When error trapping is on, then the error is trapped.
To make sure the program works correctly, anticipate errors and set up a system for handling them. You can use a TRAP statement to turn on an error-trapping mechanism in a program. When error trapping is on and an error is signaled, then the execution of the program is not halted. Instead, error trapping does the following:
Turns off the error-trapping mechanism to prevent endless looping in case additional errors occur during the error-handling process
Branches to the label that is specified in the TRAP statement
Executes the statements following the label
To pass an error to a calling program, you can use one of two methods. The method you use depends on when you want the error message to be produced. With the first method, Oracle OLAP produces the message immediately and then the error condition is passed through the chain of programs. With the second method, Oracle OLAP passes the error through the chain of programs first and then produces the message. See "Passing an Error: Method One" and "Passing an Error: Method Two" for details.
With both methods, the appropriate error handling happens in each program in the chain, and at some point Oracle OLAP sends an error message to the current outfile.
Using this method, Oracle OLAP produces the message immediately and then the error condition is passed through the chain of programs.
Use a TRAP statement with the (default) PRINT option. When an error occurs, Oracle OLAP produces an error message, and execution branches to the trap label. After the trap label, perform whatever cleanup you want, and then execute the following statement.
SIGNAL PRGERR
Using this statement creates an error condition that is passed up to the program from which the current program was run. However, PRGERR does not produce an error message. PRGERR sets the ERRORNAME option to a blank value.
When the calling program contains a trap label, execution branches to the label. When each of the programs in a sequence of nested programs uses TRAP and SIGNAL in this way, you can pass the error condition up through the entire sequence of programs.
Using this method, Oracle OLAP passes the error through the chain of programs first and then produces the message.
Use a TRAP statement with the NOPRINT option. When an error occurs, execution branches to the trap label, but the error message is suppressed. After the trap label, perform whatever cleanup you want, then execute the following statement.
SIGNAL ERRORNAME ERRORTEXT
The options ERRORNAME and ERRORTEXT contain the name and message of the original error, so this SIGNAL statement reproduces the original error. The error is then passed up to the program from which the current program was run.
When the calling program also contains a trap label, execution branches to its label. When each of the programs in a sequence of nested programs uses TRAP...NOPRINT and SIGNAL ERRORNAME ERRORTEXT in this way, you can pass the error condition up through the entire sequence of programs. Oracle OLAP produces the error message at the end of the chain.
When you reach a level where you want to handle the error and continue the application, omit the SIGNAL statement. You can display your own message with a SHOW statement.
When you do not want to produce the error message that is normally provided for a given error, then you can use TRAP statement with a NOPRINT keyword.
TRAP ON error NOPRINT
When you use the NOPRINT keyword with TRAP, control branches to the error label, and an error message is not issued when an error occurs. The statements following the error label are then executed.
When you suppress the error message, you might want to produce your own message in the abnormal exit section. A SHOW statement produces the text you specify but does not signal an error.
TRAP ON error NOPRINT
...
error:
...
SHOW 'The report will not be produced.'
The program continues with the next statement after producing the message.
All errors that occur when a statement or statement sequence does not conform to its requirements are signaled automatically. In your program, you can establish additional requirements for your own application. When a requirement is not met, you can execute a SIGNAL statement to signal an error.
You can give the error any name. When a SIGNAL statement is executed, the error name you specify is stored in the ERRORNAME option, just as an OLAP DML error name is automatically stored. When you specify your own error message in a SIGNAL statement, then your message is produced just as an OLAP DML error message is produced. When you are using a TRAP statement to trap errors, a SIGNAL statement branches to the TRAP label after the error message is produced.
For an example of signaling an error, see Example 10-123, "Signaling an Error".
When you want to produce a warning message without branching to an error label, then you can use a SHOW statement as illustrated in Example 10-121, "Creating Error Messages Using SHOW".
When handling errors in nested programs, the error-handling section in each program should restore the environment. It can also handle any special error conditions that are particular to that program. For example, when your program signals its own error, then you can include statements that test for that error.
Any other errors that occur in a nested program should be passed up through the chain of programs and handled in each program. To pass errors through a chain of nested programs, you can use one of two methods, depending on when you want the error message to be produced:
The error message is produced immediately, and the error condition is then passed through the chain of programs as illustrated in Example 10-157, "Producing a Program Error Message Immediately".
The error is passed through the chain of programs first, and the error message is produced at the end of the chain as illustrated inExample 10-158, "Producing a Program Error Message at the End of the Chain".
A SIGNAL statement is used in both methods.
To correctly handle errors that might occur while you are saving the session environment, place your PUSHLEVEL statement before the TRAP statement and your PUSH statements after the TRAP statement.
PUSHLEVEL 'firstlevel' TRAP ON error PUSH ...
In the abnormal exit section of your program, place the error label (followed by a colon) and the statements that restore the session environment and handle errors. The abnormal exit section might look like this.
error: POPLEVEL 'firstlevel' OUTFILE EOF
These statements restore saved dimension status and option values and reroute output to the default outfile.
You can explicitly compile a program by using a COMPILE statement. If you do not explicitly compile a program, then it is compiled when you run the program for the first time.
When a program is compiled, it translates the program statements into efficient processed code that executes much more rapidly than the original text of the program. When errors are encountered in the program, then the compilation is not completed, and the program is considered to be uncompiled.
After you compile a program, the compiled code is used each time you run the program in the current session. When you update and commit your analytic workspace after compiling a program, the compiled code is saved in your analytic workspace and used to run the program in future sessions. Therefore, be sure to update and commit after compiling a program. Issuing an update and commit after program compilation is particularly critical when the program is part of an application that is run by many users. Unless the compiled version of the program is saved in the analytic workspace, the program is recompiled individually in each user session.
Example 9-69, "Compiling a Program" illustrates using COMPILE to compile a program
You can use the ISCOMPILED choice of the OBJ function to determine whether a specific program in your analytic workspace has been compiled since the last time it was modified. The function returns a Boolean value.
SHOW OBJ(ISCOMPILED 'myprogram')
Program lines that include ampersand substitution are not compiled. Any syntax errors are not caught until the program is run. A program whose other lines compiled correctly is considered to be a compiled program.
When your program defines an object and then uses the object in the program, the program cannot be compiled. COMPILE treats the reference to the object as a misspelling because the object does not yet exist in the analytic workspace.
Even when your program compiles cleanly, you must also test the program by running it. Running a program helps you detect errors in statements with ampersand substitution, errors in logic, and errors in any nested programs.
To test a program by running it, use a full set of test data that is typical of the data that the program processes. To confirm that you test all the features of the program, including error-handling mechanisms, run the program several times, using different data and responses. Use test data that:
Falls within the expected range
Falls outside the expected range
Causes each section of a program to execute
Each time you run the program, confirm that the program executes its statements in the correct sequence and that the output is correct. As an aid in analyzing the execution of your program, you can include SHOW or TRACE statements in the program to produce diagnostic or status messages. Then delete the these statements after your tests are complete.
When you detect or suspect an error in your program or a nested program, you can track down the error by using the debugging techniques that are described in the rest of this section.
When you set the BADLINE option to YES, additional information is produced, along with any error message when a bad line of code is encountered. When the error occurs, the error message, the name of the program, and the program line that triggered the error are sent to the current outfile. You can edit the specified program to correct the error and then run the original program. See Example 5-4, "Using the BADLINE Option" for an example of using BADLINE.
When your program contains an error in logic, then the program might execute without producing an error message, but it executes the wrong set of statements or produces incorrect results. For example, suppose you write a Boolean expression incorrectly in an IF statement (for example, you use NE instead of EQ). The program executes the statements you specified, but it does so under the wrong conditions.
To find an error in program logic, you must often see the order in which the statements are being executed. One way you can do this is to create a debugging file and then examine the file to diagnose any problems in your programs by issuing the following DML statements:
Create a debugging file, by issuing an DBGOUTFILE statement.
Specify that you want each program line to be sent to the debugging file when a line executes by setting the PRGTRACE option to YES.
(Optional) When you want the debugging file to interweave the program lines with both the program input and error messages, set the ECHOPROMPT option to YES.
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See Also: The following examples of using a debugging file: |
You can invoke a program that does not return a value by using a CALL statement. You enclose arguments in parentheses, and they are passed by value. For example, suppose you create a simple program named addit to add two INTEGER values. You can use a CALL statement in the main program of your application to invoke the program.
You can also invoke programs in much the same way as you issue OLAP DML statements. You invoke user-defined functions in the same way as you use built-in functions. You use the program name in an expression and enclose the program arguments, if any, in parentheses. For a program that does not return a value (a user-defined command), you use the program name as you would an OLAP DML command. When you invoke a user-defined program as a function, the program returns NA.
You can also create programs that execute automatically when Oracle OLAP:
Executes an AW ATTACH. AW CREATE, AW DELETE, AW DETACH, DEFINE, MAINTAIN, PROPERTY, UPDATE, or SET statement as described in "Trigger Programs".
Encounters an NA value as described in $NATRIGGER.
This section provides overview information about the following types of programs:
Startup programs are programs that you write and that Oracle OLAP checks for by name when an AW ATTACH statement executes. Startup programs do not exist within an analytic workspace unless you define and write them. In a startup program you can execute any OLAP DML statements, or run any of your own programs. For example, a startup program might set options to values appropriate to your application.
When you first attach an analytic workspace, Oracle OLAP looks for and executes the Oracle OLAP startup programs (if they exist) in the order indicated:
Permission programs. The execution of a permission program is determined by the attachment mode specified in the AW ATTACH statement and whether or not a related permission program exists in the analytic workspace you are attaching. For more information, see "Permission Programs".
OnAttach programs. The execution of an OnAttach program is determined by how you code the ONATTACH and NOONATTACH clauses of the AW ATTACH statement and whether or not a program named ONATTACH exists in the analytic workspace you are attaching. For more information, see "OnAttach Programs".
Autogo programs. The execution of an Autogo program is determined by how you code the AUTOGO and NOAUTOGO clauses of the AW ATTACH statement and whether or not a program named AUTOGO exists in the analytic workspace you are attaching. For more information, see "Autogo Programs".
Trigger program. The execution of a Trigger program is determined by whether or not a program named TRIGGER_AW exists in an already attached analytic workspace. When a TRIGGER_AW program exists in one attached analytic workspace, it is executed whenever you create, attach, detach, or delete any other analytic workspace. For more information, see "Trigger Programs" and TRIGGER_AW.
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Note: Within a session, when you:
|
Permission programs are programs that you write that give permission to users to access workspace data. When a user first attaches an analytic workspace, Oracle OLAP checks to see if a permission program that is appropriate for the attachment mode exists.
|
Note: When you reattach an attached workspace, Oracle OLAP does not look for and execute permission programs. |
The permission program for each attachment mode must have a particular name as outlined in Table 6-2, "Names of Permission Programs for Different Attachment Modes".
Table 6-2 Names of Permission Programs for Different Attachment Modes
| Attachment Modes | Name of Program |
|---|---|
|
Read-only |
|
|
Multiwriter, Read/write |
|
When an appropriate permission program exists, Oracle OLAP executes the program. When a user specifies a password when attaching the analytic workspace, then the password is passed as an argument to the permission program for processing.
|
Note: A dimension surrogate has the access permissions of its dimension. Use a PERMIT on a dimension to grant or deny permission to access the values of a dimension surrogate for that dimension. |
Permission programs allow you to control two levels of access to the analytic workspace in which they reside.
Access at the analytic workspace level—Depending on the return value of the permission program, the user is or is not granted access to the entire analytic workspace. You can use the return value to indicate to Oracle OLAP whether or not the user has the right to attach the workspace.
Access at the object level—Within a permission program for read-only or read/write attachment, you can specify PERMIT statements that grant or restrict access to individual workspace objects. PERMIT programs must be in the same workspace as the objects for which they issue PERMIT statements.
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Note: All of the objects referred to in a given permission program must exist in the same analytic workspace. |
To create a permission program, define a user-defined function (as described in "Creating User-Defined Functions") with a recognized name, then define the contents for the program as described in "Specifying Program Contents".
An OnAttach program can have any name or it can explicitly be named ONATTACH.
|
Note: When an analytic workspace is created as an OLAP cube using the OLAP API, the OLAP API may also create a program namedONATTACH. You cannot modify an ONATTACH program that is automatically created in this way. Additionally, overriding the execution of ONATTACH is not recommended.
Consequently, when this type of |
How you specify the execution of an OnAttach program varies depending on its name:
When a program named ONATTACH. exists in an analytic workspace, each time you attach the workspace, that program executes automatically unless you include a NOOTTACH keyword in the AW ATTACH statement, or unless you include an ONATTACH clause that specifies a different program name.
To execute an OnAttach program that is not named ONATTACH, specify the name of the program within the ONATTACH clause of AW ATTACH statement.
|
Note: When you reattach an attached cached workspace, Oracle OLAP does not look for and execute OnAttach programs. To force an analytic worksapce to be fully detached so that Oracle OLAP will look for and execute OnAttach programs when you retach the workspace, specify the NOCACHE keyword in the DETACH statement that detaches the analytic workspace. |
An Autogo program can have any name or it can explicitly be named AUTOGO.
How you specify the execution of an Autogo program varies depending on its name:
When a program named AUTOGO exists in an analytic workspace, each time you attach the workspace, that program executes automatically unless you include a NOAUTOGO keyword in the AW ATTACH statement, or unless you include an AUTOGO clause that specifies a different program name.
To execute an Autogo program that is not named AUTOGO, specify the name of the program within the AUTOGO clause of AW ATTACH statement.
The OLAP DML provides support for importing data from relational tables, flat files, and spreadsheets into analytic workspace objects; and for exporting data from analytic workspace objects to relational tables, flat files, and spreadsheets.
You can embed SQL statements in OLAP DML programs using the OLAP DML SQL statement. Using the OLAP DML SQL statement you can import data from relational tables into analytic workspace objects and export data from analytic workspace objects to relational tables.
Using the OLAP DML SQL statement within an OLAP DML program you can copy relational data into analytic workspace objects using either an implicit cursor or an explicit cursor:
To copy data from relational tables into analytic workspace objects using an implicit cursor, use the SQL SELECT statement. You can use this OLAP DML statement interactively in the OLAP Worksheet or within an OLAP DML program.
To copy data from relational tables into analytic workspace objects using an explicit cursor, use the following statements in the order indicated. You can only use these statements within an OLAP DML program. You cannot use them interactively in the OLAP Worksheet.
SQL DECLARE CURSOR defines a SQL cursor by associating it with a SELECT statement or procedure.
SQL OPEN activates a SQL cursor.
SQL FETCH and SQL IMPORT retrieve and process data specified by a cursor.
PpSQL CLOSE closes a SQL cursor.
SQL CLEANUP cancels a SQL cursor declaration and frees the memory resources of an SQL cursor.
For examples of programs that copy table data into workspace objects, see SQL FETCH and SQL IMPORT.
Within a program, you can use an OLAP DML SQL statement with the INSERT keyword to copy data from analytic workspace objects into relational tables. Typically, you do this by issuing the following statements in your OLAP DML program:
SQL PREPARE statements, to precompile the INSERT and UPDATE statements.
SQL EXECUTE statements, to execute the statements that you precompiled in Step 1.
Oracle OLAP provides several statements that you can use to read data from flat files or to write data to flat files. These statements are frequently used together in a special program.
DEFINE, MAINTAIN, PROPERTY, SET (=) UPDATE, and AW commands are recognized by Oracle OLAP as events that can trigger the execution of OLAP DML programs.
Programs triggered by DEFINE, MAINTAIN, PROPERTY, UPDATE, or SET commands, are called object trigger programs and are discussed in this section and in the topic for the TRIGGER command.
A program named TRIGGER_AW that is defined within one analytic workspace and which is triggered when another analytic workspace is created, attached, detached or deleted. See the discussion of the "TRIGGER_AW" for more information.
Trigger programs are frequently written to maintain application-specific metadata. Trigger programs have certain characteristics depending on the statement that triggers them. Some trigger programs execute before the triggering statement executes; some after. Oracle OLAP passes arguments to programs triggered by some statements, but not others. Oracle OLAP does not change dimension status before most trigger programs execute, but does change dimension status before some MAINTAIN statements trigger program execution. In most cases, you can give a trigger program any name that you choose, but some events require a program with a specific name. "Characteristics of Object Trigger Programs" discusses these characteristics.
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See also: The following statements:
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Once an object is defined in an analytic workspace, you can create a trigger program for that object by following the following procedure:
Define the program as described in DEFINE PROGRAM.
Determine what to name the program and whether the program can be a user-defined program. (See Table 6-3, "Object Trigger Program Characteristics".) If the program can be a user-defined program, decide whether or not you want to define the trigger program as a user-defined function.
Code the actual program as described in"Specifying Program Contents".
Keep the following points in mind when coding trigger programs:
Use Table 6-3, "Object Trigger Program Characteristics" to determine if Oracle OLAP passes values to the program. If it does, use an ARGUMENT statement to declare these arguments in your program and the VARIABLE statement to define program variables for the values. (See Table 6-4, "Arguments Passed to Trigger Programs" for specific information about the arguments.)
A program that is triggered by an Assign event is executed each time Oracle OLAP assigns a value to the object for which the event was defined. Thus, a program triggered by an Assign event is often executed over and over again as the assignment statements loops through a object assigning values. You can use TRIGGERASSIGN to assign a value that is different from the value specified by the assignment statement that triggered the execution of the program.
In some cases, Oracle OLAP changes the status of the dimension being maintained when a Maintain event triggers the execution of a program. See Table 6-5, "How Programs Triggered by Maintain Events Effect Dimension Status" for details
Use the CALLTYPE function within a program to identify that the program was invoked as a trigger.
When the trigger program is not a TRIGGER_AFTER_UPDATE, TRIGGER_BEFORE_UPDATE, or TRIGGER_DEFINE program, associate the program with the desired object and event using the TRIGGER command.
There is no support for recursive triggers. You must set the USETRIGGERS option to NO before you issue the same DML statement within a trigger program that triggered the program itself. For example, assume that you have written a program named TRIGGER_MAINTAIN_ADD that is triggered by MAINTAIN ADD statements. Within the TRIGGER_MAINTAIN_ADD program, you must set the USETRIGGERS option to NO before you issue a MAINTAIN statement.
Object trigger programs have certain characteristics depending on the statement that triggers them. Some trigger programs execute before the triggering statement executes; some after. Oracle OLAP passes arguments to programs triggered by some statements, but not others. Oracle OLAP does not change dimension status before most trigger programs execute, but does change dimension status before some MAINTAIN statements trigger program execution. In most cases, you can give a trigger program any name that you choose, but some events require a program with a specific name.
Table 6-3, "Object Trigger Program Characteristics" lists the OLAP DML statements that trigger programs, the required name of the program (if any), whether or not Oracle OLAP uses values returned by the program, and whether or not Oracle OLAP passes arguments to the program.
Keep the following points in mind when designing trigger programs:
Triggers that execute before the DML statement—For trigger programs that execute before the triggering OLAP DML statement executes, you can define the trigger program as a user-defined function that returns a BOOLEAN value. The value returned by the program determines if Oracle OLAP executes the statement that triggered the execution of the trigger program. When the program returns FALSE, Oracle OLAP does not execute the triggering statement; when it returns TRUE or NA, the triggering statement executes.
Arguments passed to trigger programs—Oracle OLAP passes arguments to some trigger programs. These programs are identified in Table 6-3, "Object Trigger Program Characteristics". Descriptions of these arguments are provided in Table 6-4, "Arguments Passed to Trigger Programs". Use the ARGUMENT statement to declare these arguments in your program. Use VARIABLE to define program variables for the values. Use the WKSDATA function to retrieve the data type of an argument with a WORKSHEET data type.
Assign trigger programs—Oracle OLAP executes a program triggered by an Assign event each time it assigns a value to the object for which the event was defined. Thus, a program triggered by an Assign event is often executed over and over again as the assignment statements loops through a object assigning values. With each execution, the value to be assigned is passed as argument1 to the Assign trigger program. (See Table 6-4, "Arguments Passed to Trigger Programs" for more information and Example 10-163, "An ASSIGN Trigger on a Variable" for an example.) Within the Assign trigger program, you can use a TRIGGER ASSIGN statement to assign a different value than that specified by the assignment statement that triggered the execution of the Assign trigger program.
You can only assign values to a formula when the formula has an Assign trigger defined for it. When you assign a value to a formula with an Assign event, Oracle OLAP executes the trigger program for the event for assigned value and passes the assigned value to the trigger program. The Assign trigger does not change the definition of the formula itself. See Example 10-165, "An ASSIGN Trigger on a Formula" for an example of an Assign trigger on a formula.
Maintain trigger programs and dimension status —In some cases, Oracle OLAP changes the status of the dimension being maintained when a Maintain event triggers the execution of a program. See Table 6-5, "How Programs Triggered by Maintain Events Effect Dimension Status" for details.
Maintain triggers and dimension surrogates—Maintain triggers for dimension surrogates are different than Maintain triggers for other objects. You can only successfully issue a MAINTAIN statement against a dimension surrogate, when the dimension surrogate has a Maintain trigger. Issuing a MAINTAIN statement for a surrogate dimension that does not have a Maintain trigger, returns an error. Also, for Maintain Add and Maintain Merge triggers, whether or not an argument is passed to the program depends on the object on which the trigger is defined:
For dimension surrogates with a Maintain trigger, Oracle OLAP executes the trigger program one time for each value added or merged and passes that value into the program.
For other objects with a Maintain trigger, Oracle OLAP executes the trigger program only once after the MAINTAIN statement executes and no values are passed into the program
Table 6-3 Object Trigger Program Characteristics
| Triggering Statement (event) | Program Name | Return Values | Passed Arguments |
|---|---|---|---|
|
= (assignment) statement (SET) |
No required name |
No |
Yes |
|
DEFINE |
|
No |
No |
|
MAINTAIN ADD |
No required name |
No |
No |
|
MAINTAIN DELETE (not ALL) |
No required name |
Yes |
No |
|
MAINTAIN DELETE ALL |
No required name |
Yes |
No |
|
MAINTAIN MERGE |
No required name |
No |
No |
|
MAINTAIN MOVE |
No required name |
Yes |
Yes |
|
MAINTAIN RENAME |
No required name |
Yes |
Yes |
|
PROPERTY |
No required name |
Yes |
Yes |
|
UPDATE (Update AW) |
|
No |
No |
|
UPDATE (Update AW) |
|
Yes |
No |
|
UPDATE (Update Multi) |
No required name |
No |
No |
Table 6-4 Arguments Passed to Trigger Programs
| Event | Argument1 | Argument2 |
|---|---|---|
|
Property |
When the PROPERTY statement is assigning a property to an object, the name of the property. When the PROPERTY statement is deleting one or more properties, |
When the value of argument1 is |
|
Assignment |
The value to assign. When you know the data type of the object to which the value is assigned, specify that data type for the argument. When you do not know the actual data type, specify |
None. Oracle OLAP passes only one argument to the program. |
|
Maintain Add |
(Dimension surrogates only) The value added. ( | |
|
Maintain Rename |
The dimension value to rename. ( |
The new name of the dimension member. ( |
|
Maintain Merge |
(Dimension surrogates only) The value merged. ( | |
|
Maintain Move |
The position of the dimension value to move. ( |
The literal |
Table 6-5 How Programs Triggered by Maintain Events Effect Dimension Status
| Event Subevent | Dimension Status Before Program Execution |
|---|---|
|
Maintain Add |
Status set to dimension values just added. |
|
Maintain Delete |
Status set to dimension values about to be deleted. |
|
Maintain Delete All |
Current status is not changed. |
|
Maintain Merge |
Status set to dimension values just merged. |
|
Maintain Move |
Status set to dimension values about to be moved. |
|
Maintain Rename |
Current status is not changed. |
To aggregate, allocate, or model data using the OLAP DML, you first specify the calculation that you want performed by defining a calculation specification as outlined in "Creating Calculation Objects". Later, to populate variables with aggregated, allocated or modeled values as a Database maintenance procedure, write a program to execute the calculation object. For more information on the OLAP DML statements that you use in these programs, see "Running a Model", "Executing the Aggregation", and "Allocating Data".
The OLAP DML has several related statements that allow you to forecast data using the Geneva Forecasting engine which is a statistical forecasting engine from Roadmap Technologies that is used extensively in demand planning applications.
To forecast using the Geneva Forecasting engine, take the following steps:
Add the future time values to the time dimension.
Create a variable to hold the results of the forecast.
Write a forecasting program. Within the program, issue the following statements in the order indicated:
FCOPEN function -- Creates a forecasting context.
FCSET command -- Specifies the forecast characteristics.
FCEXEC command -- Executes a forecast and populates Oracle OLAP variables with forecasting data.
FCQUERY function -- Retrieves information about the characteristics of a forecast or a trial of a forecast.
FCCLOSE command -- Closes a forecasting context.
For examples of using these statements to forecast data see Example 9-119, "A Forecasting Program".
You can export an entire workspace, several workspace objects, a single workspace object, or a portion of an analytic workspace object to a specially formatted EIF file. Then you can import the information into a different workspace within the same schema or a different one.
One reason for exporting and importing is to move your data to a new location. Another purpose is to remove extra space from your analytic workspace after you have added and then deleted many objects or dimension values. To do this, issue an EXPORT statement to put all the data in an EIF file, create another workspace with a different name, and then use an IMPORT statement to import the EIF file into the new workspace. When you have imported into the same Database, you can delete the old workspace and refer to the new one with the same workspace alias that you used for the original one.
The following statement copies all the data and definitions from the current analytic workspace to an EIF file called reorg.eif in a directory object called mydir.
EXPORT ALL TO EIF FILE 'mydir/reorg.eif'
The MIN function calculates the smaller value of two expressions.
Return Value
DECIMAL. The results of MIN are dimensioned by the union of the dimensions of the two expressions.
Syntax
MIN(expression1, expression2)
Parameters
One expression to be compared.
The other expression to be compared.
Examples
Example 8-25 Calculating Whether Actual or Budget Values Are Smaller
Suppose, for each of the first six months of 1996, you want to find whether the actual value or the budget value is smaller for the line item Cost of Goods Sold (Cogs) in the Sporting division.
LIMIT line TO 'Cogs' LIMIT division TO 'Sporting' LIMIT month TO 'Jan96' TO 'Jun96' REPORT DOWN month actual budget MIN(actual budget)
The preceding statements produce the following output.
DIVISION: SPORTING
--------------LINE--------------
--------------COGS--------------
MIN
(ACTUAL
MONTH ACTUAL BUDGET BUDGET)
-------------- ---------- ---------- ----------
Jan96 287,557.87 279,773.01 279,773.01
Feb96 315,298.82 323,981.56 315,298.82
Mar96 326,184.87 302,177.88 302,177.88
Apr96 394,544.27 386,100.82 386,100.82
May96 449,862.25 433,997.89 433,997.89
Jun96 457,347.55 448,042.45 448,042.45
The NLSSORT function returns a string of bytes used to sort a text string. You can use this function to specify sorting and comparison operations based on a linguistic sort sequence rather than on the binary value of a string.
Return Value
RAW
Syntax
NLSSORT(char [, 'NLS_SORT = sort[_ai |_ci]' ])
Parameters
A text expression.
An NLS language.
Specifies an accent-insensitive sort.
Specifies a case-insensitive sort.
Examples
Example 8-36 Determining the Bytes by Which Values Are Sorted Based on Linguistic Sort Sequence
Assume you want to know the bytes by which a single value is sorted in the German language without regard to case. To do this you can execute the following SHOW command.
show NLSSORT('Mary Ann' , 'NLS_SORT = German_ai' )
501464820114555500010101010201010100
To see this same data for all of the values in a text dimension named myname are sorted, you can execute the following statement.
REPORT NLSSORT(MYname , 'NLS_SORT = German_ci' ) MYNAME NLSSORT(MYNAME , 'NLS_SORT = German_ci') ---------------- ---------------------------------------- Adelaid 1423284B143C23000101010101010100 Maryann 50146482145555000101010101010100 Mary Ann 501464820114555500010101010201010100 Donna 235A55551400010101010100
The TEXTFILL function reformats a text value to fit compactly into lines of a specified width, regardless of its current format. TEXTFILL is commonly used to reformat text with an unnecessarily ragged right margin or with a bad line width.
|
Note: TEXTFILL joins lines of text while reformatting, whereas ROW and REPORT reformat without joining lines. See Example 8-135, "The Effects of TEXTFILL on ROW" |
Return Value
TEXT or NTEXT
Syntax
TEXTFILL(text-expression, width)
Parameters
A text expression to be reformatted to the specified width, regardless of the current format of the data. When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
The desired width of the reformatted data, entered as an INTEGER value from 1 to 132.
In a structured report, TEXTFILL reformats text-expression to the width you specify if that width is less than the width of the report column. When width is greater than the column width, it is ignored by TEXTFILL, and the expression is reformatted to the width of the column.
TEXTFILL fits as many words of text-expression as it can onto one line, placing just one space between words and removing extra spaces between words. When a word is longer than width, TEXTFILL breaks it across two or more lines. In this case there may be extra spaces at the end of lines.
Examples
Example 8-135 The Effects of TEXTFILL on ROW
The following example shows the effect of TEXTFILL on a ROW command, using the nicely formatted text variable textvar.
The statement
SHOW textvar
produces the following output.
You can use the following options to control the format of your display. BMARGIN Controls the bottom margin. COLWIDTH Controls column width. COMMAS Controls the use of commas in numbers. DECIMALS Controls number of decimal places in numbers. LSIZE Controls the maximum length of a line. NASPELL Controls the spelling of NA values in output.
The ROW statement
ROW W 50 textvar
produces the following output.
You can use the following options to control the format of your display. BMARGIN Controls the bottom margin. COLWIDTH Controls column width. COMMAS Controls the use of commas in numbers. DECIMALS Controls the number of decimal places in numbers. LSIZE Controls the maximum length of a line. NASPELL Controls the spelling of NA values in output.
By contrast, the ROW statement with TEXTFILL
ROW W 50 TEXTFILL(textvar, 50)
produces the following output.
You can use the following options to control the format of your display. BMARGIN Controls the bottom margin. COLWIDTH Controls column width. COMMAS Controls the use of commas in numbers. DECIMALS Controls the number of decimal places in numbers. LSIZE Controls the maximum length of a line. NASPELL Controls the spelling of NA values in output.
The EXTBYTES function extracts a portion of a text expression.
Return Value
TEXT
Syntax
EXTBYTES(text-expression [start [length]])
Parameters
A TEXT expression from which a portion is to be extracted. When text-expression is a multiline TEXT value, EXTBYTES preserves the line breaks in the returned value.
An INTEGER that represents the byte position at which to begin extracting. The position of the first byte in text-expression is 1. When you omit this argument, EXTBYTES starts with the first byte.
An INTEGER that represents the number of bytes to be extracted. When length is not specified, or exceeds the number of bytes from start to the end of text-expression, the part from start to the end of text-expression is extracted.
Examples
Example 7-82 Extracting Text Characters Using Bytes
This example shows how to extract portions of text from the TEXT value 'hellotherejoe'.
The statement
SHOW EXTBYTES('hellotherejoe', 6, 5)
produces the following output.
there
The statement
SHOW EXTBYTES('hellotherejoe', 11)
produces the following output.
joe
The RECAP command sends statements that were previously entered during the current session to the current outfile or to a file that you specify. The statements are copied from the command log, which is a list of up to 256 statements that you have entered most recently during the current session.
|
Note: RECAP statements are not included in the command log. |
Syntax
RECAP [number|ALL] [ 'search-text' ] [ FILE file-name ]
Parameters
A positive INTEGER that indicates the number of statements to be provided. When you specify search-text, RECAP provides this number of statements from the subset that contains the search-text string. When you do not specify search-text, RECAP provides this number of statements from the most recently executed portion of the command log. The default number is 10.
When you specify search-text, ALL requests every statement that meets the search requirements. When you do not specify search-text, ALL requests every statement in the command log.
A quoted text literal. When you specify this argument, RECAP searches the statements in the command log for the ones that contain search-text. The search is not case-sensitive. These statements then compose the subset from which RECAP provides number or ALL statements.
Writes the output of a RECAP statement to the specified file For file-name specify a text expression that is the name of the file to which output should be written. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Usage Notes
Order of search-text Parameter
When you use both the search-text and the ALL or number arguments, you must specify search-text second.
RECAP with No Parameter
When you specify RECAP without an argument, the ten most recent statements are provided.
Re-Executing Statements
You can use the output of RECAP to edit a previously executed statement with REEDIT, or reexecute a previously executed statement with REDO.
Identifying Files and Directories
When specifying files and directories in OLAP DML statements, it is good practice to always enclose them in single quotes.
Examples
Example 10-88 Obtaining the Last Three Statements Containing "actual"
The following RECAP statement requests the three most recent statements that included the text literal "actual."
RECAP 3 'actual'
This statement could produce the following output.
COMMAND LOG
3: dsc actual
5: report total(actual)
8: report average(actual)
The ALLSTAT program sets the status of all dimensions in the current analytic workspace to all their values. ALLSTAT does not, however, set the status of the NAME dimension.
Syntax
ALLSTAT
Usage Notes
Limiting One Dimension
You can set the status of a single dimension to all its values with the LIMIT command.
ALLSTAT and the LOCK_LANGUAGE_DIMS Option
When LOCK_LANGUAGE_DIMS is TRUE, ALLSTAT ignores language dimensions. When LOCK_LANGUAGE_DIMS is FALSE, ALLSTAT treats language dimensions the same way it treats other dimensions.
Examples
Example 9-43 Limiting to All Values
The following STATUS statement produces the current status of the dimensions of the variable UNITS.
status units
The current status of MONTH is: Jul96 TO Dec96 The current status of PRODUCT is: Tents TO Racquets The current status of DISTRICT is: DALLAS
After you execute an ALLSTAT statement the same STATUS statement produces this output.
The current status of MONTH is: ALL The current status of PRODUCT is: ALL The current status of DISTRICT is: ALL
The NUMTODSINTERVAL function converts a number to a DSINTERVAL literal.
Syntax
NUMTODSINTERVAL (number, interval_unit)
Parameters
Any NUMBER value or an expression that can be implicitly converted to a NUMBER value.
A text value that specifies the unit of number and must resolve to one of the following string values: DAY, HOUR, MINUTE, or SECOND.
interval_unit is case insensitive. Leading and trailing values within the parentheses are ignored. By default, the precision of the return is 9.
The SIN function calculates the sine of an angle expression.
Return Value
NUMBER
The result returned by SIN is a value with the same dimensions as the specified expression.
Syntax
SIN(angle-expression)
Parameters
A numeric expression that contains an angle value, which is specified in radians.
Examples
The REPLBYTES function replaces one or more bytes in a text expression.
|
Tip: When you are using a single-byte character set, you can use the REPLCHARS function instead of the REPLBYTES function. Also, to change one or more occurrences of a specified string in a text value to another string, use the CHANGECHARS function |
Return Value
TEXT
Syntax
REPLBYTES(text-expression replacement [start])
Parameters
A TEXT expression in which REPLBYTES replaces bytes. When the bytes to replace from text-expression contain embedded line breaks, these breaks are removed. Other line breaks are preserved. Removed line breaks are not counted toward the total number of bytes replaced. Line breaks in the replacement expression are retained in the output of REPLBYTES, but are likewise not counted.
|
Tip: When you must use this function onNTEXT values, use the CONVERT or TO_CHAR function to convert the NTEXT value to TEXT. |
A text expression that contains one or more bytes that replaces existing bytes in text-expression.
An INTEGER that represents the byte position at which to begin replacing bytes. The position of the first byte in text-expression is 1. When you omit this argument, REPLBYTES starts with the first byte. REPLBYTES replaces as many bytes of text-expression as are required for the bytes specified by replacement. When the value of start is greater than the length of text-expression, REPLBYTES simply returns text-expression.
Examples
Example 8-76 Replacing Text as Bytes
This example shows how to replace a portion of the text value Hello there, Joe.
The statement
SHOW REPLBYTES('Hello there, Joe', 'Jane', 14)
produces the following output.
Hello there, Jane
Example 8-77 How REPLBYTES Handles Line Breaks
This example shows how REPLBYTES preserves but ignores line breaks.
var1 = JOINLINES('Hello' 'there' 'Joe')
var2 = JOINLINES('Hi' 'Jane')
The statement
SHOW REPLBYTES(var1 var2)
produces the following output.
Hi Janehere Joe
REPLBYTES has replaced the first 6 bytes of var1 (Hellot of HellothereJoe) with the 6 bytes of var2 (HiJane). It has preserved the line breaks following Hi (from var2) and there (from var1).
To replace all 13 bytes in var1, you must specify 13 replacement bytes; for example, you can add 7 spaces after Jane.
var2 = JOINLINES('Hi' 'Jane ')
The statement
SHOW REPLBYTES(var1 var2)
produces the following output.
Hi Jane
For each hierarchy of relation, the HIERDEPTH command calculates the depth of that hierarchy from the top of all of the hierarchies and stores that value in a previously-defined relation sometimes called the depth relation.
Syntax
HIERDEPTH parent-rel [(qdr-list)] INTO depth-rel [INHIERARCHY inh-valueset ]
Parameters
A child-parent self-relation for the hierarchical dimension. See "Parentrel Relation" for more information.
A list of QDRs that limits the values of parentrel. Specify the QDRs as described in "Syntax of a Qualified Data Reference". When you do not specify a value for qdrlist, HIERHEIGHT uses the values of parentrel that are in current status.
A previously -defined relation that the HIERDEPTH command populates when it executes. This relation can have multiple dimensions; however, it must be dimensioned by the dimensions of parentrel and one other NUMBER dimension that represents the depth of the hierarchical dimension.
For example, assuming that parent-rel has two dimensions, dim1 and dim2, the following lines of code define a NUMBER dimension named numdim with 3 values and, then, define a depth relation named depthrel which is dimensioned by dim1 and dim2 that has as its values the values of numdim.
DEFINE numdim dimension NUMBER(3) DEFINE depthrel RELATION numdim <dim1 dim2>
The name of a valueset object whose values are the hierarchical dimension values to be considered when creating grouping ids. Values not included in the valueset are ignored. See "Inhier Valueset or Variable" for more information.
Examples
Example 10-3 Creating and Populating a Depth Relation for Hierarchies
Assume that your analytic workspace contains the geog, geog_hierlist, and geog_parentrel objects described in Example 9-145, "Using GROUPINGID Command to Populate a Relation with Grouping Ids". You can create a depth relation for the hierarchies represented by these objects by issuing the following DML code.
" Define the number dimension for the depthrel
DEFINE numdepth DIMENSION NUMBER (3)
" Define the depth relation
" Populate the depth relation
HIERDEPTH geog_parentrel INTO depthrel
REPORT DOWN geog depthrel
------------------DEPTHREL-------------------
----------------GEOG_HIERLIST----------------
GEOG Political_Geog Sales_Geog
-------------- ---------------------- ----------------------
Boston 3 3
Springfield 3 3
Hartford 3 3
Mansfield 3 3
Montreal 3 3
Walla Walla 3 3
Portland 3 3
Oakland 3 3
San Diego 3 3
MA 2 2
CT 2 2
WA 2 2
CA 2 2
Quebec 2 2
East 0 1
West 0 1
All Regions 0 0
USA 1 0
Canada 1 0
All Countries 0 0
The TZ_OFFSET function returns the time zone offset corresponding to the argument based on the date the statement is executed.
|
Note: Timezone region names are needed by the daylight savings feature. The region names are stored in two time zone files. The default time zone file is a small file containing only the most common time zones to maximize performance. If your time zone is not in the default file, then you do not have daylight savings support until you provide a path to the complete (larger) file by way of the ORA_TZFILE environment variable. |
Return Values
A text value in the format shown below which represents the offset
'{ + | - } hh : mi'
Syntax
TZ_OFFSET( 'time_zone_name' | '{ + | - } hh : mi' | SESSIONTIMEZONE | DBTMEZONE)
Parameters
A text value that specifies a valid time zone name. For a listing of valid values for time_zone_name, query the TZNAME column of the V$TIMEZONE_NAMES dynamic performance view.
|
Note: Timezone region names are needed by the daylight savings feature. The region names are stored in two time zone files. The default time zone file is a small file containing only the most common time zones to maximize performance. If your time zone is not in the default file, then you do not have daylight savings support until you provide a path to the complete (larger) file by way of the ORA_TZFILE environment variable. |
Specifies a time zone offset from UTC (which simply returns itself)
Specifies the time zone of the current session.
Specifies the value of the Database time zone.
The OBJLIST function provides a list of the objects that are contained in one or more workspaces that you specify. The list of workspace objects returned by OBJLIST has duplicates removed and it is sorted in ascending order. The specified workspaces must be currently attached when you use the function.
The result, a multiline TEXT value, can be used as an argument to the OBJ function with the REFERS keyword. This usage helps in producing a cross-reference list for compilable objects, such as programs and models, in the current workspace.
|
Note: OBJLIST always returns the names of all the objects in a given workspace, even when you have limited its NAME dimension. |
Return Value
TEXT
Syntax
OBJLIST[(text-expression)]
Parameters
A text expression that contains a single name or several names of currently attached workspaces. Each workspace name must be on a separate line of a multiline TEXT value. When you do not supply this argument, OBJLIST uses the current workspace name. When text-expression includes the name of an analytic workspace that is not attached, OBJLIST does not return a value. Instead, it signals an error.
Examples
Example 8-57 Listing Objects in Three Workspaces
In the following example, OBJLIST returns a multiline TEXT value that includes all the objects in the three workspaces specified: mycode, mydata, and mytools. The statement
SHOW OBJLIST('mycode\nmydata\nmytools')
produces the following output.
ACTUAL
ADDFIVE
ADVERTISING
BUDGET
CITYLIST
CITYREPINIT
CITYREPS
...
YEAR
Example 8-58 Listing Referenced Objects
In the following example, OBJ(REFERS) returns a multiline TEXT value that contains every object from the mycode, mydata, and mytools workspaces that is referenced in the myprog program. The statement
SHOW OBJ(REFERS OBJLIST('mycode\nmydata\nmytools') 'myprog')
produces the following output.
ACTUAL BUDGET ... YEAR
The COLVAL function returns a numeric value from a column to the left of the current column in the same row of a report. COLVAL can only be used in the ROW command and the REPORT command.
Return Value
DECIMAL when the selected column contains numeric or Boolean data; NA when the column (n) contains only a TEXT or ID value; or an error when the specified column is the current column, a column to the right of the current column, or a nonexistent column
Syntax
COLVAL(n)
Parameters
The number of the column in the current row whose value you want; n can be any INTEGER expression.
Use a positive number to identify an absolute column number (counting left to right from the left margin of the report). In figuring an absolute column number, you must count all columns shown in the report. For example, when you are using a REPORT command that produces a column of labels down the left side of the report, you count this column of labels as column 1.For example, COLVAL(2) identifies the second column from the left margin of the report.
Use a negative number to identify a relative column number (counting right to left from the current column). For example, COLVAL(-2) identifies the column that is two columns to the left of the current column.
Examples
Example 7-46 Performing Column Calculations in a Report
Suppose in a report you want to show actual sales and planned sales, along with the difference between the two. You can use the COLVAL function to calculate this difference.
LIMIT month TO 'Jun96' LIMIT district TO 'Boston' FOR product ROW product sales sales.plan COLVAL(2)-COLVAL(3)
These statements produce the following output.
Tents 95,120.83 80,138.18 14,982.65 Canoes 157,762.08 132,931.39 24,830.69 Racquets 97,174.44 84,758.46 12,415.98 Sportswear 79,630.20 73,568.52 6,061.68 Footwear 153,688.02 109,219.15 44,468.87
(Read-only) The YESSPELL option holds the text that is used for TRUE Boolean values in the output of OLAP DML statements.
The value of the YESSPELL option is the word for "yes" in the current language, as specified by the NLS_LANGUAGE option. For example, when NLS_LANGUAGE is set to American, then the value of YESSPELL is YES. When NLS_LANGUAGE is set to Spanish, then the value of YESSPELL is SI.
Data Type
TEXT
Syntax
YESSPELL
Examples
The SWITCH command provides a multipath branch in a program. The specific path taken during program execution depends on the value of the control expression that is specified with SWITCH. You can use a SWITCH statement only within programs.
|
Note: Do not confuse the use of a single SWITCH command with the use of SWTICH as a conditional operator in an expression. See "SWITCH Expressions". |
Syntax
SWITCH control-expression
DO
CASE case-expression1:
statement 1.1
...
statement 1.n
BREAK
CASE case-expression2:
statement 2.1
...
statement 2.n
BREAK
[DEFAULT:
statement n.1
...
statement n.n
BREAK]
DOEND
Parameters
The control-expression argument determines the case label to which program control is transferred by the SWITCH statement. When the SWITCH statement is executed, control-expression is evaluated and compared with each of the CASE label expressions in the program. When a match is found, control is transferred to that case label. When no match is found, control transfers to the DEFAULT label (if present) or to the statement following the DOEND for SWITCH.
The CASE labels whose expressions (case-expression1, case-expression2, ...) specify the different cases you want to handle. When control-expression matches case-expression, program control is transferred to that CASE label. The CASE label expressions are evaluated at the time the program is run, in the order they appear, until a match is found.
The DEFAULT label is optional. It identifies a special case to which control should be transferred when none of the case-expressions matches the control-expression. When you omit DEFAULT, and no match is found, control is transferred to the statement that follows the DOEND for SWITCH.
All the CASE labels (including DEFAULT) for a SWITCH statement must be included within a DO/DOEND bracket immediately following the SWITCH statement. Because case-expression is a label, it must be followed by a colon (:). The statements to be executed in a given case must follow the label. Normally, the last statement in a case should be BREAK, which transfers control from SWITCH to the statement that follows the DOEND for SWITCH.
When you omit BREAK (or RETURN, SIGNAL, and so on) at the end of a case, the program goes on to execute the statements for the next case as well. Normally, you do not want this to happen. However, when you plan to execute the same statements for two cases, you can use this to your advantage by placing both CASE labels before the statements.
Usage Notes
Control and Case Expressions
The SWITCH control-expression can have any data type, as can the case-expressions. The various case-expressions can have different data types. When you specify the name of a dimension (as a literal, non-quoted text expression) as the control-expression or case-expression, Oracle OLAP uses the first value in the dimension's current status list, not the dimension name, as it searches for a match. When the dimension has no values in the status list, Oracle OLAP uses the value NA. An NA control-expression matches the first NA case-expression.
Do Not Use Ampersand Substitution with SWITCH
Avoid using ampersand substitution in a SWITCH control-expression or in a CASE label case-expression. Ampersands produce unpredictable, and usually undesirable, results.
Multiple SWITCH Commands
You can include multiple SWITCH statements in a program. You can also nest SWITCH commands. When a program contains multiple SWITCH commands, each can have its own DEFAULT label, even when the SWITCH commands are nested.
Transferring Control
While BREAK is commonly used to transfer program control within a SWITCH statement, it is not the only such statement you can use. You can also use statements such as CONTINUE, GOTO, RETURN, and SIGNAL. Keep in mind that you can use CONTINUE only when the SWITCH statement is within a FOR or WHILE loop. See also the entries for these statements and for DO ... DOEND.
Examples
Example 10-153 Multipath Branching Using SWITCH in a Program
The following program lines produce one of several types of reports. Before the SWITCH statement, the program determines which type of report the user wants and places the value Market or Finance in the variable userchoice. The program switches to the case label that matches that name and produces the report. When the report finishes, the BREAK statement transfers control to the cleanup section after the DOEND.
SWITCH userchoice
DO
CASE 'Market':
...
BREAK
CASE 'Finance':
...
BREAK
DEFAULT:
...
BREAK
DOEND
cleanup:
...
The NLS_DATE_FORMAT option specifies the default format for datetime values.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_DATE_FORMAT = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
Examples
The FILEREAD command reads records from an input file and processes data according to action statements that you specify. FILEREAD handles binary data, packed decimal data, and text. It can handle decimal data written in E-notation (such as .1E+9) or M-notation (such as 10M). It can convert the data to any appropriate data type before storing it in an Oracle OLAP variable, dimension, composite, or relation.
Syntax
FILEREAD fileunit [STOPAFTER n] [file-format] {[attribute...] action-statement1}
[[attribute...] action-statementN...]
where:
file-format specifies the format of the records in the input file. Use one of the following:
attribute provide information that is used by action statements.
For information on the placement of attributes in action statements, see "Placement of Field Attributes in FILEREAD".
action-statements perform processing, such as assignment statements and IF statements. An action-statement can be one of the following:
Parameters
A fileunit number assigned to a file that is opened for reading (READ mode) by a previous call to the FILEOPEN function.
The number of records to read from the input file. When STOPAFTER is left out, or specified with a negative number or an NA, FILEREAD processes the whole file. See "STOPAFTER Keyword".
Specifies that the record is organized in fixed-width columns, that is, character-by-character or byte-by-byte. All lines must have the same format. RULED is the default file format. Use the COLUMN, SPACE, and WIDTH attributes to specify the location of the data in the records.
CSV specifies that the data is in CSV (comma-delimited values) format. You must use the FIELD and SPACE attributes to specify the location of the data in the record.
dchar is a text expression that specifies a single character that you want Oracle OLAP to interpret as the general field delimiter in a structured file. Oracle OLAP uses the general field delimiter to identify both numeric and text fields. The default character is a comma (,).
CSV files are a common output format that is generated by spreadsheet programs. Each line of characters in a source file is treated as a single record. Each field in the record is separated by a comma by default. You can use the DELIMITER keyword to specify some other character as field delimiter.
When a group of characters in the input record is enclosed by double quotation marks, all of the following rules apply:
When the group includes the delimiter character, it is treated as a literal instead of as a delimiter.
When a double quotation mark (") is included in the group of characters, then it must be followed by another double quotation mark.
When a linefeed character (\n) is included in the group of characters, then it is ignored.
Any spaces or tabs that occur before or after the double quotation marks that enclose the group of characters is ignored.
Specifies that the record is in "structured prn" format. You must use the FIELD and SPACE attributes to specify the location of the data in the record.
Structured files are a common output format for PC software. They are text files in which the fields are composed of groups of characters. A group of characters is defined by two conditions: text enclosed in double quotes, or a sequence of numbers that is uninterrupted except by a decimal point. Consequently, an unquoted sequence of numbers containing a decimal point is stored as a single value; however, an unquoted sequence of numbers containing commas or other delimiters to mark off thousands is split into several values rather than stored as a single value. Any unquoted, non-numeric characters are ignored, except a minus sign that immediately precedes a number is considered to be part of the number. A space cannot separate the minus sign from the number.
When your file format does not conform to the pattern described here, you can use the TEXTSTART, TEXTEND, and DELIMITER keywords that let you customize the delimiters FILEREAD uses to identify the start and end of each field.
Specifies a single character that you want Oracle OLAP to interpret as the start of a text field in a structured file. schar is the value of the character. The default character is a double quote (").
Specifies a single character that you want Oracle OLAP to interpret as the end of a text field in a structured file. echarr is the value of the character. The default character is a double quote (").
Specifies a single character that you want Oracle OLAP to interpret as the general field delimiter in a structured file. Oracle OLAP uses the general field delimiter to identify both numeric and text fields. dchar is the value of the character. The default character is a comma (,).
The column in which the field starts in the input record. By default, field 1 begins in column 1 and subsequent fields begin in the column following the previous field. The current field's default column is the sum of the previous field's first column plus its width plus any spaces specified for the current field.
Table 9-7 File Attributes
| Syntax | Description |
|---|---|
|
{COLUMN|COL} n |
The column in which the field starts in the input record. By default, field 1 begins in column 1 and subsequent fields begin in the column following the previous field. The current field's default column is the sum of the previous field's first column plus its width plus any spaces specified for the current field. |
|
{SPACE|SP} n |
The number of spaces between a field and the preceding field. In a structured PRN file, the number of fields between the preceding and current field. The default is |
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{FIELD|FLD} n |
In a structured PRN file only, the field from which to extract the data. |
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{WIDTH|W} n |
For unstructured records, the number of columns the field occupies in the input record. When there is no default, WIDTH must be included for ruled records or FILEREAD generates an error. The default is derived from the data type according to the following list:
The maximum width is 4,000 characters for text input. |
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data-type |
One of the following keywords: INTEGER, SHORTINTEGER, DECIMAL, SHORTDECIMAL, NUMBER, TEXT, ID, DATE, VNF, RAW DATE, BOOLEAN.
|
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dimension-value-handling |
When the target object is a dimension or dimension surrogate, one of the following keyword clauses that specifies whether or not to add new values to the target object:
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input-field-format |
One of the following keywords that specifies the format of the input field:
|
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TRANSLATE|NOTRANSLATE |
Whether or not Oracle OLAP translates the data from the format of the original operating system, as identified by a FILESET ORIGIN statement. Specify TRANSLATE when you want Oracle OLAP to translate the data; or specify NOTRANSLATE when you do not want Oracle OLAP to translate the data. |
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SCALE n |
The number of digits to the right of the assumed decimal or binary point. The default is 0. When the input data is text, a decimal point in the input overrides the number specified by SCALE. |
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ZPUNCH|ZPUNCHL |
Provides information about how the input zone is overpunched. Specify ZPUNCH when the input is zone overpunched. Specify ZPUNCHL when the input is zone overpunched on the left. |
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LSET 'text' |
For text input and TEXT or ID target objects, adds text to the left of the value before storing. When text is a multiline value, only the first line is used. |
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RSET 'text' |
For text input and TEXT or ID target objects, adds text to the right of the value before storing. When text is a multiline value, only the first line is used. |
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stripping |
For text input, one of the following keywords that indicates if spaces or nulls are stripped from input value before storing in the target object:
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For binary or packed input, specifies that when the input is the specified numeric value, NA is assigned to the target object.
For text input, specifies that Oracle OLAP stores text as NA. When the input is the specified text, NA is assigned to the target object. Text can be a multiline string listing several possible NA values. In addition to the values specified for text, when the input is NA, then NA is assigned to the target object.
For textual numeric input, specifies that Oracle OLAP stores text as 0. When the input is the specified text, zero is assigned to the target object. Text can be a multiline string that lists several possible zero values. In addition to the values specified for text, when the input is 0, then 0 is assigned to the target object.
For text input that is BOOLEAN, specifies that Oracle OLAP stores text as YES. When the input is text then YES is assigned to the target object. Text can be a multiline string that lists several possible YES values. In addition to the values specified in text, when the input is YES, ON, or TRUE, YES is assigned to the target object.
For text input that is BOOLEAN, specifies that Oracle OLAP stores text as NO. When the input is text then NO is assigned to the target object. Text can be a multiline string that lists several possible NO values. In addition to the values specified in 'text,' when the input is NO, OFF, or FALSE, NO is assigned to the target object.
For text numeric input, specifies that Oracle OLAP fills any spaces in the resulting text with zeros. Any spaces in the input are replaced with zeros. The default is no filling with zeros.
You may specify one or more action statements to be performed each time a record is retrieved from the input file. Typically, you use action statements to set dimension status and assign data retrieved from the input record to a target object in Oracle OLAP. However, you may specify action statements that do not reference the data in the input record. For example, one of your action statements might be an assignment statement that simply increments a counter. Alternatively, an action statement might use the input data in some kind of processing, but not actually assign it to a target object in Oracle OLAP.
In your list of action statements, be sure to process dimensions before variables. FILEREAD processes each action statement from left to right for each input record. When an action statement performs dimension processing, the resulting status remains in effect for subsequent action statements. When you do not first specify action statements that limit a variable's dimensions, FILEREAD uses the first value in status to target a cell in the variable. Unless you specify an ACROSS phrase, FILEREAD assigns a single value from a field in an input record to a single cell in an Oracle OLAP variable. By default, FILEREAD does not loop over a variable's dimensions when assigning data to the variable. See "Field Order".
Use the VALUE keyword in FILEREAD action statements to represent the value in a particular field of the input record. VALUE represents this data, formatted according to the FILEREAD attributes you have specified. When the field in the record is blank, FILEREAD considers its value to be NA. By default, the data type of VALUE is the data type of the target object. However, you can specify a different data type with an attribute keyword.
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Note: When you have already specified action statements for use with FILEREAD, you can reuse the code with SQL FETCH and SQL IMPORT by simply adjusting the assignment statements and eliminating the VALUE keyword (if necessary). Most of the FILEREAD attributes (except for the attributes that control dimension processing) are not meaningful for SQL loading and are ignored when executing within SQL FETCH and SQL IMPORT. |
An assignment statement lets you assign a value to an Oracle OLAP object. An assignment statement has the following form.
object [= expression]
object is the target where the data is assigned and stored. The object can be an Oracle OLAP variable, dimension, dimension surrogate, composite, or relation.
expression is the source of the data value to be assigned to the target.
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Important: In a SQL FETCH or a SQL IMPORT assignment statement, the expression component is not optional. However, a FILEREAD assignment statement may consist only of an object name. In this case, the input data is assigned directly to object. An expression in a FILEREAD assignment statement may include the VALUE keyword. |
An IF statement lets you perform some action depending on whether a Boolean expression is TRUE or FALSE. An IF statement has the following form.
IF bool-exp
THEN action
[ELSE action]
IF evaluates the Boolean expression. When it is TRUE, the THEN action occurs. When it is FALSE, the ELSE action (if specified) occurs. When the Boolean expression is NA, no action occurs.
An action can be one of the following:
NULL (no action occurs)
An assignment statement
A SELECT statement
An IF statement
A DO … DOEND statement containing action-statements
A FILEREAD IF statement may contain invocations of the VALUE keyword. You can use a FILEREAD IF statement to process varying record types (such as records with different structures or different target objects) with one FILEREAD statement.
In FILEREAD, the VALUE keyword can be used more than once to represent different values from the same record. For each instance, specify the column from which to read each value.
A SELECT statement lets you perform some action based on the value of an expression. A SELECT statement has the following form.
SELECT select-expression
[WHEN expression1 action
[WHEN expression2 action . . .]
[ELSE action]
SELECT evaluates the SELECT expression and then sequentially compares the result with the WHEN expressions. When the first match is found, the associated action occurs. When no match is found, the ELSE action (if specified) occurs.
An action for a SELECT statement is the same as an action for an IF statement.
A FILEREAD SELECT statement may contain invocations of the VALUE keyword. You can use a FILEREAD SELECT statement to process varying record types (such as records with different structures or different target objects) with one FILEREAD statement.
An ACROSS statement causes the following action statement to execute once for every value in status of the ACROSS dimension. When you want the looping to apply to multiple action statements, enclose the action statements in angle brackets.
An ACROSS statement has the following syntax.
ACROSS dimension [limit-clause]:
action-statement
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
The following example limits month to the last six values, no matter what the current status of month is.
ACROSS month last 6: units
In a FILEREAD ACROSS statement, you can specify attributes to indicate the position in the record where Oracle OLAP begins reading the fields specified by the ACROSS phrase. To specify the position, use the attributes FIELD, SPACE, and COLUMN. A position attribute is optional when the series of fields specified in the ACROSS phrase begins in the next field for structured records, or the next byte for ruled records.
You can group several action statements by enclosing them in angle brackets. An action-statement-group has the following form.
<action-statement1 -
[action-statement2 . . .]>
A typical use for action statement groups is after an ACROSS statement. With the angle bracket syntax, you can cause multiple action statements to execute for every value in status of the ACROSS dimension.
Usage Notes
Reading One Record at a Time
As an alternative to FILEREAD, you can use the FILENEXT function to read one record at a time with one or more FILEVIEW statements to process the fields in the record.
Field Order
When an input record contains both dimension values and variable data, the dimension values must be the first fields that are read i Q߮n the record, and the variable data values must be read after those dimension values. To do this, you can either order the fields in the input record itself or you can use FILEREAD attributes to specify the field positions explicitly. (See the description for the attribute argument.)
To organize the input records so that you do not have to use position attributes with FILEREAD, put all of the dimension values in the first fields of the record and put the variable data values in the last fields of the record. For example, suppose that you have data for two variables (units and sales) that share the same dimensions in the same order (time, product, and geography). In this case, the first three fields in the input record should contain dimension values, while the fourth and fifth fields should contain variable data, such as in the following sample input record.
Sep99 Snowshoes Boston 35 5565.95
STOPAFTER Keyword
By default, FILEREAD automatically reads all the records in a file in sequential order. When you want to process only the first part of a file, use the STOPAFTER keyword. FILEREAD processes the number of records you specify, then stops. You can then close the file.
When you want to skip the first part of the file and process the remaining records, you can use the STOPAFTER keyword and omit the field descriptions. FILEREAD reads the number of records you specify without processing the data. Then you issue a second FILEREAD statement with field descriptions for processing the input. The following program lines illustrate this method.
LIMIT district TO 'Boston'
unit = FILEOPEN('bostdata' READ)
FILEREAD unit STOPAFTER 25
FILEREAD unit WIDTH 8 product SPACE 2 ACROSS month 13 TO 24:-
WIDTH 4 PACKED sales
Dimension Maintenance
When the target object of a field description is a dimension, you can specify whether or not to use the data in the file to add values to the dimension. The dimension attributes are MATCH and APPEND. When you are adding values to a dimension with APPEND, you can specify a dimension position attribute (LAST, FIRST, BEFORE pos, AFTER pos) immediately after APPEND.
In an assignment statement of the form object=expression, dimension attributes cannot appear on the right side of the equal sign, but must be specified before the target object. The only exception is when dimensions as target objects also appear on the right side, such as when you are maintaining a conjoint dimension. See Example 9-130, "Maintaining Conjoint Dimensions with File Data".
Dimension Position Numbers
When your input data consists of dimension position numbers, rather than dimension values, specify the conversion type as INTEGER in the field description, even though the dimension has a type of TEXT, ID, DAY, WEEK, MONTH, QUARTER, or YEAR.
FILEREAD unit COLUMN 1 WIDTH 8 INTEGER month
When the input contains position numbers, you cannot use the APPEND keyword to add new values to a dimension of type TEXT, ID, DAY, WEEK, MONTH, QUARTER, or YEAR, because the new position numbers have no associated value to be added.
Conjoint Dimension Maintenance
When a conjoint dimension is the target object, you can read its values using one of two methods:
Method One—When the input contains values or position numbers of the base dimensions, you must specify a dimension list surrounded by angle brackets after the equal sign, as shown in the following two sample lines.
FILEREAD unit proddist = <COL 1 W 10 product COL 20 - W 8 district> FILEREAD unit proddist = <COL 1 W 10 INTEGER product COL 20 - W 8 INTEGER district>
The preceding examples show values of the product and district dimensions being used to designate a value of the proddist concat dimension You could also use the APPEND attribute when you needed to maintain any of the dimensions. However, when you needed to process the values of product or district first, so that the syntax would require an equal sign inside the angle brackets, you would have to use an alternative method. (Nested equal signs are not allowed.) For this method you would read and process the base dimension values first, and then use the dimensions, without any field attributes, in the dimension list for the conjoint dimension. For example, to convert the base dimension values of a conjoint dimension to uppercase, use a statement similar to the following.
FILEREAD unit COL 14 W 8 product = UPCASE(VALUE) - COL 5 W 8 district = UPCASE(VALUE) - proddist = <product, district>
Method Two—When the input contains position numbers of the conjoint dimension itself, you must specify the INTEGER keyword.
FILEREAD unit INTEGER proddist
FILEREAD with Variables Dimensioned by Composites
When reading data into a variable dimensioned by a composite, FILEREAD automatically creates any missing target cells that are being assigned non-NA values. This process also adds to the composite all the dimension value combinations that correspond to those new cells. Thus, both the target object and the composite might be larger after an assignment.
Variables Dimensioned by Composites and Efficiency
When you use the automatic composite maintenance feature of FILEREAD to load data into variables dimensioned by composites, be aware of potential performance problems that might later occur when you attempt to access the variables' data. The position of a composite in the dimension list of a variable indicates whether or not performance might later become an issue.
When the composite appears at the end of the dimension list in the variable's definition (the slowest-varying position), you can use FILEREAD just as you would for a variable whose dimension list does not include composites. For example, you could use the same FILEREAD statements to read data into the variables newsales and newsales.cp (with the following definitions) without sacrificing efficiency.
DEFINE newsales VARIABLE DECIMAL <product district month> DEFINE newsales.cp VARIABLE DECIMAL <product SPARSE<district month>>
newsales.cp is dimensioned by three dimensions, the last two of which are in a composite. When, however, you have a variable like newsales2.cp (with the following definition) there can be performance implications for accessing data loaded with FILEREAD.
DEFINE newsales.cp VARIABLE DECIMAL <SPARSE<district month> product >
In this case, you can use one of two methods to avoid performance problems:
You can use CHGDFN with the SEGWIDTH keyword to change the segment size for the variable before using FILEREAD. CHGDFN SEGWIDTH lets you specify the size of a variable's segments. A segment is a portion of the total number of values a variable holds. The number of segments in a variable affects the performance of data loading and data accessing. The segment size that you specify with a CHGDFN SEGWIDTH statement is used not only for the variable you designate as varname, but also for all other variables and relations that are defined with the same combination of dimensions and composites in the same order.
You can explicitly add composite values just as you would for a conjoint dimension. You can use this method both for named and unnamed composites. See "Composite Maintenance".
Composite Maintenance
When you want to explicitly maintain composites with FILEREAD, use the same syntax that you use to maintain conjoint dimensions. When the composite is unnamed, refer to it with the form SPARSE<dim1 dim2 ...>. See "FILEREAD with Variables Dimensioned by Composites" and "Variables Dimensioned by Composites and Efficiency" to evaluate the advantages of explicit versus automatic composite maintenance with FILEREAD.
Using DWMQY Dimensions with FILEREAD
When the target object of a field is a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the default conversion type is VNF. Therefore, you do not have to specify a conversion type when the input values are formatted according to the VNF of the target dimension (or the default VNF when the dimension does not have a VNF of its own).
When the target object of a field is a DATE variable or a dimension of type DAY, WEEK, MONTH, QUARTER, and YEAR, FILEREAD interprets the values correctly when they are in a valid input style for dates as described in DATEORDER. For dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR, you must specify DATE as the conversion type. For values of a DATE variable, DATE is the default conversion type, so the DATE keyword is optional.
FILEREAD also interprets values of a time dimension or a DATE variable correctly when they are INTEGER values that represent dates (1 = January 1, 1900). In this case, you must specify RAW DATE as the conversion type.
Blank Fields
When a field is blank, its value is NA and NA is assigned to the target variable. Examples of blank fields are a text field filled with spaces, a field that begins beyond the end of the record, or a field in a structured file that has nothing, not even a space, between the field delimiters.
Placement of Field Attributes in FILEREAD
Normally, the field attributes immediately precede the target object or the expression on the right of the equal sign.
attributes object
However, when you want an attribute to apply to several fields, specify the attribute followed by the list of target objects surrounded by angle brackets. You can also include attributes that apply to one object by typing them inside the brackets before the object to which they apply.
attributes0 <attributes1 object1=expression object2 attributes3 object3>
Angle brackets are also used to surround the base values of a conjoint dimension value.
Handling Errors When FILEREAD Encounters an Error
When FILEREAD encounters an error, you can control what happens with an error trap and appropriate processing. Errors can be caused by attempts to convert data to an incompatible data type or by encountering invalid dimension values. You can use the FILEERROR function to get more information about what caused the error. After processing the error, you can use a TRAP statement to turn error trapping back on and GOTO to branch back to the FILEREAD statement. Processing continues with the next record. See Example 9-128, "Error Handling".
Specifying a Target Object that has NTEXT Values
When you specify a target object of type NTEXT for data from a structured or CSV file, FILEREAD translates the data from the file into the database character set before storing the values (even though they are assigned to an NTEXT object) which can result in data loss when the data from the file cannot be represented in the database character set. For data from a ruled file, which has fixed-width columns, FILEREAD does not translate into the database characters set, so there is no data loss.
Examples
Example 9-126 Dimension Values and Data
Suppose your analytic workspace contains six-character product identification numbers. You must import both product names and a value for the number of units sold each month. The data file for the last quarter has the following format.
Jan951234aa00Chocolate Chip Cookies 123 Jan951099bb00Oatmeal Cookies 145 Jan952355cc00Sugar Cookies 223 Jan955553ee00Ginger Snap Cookies 233 Feb951234aa00Chocolate Chip Cookies 123 Feb951099bb00Oatmeal Cookies O145 Feb952355cc00Sugar Cookies SS223 Feb955553ee00Ginger Snap Cookies G233 Mar952355cc00Sugar oCookies 223 Mar955553ee00Ginger Snap Cookies 233 Mar953222dd00Brownies 432
The dimension and variables have the following definitions.
DEFINE month DIMENSION MONTH DEFINE productid DIMENSION ID DEFINE productname VARIABLE TEXT <productid> DEFINE units.sold VARIABLE INTEGER <month productid>
The following program uses FILEREAD to add any new values for month and productid to the analytic workspace and to put the data in the correct variables. Maintain dimensions in one FILEREAD statement, close the file, and process it again to get the associated data.
DEFINE read.product PROGRAM
PROGRAM
VARIABLE fi INT
fi = FILEOPEN('Dr.Dat' READ)
FILEREAD fi COLUMN 1 APPEND WIDTH 5 month -
COLUMN 6 APPEND WIDTH 6 productid
FILECLOSE fi
fi = FILEOPEN('Dr.Dat' READ)
FILEREAD fi COLUMN 1 WIDTH 5 month -
COLUMN 6 WIDTH 6 productid -
COLUMN 12 WIDTH 30 productname -
COLUMN 44 WIDTH 22 units.sold
FILECLOSE fi
END
Example 9-127 Dimension Surrogate Values
This example uses one FILEREAD operation to add a value to the product dimension and assign a value to prodnum, which is a NUMBER dimension surrogate for the product dimension. It uses a second FILEREAD to assign a value to the units variable, which is dimensioned by month, product, and district. The data file for the dimension and surrogate values has the following format.
Kiyaks400
The following statements define a fileunit, open the file, read its contents and append a value to the product dimension and assign a value to the prodnum surrogate, and close the file.
DEFINE funit INT
funit = FILEOPEN('Ds.Dat' READ)
FILEREAD funit COL 1 APPEND W 6 product COL 7 ASSIGN W 3 prodnum
FILECLOSE funit
The data file for the variable value has the following format.
Jan02400Boston416
The following statements open the file, read its contents, match the value of the prodnum surrogate and assign a value to the units variable, and close the file.
funit = FILEOPEN('Var.Dat' READ)
FILEREAD funit COL 1 W 5 month COL 6 MATCH W 3 prodnum -
COL 9 W 6 district COL 15 W 3 INTEGER units
FILECLOSE funit
Example 9-128 Error Handling
When your input file has data that does not match the format specifications, or when it has a dimension value that is not part of the analytic workspace when you are using the default MATCH attribute, you get an error. You can use error processing at the trap label to check for that kind of error, skip the bad record, and continue processing the file. You can also use a FILEPUT statement to store the bad records in a separate file (see the FILEPUT command).
In the following example, the statements at the trap label check whether the file was successfully opened (fil.unit has an INTEGER value) and whether the user interrupted the program. When these are not the reason for the error, the program assumes it encountered a bad record, resets the trap, and branches back to the FILEREAD statement to continue processing with the next record.
DEFINE read.price PROGRAM
PROGRAM
VARIABLE fil.unit INTEGER
TRAP ON ERROR
fil.unit = FILEOPEN( ARG(1) READ)
LIMIT month TO &ARG(2)
NEXT:
FILEREAD fil.unit -
WIDTH 8 product -
WIDTH 4 BINARY price
FILECLOSE fil.unit
RETURN
error:
IF fil.unit EQ NA
THEN RETURN
IF ERRORNAME NE 'attn' AND ERRORNAME NE 'quit'
THEN DO
SHOW JOINCHARS('Record ' RECNO(fil.unit) ' is Invalid.')
TRAP ON ERROR
GOTO NEXT
DOEND
FILECLOSE fil.unit
END
Example 9-129 Preprocessing File Data Before Assigning to an analytic workspace Object
You can also process the data in each field before assigning it to a variable or dimension in the analytic workspace. Suppose your data file has product identifiers that are six-digit numbers, and your analytic workspace has a product dimension whose values are these same product numbers, preceded by a "P." You can process the identifiers in the file by adding a "P" at the beginning of each value.
FILEREAD unit COLUMN 1 WIDTH 6 APPEND LSET 'p' product
Example 9-130 Maintaining Conjoint Dimensions with File Data
To maintain a conjoint dimension with FILEREAD, you first maintain its base dimensions by appending any new values from the input file. Then you assign the resulting combination of base dimension values to the conjoint dimension. The following example gets base dimension values from two separate fields, appends the values to the base dimensions, then appends the combination to the conjoint dimension.
FILEREAD unit APPEND proddist = <W 8 product, W 8 district>
In the preceding statement, the angle brackets automatically cause APPEND to apply to all three dimensions. When you do not want to add new values to the base dimensions, but want only to add new conjoint dimension values, you must explicitly state the keyword MATCH or change the order of the target objects, as shown in the two following statements.
fileread unit APPEND proddist = <W 8 MATCH product,W 8 MATCH district>
or
FILEREAD unit W 8 product W 8 district APPEND proddist = <product, district>
Example 9-131 Reading Data From a Structured PRN File
Suppose you want to read data from a structured PRN file with values of the product dimension in field two, values of the district dimension in field three, and several months of sales values beginning in field six. You could read the first 10 records in the file with the following statement.
FILEREAD unit STOPAFTER 10 STRUCTURED FIELD 2 product - district FIELD 6 ACROSS month: sales
The BASEDIM function loops over a concat dimension and returns the name of the dimension from which the current value of a concat dimension comes.
Return Value
TEXT
Syntax
BASEDIM(concatdim [LEAF])
Parameters
Specifies the concat dimension for which you want the names of the base or component dimensions. The data type of the values returned is TEXT.
The LEAF keyword causes BASEDIM to return the names of the component dimensions of the concatdim dimension. The base dimensions of a concat dimension are the simple, conjoint, or other concat dimensions that you specify with the basedimlist argument when you define the concat. Simple dimensions and conjoint dimensions are the bottom-level components, or leaves, of a concat dimension.
When you specify a concat dimension as a base dimension when defining a concat, then the base dimensions of that inner concat are component dimensions of the outer concat. Using the LEAF keyword results in BASEDIM returning the names of the component simple and conjoint dimensions of the inner concat dimension.
When the base dimensions are all simple dimensions or conjoint dimensions, then the base dimensions are the bottom-level components and therefore BASEDIM returns the names of those dimensions whether or not you use the LEAF keyword.
When the base dimensions are all simple dimensions or conjoint dimensions, then the base dimensions are the bottom-level components and therefore BASEDIM returns the names of those dimensions whether or not you use the LEAF keyword.
Examples
Example 7-28 Returning Base Dimension Names
In this example the product dimension is limited to two values, the district dimension is limited to its first three values and the region dimension has only three values. The example defines a nonunique concat dimension with region and district as its base dimensions and then defines another nonunique concat dimension with product and the first concat dimension as its base dimensions. The example then gets the names of the base dimensions of the outer concat.
LIMIT district TO 'Boston' TO 'Chicago' LIMIT product TO 'Tents''Canoes' DEFINE region.district DIMENSION CONCAT(region district) DEFINE product.region.district DIMENSION CONCAT(product region.district) REPORT BASEDIM(product.district.region)
The preceding statements return the following.
PRODUCT PRODUCT REGION.DISTRICT REGION.DISTRICT REGION.DISTRICT REGION.DISTRICT REGION.DISTRICT REGION.DISTRICT
Example 7-29 Returning Component Dimension Names
This example uses the same objects as the previous example. It gets the names of the component dimensions of the concat dimension.
REPORT BASEDIM(product.region.district LEAF)
The preceding statement returns the following.
PRODUCT PRODUCT REGION REGION REGION DISTRICT DISTRICT DISTRICT
The MAX function calculates the larger value of two expressions.
Return Value
DECIMAL. The results of MAX are dimensioned by the union of the dimensions of the two expressions
Syntax
MAX(expression1, expression2)
Parameters
One expression to be compared.
The other expression to be compared.
Examples
Example 8-21 Calculating Whether Actual or Budget Values Are Larger
Suppose, for each of the first six months of 1996, you want to find whether the actual value or the budget value is larger for the line item Cost of Goods Sold (Cogs) in the Sporting division.
LIMIT line TO 'Cogs' LIMIT division TO 'Sporting' LIMIT month TO 'Jan96' TO 'Jun96' REPORT DOWN month actual budget MAX(actual budget)
The preceding statements produce the following output.
DIVISION: SPORTING
--------------LINE--------------
--------------COGS--------------
MAX
(ACTUAL
MONTH ACTUAL BUDGET BUDGET)
-------------- ---------- ---------- ----------
Jan96 287,557.87 279,773.01 287,557.87
Feb96 315,298.82 323,981.56 323,981.56
Mar96 326,184.87 302,177.88 326,184.87
Apr96 394,544.27 386,100.82 394,544.27
May96 449,862.25 433,997.89 449,862.25
Jun96 457,347.55 448,042.45 457,347.55
The OLAP_ON function returns a boolean indicating whether or not the OLAP option is installed in the database.
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Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
OLAP_ON ( )
RETURN BOOLEAN;
Returns
The value of the OLAP parameter in the V$OPTION table.
Example
The following PL/SQL code tests the value returned by OLAP_ON and returns a status message.
BEGIN
IF dbms_aw.olap_on() = true
THEN dbms_output.put_line('The OLAP option is installed');
ELSE dbms_output.put_line('The OLAP option is not installed');
END IF;
END;
/
The OLAP option is installed
The NLS_ISO_CURRENCY option specifies the international currency symbol for the C number format element.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_ISO_CURRENCY = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
The PUSH command saves the current status of a dimension (including the NAME dimension), the status of a valueset, or the value of an option or single-cell variable. You can then restore these saved values and status at a later time with a POP statement.
PUSH and POP are commonly used within a program to make changes to options and dimension status that apply only during the program's execution. Afterward, the options and status are the same as they were before the execution of the program.
Syntax
PUSH name1 [name]
Parameters
The name of a dimension, valueset, option, or variable whose status or value you want to save.
Usage Notes
Effect of a MAINTAIN Statement on a Dimension's Pushed Status
Using a MAINTAIN statement with a dimension clears that dimension's pushed status lists. For example, suppose you have pushed the dimension month several times, with different limits each time. When you then use a MAINTAIN statement to perform any maintenance activity on the month dimension, Oracle OLAP resets the status of month to ALL (the default), and popping that dimension has no effect.
Examples
Example 10-84 Saving and Restoring Values
The following program uses PUSH and POP to produce sales figures without decimal places for a specific selection of products, districts, and months, and then restores the status settings and the value of DECIMALS to what they were before the program was run.
DEFINE report1 PROGRAM PROGRAM TRAP ON cleanup PUSH DECIMALS product district month DECIMALS = 0 LIMIT product TO 'Sportswear' 'Footwear' LIMIT district TO 'Atlanta' 'Dallas' LIMIT month TO 'Jan96' TO 'Jun96' REPORT sales cleanup: POP DECIMALS product district month END
The DATE_FORMAT command assigns a format template to the definition of an object that has a DATETIME, TIMESTAMP, TIMESTAMP_TZ, TIMESTAMP_LTZ, DSINTERVAL, or YMINTERVAL data type.
The datetime format template is a template that describes the format of datetime data stored in a character string. The template does not change the internal representation of the value in the Database. When you convert a character string into a date, the template determines how Oracle OLAP interprets the string.
|
Note: You can only use this statement with objects that have a datetime data type that corresponds to a SQL datetime data type.You cannot use this statement for time dimensions that have a DATE-only data type that is unique to the OLAP DML. |
To assign a datetime format template to a definition, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
Syntax
DATE_FORMAT [datetime_format_template]
Parameters
An expression composed of one or more datetime format elements that specifies the format for entering and displaying the values of the current object. See Table 9-4, "Datetime Format Elements" for the elements that you can specify in the template. Keep the following points in mind when creating a template:
The total length of a datetime format template cannot exceed 22 characters
For input format models, format items cannot appear twice, and format items that represent similar information cannot be combined. For example, you cannot use 'SYYYY' and 'BC' in the same format string.
Some datetime format elements cannot be used in the TO_* datetime functions, as noted in Table 2-7, "Datetime Fields and Values".
The following datetime format elements can be used in timestamp and interval format models, but not in the original DATETIME format model: FF, TZD, TZH, TZM, and TZR.
Many datetime format elements are blank padded to a specific length.
When template is omitted, any existing date format template for the current definition is deleted and the default datetime format template is used. (See "Default Datetime Format Template", for a discussion of the default datetime format template.)
Table 9-4 Datetime Format Elements
| Element | Specify in TO_* datetime functions? | Description |
|---|---|---|
- / , . ; : "text" |
Yes |
Punctuation and quoted text is reproduced in the result. |
AD A.D. |
Yes |
AD indicator with or without periods. |
AM A.M. |
Yes |
Meridian indicator with or without periods. |
BC B.C. |
Yes |
BC indicator with or without periods. |
CC SCC |
No |
Century.
For example, 2002 returns 21; 2000 returns 20. |
D |
Yes |
Day of week (1-7). |
DAY |
Yes |
Name of day, padded with blanks to display width of the widest name of day in the date language used for this element. |
DD |
Yes |
Day of month (1-31). |
DDD |
Yes |
Day of year (1-366). |
DL |
Yes |
Returns a value in the long date format, which is an extension of Oracle Database's Restriction: You can specify this format only with the |
DS |
Yes |
Returns a value in the short date format. Makes the appearance of the date components (day name, month number, and so forth) depend on the Restriction: You can specify this format only with the |
DY |
Yes |
Abbreviated name of day. |
E |
No |
Abbreviated era name (Japanese Imperial, ROC Official, and Thai Buddha calendars). |
EE |
No |
Full era name (Japanese Imperial, ROC Official, and Thai Buddha calendars). |
|
Yes |
Fractional seconds; no radix character is printed (use the Examples:
|
|
Yes |
Returns a value with no leading or trailing blanks. See Also: "Format Model Modifiers" in Oracle Database SQL Language Reference |
|
Yes |
Requires exact matching between the character data and the format model. See Also: "Format Model Modifiers" in Oracle Database SQL Language Reference |
HH |
Yes |
Hour of day (1-12). |
HH12 |
No |
Hour of day (1-12). |
HH24 |
Yes |
Hour of day (0-23). |
IW |
No |
Week of year (1-52 or 1-53) based on the ISO standard. |
IYY IY I |
No |
Last 3, 2, or 1 digit(s) of ISO year. |
IYYY |
No |
4-digit year based on the ISO standard. |
J |
Yes |
Julian day; the number of days since January 1, 4712 BC. Number specified with J must be integers. |
MI |
Yes |
Minute (0-59). |
MM |
Yes |
Month (01-12; January = 01). |
MON |
Yes |
Abbreviated name of month. |
MONTH |
Yes |
Name of month, padded with blanks to display width of the widest name of month in the date language used for this element. |
PM P.M. |
No |
Meridian indicator with or without periods. |
Q |
No |
Quarter of year (1, 2, 3, 4; January - March = 1). |
RM |
Yes |
Roman numeral month (I-XII; January = I). |
RR |
Yes |
Lets you store 20th century dates in the 21st century using only two digits. See Also: "The RR Datetime Format Element" in Oracle Database SQL Language Reference |
RRRR |
Yes |
Round year. Accepts either 4-digit or 2-digit input. If 2-digit, provides the same return as |
SS |
Yes |
Second (0-59). |
SSSSS |
Yes |
Seconds past midnight (0-86399). |
TS |
|
Returns a value in the short time format. Makes the appearance of the time components (hour, minutes, and so forth) depend on the Restriction: You can specify this format only with the |
TZD |
Yes |
Daylight savings information. The Example: |
TZH |
Yes |
Time zone hour. (See Example: |
TZM |
Yes |
Time zone minute. (See Example: |
TZR |
Yes |
Time zone region information. The value must be a time zone region supported in the Database. Example: US/Pacific |
WW |
No |
Week of year (1-53) where week 1 starts on the first day of the year and continues to the seventh day of the year. |
W |
No |
Week of month (1-5) where week 1 starts on the first day of the month and ends on the seventh. |
X |
Yes |
Local radix character. Example: |
Y,YYY |
Yes |
Year with comma in this position. |
YEAR SYEAR |
No |
Year, spelled out; |
YYYY SYYYY |
Yes |
4-digit year; |
YYY YY Y |
Yes |
Last 3, 2, or 1 digit(s) of year. |
Usage Notes
Default Datetime Format Template
The default datetime format template is specified either explicitly with the initialization parameter NLS_DATE_FORMAT or implicitly with the initialization parameter NLS_TERRITORY. You can change the default datetime formats for your session with the ALTER SESSION statement.
ISO Standard Date Format Elements
Oracle calculates the values returned by the datetime format elements IYYY, IYY, IY, I, and IW according to the ISO standard.
For information on the differences between these values and those returned by the datetime format elements YYYY, YYY, YY, Y, and WW, see the discussion of globalization support in Oracle Database Globalization Support Guide.
The RR Datetime Format Element
The RR datetime format element is similar to the YY datetime format element, but it provides additional flexibility for storing date values in other centuries. The RR datetime format element lets you store 20th century dates in the 21st century by specifying only the last two digits of the year.
If you use the TO_DATE function with the YY datetime format element, then the year returned always has the same first 2 digits as the current year. If you use the RR datetime format element instead, then the century of the return value varies according to the specified two-digit year and the last two digits of the current year.
That is:
If the specified two-digit year is 00 to 49, then
If the last two digits of the current year are 00 to 49, then the returned year has the same first two digits as the current year.
If the last two digits of the current year are 50 to 99, then the first 2 digits of the returned year are 1 greater than the first 2 digits of the current year.
If the specified two-digit year is 50 to 99, then
If the last two digits of the current year are 00 to 49, then the first 2 digits of the returned year are 1 less than the first 2 digits of the current year.
If the last two digits of the current year are 50 to 99, then the returned year has the same first two digits as the current year.
Datetime Format Element Suffixes
Table 9-5, "Date Format Element Suffixes" lists suffixes that can be added to datetime format elements:
Table 9-5 Date Format Element Suffixes
| Suffix | Meaning | Example Element | Example Value |
|---|---|---|---|
|
TH |
Ordinal Number |
|
|
|
SP |
Spelled Number |
|
|
|
SPTH or THSP |
Spelled, ordinal number |
|
|
Keep the following in mind when using date format element suffixes:
When you add one of these suffixes to a datetime format element, the return value is always in English.
Datetime suffixes are valid only to format output. You cannot use them to insert a date into the Database.
Datetime Format Elements and Globalization Support
The functionality of some datetime format elements depends on the country and language in which you are using Oracle Database. For example, these datetime format elements return spelled values:
MONTH
MON
DAY
DY
BC or AD or B.C. or A.D.
AM or PM or A.M or P.M.
The language in which these values are returned is specified either explicitly with the initialization parameter NLS_DATE_LANGUAGE or implicitly with the initialization parameter NLS_LANGUAGE. The values returned by the YEAR and SYEAR datetime format elements are always in English.
The datetime format element D returns the number of the day of the week (1-7). The day of the week that is numbered 1 is specified implicitly by the initialization parameter NLS_TERRITORY.
|
See Also: Oracle Database Reference and Oracle Database Globalization Support Guide for information on globalization support initialization parameters |
Uppercase Letters in Date Format Elements
Capitalization in a spelled-out word, abbreviation, or Roman numeral follows capitalization in the corresponding format element. For example, the datetime format template 'DAY' produces capitalized words like 'MONDAY'; 'Day' produces 'Monday'; and 'day' produces 'monday'.
Punctuation and Character Literals in Datetime Format Templates
You can include these characters in a datetime format template:
Punctuation such as hyphens, slashes, commas, periods, and colons
Character literals, enclosed in double quotation marks
These characters appear in the return value in the same location as they appear in the format model.
Oracle returns an error if an alphanumeric character is found in the date string where a punctuation character is found in the format string. For example, the following format string returns an error:
TO_CHAR (TO_DATE('0297','MM/YY'), 'MM/YY')
Examples
Example 9-75 Changing the Datetime Format Template for an Object
Assume that the default datetime format template is DD_MON_RR as shown in the following statement.
SHOW NLS_DATE_FORMAT DD-MON-RR
Assume also that you define a variable named mydatetime and assign it the value of CURRENT_TIMESTAMP.
DEFINE mydatetime VARIABLE DATETIME mydatetime = CURRENT_TIMESTAMP
When you report on value of mydatetime, the following value is displayed. This value has the format determined by the setting NLS_DATETIME FORMAT. It shows only day, month, and year values in the order specified by
REPORT mydatetime MYDATETIME ----------- 02-FEB-07
Now you change the date format map for mydatetime by issuing the following statements.
CONSIDER mydatetime DATE_FORMAT MON-RRRR-DD-HH24
A display of the value of mydatetime, now includes hour as a 24-hour value.
REPORT mydatetime MYDATETIME -------------- FEB-2007-02-10
The REMBYTES function removes one or more bytes from a text expression and returns the value that remains.
Return Value
TEXT
Syntax
REMBYTES(text-expression start [length])
Parameters
The TEXT expression from which REMBYTES removes bytes. When the characters to be removed from text-expression contain embedded line breaks, these breaks are also removed. Other line breaks are preserved. Removed line breaks are not counted toward the total number of characters removed.
|
Tip: When you must use this function on NTEXT values, use the CONVERT or TO_CHAR function to convert the NTEXT value to TEXT. |
An INTEGER that represents the character position at which to begin removing characters. The position of the first character in text-expression is 1. When the value of start is greater than the length of text-expression, REMBYTES simply returns text-expression.
An INTEGER that represents the number of characters to be removed. When length is not specified, only the character at start is removed.
Examples
The AGGCOUNT function retrieves the values of the Aggcount variable associated with the specified variable. An Aggcount variable is an INTEGER variable that Oracle OLAP automatically creates when it creates a variable defined using a DEFINE VARIABLE statement that includes a USING AGGOUNT phrase.
Return Value
INTEGER
The values of the Aggcount variable that are the non-NA counts of the number of leaf nodes that contribute to the calculation of aggregate values when RELATION (for aggregation) statements that have an AVERAGE, HAVERAGE, WAVERAGE, or HWAVERAGE execute.
Syntax
AGGCOUNT(variable-name)
Parameters
The name of the variable with which the Aggcount variable is associated.
Examples
Example 7-3 Reporting on an Aggcount Variable
Assume that within your analytic workspace you have objects with the following definitions.
DEFINE geog DIMENSION TEXT DEFINE time DIMENSION TEXT DEFINE product DIMENSION TEXT DEFINE cc_geog_product COMPOSITE <geog product> COMPRESSED DEFINE sales VARIABLE DECIMAL <time cc_geog_product <geog product>> WITH AGGCOUNT DEFINE geog_parentrel RELATION geog <geog> DEFINE product_parentrel RELATION product <product> DEFINE time_parentrel RELATION time <time> DEFINE aggsales AGGMAP AGGMAP RELATION time_parentrel OPERATOR AVERAGE ARGS COUNT YES RELATION geog_parentrel RELATION product_parentrel END
Notice that the definition for the sales variable includes a request for an Aggcount variable and that, within the aggsales aggmap, the RELATION statement for the time_parentrel relation incudes an AVERAGE operator.
Assume also that when only the base values of the sales variable are populated, sales has the following values for Radios and TVs.
REPORT sales
PRODUCT: Radio
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 122.93 176.69 NA
California 168.32 150.92 NA
Quebec NA NA NA
Ontario 187.46 164.46 NA
USA NA NA NA
Canada NA NA NA
World NA NA NA
PRODUCT: TV
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 184.75 135.40 NA
California 139.89 145.71 NA
Quebec NA NA NA
Ontario 123.63 113.32 NA
USA NA NA NA
Canada NA NA NA
World NA NA NA
PRODUCT: AV
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine NA NA NA
California NA NA NA
Quebec NA NA NA
Ontario NA NA NA
USA NA NA NA
Canada NA NA NA
World NA NA NA
Since no aggregation has occurred, for AV, Oracle OLAP has not yet populated the Aggcount variable and the Aggcount variable for sales contains only NA values.
Now assume that you aggregate the sales variable by issuing the following statement.
AGGREGATE sales USING aggsales
A report of sales shows the following values.
REPORT sales
PRODUCT: Radio
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 122.93 176.69 149.81
California 168.32 150.92 159.62
Quebec NA NA NA
Ontario 187.46 164.46 175.96
USA 291.24 327.61 309.42
Canada 187.46 164.46 175.96
World 478.70 492.07 485.38
PRODUCT: TV
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 184.75 135.40 160.07
California 139.89 145.71 142.80
Quebec NA NA NA
Ontario 123.63 113.32 118.47
USA 324.64 281.11 302.87
Canada 123.63 113.32 118.47
World 448.27 394.42 421.35
PRODUCT: AV
-------------SALES--------------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 307.67 312.08 309.88
California 308.21 296.63 302.42
Quebec NA NA NA
Ontario 311.09 277.78 294.43
USA 615.88 608.71 612.30
Canada 311.09 277.78 294.43
World 926.97 886.49 906.73
A report of the Aggcount variable shows that it is populated with the INTEGER values that are needed to aggregate the average sales.
REPORT AGGCOUNT (sales)
PRODUCT: Radio
--------AGGCOUNT (SALES)--------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine NA NA 2
California NA NA 2
Quebec NA NA NA
Ontario NA NA 2
USA 2 2 4
Canada NA NA 2
World 3 3 6
PRODUCT: TV
--------AGGCOUNT (SALES)--------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine NA NA 2
California NA NA 2
Quebec NA NA NA
Ontario NA NA 2
USA 2 2 4
Canada NA NA 2
World 3 3 6
PRODUCT: AV
--------AGGCOUNT (SALES)--------
--------------TIME--------------
GEOG 2004 2005 Average
-------------- ---------- ---------- ----------
Maine 2 2 4
California 2 2 4
Quebec NA NA NA
Ontario 2 2 4
USA 4 4 8
Canada 2 2 4
World 6 6 12
The TRIGGER command associates a previously-created program to an object and identifies the object event that automatically executes the program; or disassociates a trigger program from the object.
To assign a trigger program to an object, the object must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
Syntax
TRIGGER {event-name [program-name] }... | {DELETE event-name}... | DELETE ALL
where event-name is one of the following:
You can use the same keyword many times in a single TRIGGER statement; however, in this case, Oracle OLAP ignores all but the last occurrence of the keyword. See "Multiple Occurrences of the Same Keyword", for details.
Parameters
Specifies that the trigger for the program is a Maintain event. A Maintain event is the execution of the MAINTAIN statement. As outlined in Table 8-19, "Subevents for the MAINTAIN Event", the Maintain event has several subevents that correspond to the major keywords of the MAINTAIN command. Exactly when a program triggered by a Maintain event is executed is dependent on the Maintain subevent that triggered the program and the object type for which the Maintain event is defined:.
Programs triggered by Maintain Add and Maintain Merge events on dimensions and composites are executed after the entire MAINTAIN statement executes.
Programs triggered by Maintain Add and Maintain Merge events on dimension surrogates are executed multiple times—once after each value is added or merged.
Programs triggered by other Maintain subevents are executed before the MAINTAIN statement is executed.
Specifies that the trigger for the program is a Delete event. A Delete event is a DELETE statement for the object. Oracle OLAP executes the specified program immediately before a DELETE statement deletes the object.
Specifies that Oracle OLAP executes the specified program in response to a Property event. A Property event is the execution of a PROPERTY statement to create, modify, or delete an object property. A program that is triggered by a Property event is executed before the statement that triggered it.
Specifies that Oracle OLAP executes the specified program in response to a Assign event. An Assign event is executed when SET assigns values to variable, relation, worksheet object, or a formula. A program that is triggered by SET is executed each time Oracle OLAP assigns a value to the object for which the event was defined. Thus, a program triggered by an Assign event is often executed over and over again as the assignment statements loops through a object assigning values.
When the object has been acquired using ACQUIRE in an analytic workspace that is attached in multiwriter mode, specifies that Oracle OLAP executes the specified program immediately after the object is updated.
|
Tip: To specify processing when the entire analytic workspace is updated, create a TRIGGER_AFTER_UPDATE or TRIGGER_BEFORE_UPDATE program. |
The name of the trigger program. When omitted for an event, the event does not trigger an action.
Deletes the triggers for the specified object events. Oracle OLAP disassociates the trigger program from the specified object event.
Deletes all of the triggers for the specified object. Oracle OLAP disassociates the trigger program from all events for object.
Usage Notes
Multiple Occurrences of the Same Keyword
You can use all of the keywords in a single TRIGGER statement. However, if you use the same keyword twice in a TRIGGER statement, then Oracle OLAP recognized the last occurrence of the keyword; other occurrences are ignored.
For example, assume that you code the following TRIGGER statement.
TRIGGER PROPERTY progname1 PROPERTY progname2 PROPERTY progname3
When executing this TRIGGER statement, Oracle OLAP executes progname3 immediately before a property of the object is created, modified, or deleted; Oracle OLAP does not execute progname1 or progname2.
Examples
Example 10-159 Creating Triggers
Assume that your analytic workspace contains a TEXT dimension named city and that you want to create programs that automatically execute when a MAINTAIN statement executes against city or when a property is created or deleted for city. To create these triggers, you issue the following statements.
"Define the trigger programs DEFINE trigger_maintain_move_city PROGRAM BOOLEAN DEFINE trigger_property_city PROGRAM BOOLEAN "Associate the trigger programs to events for the city dimension CONSIDER city TRIGGER PROPERTY trigger_property_city TRIGGER MAINTAIN trigger_maintain_move_city
Example 10-160 Describing Triggers
Assume that you have created the triggers for city as described in Example 10-159, "Creating Triggers" . Later you want to see the description of the triggers, to do so you cannot issue a DESCRIBE statement for your analytic workspace. Instead, you must issue a FULLDSC statement.
DEFINE CITY DIMENSION TEXT
TRIGGER MAINTAIN TRIGGER_MAINTAIN_MOVE_CITY -
PROPERTY TRIGGER_PROPERTY_CITY
DEFINE TRIGGER_MAINTAIN_MOVE_CITY PROGRAM BOOLEAN
DEFINE TRIGGER_PROPERTY_CITY PROGRAM BOOLEAN
Example 10-161 Deleting Triggers
Assume that you have created the triggers described in Example 10-159, "Creating Triggers" . Now you want to delete the MAINTAIN trigger for city. To delete this trigger you issue the following statements.
CONSIDER city TRIGGER DELETE MAINTAIN
When you issue a FULLDSC statement, you confirm that the MAINTAIN trigger for city has been deleted although the trigger_maintain_move_city program remains.
DEFINE CITY DIMENSION TEXT TRIGGER PROPERTY TRIGGER_PROPERTY_CITY DEFINE TRIGGER_MAINTAIN_MOVE_CITY PROGRAM BOOLEAN DEFINE TRIGGER_PROPERTY_CITY PROGRAM BOOLEAN
To actually delete the trigger_maintain_move_city program you must issue the following statement.
DELETE TRIGGER_MAINTAIN_MOVE_CITY
Example 10-162 A MAINTAIN Trigger Program
Assume that you have a dimension with the following definition in your analytic workspace.
DEFINE CITY DIMENSION TEXT
To create a Maintain trigger for city, you take the following steps:
Define the trigger program as a user-defined function. It can have any name that you want. The following statement defines a program named trigger_maintain_city.
DEFINE trigger_maintain_city PROGRAM BOOLEAN
Specify the content of the program.
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
RETURN TRUE
END
Issue a TRIGGER statement to associate the trigger program with the city dimension as a program to be executed when a Maintain event occurs. Remember to use a CONSIDER statement to make the definition for city the current definition.
CONSIDER city TRIGGER MAINTAIN TRIGGER_MAINTAIN_CITY
When you issue a FULLDSC statement to see a full description of your analytic workspace, you can see the definition of city (including its Maintain trigger) and the trigger_maintain_city program.
DEFINE CITY DIMENSION TEXT
TRIGGER MAINTAIN TRIGGER_MAINTAIN_CITY
DEFINE TRIGGER_MAINTAIN_CITY PROGRAM BOOLEAN
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
RETURN TRUE
END
As illustrated in the following statements and output, when you issue MAINTAIN statements for city, the trigger_maintain_city program executes.
MAINTAIN city ADD 'Boston' 'Houston' 'Dallas' calltype = TRIGGER triggering event = MAINTAIN triggering subevent = ADD REPORT city CITY -------------- Boston Houston Dallas MAINTAIN city MOVE 'Dallas' to 2 calltype = TRIGGER triggering event = MAINTAIN triggering subevent = MOVE REPORT city CITY -------------- Boston Dallas Houston
Example 10-163 An ASSIGN Trigger on a Variable
Assume that your analytic workspace contains objects with the following definitions.
DEFINE geog DIMENSION TEXT DEFINE sales VARIABLE DECIMAL <geog> DEFINE percent_sales VARIABLE INTEGER <geog>
The sales variable contains the following values.
GEOG SALES -------------- ---------- North America 0.59 Europe 9.35 Asia NA
The percent_sales variable is empty.
Assume that you want specialized processing of values when you assign values to percent_sales. To handle this processing automatically, you can create a Assign trigger program for percent_sales by taking the following steps:
Create a trigger program that executes each time you assign values to percent_sales.
DEFINE TRIGGER_EQ PROGRAM BOOLEAN
PROGRAM
ARGUMENT datavalue WORKSHEET
show 'description of triggering object = '
FULLDESCRIBE &TRIGGER(NAME)
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
SHOW JOINCHARS ('value being assigned = ' datavalue)
SHOW ' '
END
Add an assign trigger to percent_sales using a TRIGGER statement. Remember to first issue a CONSIDER statement to make the definition for the percent_sales variable the current definition.
CONSIDER percent_sales TRIGGER ASSIGN TRIGGER_EQ
Assign values to percent_sales.
percent_sales = (sales/TOTAL(sales))*100
Assigning values to percent_sales triggers the execution of the trigger_eq program and produces the following output lines.
description of triggering object = DEFINE PERCENT_SALES VARIABLE INTEGER <GEOG> TRIGGER ASSIGN TRIGGER_EQ calltype = TRIGGER triggering event = ASSIGN triggering subevent = value being assigned = 6 description of triggering object = DEFINE PERCENT_SALES VARIABLE INTEGER <GEOG> TRIGGER ASSIGN TRIGGER_EQ calltype = TRIGGER triggering event = ASSIGN triggering subevent = value being assigned = 94 description of triggering object = DEFINE PERCENT_SALES VARIABLE INTEGER <GEOG> TRIGGER ASSIGN TRIGGER_EQ calltype = TRIGGER triggering event = ASSIGN triggering subevent = value being assigned =
|
Note: From the output you can see that Oracle OLAP called thetrigger_eq program three times—each time it assigned a value to percent_sales. |
When you issue REPORT commands for sales and percent_sales you can see the result of the calculations. The percent_sales variable contains values that are the percent of sales for each continent.
GEOG SALES -------------- -------------------- North America 0.59 Europe 9.35 Asia NA GEOG PERCENT_SALES -------------- -------------------- North America 6 Europe 94 Asia NA
Example 10-164 Setting Values in an ASSIGN Trigger Program
Assume that you have the following objects in your analytic workspace.
DEFINE GEOGRAPHY DIMENSION TEXT WIDTH 12 LD Geography Dimension Values DEFINE PRODUCT DIMENSION TEXT WIDTH 12 LD Product Dimension Values DEFINE TIME DIMENSION TEXT WIDTH 12 LD Time Dimension Values DEFINE CHANNEL DIMENSION TEXT WIDTH 12 LD Channel Dimension Values DEFINE F.MARGIN FORMULA DECIMAL <CHANNEL GEOGRAPHY PRODUCT TIME> LD Margin EQ f.sales-f.costs DEFINE F.COSTS VARIABLE SHORT <GEOGRAPHY PRODUCT CHANNEL TIME> LD Costs DEFINE F.SALES VARIABLE SHORT <GEOGRAPHY PRODUCT CHANNEL TIME> LD Sales
Note that f.costs, f.sales, and f.margin all have the same dimensions.
Now you add an Assign trigger to f.margin that executes a program named t.margin. The definition of f.margin is modified to the following definition.
DEFINE F.MARGIN FORMULA DECIMAL <CHANNEL GEOGRAPHY PRODUCT TIME> LD Margin TRIGGER ASSIGN T.MARGIN EQ f.sales-f.costs
Now you actually write the t.margin program. When an expression is assigned to the f.margin formula, the program uses this value to compute new values for f.costs and f.sales.
DEFINE T.MARGIN PROGRAM PROGRAM ARG newVal DECIMAL " The value passed to the program by the Assign trigger VARIABLE t.valDiff DECIMAL " Difference between newVal and old value VARIABLE t.costInc DECIMAL " Amount the difference makes to costs "show the value of newVal SHOW 'newVal = ' NONL SHOW newVal " Compute the difference between the current value and the new one t.valDiff = newVal - f.margin " Now increase costs proportional to their existing amounts t.costInc = (newVal - f.margin) * (f.costs/f.sales) " Adjust the values of sales and costs to get the new value SET1 f.costs = f.costs + t.costInc SET1 f.sales = f.sales + t.valDiff + t.costInc SHOW geography NONL SHOW ' ' NONL SHOW product NONL SHOW ' ' NONL SHOW channel NONL SHOW ' ' NONL SHOW time NONL SHOW ' f.costs = 'NONL SHOW f.costs NONL SHOW ' f.sales = 'NONL SHOW f.sales END
Now assume that you issue the following LIMIT statements to identify a subset of data and issue a REPORT statement to report on the values of f.margin.
LIMIT t0.hierdim TO 'STANDARD'
LIMIT time TO t0.levelrel EQ 'L2'
LIMIT geography TO FIRST 1
LIMIT channel TO FIRST 1
LIMIT product TO FIRST 5
REPORT DOWN time ACROSS product: f.margin
GEOGRAPHY: WORLD
CHANNEL: TOTALCHANNEL
-----------------------F.MARGIN-----------------------
-----------------------PRODUCT------------------------
TIME TOTALPROD AUDIODIV PORTAUDIO PORTCD PORTST
-------------- ---------- ---------- ---------- ---------- ----------
Q1.96 54,713,974 29,603,546 5,379,661 2,480,914 1,615,708
Q2.96 63,919,784 34,594,087 6,331,848 2,869,265 1,931,785
Q3.96 58,303,490 31,543,152 5,792,725 2,616,515 1,795,701
Q4.96 71,197,892 38,383,878 7,059,581 3,163,804 2,232,880
Q1.97 55,489,723 29,989,262 5,368,237 2,491,475 1,607,344
Q2.97 41,687,908 22,532,979 4,070,725 1,855,992 1,245,161
Now you issue the following assignment statement that increase the value of f.margin by 10% and report it
f.margin = f.margin * 1.1
The execution of this assignment statement triggers the execution of the Assign trigger program named t.margin. The output of that program follows.
newVal = 60,185,371.40 WORLD TOTALPROD TOTALCHANNEL Q1.96 f.costs = 1,298,474.00 f.sales = 61,483,840.00 newVal = 32,563,900.67 WORLD AUDIODIV TOTALCHANNEL Q1.96 f.costs = 664,226.90 f.sales = 33,228,130.00 newVal = 5,917,626.67 WORLD PORTAUDIO TOTALCHANNEL Q1.96 f.costs = 97,976.04 f.sales = 6,015,603.00 newVal = 2,729,005.43 WORLD PORTCD TOTALCHANNEL Q1.96 f.costs = 34,301.53 f.sales = 2,763,307.00 newVal = 1,777,278.95 WORLD PORTST TOTALCHANNEL Q1.96 f.costs = 25,160.72 f.sales = 1,802,440.00 newVal = 70,311,762.13 WORLD TOTALPROD TOTALCHANNEL Q2.96 f.costs = 1,504,051.00 f.sales = 71,815,820.00 newVal = 38,053,495.70 WORLD AUDIODIV TOTALCHANNEL Q2.96 f.costs = 768,788.10 f.sales = 38,822,280.00 newVal = 6,965,032.86 WORLD PORTAUDIO TOTALCHANNEL Q2.96 f.costs = 114,558.20 f.sales = 7,079,591.00 newVal = 3,156,191.20 WORLD PORTCD TOTALCHANNEL Q2.96 f.costs = 39,256.88 f.sales = 3,195,448.00 newVal = 2,124,963.02 WORLD PORTST TOTALCHANNEL Q2.96 f.costs = 29,780.54 f.sales = 2,154,744.00 newVal = 64,133,838.86 WORLD TOTALPROD TOTALCHANNEL Q3.96 f.costs = 1,350,733.00 f.sales = 65,484,570.00 newVal = 34,697,467.06 WORLD AUDIODIV TOTALCHANNEL Q3.96 f.costs = 691,887.10 f.sales = 35,389,360.00 newVal = 6,371,997.63 WORLD PORTAUDIO TOTALCHANNEL Q3.96 f.costs = 103,203.70 f.sales = 6,475,202.00 newVal = 2,878,166.40 WORLD PORTCD TOTALCHANNEL Q3.96 f.costs = 35,358.18 f.sales = 2,913,525.00 newVal = 1,975,270.68 WORLD PORTST TOTALCHANNEL Q3.96 f.costs = 27,339.77 f.sales = 2,002,611.00 newVal = 78,317,681.06 WORLD TOTALPROD TOTALCHANNEL Q4.96 f.costs = 1,618,915.00 f.sales = 79,936,590.00 newVal = 42,222,265.94 WORLD AUDIODIV TOTALCHANNEL Q4.96 f.costs = 826,923.40 f.sales = 43,049,190.00 newVal = 7,765,539.34 WORLD PORTAUDIO TOTALCHANNEL Q4.96 f.costs = 123,269.50 f.sales = 7,888,809.00 newVal = 3,480,184.35 WORLD PORTCD TOTALCHANNEL Q4.96 f.costs = 41,998.90 f.sales = 3,522,183.00 newVal = 2,456,168.00 WORLD PORTST TOTALCHANNEL Q4.96 f.costs = 33,357.19 f.sales = 2,489,525.00 newVal = 61,038,695.03 WORLD TOTALPROD TOTALCHANNEL Q1.97 f.costs = 1,423,963.00 f.sales = 62,462,660.00 newVal = 32,988,187.65 WORLD AUDIODIV TOTALCHANNEL Q1.97 f.costs = 679,477.80 f.sales = 33,667,660.00 newVal = 5,905,060.56 WORLD PORTAUDIO TOTALCHANNEL Q1.97 f.costs = 158,854.40 f.sales = 6,063,915.00 newVal = 2,740,622.56 WORLD PORTCD TOTALCHANNEL Q1.97 f.costs = 53,144.41 f.sales = 2,793,767.00 newVal = 1,768,078.14 WORLD PORTST TOTALCHANNEL Q1.97 f.costs = 40,784.62 f.sales = 1,808,863.00 newVal = 45,856,698.46 WORLD TOTALPROD TOTALCHANNEL Q2.97 f.costs = 1,070,465.00 f.sales = 46,927,160.00 newVal = 24,786,276.35 WORLD AUDIODIV TOTALCHANNEL Q2.97 f.costs = 512,435.60 f.sales = 25,298,710.00 newVal = 4,477,797.64 WORLD PORTAUDIO TOTALCHANNEL Q2.97 f.costs = 118,791.70 f.sales = 4,596,590.00 newVal = 2,041,591.56 WORLD PORTCD TOTALCHANNEL Q2.97 f.costs = 39,287.77 f.sales = 2,080,879.00 newVal = 1,369,677.57 WORLD PORTST TOTALCHANNEL Q2.97 f.costs = 30,038.08 f.sales = 1,399,716.00
Example 10-165 An ASSIGN Trigger on a Formula
The way Oracle OLAP handles assigning values to a formula varies depending on whether or not the formula has an Assign trigger as part of its definition.
Assume your analytic workspace contains objects with the following definitions and values.
DEFINE geog.d DIMENSION TEXT DEFINE time.d DIMENSION TEXT DEFINE sales VARIABLE DECIMAL <time.d geog.d> DEFINE f_modified_sales FORMULA DECIMAL <time.d geog.d> EQ sales+20
A report of sales, shows the base values.
-------------------SALES-------------------
------------------TIME.D-------------------
GEOG.D Jan2004 Feb2004 Mar2004 2004
-------------- ---------- ---------- ---------- ----------
Boston 4.00 4.66 5.91 NA
Medford 4.37 5.80 4.45 NA
San Diego 4.97 5.95 4.75 NA
Sunnydale 5.85 5.26 4.08 NA
A report of f_modified_sales formula displays the following report that contains the values computed by the formula.
-------------F_MODIFIED_SALES--------------
------------------TIME.D-------------------
GEOG.D Jan2004 Feb2004 Mar2004 2004
-------------- ---------- ---------- ---------- ----------
Boston 24.00 24.66 25.91 NA
Medford 24.37 25.80 24.45 NA
San Diego 24.97 25.95 24.75 NA
Sunnydale 25.85 25.26 24.08 NA
The f_modified_sales formula does not presently have an Assign trigger on it. Consequently, as illustrated in the following code, any attempt to assign values to f_modified_sales results in an error.
f_modified_sales = 3 ORA-34142: You cannot assign values to a FORMULA.
To create an Assign trigger on f_modified_sales take the following steps:
Define the trigger program
DEFINE TRIGGER_ASSIGN_MODIFIED_SALES PROGRAM
PROGRAM
ARGUMENT datavalue NUMBER
SHOW 'description of triggering object = '
DESCRIBE &TRIGGER(NAME)
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('value being assigned = ' datavalue)
SHOW ' '
END
Add the Assign trigger to the definition of the formula using the following statements.
CONSIDER f_modified_sales TRIGGER ASSIGN trigger_assign_modified_sales
Issuing a FULLDSC f_modified_sales statement displays the new complete definition for f_modified_sales.
DEFINE F_MODIFIED_SALES FORMULA DECIMAL <TIME.D GEOG.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES EQ sales+20
Now when you issue the following statement to assign a value to f_modified_sales, an error does not occur. Instead, the trigger_assign_modified_sales trigger program executes 16 times, once for each dimension value of sales.
f_modified_sales = 3 description of triggering object = DEFINE F_MODIFIED_SALES FORMULA DECIMAL <TIME.D GEOG.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES EQ sales+20 calltype = TRIGGER triggering event = ASSIGN value being assigned = 3.00 description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ... description of triggering object = ...
However, as issuing a REPORT statement for f_modified_sales illustrates, the values calculated by a simple execution of the formula have not changed.
report f_modified_sales
-------------F_MODIFIED_SALES--------------
------------------TIME.D-------------------
GEOG.D Jan2004 Feb2004 Mar2004 2004
-------------- ---------- ---------- ---------- ----------
Boston 24.00 24.66 25.91 NA
Medford 24.37 25.80 24.45 NA
San Diego 24.97 25.95 24.75 NA
Sunnydale 25.85 25.26 24.08 NA
The FINDCHARS function returns the character position of the beginning of a specified group of characters within a text expression.
|
Tip: When you are using a multibyte character set, you can use the FINDBYTES function instead of the FINDCHARS function. |
Return Value
INTEGER
Syntax
FINDCHARS(text-expression, characters [starting-pos [LINENUM]])
Parameters
The text expression in which you are searching for the specified characters. Text-expression can be a multiline value. In this case, FINDCHARS searches all lines for the specified characters. The match must be exact, including a match of upper- and lowercase characters.
FINDCHARS accepts TEXT values and NTEXT values as arguments. When only one argument is NTEXT, then FINDCHARS automatically converts the other argument to NTEXT before performing the function operation
The group of characters for which you are searching. When characters is a multiline value, FINDCHARS ignores all lines except the first one.
When characters is not found in text-expression, FINDCHARS returns zero. When the group of characters occurs more than once, FINDCHARS returns the position of its first occurrence.
An INTEGER expression that specifies the character position where the search in text-exp should start. The default is at position 1 (the first character) in text-exp.
Specifies that FINDCHARS should return the line number instead of the character position of the beginning of the specified text.
Examples
Example 7-96 Finding the Starting Position of a Character Group
This example shows how to find the starting position of various groups of characters in the literal TEXT value hellotherejoe.
The statement
SHOW FINDCHARS('hellotherejoe', 'joe')
produces the following output.
11
The statement
SHOW FINDCHARS('hellotherejoe', 'al')
produces the following output.
0
The FILEGET function returns text from a non-binary file that has been opened for reading. When FILEGET reaches the end of the file, it returns NA. All text read with FILEGET is translated into the database character set. FILEGET cannot read data that cannot be represented in the database character set.
Return Value
TEXT
Syntax
FILEGET(fileunit [LENGTH int-expression])
Parameters
An INTEGER value that was assigned to a file opened for reading in a previous call to the FILEOPEN function.
An INTEGER expression specifying the number of bytes FILEGET returns from the file. When an end-of-line character is reached in the input file, FILEGET simply starts a new line in the result it is constructing. When LENGTH is omitted, FILEGET reads one line or record regardless of how many bytes it contains.
Usage Notes
Difference Between Number of Bytes Read and Number of Bytes Returned
The value specified by LENGTH refers to the number of bytes that the FILEGET function returns, not to the number of bytes that it reads. In some cases, these values may differ. For example, when the file being read contains a tab character, the number of bytes returned by FILEGET includes the bytes for tab expansion (if any); consequently, the number of bytes returned by FILEGET could be larger than the number of bytes read by FILEGET.
Examples
Example 7-89 Program for Reading a File
Suppose you have a program called readfile that takes a file name as its argument. It opens the file, reads the lines of the file, adds them to a multiline text variable named wholetext, then closes it. readfile uses local variables to store the fileunit number and each line of the file as it is read.
DEFINE wholetext VARIABLE TEXT LD Multiline text variable DEFINE readfile PROGRAM LD Program to store data from a file in a multiline text variable PROGRAM VARIABLE fil.unit INTEGER "Local Var To Store File Unit VARIABLE fil.text TEXT "Local Var To Store Single Lines FIL.UNIT = FILEOPEN(ARG(1) READ) FIL.TEXT = FILEGET(fil.unit) "Read The First Line WHILE fil.text NE NA "Test For End-of-file DO wholetext = JOINLINES(wholetext, fil.text) fil.text = FILEGET(fil.unit) "Read The Next Line DOEND FILECLOSE fil.unit END
Typically used only when debugging, the SESSCACHE option controls whether Oracle OLAP creates an Oracle OLAP session cache described in "What is an Oracle OLAP Session Cache?".
Data Type
BOOLEAN
Syntax
SESSCACHE = {YES|NO}
Parameters
The session cache is created to hold the data described in "What is an Oracle OLAP Session Cache?".
Oracle OLAP does not read or write to the session cache. When you specify NO, caching does not occur even when you have specified caching by coding a CACHE SESSION statement in the specification for one or more aggmap objects, by setting one or more $VARCACHE properties to SESSION, or by setting the VARCACHE option to SESSION.
Usage Notes
What is an Oracle OLAP Session Cache?
An Oracle OLAP session cache is a special place in memory used to hold:
All data that was calculated on the fly when an AGGREGATE function executed in the following situations:
The specification for the aggregation included a CACHE SESSION.
The specification for the aggregation did not include a CACHE SESSION statement, but the variable being aggregated had a $VARCACHE property with the value of SESSION.
The specification for the aggregation did not include a CACHE SESSION statement and the variable being aggregated did not have a $VARCACHE property, but the VARCACHE option was set to SESSION.
The NA values (only) that were calculated when an AGGREGATE function executed and the specification for the aggregation included a CACHE NA statement.
All data that was calculated when a $NATRIGGER expression executed in the following situations:
The variable with the $NATRIGGER property also had a $VARCACHE property with the value of SESSION.
The variable with the $NATRIGGER property did not have a $VARCACHE property, but the VARCACHE option was set to SESSION.
There is one internal cache for a session. Cached data is ignored by UPDATE and COMMIT statements. However, once data is cached, Oracle OLAP uses the values in the cache for all calculations unless an AGGREGATE function with the FORCECALC keyword executes. In this case, the FORCECALC keyword specifies that Oracle OLAP recalculate the values.
When a session is terminated, its cache is cleared. To clear the session cache without terminating the session, issue a CLEAR statement.
The effectiveness of a session cache is tracked in the V$AW_CALC dynamic performance view.
The AW_UPDATE procedure saves the changes made to an analytic workspace in its permanent database table. For the updated version of this table to be saved in the database, you must issue a SQL COMMIT statement before ending your session.
If you do not specify an analytic workspace to update, AW_UPDATE updates all the user-defined workspaces that are currently attached with read/write access.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_UPDATE (
awname IN VARCHAR2 DEFAULT NULL);
AW_UPDATE (
schema IN VARCHAR2 DEFAULT NULL,
awname IN VARCHAR2 DEFAULT NULL);
Parameters
Table B-18 AW_UPDATE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
Saves changes to awname by copying them to a table named |
Example
The following commands save changes to the GLOBAL analytic workspace from the temporary to the permanent tablespace, then commit the change to the database.
EXECUTE dbms_aw.aw_update('global');
COMMIT;
The CLEAR command deletes the data that you specify for one or more variables.
Syntax
CLEAR [STATUS | {ALL [CACHE]}] [VALUES | {aggdata [USING aggmapname]}] -
FROM {varname [ ( PARTITION partition-name ) ] } [, ... ]
where aggdata is one or more of the following keywords that identifies the type of aggregated data that you want deleted from the variable.
Parameters
Specifies that only the data that is currently in status is taken into consideration. (Default)
|
Tip: When clearing a compressed composite, do not execute a CLEAR when only some values are in status. |
Specifies that the command consider all of a variable's data regardless of the current status. Required when you specify either the CACHE or AGGREGATES keywords.
Empties the session cache. When you specify this keyword, you must also specify the ALL keyword.
(Default) Deletes all of a variable's stored data and replaces each deleted data value with an NA value.
Deletes the data in all cells populated by the execution of an AGGREGATE command or an AGGREGATE function. When you specify this keyword, you must also specify the ALL keyword.
For all variables except those dimensioned by a compressed composite, deletes any data that was calculated when an AGGREGATE command executed and replaces that data with NA values.
Deletes any data that was calculated on the fly when a AGGREGATE function executed and replaces that data with NA values.
Deletes the detail-level data, meaning, the "leaf" data.
|
Note: You cannot specify this keyword for a variable dimension by a compressed composite. |
The name of a variable from which data is deleted.
The name of the aggmap that should be used.
You must include this phrase to clear a variable that is not a compressed composite or that does not have an $AGGMAP property. You do not have to specify this phrase to clear:
A variable that is dimensioned by a compressed composite. By default, CLEAR uses the structure of the compressed composite to clear the variable.
A variable that has an $AGGMAP property when you want CLEAR to use the aggmap specified by that property. If you do not specify a USING phrase for a variable that has an $AGGMAP property, then CLEAR uses the aggmap specified by that property.
When you include this phrase for a dimensioned aggmap, the dimensionality of every variable included in the CLEAR command must be identical to the dimensionality of the aggmap. In other words, every variable definition must have the same dimensions in the same order as those in the definition of the aggmap.
For a partitioned variable, specifies the name of a partition from which you want to clear data.
|
Note: Clearing only a single partition of a compressed composite is resource intensive and time consuming as the variable is decompressed during the process. |
Examples
Example 9-65 Clearing a Variable's Data
The CLEAR command gives you an easy way to delete all of a variable's stored data. Suppose you have defined a sales variable and loaded data into it. You then find out that much of this data has changed. It is more efficient to clear the sales variable and reload all of the data than it would be to change the existing data. You can do so with the following statement.
CLEAR ALL FROM sales
In this example, the VALUES keyword is assumed by default. Therefore, all of the sales data is deleted and replaced with NA values.
Example 9-66 Clearing Aggregated Data
Suppose you have aggregated data for your sales and units variable, and you have specified that all other data should be calculated on the fly.
The sales and units variables are defined with the same dimensions in the same order: time, product, and geography. Therefore, they have been aggregated with the sales.agg aggmap, which has the following definition.
DEFINE sales.agg AGGMAP <time, product, geography>
The sales.agg aggmap has the following contents.
RELATION time.r PRECOMPUTES (time ne 'YEAR99') RELATION product.r PRECOMPUTES (product ne 'ALL') RELATION geography.r
After aggregating both sales and units, you learn that there are certain geographic regions that none of your users access. Because geography is the slowest-varying dimension, you can probably reduce the number of pages needed to store data by deleting data for the geographic regions that no one needs which can reduce the size of your analytic workspace and possibly improve performance.
Set the status for each dimension. The only geographic regions that users need are New England, Europe, and Australasia. The following statements put all time periods and all products for every geographic region in the current status, except for the geographic regions that users need. In other words, the following statements put all of the data that users do not have to access in status.
LIMIT time TO ALL LIMIT product TO ALL LIMIT geography COMPLEMENT 'NewEngland' 'Europe' 'Australasia'
Use the following statement to delete the unneeded data.
CLEAR STATUS PRECOMPUTES FROM sales units USING sales.agg
Example 9-67 Clearing Cached Data
Data is cached when an aggmap specifies calculation on the fly and contains a CACHE SESSION statement.
For example, suppose the sales.agg aggmap has the following contents.
RELATION time.r PRECOMPUTES (time ne 'YEAR99') RELATION product.r PRECOMPUTES (product ne 'ALL') RELATION geography.r CACHE SESSION
Note that the sales.agg contains a CACHE SESSION command. Consequently, Oracle OLAP calculates some data at the time a user requests it, and then stores it in the session cache. To clear this data from the sales variable, use the following statement.
CLEAR ALL CACHE FROM sales
The REGRESS.REPORT program produces a standard report of a regression performed using the REGRESS command.
Syntax
REGRESS.REPORT
Examples
Example 10-93 Report for a Simple Regression
Assume that you have performed the simple regression illustrated in Example 10-91, "Simple Regression" . You can now execute REGRESS.REPORT to see the results of the regression.
Regression Analysis
===================
Dependent Variable: SALES
WEIGHTBY Variable: NONE
Regressor Coefficient Std. Error T-ratio
-------------------- ------------ ------------ --------
ADVERTISING 0.36 0.16 2.24
PRICE -8.66 1.80 -4.82
EXPENSE 1.05 0.01 79.69
Corrected R-square 1.00
F-Statistic (2, 141) NA
Number of observations 144
Standard error of estimate 1,477.16
Example 10-94 Report for a Weighted Regression
Assume that you have performed the simple regression illustrated in Example 10-92, "Weighted Regression" . You can now execute REGRESS.REPORT to see the results of the regression.
Regression Analysis
===================
Dependent Variable: SALES
WEIGHTBY Variable: RELIABILITY
Regressor Coefficient Std. Error T-ratio
-------------------- ------------ ------------ --------
ADVERTISING 0.44 0.17 2.64
PRICE -8.03 1.92 -4.19
EXPENSE 1.04 0.01 76.45
Corrected R-square 1.00
F-Statistic (2, 141) NA
Number of observations 144
Standard error of estimate 1,373.15
The ROOTOFNEGATIVE option determines the result of any attempt to obtain a root of a negative number.
Data Type
BOOLEAN
Syntax
ROOTOFNEGATIVE = YES|NO
Parameters
Allows any attempt to obtain a root of a negative number. Consequently, a statement that attempts to obtain a root of a negative number executes without an error; however, the result of the attempt to obtain the root is NA. When you are working with a dimensioned variable or expression, setting ROOTOFNEGATIVE to YES enables you to obtain the root of most of the expression's values when a few of the values might be negative.
(Default) Disallows any attempt to obtain a root of a negative number. Any statement that attempts to obtain a root of a negative number stops executing and an error message is produced.
Usage Notes
Raising to a Noninteger Power
Raising a number to a noninteger power (for example, 5 ** 0.3 or 14 ** 2.7) is an attempt to obtain a root.
Examples
Example 5-96 The Effect of ROOTOFNEGATIVE
The following example shows the effect of changing the value of the ROOTOFNEGATIVE option. The variable TESTNUMBER has a value of -56. When you execute a SHOW statement such as the following one, without changing the ROOTOFNEGATIVE option from its default value of NO, an attempt is made to obtain the square root and then an error message is produced.
SHOW SQRT(testnumber)
When you change ROOTOFNEGATIVE to YES, the same statement executes without error
ROOTOFNEGATIVE = YES SHOW SQRT(testnumber)
and produces the following result.
NA
The DAYABBRLEN option specifies the number of characters to use for abbreviations of day names that are stored in the DAYNAMES option. You can specify how many characters to use for abbreviating particular day names when you specify the <WT>, <WTXT>, and <WTXTL> formats with the DATEFORMAT text option.
Data Type
TEXT
Syntax
DAYABBRLEN = specification [;|, specification]...
where specification is a text expression that has the following form:
startpos [- endpos] : length
You can define many different groups of days, each with different abbreviation lengths. When you do so, separate the groups with a comma or a semicolon as shown in the syntax.
Parameters
Numbers that represent the first and last days whose abbreviation length is defined by length. These numeric positions apply to the corresponding lines of text in the DAYNAMES option. You can specify these ranges of values in reverse order, endpos [-startpos], when you prefer.
The DAYNAMES option can have more than seven lines, so you can specify startpos and endpos greater than seven in the setting of DAYABBRLEN. When you specify a range where neither startpos nor endpos has a corresponding text value in the DAYNAMES option, then Oracle OLAP has no text values to abbreviate for that range. When you later change your day names list so that startpos is valid, the specified abbreviation is applied.
A number that specifies the length in characters (not bytes) of abbreviated day names. When you do not specify an abbreviation length for a given position in the DAYNAMES option, or when you explicitly set a given position to zero, Oracle OLAP uses the default abbreviations of one character for <WT> and three characters for <WTXT> and <WTXTL>. Oracle OLAP never uses abbreviations when you have designated the full name specifications <WTEXT> and <WTEXTL>.
Usage Notes
Ambiguous Day Names
You can use DAYABBRLEN to interpret ambiguous names, for example, whether 'T' stands for Tuesday or Thursday. When the DAYABBRLEN for Tuesday was 1 and for Thursday was 2, then 'T' would always match Tuesday, and it would require at least 'Th' to match Thursday. This interpretation does not depend on the order of Tuesday and Thursday in the week; it would work the same way when the two days were reversed. If, on the other hand, the DAYABBRLEN for each of these was 2, then 'T' would not match either one, and you would have to enter at least 'Tu' or 'Th' to get a match.
Examples
Example 5-16 Specifying Day Abbreviations
The following DAYABBRLEN setting specifies that the first five days of the week are abbreviated with one character and the last two days are abbreviated with two characters.
DAYABBRLEN = '1-5:1, 6-7:2'
DATEFORMAT = '<WTXT> <MTXT> <D>, <YYYY>'
SHOW CONVERT ('2 august 2005' DATE)
These statements product the following result, with Tuesday abbreviated to one character.
T AUGUST 2, 2005
The GROUPINGID function retrieves a grouping id for the value of a hierarchical dimension using a grouping relation previously created by the GROUPINGID command.
Return Values
NUMBER
Syntax
GROUPINGID (gidrel...)
Parameters
A grouping id relation for the hierarchical dimension that you previously created using the GROUPINGID command.
Examples
Example 7-106 Retrieving the Value of a Single GroupingID
Assume that you have use the GROUPINGID command to define grouping ids for the two hierarchies in the geog dimension as described in Example 9-145, "Using GROUPINGID Command to Populate a Relation with Grouping Ids". Now you can use the GROUPINGID function to retrieve the grouping id of a value in the geog dimension.
" For the Political Geog hierarchy LIMIT geog TO 'Hartford' LIMIT geog_hierlist TO 'Political_Geog' SHOW GROUPINGID(geog_gidrel) 0.00 SHOW OBJ(PROPERTY '$GID_DEPTH' 'geog_gidrel') 4 LIMIT geog TO ALL LIMIT geog TO 'Canada' SHOW GROUPINGID(geog_gidrel) 3.00 SHOW OBJ(PROPERTY '$GID_DEPTH' 'geog_gidrel') 4 " For the Sales Geog hierarchy LIMIT geog TO 'Hartford' LIMIT geog_hierlist TO 'Sales_Geog' SHOW GROUPINGID(geog_gidrel) 0.00 SHOW OBJ(PROPERTY '$GID_DEPTH' 'geog_gidrel') 4 LIMIT geog TO ALL LIMIT geog TO 'West' SHOW GROUPINGID(geog_gidrel) 3.00 SHOW OBJ(PROPERTY '$GID_DEPTH' 'geog_gidrel') 4
The AW function returns information about currently attached workspaces.
Return Value
The return value depends on the keyword you specify, as described in Table 7-2, "Keywords for AW Function".
Syntax
AW(keyword [workspace])
Parameters
Indicates the specific information you want. The keywords that you can use with the AW function are listed in Table 7-2, "Keywords for AW Function" with the data type of the value they return and the meaning of the information.
Table 7-2 Keywords for AW Function
A text expression that indicates the name of the workspace for which you want information. When you do not specify this argument, the AW function ordinarily returns information about the current workspace. The ATTACHED, LIST, and NAME keywords are exceptions to this rule.
Usage Notes
Analytic Workspace Status Information
You can use the SHARED, CHANGED, RO, and RW keywords to get information about the current status of a shared workspace. You can check if SHARED, RO, and CHANGED are TRUE to find out if another user has updated an analytic workspace since you attached it.
Examples
Example 7-26 Ascertaining the Active Workspace
The following program line checks which workspace is currently active so the program can choose the appropriate data to report. With this method, you can use the same report program in several workspaces, each containing different data.
REPORT IF AW(NAME) EQ 'mysales' THEN mysales ELSE gensales
The LPAD function returns an expression, left-padded to a specified length with the specified characters; or, when the expression to be padded is longer than the length specified after padding, only that portion of the expression that fits into the specified length.
To right-pad a text expression, use RPAD.
Return Value
TEXT or NTEXT based on the data type of the expression you want to pad (text-exp).
Syntax
LPAD (text-exp , length [, pad-exp])
Parameters
A text expression to pad.
The total length of the return value as it is displayed on your screen. In most character sets, this is also the number of characters in the return value. However, in some multibyte character sets, the display length of a character string can differ from the number of characters in the string.
When you specify a value for length that is shorter than the length of text-exp, then this function returns only that portion of the expression that fits into the specified length.
A text expression that specifies the padding characters. The default value of pad-exp is a single blank.
Examples
The DECIMALS option controls the number of decimal places that are shown in numeric output. Values are rounded to fit the specified number of decimal places. (Note, however, that the setting of DECIMALS does not affect the format of INTEGER values in output. INTEGER values are shown with no decimal places, unless you explicitly apply a DECIMAL attribute to them in a HEADING, REPORT, or ROW command.)
Data Type
INTEGER
Syntax
DECIMALS = n
Parameters
An INTEGER expression that specifies the number of decimal places to include in all output of DECIMAL and SHORTDECIMAL values; n can be any number in the range 0 to 40 or the number 255. (When you set DECIMALS to 255, you are specifying the formats for values of both SHORTDECIMAL and DECIMAL data types. See "Comparing 2 Decimal Places with Best Presentation Format".) The default is 2.
Examples
Example 5-20 Showing Data with No Decimal Places
To show no decimal places in numeric output, set the DECIMALS option to 0 (zero) before you produce your report.
DECIMALS = 0 LIMIT line TO 'COGS' LIMIT month TO 'Jan96' 'Feb96' REPORT DOWN division ACROSS month: budget
These statements produce the following output.
LINE: COGS
-------BUDGET--------
--------MONTH--------
DIVISION Jan96 Feb96
-------------- ---------- ----------
Camping 355,933 385,308
Sporting 279,773 323,982
Clothing 528,370 546,468
Example 5-21 Comparing 2 Decimal Places with Best Presentation Format
This example contrasts the effects of setting DECIMALS to 2 and setting it to 255 ("best presentation" format).
The OLAP DML statements
DECIMALS = 2 SHOW JOINCHARS(1.1 'A')
produce the following output.
1.10A
The OLAP DML statements
DECIMALS = 255 SHOW JOINCHARS(1.1 'A')
produce the following output.
1.1A
The LIKECASE option controls whether the LIKE operator is case sensitive.
|
Tip: The LIKENL option controls whether the LIKE operator recognizes newline characters. |
Data Type
BOOLEAN
Syntax
LIKECASE = {YES|NO}
Parameters
(Default) Specifies that the LIKE operator is case sensitive.
Specifies that the LIKE operator is not case sensitive.
Examples
Example 5-39 The Effect of LIKECASE
The following statements show the use of the LIKECASE option.
LIKECASE = YES SHOW 'oracle' LIKE 'Oracle%'
The output of this SHOW statement is
NO
The SHOW statement
SHOW 'ORACLE' LIKE '%orc%'
produces the following output.
NO
The statements
LIKECASE = NO SHOW 'ORACLE' like 'orc%'
produce the following output.
YES
The EVAL_NUMBER function evaluates a numeric expression in an analytic workspace and returns the resulting number.
You can specify the EVAL_NUMBER function in a SELECT from DUAL statement to return a numeric constant defined in an analytic workspace. For more information, see "Selecting from the DUAL Table" in Oracle Database SQL Language Reference.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
EVAL_NUMBER (
olap_numeric_expression IN VARCHAR2)
RETURN NUMBER;
Parameters
Table B-20 EVAL_NUMBER Function Parameters
| Parameter | Description |
|---|---|
|
|
An OLAP DML expression that evaluates to a number. Refer to Chapter 2, "OLAP DML Expressions". |
Example
The following example returns the value of the DECIMALS option in the current analytic workspace. The DECIMALS option controls the number of decimal places that are shown in numeric output. In this example, the value of DECIMALS is 2, which is the default.
SET serveroutput ON
SELECT dbms_aw.eval_number('decimals') "Decimals" FROM dual;
Decimals
----------
2
The ADVISE_PARTITIONING_DIMENSION function identifies the dimension that the Sparsity Advisor partitioned over, if any. It returns NULL when the Sparsity Advisor did not partition the cube.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_PARTITIONING_DIMENSION (
cubename IN VARCHAR2,
sources IN dbms_aw$_dimension_sources_t,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Parameters
Table B-6 ADVISE_PARTITIONING_DIMENSION Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a table created by the |
Example
The following program fragment shows the ADVISE_PARTITIONING_DIMENSION function being used to query the results after using the Sparsity Advisor.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_output.put_line('Partitioning Dimension: ' ||
dbms_aw.advise_partitioning_dimension('units_cube', dimsources,
'aw_sparsity_advice'));
END;
/
The program uses DBMS_OUTPUT to display the partitioning dimension, which in this case is the TIME dimension.
Partitioning Dimension: time
The TODAY function returns the current date as a DATE or TEXT value.
Return Value
DATE or TEXT depending on the data type that is expected:
DATE
When you display a returned DATE value, the value has the format specified by the date template in the DATEFORMAT option. When the day of the week or the name of the month is used in the date template, TODAY uses the day names specified in the DAYNAMES option and the month names specified in the MONTHNAMES option.
TEXT
Where a text value is expected. TODAY automatically converts the date to a TEXT value, using the current template in the DATEFORMAT option to format the text value. When you want to override the current DATEFORMAT template, you can convert the date result to text by using the CONVERT function with a date-format argument.
Syntax
TODAY
Examples
The INFILE command causes Oracle OLAP to read statement input from a specified file.
Syntax
INFILE {file-id|EOF} [NOW] [NLS_CHARSET charset-exp]
Parameters
The name of a file from which to read input. File-id is a text expression that represents the name of the file. The name must be in a standard format for a file identifier.
The input file must contain only OLAP DML statements, along with appropriate responses to any prompts generated by the statements. Each statement or response must appear on a separate line in the file.
Terminates the reading of input from the current file and causes Oracle OLAP to resume reading input from the location from which the INFILE statement was executed. Use of INFILE EOF is optional. See "About the Input File" and "INFILE with Both NOW and EOF".
Indicates that Oracle OLAP should open the input file specified in the INFILE and read its statements immediately upon encountering the INFILE instead of waiting until the program containing the INFILE is finished which has the effect of nesting the input file's statements within the program. See "INFILE with Both NOW and EOF". This argument must be specified after file-id.
Specifies the character set that Oracle OLAP uses when reading data from the file specified by file-id which allows Oracle OLAP to convert the data accurately into the current character set, as identified by the NLS_LANG option. This argument must be specified after file-id. When this argument is omitted, then Oracle OLAP handles the data in the file as having the database character set, which is recorded in the NLS_LANG option.
Usage Notes
About the Input File
When the end of the input file is reached, Oracle OLAP resumes reading input from the location from which the INFILE statement was executed (which could be another input file). You do not have to end the input file with the statement INFILE EOF.
INFILE ignores trailing blanks at the end of a line, or between the last text on a line and a continuation mark. INFILE also ignores blank lines.
When you use the NOW keyword and the input file ends with a continued statement, the statement is ignored. For example, if the file ends with "show - ," Oracle OLAP ignores a SHOW statement.
Using INFILE in a Program
When you include an INFILE statement without the NOW keyword in a program, the INFILE statement is not executed until the program has finished executing. In a nested program, it is not executed until all the programs involved have finished executing. Also, when several INFILE commands have been executed by a program, the input files are read in the opposite order from which they were specified.
For example, assume that program.a calls program.b which calls program.c, and each program contains two INFILE commands, one before and one after the call to the next program (as illustrated in the following code). In this case, the order of execution is: a2, b2, c2, c1, b1, a1.
program.a
INFILE a1
"
program.b
INFILE b1
"
program.c
INFILE c1
INFILE c2
"
INFILE b2
"
INFILE a2
When you include an INFILE statement in a program with the NOW keyword, the INFILE statement executes immediately. However, INFILE with the NOW keyword requires more space than usual on the program stack. To conserve stack space, use the NOW keyword only when it is necessary.
INFILE with NOW Outside of Programs
The NOW keyword is intended for use within programs, but you can use it at any time. When you use it when the input file would not ordinarily be deferred, the NOW keyword has no visible effect. However, since NOW requires extra stack space, do not use it in these situations.
INFILE with Both NOW and EOF
When you use both the NOW and EOF keywords, the NOW keyword is ignored.
Displaying Infiled Statements and Responses
When you want the statements from a disk file to be copied to a debugging file as they are executed, see the DBGOUTFILE command.
Examples
The VPMTSCHED function calculates a payment schedule (principal plus interest) for paying off a series of variable-rate installment loans over a specified number of time periods. VPMTSCHED calculates the payment for a given time period as the sum of the principal and interest due on each loan that is incurred or outstanding in that period. For each time period, you specify the initial amount of the loans incurred in that time period and the interest rate that is charged in that time period for each new or outstanding loan.
Return Value
DECIMAL
The result returned by the VPMTSCHED function is dimensioned by the union of all the dimensions of loans and rates and the dimension used as the time-dimension argument.
Syntax
VPMTSCHED(loans, rates, n, [time-dimension] [STATUS])
Parameters
A numeric expression that contains the initial amounts of the loans. When loans does not have a time dimension, or when loans is dimensioned by multiple time dimensions, the time-dimension argument is required.
A numeric expression that contains the interest rates charged for loans. When rates is a dimensioned variable, it can be dimensioned by any dimension, including a different time dimension. When rates is dimensioned by a time dimension, you specify the interest rate in each time period that applies to the loans incurred or outstanding in that period. The interest rates are expressed as decimal values; for example, a 5 percent rate is expressed as .05.
A numeric expression that specifies the number of payments required to pay off the loans in the series. The n expression can be dimensioned, but it cannot be dimensioned by the time dimension argument. One payment is made in each time period of the time dimension by which loans is dimensioned or in each time period of the dimension specified in the time-dimension argument. For example, one payment a month is made when loans is dimensioned by month.
The name of the dimension along which the interest payments are calculated. When loans has a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional, unless loans has more than dimension of this type.
Specifies that VPMTSCHED should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the payment schedule. By default VPMTSCHED uses the default status list.
Usage Notes
VPMTSCHED and NA Values
When loans has a value other than NA and the corresponding value of rates is NA, an error occurs.
VPMTSCHED is affected by the NASKIP option. When NASKIP is set to YES (the default), and a loan value is NA for the affected time period, the result returned by VPMTSCHED depends on whether the corresponding interest rate has a value of NA or a value other than NA. Table 8-21, "How NASKIP Affects the Results When a Loan or Rate Value is NA for a Given Time Period" illustrates how NASKIP affects the results when a loan or rate value is NA for a given time period.
As an example, suppose a loan expression and a corresponding interest expression both have NA values for 1994, but both have values other than NA for succeeding years. When the number of payments is 3, VPMTSCHED returns NA for 1994, 1995, and 1996. For 1997, VPMTSCHED returns the payment due for loans incurred in 1995, 1996, and 1997.
VPTMPTSCHED Ignores the Status of the Time Dimension
The VPMTSCHED calculation begins with the first value of the time dimension, regardless of how the status of that dimension may be limited. For example, suppose loans is dimensioned by year, and the values of year range from Yr95 to Yr99. The calculation always begins with Yr95, even when you limit the status of year so that it does not include Yr95.
However, when loans is not dimensioned by the time dimension, the VPMTSCHED calculation begins with the first value in the current status of the time dimension. For example, suppose loans is not dimensioned by year, but year is specified as time-dimension. When the status of year is limited to Yr97 to Yr99, the calculation begins with Yr97 instead of Yr95.
Examples
Example 8-165 Using VPMTSCHED
The following statements create two variables called loans and rates.
DEFINE loans DECIMAL <year> DEFINE rates DECIMAL <year>
Suppose you assign the following values to the variables loans and rates.
YEAR LOANS RATES -------------- ---------- ---------- Yr95 100.00 0.05 Yr96 200.00 0.06 Yr97 300.00 0.07 Yr98 0.00 0.07 Yr99 0.00 0.07
For each year, loans contains the initial value of the variable-rate loan incurred during that year. For each year, the value of rates is the interest rate that is charged for that year on any loans incurred or outstanding in that year.
The following statement specifies that each loan is to be paid off in three payments, calculates the schedule for paying off the principal and interest on the loans,
REPORT W 20 HEADING 'Payment' VPMTSCHED(loans, rates, 3, year)
and produces the following report.
YEAR Payment -------------- -------------------- Yr95 36.72 Yr96 112.06 Yr97 227.78 Yr98 190.19 Yr99 114.32
The payment for 1995 is the principal due on the loan of $100 incurred in 1995, plus interest on the loan at 5 percent. The payment due in 1996 is the sum of the second payment of principal on the loan incurred in 1995, plus the first payment of principal on the loan of $200 incurred in 1996, plus interest on the remaining principals of both loans at 6 percent. The 1997 payment is the sum of the third and final principal payment on the loan incurred in 1995, the second of the three principal payments on the 1996 loan, the first payment of principal on the loan of $300 incurred in 1997, plus interest on the remaining principals of all three loans at 7 percent. Since the 1995 loan is paid off in 1997, the payment for 1998 covers the principal and interest for the 1996 and 1997 loans. The payment for 1999 is the final payment of principal and interest for the 1997 loan.
The SORTLINES function sorts the lines in a multiline TEXT value.
Return Value
TEXT or NTEXT
Syntax
SORTLINES(text-expression [A|D])
Parameters
A multiline text expression whose lines SORTLINES sorts. When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
Specifies whether the sorting order should be ascending, or alphabetical (A), or descending, or reverse alphabetical (D). The default is A (ascending). The sort order is controlled by the NLS_SORT option.
Examples
Example 8-103 Sorting Text Lines
This example shows how to sort the lines in a multiline text value in a variable called MKTREGIONS.
The statement
SHOW mktregions
produces the following output.
New York Boston Atlanta San Francisco
The statement
SHOW SORTLINES(mktregions)
produces the following output.
Atlanta Boston New York San Francisco
The REPLCOLS function replaces some or all of the character columns in one multiline TEXT value with the columns of another. The function returns a multiline TEXT value composed of the resulting lines.
Columns refer to the character positions in each line of a multiline TEXT value. The first character in each line is in column one, the second is in column two, and so on.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
The number of lines in the return value is always the same as the number of lines in text-expression. When the columns text expression has fewer lines, REPLCOLS repeats its last line in each subsequent line of the return value.
Syntax
REPLCOLS(text-expression columns [start])
Parameters
The text expression in which you want to replace one or more columns.
A text expression containing one or more lines. This expression provides the columns to replace some or all of the columns in text-expression.
An INTEGER, between 1 and 4,000, representing the column position at which to begin replacing. The column position of the first character in each line of text-expression is 1. When you do not specify start, replacement begins with Column 1. When you specify a starting column that is to the right of the last character in a given line in text-expression, the corresponding line in the return value has spaces filling in the intervening columns. See Example 8-80, "Joining and Aligning Columns".
Examples
Example 8-80 Joining and Aligning Columns
In the following example, the citylist and cityreps lines are joined so that the values are aligned, one under the other. The replacement begins at Column 11. When JOINCOLS were used instead of REPLCOLS, the cityreps list would be misaligned.
The statement
SHOW citylist
produces the following output.
Boston Houston Chicago Denver
The statement
SHOW cityreps
produces the following output.
Brady Lopez Alfonso Cody
The statement
SHOW REPLCOLS(citylist cityreps 11)
produces the following output.
Boston Brady Houston Lopez Chicago Alfonso Denver Cody
The FILEPUT command writes data that is specified in a text expression to a file that is opened in WRITE or APPEND mode.
Syntax
FILEPUT fileunit {text-exp|FROM infileunit} [EOL|NOEOL]
Parameters
A fileunit number assigned to a file that is opened for writing (WRITE or APPEND mode) by a previous call to the FILEOPEN function or by the OUTFILE command.
A text expression that contains data for output.
|
Note: When you specify NTEXT data to be written to a file, FILEPUT translates the text to the character set of the file. When that character set cannot represent all of the NTEXT characters, then data is lost. |
Transfers a record read from infileunit by the FILENEXT function directly to the file specified by fileunit. When you specify this clause, you can write selected records to an output file while continuing to process data with the FILEVIEW command.
|
Note: When you use the keyword phrase FROM infileunit, you cannot mix binary and non-binary files. When either file was opened with the BINARY keyword, the other must be binary too. |
(Default) Specifies that a newline character is appended to the output string and written to the file.
Specifies that no newline character is added to the text written to the file.
Examples
Example 9-124 Writing Data to a File Using FILEPUT
Following is an example of a program that writes a file of sales data for three months. The name of the file is the first argument. The following program excerpt opens the file, writes the lines of data to the file, then closes it. This program takes four arguments on the statement line after the program name: the file name of the input data and three month names.
DEFINE salesdata PROGRAM
LD Write Sales Data To File. Args: File Name, 3 Month Names
PROGRAM
VARIABLE fil.unit INTEGER
VARIABLE fil.text TEXT
fil.unit = FILEOPEN(ARG(1) WRITE)
LIMIT month TO &ARG(2) &ARG(3) &ARG(4)
LIMIT product TO ALL
LIMIT district TO ALL
COMMAS = NO
DECIMALS = 0
FOR district
DO
FOR product
DO
fil.text = product
FOR month
fil.text = JOINCHARS(fil.text ' ' -
CONVERT(sales TEXT))
FILEPUT fil.unit fil.text
DOEND
FILEPUT fil.unit ''
DOEND
FILECLOSE fil.unit
END
Example 9-125 Preprocessing Data
The following example uses a data file with the 1996 sales figures for the products sold in each district. Only the records that begin with "A" are important right now, but you want to save the rest of the records in a separate file for later processing. The following program excerpt uses FILENEXT to retrieve each record and FILEVIEW to find out what kind of record it is. A second FILEVIEW statement processes the record when it is type "A." When not, a FILEPUT statement writes it to the output file.
DEFINE rectype VARIABLE ID
LD One Letter Code Identifying The Record Type
VARIABLE in.unit INTEGER
VARIABLE out.unit INTEGER
. . .
in.unit = FILEOPEN( GET(TEXT PROMPT 'Input Filename: ') READ)
out.unit = FILEOPEN( GET(TEXT PROMPT 'Output Filename: ') -
WRITE)
WHILE FILENEXT(in.unit)
DO
FILEVIEW in.unit WIDTH 1 rectype
IF rectype EQ 'A'
THEN FILEVIEW COLUMN 2 WIDTH 8 district SPACE 2 -
WIDTH 8 product ACROSS month year Yr96: saleS
ELSE FILEPUT out.unit FROM in.unit
DOEND
FILECLOSE in.unit
FILECLOSE out.unit
. . .
END
The REMAINDER function returns the remainder when one number is divided by another.
Return Values
Numeric. Oracle OLAP determines the argument with the highest numeric precedence, implicitly converts the remaining arguments to that data type, and returns that data type.
Syntax
REMAINDER (diviidend, divisor)
Parameters
A numeric expression (or an expression that Oracle OLAP can implicitly convert to a numeric expression) that is the number you want to divide.
A numeric expression (or an expression that Oracle OLAP can implicitly convert to a numeric expression) that is the divisor.
Examples
The DECIMALOVERFLOW option controls the result of arithmetic operations that produce out-of-range numbers. Decimal numbers are stored as a mantissa and an exponent. Decimal overflow occurs when the result of a calculation is very large and can no longer be represented by the exponent portion of the decimal representation.
Data Type
BOOLEAN
Syntax
DECIMALOVERFLOW = YES|NO
Parameters
Allows overflow. A calculation that generates overflow executes without error, and the results of the calculation are NA.
(Default) Disallows overflow. A calculation involving overflow stops executing, and an error message is produced.
Examples
Example 5-19 The Effect of DECIMALOVERFLOW
This example shows the effect of changing the value of the DECIMALOVERFLOW option.
When you execute a SHOW statement such as the following without changing DECIMALOVERFLOW from its default value of NO, an error occurs.
SHOW 1000000.0 ** 133
When you change DECIMALOVERFLOW to YES, the same statement executes without an error and produces NA as the result of the operation. The statements
DECIMALOVERFLOW = YES SHOW 1000000.0 ** 133
produce the following result.
NA
The ROW function returns a line of data in cells, one after another in a single row. It is identical to the ROW command, except that it returns a text value, instead of sending the text to the current outfile.
The ROW function, just like the ROW command, consists of a series of column descriptions that specify the data to be returned and, optionally, the way in which it is to be formatted. The ROW function lets you assign the returned value to a text variable, send it to your current outfile with the SHOW or REPORT command, or process it further as an argument to a character manipulation function.
Return Value
TEXT
Syntax
ROW([attribs] [ACROSS dimension [limit-clause]:] {exp1|SKIP} -
[[attribs] [ACROSS dimension [limit-clause]:] {expn|SKIP}])
See the ROW command for a complete description of the arguments.
The ROW function without any arguments returns a blank line.
Usage Notes
The notes for the ROW command also apply to the ROW function.
Examples
Example 8-89 Assigning Output to a Text Variable
The following assignment statement assigns three lines of output to the text variable textvar.
textvar = ROW(OVER '-' UNDER '=' 'This is a Row.') SHOW textvar
These statements produce the following output.
-------------- This is a Row. ==============
Example 8-90 Producing Multiple Rows of Output
You can use the ROW function with JOINLINES in a program to loop over a group of dimension values and assign several rows of data to a text variable. Instead of using the SHOW command in the following program excerpt, you could use the contents of textvar for some other purpose.
LIMIT month TO 'Jan95' 'Feb95' LIMIT district TO 'Boston' 'Atlanta' 'Chicago' textvar = NA textvar = ROW(W 8 SKIP ACROSS month: <month SKIP>) textvar = JOINLINES(textvar ROW(W 8 SKIP ACROSS month: - CENTER <'Sales' 'Plan'>)) FOR district textvar = JOINLINES(textvar ROW(W 8 district ACROSS month: - <sales sales.plan>)) SHOW textvar
These statements produce the following output.
OUTPUT:
Jan95 Feb95
Sales Plan Sales Plan
Boston 32,153.52 42,346.89 32,536.30 43,265.50
Atlanta 40,674.20 54,583.41 44,236.55 57,559.87
Chicago 29,098.94 36,834.37 29,010.20 37,667.66
The MMOF function returns an INTEGER in the range of 1 to 12, giving the month in which a specified date falls. The result returned by MMOF has the same dimensions as the specified DATE expression.
Return Value
INTEGER
Syntax
MMOF(date-expression)
Parameters
An expression that has the DATE data type, or a text expression that specifies a date. The values of the text expression are converted automatically to DATE values, using the current setting of the DATEORDER option to resolve any ambiguity.
Examples
The DAYNAMES option holds the list of valid names for the days of the week. The names are used to display values of type DATE-only or to convert DATE-only values to text.
Oracle OLAP consults the DAYNAMES list when it displays or converts a date using the <WT>, <WTXT>, <WTXTL>, <WTEXT>, or <WTEXTL> formats. These formats are specified in the DATEFORMAT option. When you have multiple sets of day names, Oracle OLAP chooses the synonym whose number of characters and capitalization pattern best match the DATEFORMAT specification.
Data Type
TEXT
Syntax
DAYNAMES = name-list
Parameters
A multiline text expression that lists the names of the seven days of the week. Each name occupies a separate line. Regardless of which day you are treating as the first day of the week, the list must begin with the name for Sunday. The default value is the list of English names for the days of the week, in uppercase. You can include multiple sets of seven names in your list. The eighth name is a synonym for the first name, the ninth name is a synonym for the second name, and so on.
Examples
Example 5-17 Specifying Day Names
The following statements set DAYNAMES to the French names for the days of the week and send the output to the current outfile.
DAYNAMES = 'dimanche\nlundi\n- mardi\nmercredi\njeudi\nvendredi\nsamedi' SHOW DAYNAMES
These statements produce the following output.
dimanche lundi mardi mercredi jeudi vendredi samedi
The ADD_DIMENSION_MEMBER program adds a member to an OLAP cube dimension. An OLAP cube dimension (sometimes also called an "OLAP logical dimension") is an OLAP dimension that is defined as a first-class data object in the Oracle data dictionary.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL ADD_DIMENSION_MEMBER(member_id, logical_dim, hier_list, level_name, -
parent-member_id, [ auto_compile, [ merge ]])
Parameters
Since ADD_DIMENSION_MEMBER is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the value of the member that you want to add to the cube dimension.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A multi-line text expression consisting of the Oracle data dictionary names of all of the hierarchies that you want the dimension member added to. Specify one hierarchy name per line.
When you want the member to be added to all of the cube dimension hierarchies, specify NA.
For level hierarchies, a text value that specifies the hierarchy level at which the program will add the member to the cube dimension. For level hierarchies, the value you specify for level_name must be:
Compatible with the value you specify for parent_member_id
At the same hierarchy level as the existing cube dimension member since a cube dimension member cannot be in two different levels across hierarchies.
When the member participates in a value hierarchy (that is, when there are no levels), specify NA.
A text expression that specifies the value of the member which is the parent of the member that you want to add to the cube dimension. When you want to add the member as the top member of a hierarchy, specify NA.
A Boolean expression that specifies whether or not you want related analytic workspace objects (for example, he parent relation) to be updated immediately. The default value is TRUE in which case all of the changes to the analytic workspace that are needed to add the cube dimension member happen now. Specify FALSE only when, for performance reasons, you want to make a bulk set of changes before issuing a compile. In this case, you need to explicitly compile the cube dimension before the values of the analytic workspace objects take effect as described in "Explicitly Compiling a Cube Dimension".
|
Note: Regardless of the value that you specify for this argument, the new member is always immediately added to the dimension -- even when an error is signaled during compilation. |
A Boolean expression that specifies whether or not the program updates the dimension member if it exists or creates it if it does not. The default value is FALSE.
Usage Notes
Explicitly Compiling a Cube Dimension
When you specify FALSE for auto_compile, you need to explicitly compile the cube dimension before the values of the analytic workspace objects take effect. You perform the compilation with a DBMS_CUBE.BUILD package call. You can make this call within Analytic Workspace Manager by issuing the following statement where cube_dimension_name is the fully-qualified name of the cube dimension as defined in the Oracle data dictionary.
SQL PROCEDURE DBMS_CUBE.BUILD('cube_dimension_name USING (COMPILE)');
By default, issuing the above statement performs an UPDATE and COMMIT to the database. To prevent an UPDATE and COMMIT from occurring, add NO COMMIT to the statement as shown below.
SQL PROCEDURE DBMS_CUBE.BUILD'NO COMMIT cube_dimension_name USING (COMPILE)');
Guidelines for Specifying Values for the Names of Logical OLAP Objects
In an OLAP DML statement the text expression that you specify for an OLAP logical object (that is, a first-class OLAP object that is defined in the Oracle data dictionary such as a cube or cube dimension) must resolve to a value with the following form where LOGICAL_OBJECT_NAME is the Oracle data dictionary name of the OLAP object:
[SCHEMA_NAME.] LOGICAL_OBJECT_NAME
For example, valid expressions for referencing the XADEMO cube dimension in the XADEMO schema include:
'product' 'xademo.product' 'PRODUCT' 'XADEMO.product' '\"XADEMO\".\"PRODUCT\"'
|
Note: OLAP DML cube-aware programs interpret a text value that you specify for an OLAP logical object as upper case text unless you enclose the value in double quotes. |
Transaction Scope of Cube-Aware OLAP DML Statements
Unless otherwise noted, the scope of a cube-aware OLAP DML statement, just like other OLAP DML statement, is a single session. To persist any changes, you must have attached the analytic workspace in Read/Write mode before you issue the statement and issue OLAP DML UPDATE and COMMIT statements after you execute the statement. If the analytic workspace is attached Read Only or if you do not issue UPDATE and COMMIT statements, then the changes exist only in the session while the analytic workspace is attached.
Invalid Level Names in Cube-Aware OLAP DML Statements
If you specify an invalid value for level_name or parent_member_id, a compile-time error is thrown. Also, an error will occur if you specify a hierarchy level for the member that is different from the level it participates in another hierarchy. In this case, a call error is thrown if auto_compile is FALSE.
Examples
Example 9-5 Adding Members to an OLAP Cube Dimension
This example adds members to an OLAP cube dimension named my_time.
Execute the following PL/SQL statement to report on the values and hierarchy of the my_time cube dimension before any changes are made.
select dim_key||' '||level_name||' '||parent
from my_time_lvl_hier_view
order by dim_key asc;
DIM_KEY||''||LEVEL_NAME||''||PARENT
-------------------------------------------------------------------------------
L1_0 L1
L1_1 L1
L2_1 L2 L1_1
L2_2 L2 L1_1
L3_1 L3 L2_1
L3_2 L3 L2_1
L3_3 L3 L2_2
L3_4 L3 L2_2
L3_5 L3 L2_2
9 rows selected.
Execute the following PL/SQL statement to execute the user-written OLAP DML program named ADD_LQ_2.
exec dbms_aw.execute('call my_util_aw!add_l1_2');
The definition of the user-written OLAP DML program named ADD_LQ_2 is shown below. Note that it calls the ADD_DIMENSION_MEMBER program provided with the OLAP DML to add new members to the my_time cube dimension.
DEFINE ADD_L1_2 PROGRAM
PROGRAM
VARIABLE _aw_dim text
VARIABLE _aw_sales text
VARIABLE _members text
VARIABLE _member text
VARIABLE _i integer
_aw_dim = OBJORG(DIM 'my_time')
_aw_sales = OBJORG(MEASURE 'my_cube' 'sales')
" Adds L1_2, L2_3, L3_6 CALL ADD_DIMENSION_MEMBER('L1_2', 'my_time', NA, 'L1', NA, NO)
CALL ADD_DIMENSION_MEMBER('L2_3', 'my_time', NA, 'L2', 'L1_2', NO)
CALL ADD_DIMENSION_MEMBER('L3_6', 'my_time', NA, 'L3', 'L2_3', NO)
" Set my_time attribute (to meaningless values) so dimension can compile
LIMIT &_aw_dim TO 'L1_2', 'L2_3', 'L3_6'
_members = VALUES(&_aw_dim)
_i = 1
WHILE _i LE NUMLINES(_members)
DO
_member = EXTLINES(_members, _i, 1)
_i = _i + 1
CALL UPDATE_ATTRIBUTE_VALUE(_member, 'my_time', 'start_date', -
to_date('01/01/08', 'MM/DD/YY'), NO)
CALL UPDATE_ATTRIBUTE_VALUE(_member, 'my_time', 'timespan', 1, NO)
DOEND
&_aw_sales(&_aw_dim 'L3_6') = 3
UPDATE
COMMIT
END
Issue the following PL/SQL statement to compile the my_time cube dimension.
exec dbms_cube.build('MY_TIME USING (COMPILE)');
Report the values and hierarchy of the my_time cube dimension after compilation
select dim_key||' '||level_name||' '||parent
from my_time_lvl_hier_view
order by dim_key asc;
DIM_KEY||''||LEVEL_NAME||''||PARENT
-------------------------------------------------------------------------------
L1_0 L1
L1_1 L1
L1_2 L1
L2_1 L2 L1_1
L2_2 L2 L1_1
L2_3 L2 L1_2
L3_1 L3 L2_1
L3_2 L3 L2_1
L3_3 L3 L2_2
L3_4 L3 L2_2
L3_5 L3 L2_2
L3_6 L3 L2_3
12 rows selected.
Execute the following PL/SQL statement to solve my_cube with the new hierarchy.
exec dbms_cube.build(script => 'MY_CUBE USING (SOLVE)', add_dimensions => false);
Issue the following PL/SQL statement to report on the values of the sales and moving_sales measure in my-cube. Note that the new my_time cube dimension values are shown.
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2) from my_cube_view order by my_time asc; MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2) -------------------------------------------------------------------- L1_0 24 27 L1_1 14 38 L1_2 3 3 L2_1 2 5 L2_2 12 14 L2_3 3 3 L3_1 1 4 L3_2 1 2 L3_3 10 11 L3_4 1 11 L3_5 1 2 L3_6 3 3 12 rows selected.
The STATDEPTH function returns the number of status lists that Oracle OLAP has saved for a specified dimension. The current status list of a dimension is at the top of the stack which means that it has a depth of 1 (one.
Return Value
INTEGER
Syntax
STATDEPTH (dimension)
Parameters
The name of the dimension for which you want to retrieve information.
Usage Notes
What is a Status List Stack?
A status list stack for a dimension is a stack of the dimension statuses that Oracle OLAP uses to manage status when executing PUSH and POP statements. The depth of the list varies depending on what Oracle OLAP statements have executed:
When you first attach an analytic workspace, the current status of each dimension is ALL and the status list stack for each dimension has a depth of one (that is, there is only one status list in the stack).
The depth of the status list stack for a dimension stays at one (for the current status list) no matter how often current status changes (that is, no matter how many LIMIT commands execute against it), except in the following situations:
Oracle OLAP executes a PUSH statement for the dimension. After a PUSH statement executes, each time a LIMIT command executes for a pushed dimension, Oracle OLAP adds status list to the status list stack for that dimension. A POP statement for the dimension originally pushed, clears the status list stack for the dimension. The status list stack for the dimension, once again becomes one.
Oracle OLAP executes a statement (like CHGDIMS or TEMPSTAT) that temporarily changes the status of the dimension. In this case, Oracle OLAP adds a status list to the status list stack during the time the statement is in effect, and removes it immediately afterward. You can only access the status list from the status list stack while the temporary status is in effect.
Within an OLAP DML program, the VARIABLE command declares a local variable or valueset for use within that program. A local variable cannot have any dimensions and exists only while the program is running.
Syntax
VARIABLE name {datatype|dimension|VALUESET dim}
Parameters
The name for the local variable or valueset. When you use the same name as an existing analytic workspace object, the local variable or valueset takes precedence over the analytic workspace object. After you assign a value to the variable or valueset, its value is available within the program where the VARIABLE statement occurs. You name a variable or valueset according to the rules for naming analytic workspace objects (see the main entry for the DEFINE command).
The data type of the variable, which indicates the kind of data to be stored. You can specify any of the data types that are listed and described in the DEFINE VARIABLE entry. Also, when you want to the program to be able to receive an argument without converting it to a specific data type, you can also specify WORKSHEET for the data type.
Indicates that name is a relation variable, which holds a single value of the specified dimension. The variable can hold a value of the dimension or a position (INTEGER) of the specified dimension. Assigning a value that does not currently exist in the dimension causes an error.
Indicates that name is a valueset. The dim argument is the name of the dimension for which the valueset holds values.
Usage Notes
Persistence of a Local Variable
A local variable or valueset exists only while the program that specified it is running. When the program terminates, the variable or valueset ceases to exist and its value is lost. A program can terminate when a RETURN statement, SIGNAL statement, or the last line of the program executes. When the program calls another program, the original program is temporarily suspended and the variable or valueset does exist when the called program ends and control returns to the original program. A program that calls itself recursively has separate local variable or valuesets for each running copy of the program.
Declarations at the Start Of A Program
You must specify all your local variables or valuesets at the beginning of a program, before any executable statements.
Initial Value of a Local Variable or Valueset
The value of a local variable or valueset is initially NA.
Duplicating the Name of an Analytic Workspace Object
When you give a local variable or valueset the same name as an analytic workspace object, Oracle OLAP assumes you are referring to the local variable or valueset within the program. The analytic workspace object has priority only when the statement requires an analytic workspace object as an argument.
Although the OBJ and EXISTS functions expect an analytic workspace object as an argument, you can use a local text variable or valueset to specify the name of an object.
Formulas and Models
You cannot use local variables or valuesets in a formula or model.
EXPORT and IMPORT Commands
In a program, you can use an EXPORT (EIF) statement to store the value of a local variable or valueset in an EIF file. You must use the AS keyword to give the variable or valueset an analytic workspace object name. The name can be the same as the name of the local variable or valueset. When you use IMPORT (EIF) to retrieve the value, it is stored as an analytic workspace object. You cannot import the value into a local variable or valueset.
Examples
Example 10-171 Saving a File Unit Number
Suppose you want to write a program to read data from an input file with Data Reader statements. First you must open the file and save the value of the file unit number assigned to it. At the beginning of the program you can specify a local variable called unit to hold the file unit number.
DEFINE read.file PROGRAM
LD Read monthly sales data into the analytic workspace
PROGRAM
VARIABLE unit INTEGER
TRAP ON error
unit = FILEOPEN('sales.data' READ)
...
Example 10-172 Returning a Dimension Value from a Program
Suppose you want to write a program that analyzes sales for various districts and returns the name of the district in which sales were highest. For the purpose of analysis, the program defines a local variable to hold the district name. When the program ends, it returns the value of the local variable.
DEFINE highsales PROGRAM PROGRAM VARIABLE districtname district ... "(statements that find the highest district) RETURN districtname END
The LIMIT function returns the dimension or dimension surrogate values that result from a specified LIMIT command or a specified dimension status stack. A dimension and any surrogate for that dimension share the same status. The LIMIT function does not change the status of a dimension or a valueset.
Return Value
The return value varies depending on the use of the function and whether or not you specify the INTEGER keyword:
When the LIMIT function is an argument to an OLAP DML statement (including a user-defined command or function) that expects a valueset, it returns a valueset.
When the LIMIT function returns an empty valueset, it returns it as a valueset with null status.
In all other cases, the LIMIT function returns either a TEXT value or an INTEGER value depending on whether or not you include the INTEGER keyword. When it returns a TEXT value that represents empty status, it returns it as NA.
Syntax
The syntax of the LIMIT function varies depending on whether you want to retrieve the values of the dimension or dimension surrogate values that result from a specified LIMIT command or the values of a a specified dimension status stack.
Syntax for Retrieving Values From a LIMIT Command
LIMIT([INTEGER] {dimension | valueset | LIMIT_function} [concat-component] limit-type -
[limit-clause] [IFNONE label])
Syntax for Retrieving Values From a Dimension Status Stack
LIMIT([INTEGER] dimension STATDEPTH stack-position] [IFNONE label])
Parameters
See the LIMIT command for a complete description of this argument.
See the LIMIT command for a complete description of this argument.
Another LIMIT function.
|
Note: When you nest LIMIT functions inside each other in this manner, the first argument of the innermost LIMIT function must be the a dimension or a valueset. See also "Nesting the LIMIT Function". |
See the LIMIT command for a complete description of this argument.
See the LIMIT command for a complete description of this argument.
Specifies the values to use for the limit. There are several types of limit clauses— for example, a limit clause you can use to specifying the limit using values (including using a valueset) and a limit clause you can use to specify the limit using a related dimension. Each of these types of limit clauses has a very complex syntax. Because the syntax is complex, the syntax for the various types of limit clauses are documented separately as part of the following topics:
In the syntax of each of these LIMIT command topics, the limit-clause is that portion of the syntax following the limit-type argument.
When you use the INTEGER keyword, the function returns the position numbers of the values in the default dimension status rather than the names. When you use INTEGER with a valueset, the function returns the position numbers of the values in the default dimension status, not in the valueset.
Specifies that Oracle OLAP retrieve the status list values for the status list stack for the specified dimension.
An INTEGER value that specifies the position in the status list stack from which to retrieve the values. Keep the following in mind when specifying a value:
Values from 0 to 1-STATDEPTH(dimension) retrieve stacked values from the top (current status) to the bottom (oldest status.)
Values from 1 to STATDEPTH(dimension) retrieve stacked values from the bottom of the stack (that is, the oldest status) to the top of the stack (that is, the current status).
See the STATDEPTH function for more information about status list stacks.
Usage Notes
Nesting the LIMIT Function
Use the following syntax to return the result of several LIMIT commands for the same dimension by nesting the LIMIT function.
LIMIT (LIMIT (LIMIT (lim-exp1) lim-exp2) lim-exp3)
Use this nested construction to find the status of a series of LIMIT commands. For example, to see the status of the following commands
LIMIT product TO division 'Camping' LIMIT product KEEP - EVERY(sales GT 50000, product) LIMIT product KEEP FIRST 1
you execute this statement.
REPORT LIMIT(LIMIT(LIMIT(product TO - division 'Camping') KEEP EVERY - (sales GT 50000, product))KEEP FIRST 1)
Limiting with a Component of a Concat Dimension
You can limit a concat dimension to the current status of one of its component dimensions as in the following statement.
LIMIT(reg.dist.ccdim TO district)
You can also limit a concat dimension to a set of the values of one of its component dimensions as in the following statement.
LIMIT(reg.dist.ccdim TO district 'Boston' 'Chicago' 'Seattle')
Returning Multidimensional Results
The LIMIT function returns multidimensional results when evaluating multidimensional expressions. In the following example, the sales variable has three dimensions: product, district, and month.
LIMIT product TO ALL LIMIT district TO 'Boston' LIMIT month TO 'Jan95' 'Feb95' 'Mar95'
A REPORT sales statement produces the following output.
DISTRICT: BOSTON
-------------SALES--------------
-------------MONTH--------------
PRODUCT Jan95 Feb95 Mar95
--------- ---------- ---------- ----------
Tents 32,153.52 32,536.30 43,062.75
Canoes 66,013.92 76,083.84 91,748.16
Racquets 52,420.86 56,837.88 58,838.04
Sportswear 53,194.70 58,913.40 62,797.80
Footwear 91,406.82 86,827.32 100,199.46
Suppose you want a list of products whose sales exceed $90,000 for the status shown in the preceding report. The LIMIT function evaluates the product sales in each month and district combination and produces a list that is dimensioned by the months and districts in status.
A REPORT limit (product TO sales GT 90000) statement produces the following output.
---LIMIT (PRODUCT TO SALES GT---
-------------90000)-------------
-------------MONTH--------------
DISTRICT Jan95 Feb95 Mar95
--------- ---------- ---------- ----------
Boston Footwear NA Canoes
Footwear
Examples
Example 8-9 Returning Multidimensional Results
This example prints a report of the products whose sales were greater than $50,000 in the first two months of 1995 in Boston and Atlanta. Notice that the LIMIT function returns multidimensional results.
These statements
LIMIT month TO 'Jan95' 'Feb95' LIMIT district TO 'Boston' 'Atlanta' LIMIT product TO ALL REPORT LIMIT (product TO sales GT 50000)
produce this report.
--LIMIT (PRODUCT TO--
---SALES GT 50000)---
--------MONTH--------
DISTRICT JAn95 Feb95
-------------- ---------- ----------
Boston Canoes Canoes
Racquets Racquets
Sportswear Sportswear
Footwear Footwear
Atlanta Racquets Canoes
Sportswear Racquets
Footwear Sportswear
Footwear
Example 8-10 LIMIT Command with the LIMIT Function
The following example shows the LIMIT function being used as an argument to the LIMIT command. The result of the LIMIT function is converted to a valueset.
ALLSTAT LIMIT month TO LIMIT (LIMIT (month TO LAST 10) KEEP FIRST 3)
After the preceding LIMIT statement, a STATUS month statement produces this output.
The current status of MONTH is: MAR97 TO MAY97
The ASCII function returns the decimal representation of the first character of an expression.
Return Value
INTEGER
Syntax
ASCII (text-exp)
Parameters
A text expression.
Usage Notes
Returning EBCDIC Values
When your database character set is 7-bit ASCII, then this function returns an ASCII value. When your database character set is EBCDIC Code, then this function returns an EBCDIC value. There is no corresponding EBCDIC character function
Examples
The ARCTAN2 function returns a full-range (0 - 2 pi) numeric value indicating the arc tangent of a given ratio. The function returns values in the range of -pi to pi, depending on the signs of the arguments. The values are expressed in radians.
To calculate the angle value (in radians) of a specified tangent that is not a ratio, use ARCTAN.
Return Value
NUMBER
Syntax
ARCTAN2 (n / m)
Parameters
A numeric expression that specifies one component of the ratio. The argument n can be in an unbounded range.
A numeric expression that specifies the other component of the ratio.
Examples
OLAP_CONDITION is a SQL function that dynamically executes an OLAP DML command during a query of an analytic workspace.
The OLAP_CONDITION function executes an OLAP DML command at one of three entry points in the limit map used in a call to OLAP_TABLE as described in "Entry Points for OLAP_CONDITION in the OLAP_TABLE Limit Map".
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
The number 1 to indicate a successful invocation of OLAP_CONDITION.
Syntax
OLAP_CONDITION(
r2c IN RAW(32),
expression IN VARCHAR2,
event IN NUMBER DEFAULT 1);
RETURN NUMBER;
Parameters
The name of a column specified by a ROW2CELL clause in the limit map. This parameter is used by OLAP_CONDITION to identify a particular invocation of OLAP_TABLE.
The ROW2CELL column is used in the processing of the single-row functions. (See "OLAP_EXPRESSION") OLAP_CONDITION simply uses it as an identifier.
For information on creating a ROW2CELL column, see "ROW2CELL Clause".
A single OLAP DML command to be executed within the context of the OLAP_TABLE function identified by the r2c parameter
The event during OLAP_TABLE processing that triggers the execution of the OLAP DML command specified by the expression parameter. This parameter can have the value 0, 1, or 2, as described in Table A-2
Usage Notes
Entry Points for OLAP_CONDITION in the OLAP_TABLE Limit Map
Parameters of OLAP_CONDITION identify an invocation of OLAP_TABLE, specify an entry point in the limit map, and provide the OLAP DML command to be executed at that entry point.
The target limit map must include a ROW2CELL column. OLAP_CONDITION uses this column to identify an instance of OLAP_TABLE. Within that instance OLAP_CONDITION executes the OLAP DML command at one of three possible entry points. The entry point that you specify determines whether the condition affects the data returned by the query and whether the condition remains in effect upon completion of the query.
OLAP_CONDITION can be triggered at any of the following points:
Before the status of the dimensions in the limit map is saved (which occurs before the result set is calculated).
After the result set has been calculated and before it is fetched. (Default)
After the result set has been fetched and the status of the dimensions in the limit map has been restored.
The entry points for OLAP_CONDITION are described in Table A-2. Refer to "Order of Processing in OLAP_TABLE" to determine where each entry point occurs.
Table A-2 Entry Points for OLAP_CONDITION in the OLAP_TABLE Limit Map
| Entry Point | Description |
|---|---|
|
0 |
Execute the OLAP DML command after the The entry point is between steps 1 and 2 in "Order of Processing in OLAP_TABLE". If |
|
1 |
Execute the OLAP DML command after the conditions of the The entry point is between steps 4 and 5 in "Order of Processing in OLAP_TABLE". If an OLAP DML command (other than If |
|
2 |
Execute the OLAP DML command after the data is fetched and the status of dimensions in the limit map has been restored. The entry point is after step 8 in "Order of Processing in OLAP_TABLE". If |
Examples
Several sample queries using OLAP_CONDITION are shown in Example A-11, "Queries of UNIT_COST_PRICE_VIEW Using OLAP_CONDITION". These examples use the PRICE_CUBE in an analytic workspace namedMYAW. The cube has a time dimension, a product dimension, and measures for unit cost and unit price.
The examples are based on a view called unit_cost_price_view. The SQL for creating this view is shown in Example A-10, "View of PRICE_CUBE". For information about creating views of analytic workspaces, see "Creating Relational Views Using OLAP_TABLE".
Example A-10 View of PRICE_CUBE
-- Create the logical row
SQL>CREATE TYPE unit_cost_price_row AS OBJECT (
aw_unit_cost NUMBER,
aw_unit_price NUMBER,
aw_product VARCHAR2(50),
aw_product_gid NUMBER(10),
aw_time VARCHAR2(20),
aw_time_gid NUMBER(10),
r2c RAW(32));
-- Create the logical table
SQL>CREATE TYPE unit_cost_price_table AS TABLE OF unit_cost_price_row;
-- Create the view
SQL>CREATE OR REPLACE VIEW unit_cost_price_view AS
SELECT aw_unit_cost, aw_unit_price, aw_product, aw_product_gid,
aw_time, aw_time_gid, r2c
FROM TABLE(OLAP_TABLE(
'myaw DURATION SESSION',
'unit_cost_price_table',
'',
'MEASURE aw_unit_cost FROM price_cube_unit_cost
MEASURE aw_unit_price FROM price_cube_unit_price
DIMENSION product WITH
HIERARCHY product_parentrel
INHIERARCHY product_inhier
GID aw_product_gid FROM product_gid
ATTRIBUTE aw_product FROM product_short_description
DIMENSION time WITH
HIERARCHY time_parentrel
INHIERARCHY time_inhier
GID aw_time_gid FROM time_gid
ATTRIBUTE aw_time FROM time_short_description
ROW2CELL r2c'));
-- query the view
SQL>SELECT * FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('2000', '2001', '2002', '2003')
ORDER BY aw_time;
AW_UNIT_COST AW_UNIT_PRICE AW_PRODUCT AW_PRODUCT_GID AW_TIME AW_TIME_GID R2C
------------ ------------- ---------- -------------- ------- ----------- -----
211680.12 224713.71 Hardware 3 2000 3 00...
195591.60 207513.16 Hardware 3 2001 3 00...
184413.05 194773.78 Hardware 3 2002 3 00...
73457.31 77275.06 Hardware 3 2003 3 00...
Example A-11 Queries of UNIT_COST_PRICE_VIEW Using OLAP_CONDITION
The queries in this example use OLAP_CONDITION to modify the query of UNIT_COST_PRICE_VIEW in Example A-10, "View of PRICE_CUBE". In each query, OLAP_CONDITION uses a different entry point to limit the TIME dimension to the year 2000.
In the first query, OLAP_CONDIITON uses entry point 0. The limited data is returned by OLAP_TABLE, and the limit remains in effect in the analytic workspace.
SQL>SELECT * FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('2000', '2001', '2002', '2003')
AND OLAP_CONDITION(r2c,
'limit time to time_short_description eq ''2000''', 0)=1
ORDER BY aw_time;
AW_UNIT_COST AW_UNIT_PRICE AW_PRODUCT AW_PRODUCT_GID AW_TIME AW_TIME_GID R2C
------------ ------------- ---------- -------------- ------- ----------- -----
211680.12 224713.71 Hardware 3 2000 3 00...
--Check status in the analytic workspace
SQL>exec dbms_aw.execute('rpr time_short_description');
TIME TIME_SHORT_DESCRIPTION
---- ----------------------
3 2000
-- Reset status
SQL>exec dbms_aw.execute('allstat');
In the next query, OLAP_CONDIITON uses entry point 1. The limited data is returned by OLAP_TABLE, but the limit does not remain in effect in the analytic workspace.
Note that the third parameter is not required in this case, since entry point 1 is the default.
SQL>SELECT * FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('2000', '2001', '2002', '2003')
AND OLAP_CONDITION(r2c,
'limit time to time_short_description eq ''2000''', 1)=1
ORDER BY aw_time;
AW_UNIT_COST AW_UNIT_PRICE AW_PRODUCT AW_PRODUCT_GID AW_TIME AW_TIME_GID R2C
------------ ------------- ---------- -------------- ------- ----------- -----
211680.12 224713.71 Hardware 3 2000 3 00...
--Check status in the analytic workspace
SQL>exec dbms_aw.execute('rpr time_short_description');
TIME TIME_SHORT_DESCRIPTION
---- ----------------------
19 Jan-98
20 Feb-98
21 Mar-98
22 Apr-98
.
.
.
1 1998
2 1999
3 2000
4 2001
85 2002
102 2003
119 2004
-- Reset status
SQL>exec dbms_aw.execute('allstat');
In the final query, OLAP_CONDIITON uses entry point 2. The limit does not affect the data returned by OLAP_TABLE, but the limit remains in effect in the analytic workspace.
SQL>SELECT * FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('2000', '2001', '2002', '2003')
AND OLAP_CONDITION(r2c,
'limit time to time_short_description eq ''2000''', 2)=1
ORDER BY aw_time;
AW_UNIT_COST AW_UNIT_PRICE AW_PRODUCT AW_PRODUCT_GID AW_TIME AW_TIME_GID R2C
------------ ------------- ---------- -------------- ------- ----------- -----
211680.12 224713.71 Hardware 3 2000 3 00...
195591.60 207513.16 Hardware 3 2001 3 00...
184413.05 194773.78 Hardware 3 2002 3 00...
73457.31 77275.06 Hardware 3 2003 3 00...
--Check status in the analytic workspace
SQL>exec dbms_aw.execute('rpr time_short_description');
TIME TIME_SHORT_DESCRIPTION
---- ----------------------
3 2000
The Oracle OLAP DML Reference provides a complete description of the OLAP Data Manipulation Language (OLAP DML) used to create analytic workspace definitions that are stored within an analytic workspace and to manipulate these object.
Oracle OLAP DML Reference is intended for programmers and database administrators who write OLAP DML programs and who create analytic workspaces and analytic workspace objects using the OLAP DML.
For information about Oracle's commitment to accessibility, visit the Oracle Accessibility Program website at http://www.oracle.com/pls/topic/lookup?ctx=acc&id=docacc.
Access to Oracle Support
Oracle customers have access to electronic support through My Oracle Support. For information, visit http://www.oracle.com/pls/topic/lookup?ctx=acc&id=info or visit http://www.oracle.com/pls/topic/lookup?ctx=acc&id=trs if you are hearing impaired.
For more information about working with Oracle OLAP, see these Oracle resources:
The following text conventions are used in this reference:
| Convention | Meaning |
|---|---|
| boldface | Boldface type indicates graphical user interface elements associated with an action, or terms defined in text or the glossary. |
| italic | Italic type indicates book titles, emphasis, or placeholder variables for which you supply particular values. |
monospace | Monospace type indicates URLs, code in examples, text that appears on the screen, or text that you enter. |
This reference presents OLAP DML syntax in a simple variant of Backus-Naur Form (BNF) that includes the following symbols and conventions.
| Symbol or Convention | Meaning |
|---|---|
| [ ] | Brackets enclose optional items. |
| { } | Braces enclose items only one of which is required. |
| | | A vertical bar separates alternatives. |
| ... | Ellipsis points show that the preceeding syntactic element can be repeated |
| delimiters | Delimiters other than brackets, braces, vertical bars, and ellipses must be entered as shown |
| italics | Words appearing in italics are placeholders for which you must substitute a name or a value. Words that are not in italics are keywords. They must be typed as shown. |
The ALLOCMAP command identifies an aggmap object as an allocation specification and enters the contents of the specification. To use AGGMAP to assign an allocation specification to n aggmap object, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
An alternative to the AGGMAP command is the EDIT AGGMAP command, which is available only in OLAP Worksheet. The EDIT AGGMAP command opens an Edit window in which you can delete or change an allocation specification for an aggmap object. To use the OLAP Worksheet, to code an allocation specification follow the instructions given in "Editing a Newly Defined Aggmap to Code an Allocation Specification".
Syntax
ALLOCMAP [specification]
Parameters
A multiline text expression that is the allocation specification for the current aggmap object. An allocation specification begins with an ALLOCMAP statement and ends with an END statement. Between these statements, you code one or more of the following statements depending on the calculation that you want to specify:
Each statement is a line of the multiline text expression. When coding an ALLOCMAP statement at the command line level, separate statements with newline delimiters (\n), or use JOINLINES.
For a discussion of how to determine which statements to include, see "Designing an Allocation Specification".
Usage Notes
Designing an Allocation Specification
Minimally, an allocation specification consists of a RELATION statement or a VALUESET statement However, you can create more complex allocation specifications and change the default settings for error handling by including additional OLAP DML statements in the specification, as follows:
For hierarchical allocations, a RELATION statement that specifies a self-relation that identifies the child-parent relationships of the hierarchy. List the statements in the order in which you want to perform the various operations; or if this is not important, list the RELATION statements in the same order as the dimensions appear in the variable definition.
For non-hierarchical allocations, a VALUESET statement that specifies the values to be used when allocating.
A CHILDLOCK statement that tells the ALLOCATE command whether to determine if RELATION statements in the aggmap specify lock on both a parent and a child element of a dimension hierarchy.
A DEADLOCK statement that tells the ALLOCATE command whether to continue an allocation when it encounters a deadlock, which occurs when the allocation cannot distribute a value because the targeted cell is locked or, for some operations, has a basis value of NA.
When a dimension is not shared by the target variable and the source or the basis objects, a DIMENSION (for allocation) statement that specifies a single value to set as the status of that dimension.
An ERRORLOG statement that specifies how many errors to allow in the error log specified by the ALLOCATE command and whether to continue the allocation when the maximum number of errors has occurred.
An ERRORMASK statement that specifies which error conditions to exclude from the error log.
When the source data comes from a variable, a SOURCEVAL statement that specifies whether ALLOCATE changes the source data value after the allocation.
Aggmap Type
You can use the AGGMAPINFO function to learn the type of an aggmap. An aggmap into which you have entered an allocation specification using the ALLOCMAP has the type ALLOCMAP and an aggmap into which you have entered an aggregation specification using an AGGMAP statement has the type AGGMAP. When you have defined an aggmap but have not yet entered a specification in it, its type is NA.
One RELATION for Each Dimension
An aggmap can have only one RELATION statement for any given dimension.
One Hierarchy For Each Dimension
An allocation operation proceeds down only one hierarchy in a dimension. When a dimension has multiple hierarchies, then you must limit the dimension to a hierarchy with a qualified data reference after the rel-name argument.
Examples
Example 9-37 Allocation Specification from an Input File
In this example an aggmap and its specification are defined in an ASCII disk file called salesalloc.txt. The statements in the file are then executed in the analytic workspace through the use of the INFILE statement. The statements in salesalloc.txt are the following.
IF NOT EXISTS ('salesalloc')
THEN DEFINE salesalloc AGGMAP
ELSE CONSIDER salesalloc
ALLOCMAP
RELATION time.parent OPERATOR EVEN
RELATION product.parent OPERATOR EVEN
RELATION geography.parent OPERATOR EVEN
SOURCEVAL ZERO
DEADLOCK SKIP
END
To include the salesalloc aggmap in your analytic workspace, execute the following statement.
INFILE 'salesalloc.txt'
The sales.agg aggmap has now been defined and contains three RELATION statements and the SOURCEVAL and DEADLOCK statements. In this example, the ALLOCATE statement allocates its source value evenly to all of the aggregate level cells and the detail level cells of the target variable because the relations time.parent, product.parent, and geography.parent relate each child dimension value to its parent in the dimension hierarchy. The DEADLOCK statement tells the ALLOCATE statement to log an error and continue the allocation when a branch of a target hierarchy is locked or has a value of NA. The SOURCEVAL statement tells ALLOCATE to assign a zero value to the source cells after allocating the source data.
You can now use the salesalloc aggmap with an ALLOCATE statement, such as.
ALLOCATE sales USING salesalloc
Example 9-38 Allocation Specification from a Text Expression
In this example the salesalloc aggmap has already been defined. The specification is added to the aggmap as a text expression argument to the ALLOCMAP statement.
CONSIDER salesalloc ALLOCMAP RELATION time.parent OPERATOR EVEN RELATION product.parent OPERATOR EVEN RELATION geography.parent OPERATOR EVEN SOURCEVAL ZERO DEADLOCK SKIP
Example 9-39 Specifying a Single Dimension Value in an Allocation Specification
This example proportionally allocates a value it calculates from the sales variable to cells in a projectedsales variable. The sales variable is dimensioned by the time, product, customer, and channel dimensions.
The example defines the projectedsales variable to use as the target of the allocation and the increasefactor formula to use as the source. The formula multiplies values from sales by ten percent. The example limits the time dimension and creates the ytoq.rel relation, which relates the year 2001 to the quarters of 2002. The next LIMIT commands limit the dimensions shared by sales and projectedsales.
The example creates an aggmap and uses the ALLOCMAP statement to enter a RELATION and a DIMENSION statement into the map. The RELATION statement specifies the ytoq.rel relation as the dimension hierarchy to use for the allocation and specifies that the allocation is proportional. The DIMENSION statement tells ALLOCATE to set the status of the channel dimension to totalchannel for the duration of the allocation.
DEFINE projectedSales DECIMAL VARIABLE <time, SPARSE <product, customer>> DEFINE increaseFactor DECIMAL FORMULA <product> EQ sales * 1.1 LIMIT time TO '2001' 'Q1.02' TO 'Q4.02' DEFINE YtoQ.rel RELATION time <time> LIMIT time TO 'Q1.02' to 'Q4.02' YtoQ.rel = '2001' LIMIT time TO '2001' 'Q1.02' to 'Q4.02' LIMIT product TO 'TotalProduct' 'Videodiv' 'Audiodiv' 'Accdiv' LIMIT customers TO 'TotalCustomer' DEFINE time.alloc AGGMAP ALLOCMAP RELATION YtoQ.rel OPERATOR PROPORTIONAL DIMENSION channel 'TotalChannel' END ALLOCATE increaseFactor BASIS sales TARGET projectedSales USING time.alloc
The sales values that are the basis of the allocation are the following.
CHANNEL: TOTALCHANNEL
CUSTOMERS: TOTALCUSTOMER
---------------PROJECTEDSALES---------------
--------------------TIME--------------------
PRODUCT 2001 Q1.02 Q2.02 Q3.02 Q4.02
------------ ------ ------ ------ ------ ------
TotalProduct 7000 1000 2000 3000 1000
Videodiv 4100 600 1100 1900 500
Audiodiv 1700 200 600 600 300
Accdiv 1200 200 300 500 200
The following shows a report of projectedsales for totalchannel after the allocation.
CHANNEL: TOTALCHANNEL
CUSTOMERS: TOTALCUSTOMER
---------------PROJECTEDSALES---------------
--------------------TIME--------------------
PRODUCT 2001 Q1.02 Q2.02 Q3.02 Q4.02
------------ ------ ------ ------ ------ ------
TotalProduct NA NA NA NA NA
Videodiv NA 660 1210 2090 550
Audiodiv NA 220 660 660 330
Accdiv NA 220 330 550 220
Example 9-40 Entering RELATION Statements in an Allocation Specification
This example defines a time.type dimension and adds to it the two hierarchies of the time dimension. It defines the time.time relation that relates the hierarchy types (that is, time.type) to the time dimension. The example defines the time.alloc aggmap. With the ALLOCMAP command, it enters a RELATION statement in the aggmap. The RELATION statement specifies the values of the time dimension hierarchy to use in the allocation, limits the time dimension to one hierarchy with the QDR, and the specifies the EVEN operation for the allocation. The ALLOCATE command then allocates data from the source object to the target variable using the time.alloc aggmap. In the ALLOCATE command the source, basis, and target objects are the same sales variable.
DEFINE time.type TEXT DIMENSION MAINTAIN time.type add 'Fiscal' MAINTAIN time.type add 'Calendar' DEFINE time.time RELATION time <time, time.type> DEFINE time.alloc AGGMAP ALLOCMAP RELATION time.time (time.type 'Fiscal') OPERATOR EVEN END ALLOCATE sales USING time.alloc
Within an allocation specification, a CHILDLOCK statement tells the ALLOCATE statement to determine if RELATION statements in the allocation specification have specified locks on both a parent and on a child of the parent in a dimension hierarchy. Locking both a parent and one of its children can cause incorrect allocation results.
Syntax
CHILDLOCK [DETECT|NODETECT]
Parameters
Tells the ALLOCATE statement to detect that an allocation lock exists on a parent and also on one of its children in a dimension hierarchy. When it detects a locked parent and child, the ALLOCATE statement creates an entry in the error log for the allocation.
(Default) Tells the ALLOCATE statement to continue an allocation even when a lock exists on a parent and also on one of its children in a hierarchy.
Examples
For an example of using a CHILDLOCK statement in an allocation specification, see Example 9-79, "Creating an Aggmap for Allocation".
Within an allocation specification, a DEADLOCK statement tells the ALLOCATE statement what to do when it cannot distribute a source value to a target cell specified by a value in a dimension hierarchy because the target cell is either locked by a RELATION statement in the allocation specification or the cell has a basis value of NA.
Syntax
DEADLOCK [SKIP|NOSKIP]
Parameters
Tells the ALLOCATE statement to log the error and continue with the allocation even though it cannot distribute source values to cells specified by a branch of a dimension hierarchy because a target cell is locked or the basis value of the cell is NA.
Tells the ALLOCATE statement to stop the allocation and to return an error when it cannot distribute source values to cells in a branch of a dimension hierarchy because a target cell is locked or the basis value is NA. NOSKIP is the default action when you do not include a DEADLOCK statement in the aggmap used by the ALLOCATE command.
Examples
For examples of using a DEADLOCK statement in an allocation specification, see Example 9-37, "Allocation Specification from an Input File" and Example 9-38, "Allocation Specification from a Text Expression".
Within an allocation specification, a DIMENSION statement sets the status to a single value of a dimension. Within an allocation specification this dimension is a dimension that the source, basis, and target objects do not have in common. When an allocation specification does not specify such single values with DIMENSION statements, Oracle OLAP uses the current status values of the dimensions when performing the allocation.
You use a DIMENSION statement to ensure that the status of a dimension is set to the value that you want it to have for the allocation. You must use a separate DIMENSION statement for each dimension that is not shared by the source, basis, and target objects.
Syntax
DIMENSION dimension 'dimval'
Parameters
the name of the dimension to limit.
The single value of the dimension to which you want the status of the dimension set for the duration of an allocation.
Examples
For an example of using a DIMENSION statement in an allocation specification, see Example 9-39, "Specifying a Single Dimension Value in an Allocation Specification".
Within an allocation specification, an ERRORLOG statement specifies how many allocation error conditions to log and whether to continue or to stop the allocation when the specified maximum number of errors have been logged. You specify the error log with the ERRORLOG keyword to the ALLOCATE command.
Syntax
ERRORLOG [UNLIMITED|MAX <num>] [STOP|NOSTOP]
Parameters
Tells the ALLOCATE command to write an unlimited number of errors to the error log. (Default.)
Specifies a maximum number of errors that ALLOCATE can write to the error log.
Specifies whether to stop the allocation when ALLOCATE has written the maximum number of errors to the error log. When you specify STOP, the allocation stops. When you specify NOSTOP, the allocation continues but ALLOCATE does not write any more errors to the error log. When you have specified UNLIMITED, then the STOP and NOSTOP arguments have no effect and the allocation continues no matter how many errors occur.
Usage Notes
Formatting the Error Log
The ALLOCERRLOGFORMAT option determines the contents and the formatting of the error log that you specify with the ERRORLOG argument to the ALLOCATE command. You can specify a header for the error log with the ALLOCERRLOGHEADER option.
Within an allocation specification, an ERRORMASK statement specifies the error conditions that you do not want to appear in the allocation error log. You specify the error log with the ERRORLOG keyword to the ALLOCATE command.
Syntax
ERRORMASK <num...>
Parameters
The number of the error that you do not want to appear in the error log.
Examples
Example 9-41 Excluding CHILDLOCK Errors
To exclude a CHILDLOCK error, you would enter the following statement in the allocation specification.
ERRORMASK 10
Example 9-42 Excluding All Allocation Errors
To exclude all errors, you would enter the following statement in the allocation specification.
ERRORMASK 1 2 3 4 5 6 7 8 9 10
Within an allocation specification, a MEASUREDIM statement identifies the name of a measure dimension that is specified in the definition of an operator variable or an argument variable. However, you cannot specify a measure dimension when it is included in the definition of the aggmap object.
Syntax
MEASUREDIM name
Parameters
The name of the measure dimension. A measure dimension is a dimension that you define. The dimension values are names of existing variables.
Within an allocation specification, a RELATION statement identifies a relation that specifies the path through a dimension hierarchy and the method of the allocation. To allocate a source data down a hierarchy of a dimension, you must specify with a RELATION statement the values of the hierarchy that identify the cells of the variable that are the targets of the allocation. When the target of the allocation is a multidimensional variable, then you must include a separate RELATION statement for each dimension down which you want to allocate the source data. The order of the RELATION statements in an aggmap determines the order of the allocation. The allocation proceeds down the dimension hierarchy in the first RELATION statement, then down the second, and so on.
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Note: Do not confuse this RELATION statement which can only be used as part of an AGGMAP command with either the RELATION command that defines a default relation for a dimension or the RELATION statement that is used as part of an AGGMAP command. |
Syntax
RELATION rel-name [(qdr. . .)] OPERATOR {operator|} -
[NAOPERATOR operator] [REMOPERATOR operator] -
[PARENTALIAS dimension-alias-name] -
[ARGS {[FLOOR floorval] [CEILING ceilval] [MIN minval] [MAX maxval] -
[NAHANDLE {IGNORE|CONSIDER|PREFER}] -
[ADD|ASSIGN] [PROTECT [NONORMALIZE] [READWRITE|WRITE] lockvalueset] -
[WEIGHTBY [ADD|MULTIPLY] [WNAFILL nafillval] weightobj]}]
Parameters
An Oracle OLAP self-relation that specifies the values of a dimension hierarchy that identify the path of allocation. The cells in the target variable identified by the values in rel-name receive the allocated data.
One or more qualified data references that specify a single dimension value for each dimension of the relation that is not part of the self-relation. When the self-relation has multiple hierarchies, you must provide a qdr for the hierarchy dimension of the self-relation dimension that limits to single values any hierarchies not involved in the allocation.
Specifies an allocation method described in Table 9-3, "Allocation Operators" or returned by ALLOCOPS. The method determines the cells of the target variable for the rel-name relation to which ALLOCATE assigns a value. For the FIRST, LAST, HFIRST, and HLAST operators, ALLOCATE uses the order of the value in the dimension to determine the cell. The dimension order is the default logical order of the allocation dimension. There is no default operator for allocation.
Table 9-3 Allocation Operators
| Operator | Description |
|---|---|
|
COPY |
Copies the allocation source to all of the target cells that have a basis data value that is not |
|
HCOPY |
Copies the allocation source to all of the target cells specified by the hierarchy even when the data in any of those cells is |
|
MIN |
Copies the allocation source to the target that has the smallest basis data value. |
|
MAX |
Copies the allocation source to the target that has the largest basis data value. |
|
FIRST |
Copies the allocation source to the first target cell that has a non- |
|
HFIRST |
Copies the allocation source to the first target cell specified by the hierarchy even when the current data value of that cell is |
|
LAST |
Copies the allocation source to the last target cell that has a non- |
|
HLAST |
Copies the allocation source to the last target cell specified by the hierarchy even when the current data value of that cell is |
|
EVEN |
Divides the allocation source by the number of target cells that have non- |
|
HEVEN |
Divides the allocation source by the number of target cells, including the ones that have |
|
PROPORTIONAL |
Divides the allocation source by the sum of the data values of the target cells that have non- |
The operator after the NAOPERATOR keyword specifies the operator that the ALLOCATE o0eϚperation uses when it encounters an NA or lock-based deadlock. Valid operators are HFIRST, HLAST, and HEVEN which are described in Table 9-3, "Allocation Operators".
The operator after the REMOPERATOR keyword specifies the operator that the ALLOCATE operation uses when storing a remainder produced by an allocation. For example, assume you allocate the INTEGER 10 to three cells at the same level in a hierarchy, there is a remainder of 1. The REMOPERATOR specifies where you want the allocation operation to store this remainder. Valid operators for REMOPERATOR are MIN, MAX, FIRST, HFIRST, LAST, and HLAST which are described in Table 9-3, "Allocation Operators".
Indicates additional arguments specify additional parameters for the allocation operation. All of these arguments apply uniformly to the dimension hierarchy specified by rel-name.
Specifies specialized allocation depending on the parent (for example, weighting by parent or child). For dimension-alias-name, specify the name of the alias for the dimension of rel-name.
One or more arguments after the ARGS keyword that specify additional parameters for the allocation operation. All of these arguments apply uniformly to the dimension hierarchy specified by rel-name.
Specifies that when an allocated target data value is less than floorval, the data allocated to the target cell is NA. This argument applies to the relation only when the PROPORTIONAL operator is specified.
Specifies that when an allocated target data value is greater than ceilval, the data allocated to the target cell is NA. This argument applies to the relation only when the PROPORTIONAL operator is specified.
Specifies that when an allocated target data value is less than minval, the data allocated to the target cell is minval.
Specifies that when an allocated target data value is greater than maxval, the value allocated to the target cell is maxval.
Specifies how ALLOCATE treats NA values. Valid only when the OPERATOR is MIN or MAX.
IGNORE specifies that ALLOCATE does not consider NA values in a MIN or MAX operation. (Default)
CONSIDER specifies that ALLOCATE treats an NA value as a zero; however, when the data value of a target cell is actually zero, the zero cell receives the allocated data value and not the NA cell.
PREFER specifies that ALLOCATE treats an NA value as a zero and the NA has priority over a zero value, so the NA cell receives the allocated data value and not the cell with the actual zero value.
Specifies that ALLOCATE adds the allocated data to the current data in the target cell.
Specifies that ALLOCATE replaces the data in the target cell with the allocated data, which is the default behavior.
Specifies a set of dimension values to lock so that they cannot be targets of the allocation. Before allocating the source data, the allocation operation normalizes the sources by subtracting the data values of the specified locked cells from the source data.
Specifies that the allocation operation does not normalize the source data. Using NONORMALIZE effectively removes from the allocation the values of the hierarchy at and below the dimension values specified by lockvalueset.
Specifies that the locked data values cannot be used as source data in a subsequent allocation, thereby locking the data of the hierarchy below the lockvalueset values.
Specifies that the allocation cannot store data values in the cells identified by the lockvalueset dimension values but the allocation can use the data in those cells as source data in its subsequent steps. However, when in the aggmap you include a SOURCEVAL statement that specifies NA or ZERO and the locked cell is the source of an allocation, then ALLOCATE sets the value of the locked cell to NA or zero after the allocation.
Specifies that the allocation uses a the value specified by weightobj. Using this clause allows for processes such as unit or currency conversion.
Specifies that ALLOCATE adds the value specified by weightobj to the existing data value of the target and assigns the sum to the target cell.
(Default) Specifies that ALLOCATE multiplies the value specified by weightobj by the data value of the target and assigning the product.
Specifies that ALLOCATE replaces NA values in a cell before applying the value specified by weightobj to the nafillval value.
The value that the ALLOCATE replaces NA values with. When you specify the ADD option to the WEIGHTBY clause, the default NA fill value is 0; in all other cases, the default NA fill value is 1.
The name of an variable, formula, or relation whose value or values are the weights that Oracle OLAP applies to the allocated data just before it is stored in the target cell. When a relation is used, the target variable is referenced based on the weight relation and the cell is applied to the allocation target cell.
Usage Notes
Specifying the Path of the Allocation
The path of the allocation is the route the allocation system takes to go from the source data to the target data. Very different results derive from different allocation paths. You specify the path with the RELATION statements that you enter in the aggmap. The relation objects in the RELATION statements and the order of those statements specify the path and the method of allocation.
The allocation path goes from any level in the hierarchy of a dimension to any lower level of the hierarchy. You use a relation object that relates the members of the hierarchy to each other (a self-relation) to identify the elements of the hierarchy that you want to participate in the allocation. The allocation proceeds down the hierarchy of the dimension in the first RELATION statement in the aggmap, then down the hierarchy of the second RELATION statement, and so on.
When the dimension has multiple hierarchies, you must use the qdr argument in the RELATION statement to specify which hierarchy to use for the allocation. The hierarchy that you specify with a relation must not contain a circular relation (for example, one in which dimension value A relates to dimension value B which relates to dimension value C which relates to dimension value A).
Types of Allocation Paths
You can allocate values from a source to a target with any one of the following types of paths:
Direct allocation path — You can allocate values directly from a source to the final target cells with no allocations to intermediate nodes of the hierarchy. For example, you can allocate source data values specified by dimension values at the Quarter level of a hierarchical time dimension to those at the Month level or those specified by dimension values at the Year level to those at the Month level.
Recursive descent hierarchy path — You can allocate values to intermediate nodes of the hierarchy and then to final target cells. For example, you can allocate source data values specified by dimension values at the Category level of a product dimension to those at the Subcategory level and then to those at the ProductID level.
Multidimensional allocation path — You can allocate values first down one dimension and then down another dimension. The allocations can be direct or recursive or a combination of both. The results might vary depending on the order of the allocation.
Simultaneous multidimensional allocation path — You can do a direct allocation of values simultaneously to variable cells specified by multiple dimensions by creating a composite dimension that specifies the non-NA cells of the variable to which you want to allocate values. You then use that composite as the basis of the allocation.
Restrictions When Designing a RELATION Statement for Allocation
Keep the following restrictions in mind when designing a RELATION statement:
Oracle OLAP can perform allocations on only one hierarchy in a dimension in one execution of the ALLOCATE command. When a dimension has multiple hierarchies, then you must supply a qdr argument to limit the relation to only one hierarchy.
An allocation specification must include either a RELATION statement or a VALUESET statement.
Only one RELATION statement or VALUESET statement may be used for each dimension in the allocation specification.
Locking Cells in the Allocation Path
Sometimes you want a cell to retain its existing value and to not be affected by an allocation. You can lock a value of the hierarchy of the dimension and thereby remove that value from the allocation path.When you lock a value above the detail level in a hierarchy, then you remove the branch of the hierarchy below that value from the allocation. To lock a value, use the PROTECT argument to the RELATION statement.
For example, when you want to allocate a yearly budget that you revise monthly, then you would set the value of the budget at the Year level of the time dimension hierarchy. You would allocate data to the elements that are at the Month level. As the year progresses, you would enter the actual data for a month and then lock that element and reallocate the remaining yearly budget value to see the new monthly targets that are required to meet the annual goal.
When you lock an element, you can specify whether the source value is renormalized. By default, when you lock an element of the hierarchy, the value of the cell of the target variable specified by that element is subtracted from the source value and the remainder is allocated to the target cells. When you do not want the source renormalized during the allocation, specify NONORMALIZE after the PROTECT argument.
Examples
For an example of using RELATION statements in an allocation statement, see the examples in the ALLOCMAP command, especially Example 9-40, "Entering RELATION Statements in an Allocation Specification".
Within an allocation specification, a SOURCE VAL statement specifies the value that the ALLOCATE command assigns to a source cell in an allocation operation after it successfully allocates the value that the cell contained before the allocation.
The default value of SOURCEVAL is NA, which means that ALLOCATE sets the value of each of the allocated source cells to NA following the allocation. When you specify CURRENT as the SOURCEVAL, then the allocated source cells retain the values that they had before the allocation. When you specify ZERO as the SOURCEVAL, then ALLOCATE assigns a zero value to each source cell that is allocated.
Syntax
SOURCEVAL [CURRENT|ZERO|NA]
Parameters
Specifies that the value of a source cell after the allocation equals its value before the allocation.
Specifies that the value of a source cell after the allocation is zero.
Specifies that the value of a source cell after the allocation is NA. (Default value.)
Within an allocation specification, a VALUESET statement specifies the target dimension values of an allocation. A dimensioned valueset can be used to specify the allocation targets for an entire non-hierarchical dimension such as a measure or line dimension.
|
Note: Keep the following restrictions in mind:
|
Syntax
VALUSET vs-name[(nondimvalueset)| qdr... ] OPERATOR operator | opvar –
[NAOPERATOR text -exp] [REMOPERATOR text -exp] -
[ARGS [FLOOR floorval] [CEILING ceilval] –
[MIN minval] [MAX maxval] –
[ADDT [ {TRUE|FALSE} | ASSIGN] –
[{PROTECTRW| PROTECTW} [NONORMALIZE] lockvalueset] –
[WEIGHTBY [ADD] weightobj [WNAFILL nafillval]] | -
[WEIGHTBY WEIGHTVAR wobjr]]
Parameters
Specifies the name of a valueset object that specifies the values of a dimension which are the path of allocation. The cells in the target variable identified by the values in vs-name receive the allocated data.
When vs-name is a dimensioned valueset, specifies a nondimensioned valueset that is the status used to loop the valueset dimension. When you do not include nondimvalueset or qdr, Oracle OLAP uses the default logical order of the dimensions, not its current status.
When vs-name is a a non-dimensioned valueset, one or more qualified data references that specify the dimension values to use when allocating data.
The operator argument after the OPERATOR keyword is a text expression that is an operator type described in Table 9-3, "Allocation Operators". The operator type specifies the method of the allocation. The method determines the cells of the target variable for the vs-name relation to which ALLOCATE assigns a value. Unless you have specified a different status using dimorder valueset, for the FIRST, LAST, HFIRST, and HLAST operators, ALLOCATE uses the default logical order of the allocation dimension to determine the cell. There is no default operator for allocation.
The opvar argument after OPERATOR keyword specifies a TEXT variable that specifies different the operation for each of the values of a dimension. The values of the variable are the allocation operators described in Table 9-3, "Allocation Operators". An operator variable is used to change the allocation operator with the values of one dimension. The opvar argument is used with the following types of dimensions:
Measure dimension -- Changes the allocation method depending upon the variable being allocated. The values of the measure dimension are the names of the variables to be allocated. It dimensions a text variable whose values identify the operation to be used to allocate each measure. The allocation specification must include a MEASUREDIM (for allocation) statement that identifies the measure dimension.
Line item dimension -- Changes the allocation method depending upon the line item being allocated. The line item dimension is typically non-hierarchical and identifies financial allocations. The line item dimension is used both to dimension the data variable and to dimension a text variable that identifies the operation to be used to allocate each item. The operation variable is typically used to allocate line items over time.
The opvar argument cannot be dimensioned by the dimension it is used to allocate. For example, when you want to specify different operations for the geography dimension, then opvar cannot be dimensioned by geography.
|
Tip: To minimize the amount of paging for the operator variable, define the opvar variable as type ofTEXT with a fixed width of 8. |
The operator after the NAOPERATOR keyword specifies the operator that the ALLOCATE operation uses when it encounters an NA or lock-based deadlock. Valid operators are HFIRST, HLAST, and HEVEN which are described in Table 9-3, "Allocation Operators".
The operator after the REMOPERATOR keyword specifies the operator that the ALLOCATE operation uses when storing a remainder produced by an allocation. For example, assume you allocate the INTEGER 10 to three cells at the same level in a hierarchy, there is a remainder of 1. The REMOPERATOR specifies where you want the allocation operation to store this remainder. Valid operators for REMOPERATOR are MIN, MAX, FIRST, HFIRST, LAST, and HLAST which are described in Table 9-3, "Allocation Operators".
Indicates that additional arguments specify additional parameters for the allocation operation. All of these arguments apply uniformly to the valueset.
Specifies that when an allocated target value falls below the value specified in floorval, Oracle OLAP stores the value as NA.
Specifies that when an allocated target value exceeds the value specified in ceilval, then Oracle OLAP stores the value as NA.
Specifies that when an allocated target value falls below the value specified minval, then Oracle OLAP stores the value of minval in the target.
Specifies that when an allocated target value exceeds the value specified maxval, then Oracle OLAP stores the value of maxval in the target
The ADDT phrase specifies the sign of the addition when Oracle OLAP adds target cells to the existing contents of the target cell:
TRUE specifies that the results of the allocation are added to the target. (Default)
FALSE specifies that the results of the allocation are subtracted from the target cell.
Specifies that the dimension members specified by lockvalueset cannot be the targets or source values of allocation. Using this phrase allows users to specify an allocation "lock" on a hierarchical subtree. The current contents of the target cell are subtracted from the source and the source and basis is renormalized.
Specifies that the dimension members specified by lockvalueset cannot be the targets of an allocation. However, these target cells are used as the source values for subsequent steps in the allocation process. When the SOURCEVAL statement is set to 0 (zero) or NA and these values are reallocated, they are set appropriately.
Specifies that Oracle OLAP should not renormalize the source and basis based on the protected cells. Specifying this keyword has an effect similar to removing a sub-branch from a hierarchy. Frequently, when you use this keyword, if, after allocation, data is aggregated from the allocation level, the source cell probably does not contain the original allocated amount
Specifies a weight that should be applied to the target cell just before it is stored. Using this phrase allows for processes such and unit or currency conversion. Value weight objects are variables, formulas and relations. When a relation is used, the target variable is referenced based on the weight relation, and the cell is applied the allocation target cell.
Specifies that Oracle OLAP adds the value of the weight to the allocation target rather than using multiplication.
Specifies the default value of the weight variable that should be used. When you do not include an ADD clause, the default value of nafillval is 1. When you include the ADD clause, the default value of nafillval is 0 (zero).
Specifies that the allocated data should be weighted. The wobj argument is the name of a variable, relation, or formula whose values are the weights that Oracle OLAP applies to the allocated data just before it is stored in the target cell. Using this clause allows for processes such as unit or currency conversion and enables you to use different weight objects with the different operators specified in the operator variable you created for the OPERATOR opvar clause.
The TRIGGERSTOREOK option controls whether you can use $STORETRIGGERVAL properties to specify that NA values in an object be permanently replaced by the values specified by a $NATRIGGER property.
|
Important: The value of the TRIGGERSTOREOK option is only one factor that Oracle OLAP uses to determine what to do with variable data that is the result of $NATRIGGER expression execution. For a discussion of the other factors and their interrelationship, see "How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER". |
Data Type
BOOLEAN
Syntax
TRIGGERSTOREOK = {NO|YES}
Parameters
(Default) NA values are not permanently replaced with the $NATRIGGER property expression that is set for a variable.
NA values are permanently replaced with the $NATRIGGER property expression that is set for a variable. The default value is NO.
For Oracle OLAP to permanently replace NA values for a variable with the valid $NATRIGGER property expression that is set for the variable, you must set both the TRIGGERSTOREOK option and the $STORETRIGGERVAL property for the variable to YES.
Usage Notes
About the $NATRIGGER and STORETRIGGERVAL Properties
The TRIGGERSTOREOK option works with the $NATRIGGER and $STORETRIGGERVAL properties of a variable.
Examples
Example 5-109 Replacing NA Values Temporarily
This example replaces the NA values in the cells of a variable temporarily. The following statements define a dimension with three values and define a variable dimensioned by the dimension. They add the $NATRIGGER property to the variable, then put a value in one cell of the variable and leave the other cells empty, so that their values are NA. Finally, they report the values in the cells of the variable.
DEFINE d1 INTEGER DIMENSION MAINTAIN d1 ADD 3 DEFINE v1 DECIMAL <d1> PROPERTY '$NATRIGGER' '500.0' v1(d1 1) = 333.3 REPORT v1
The preceding statements produce the following output.
D1 V1
--------- ----------
1 333.30
2 500.00
3 500.00
This statement deletes the $NATRIGGER property from the v1 variable.
CONSIDER v1 PROPERTY DELETE '$NATRIGGER' REPORT v1
The preceding statements produce the following output.
D1 V1
--------- ----------
1 333.30
2 NA
3 NA
Example 5-110 Replacing NA Values Permanently
The following statements add the $NATRIGGER property to the v1 variable that was defined in the previous example and set the TRIGGERSTOREOK option and the $STORETRIGGERVAL properties to YES. They then report the values in the cells of the variable.
CONSIDER v1 PROPERTY '$NATRIGGER' '800.0' TRIGGERSTOREOK = YES PROPERTY 'STORETRIGGERVAL' YES REPORT v1
The preceding statements produce the following output.
D1 V1
-------------- ----------
1 333.30
2 800.00
3 800.00
The following statements delete the $NATRIGGER property from the v1 variable and report the values in the cells of the variable.
CONSIDER v1 PROPERTY DELETE '$NATRIGGER' REPORT v1
The preceding statements produce the following output.
D1 V1
-------------- ----------
1 333.30
2 800.00
3 800.00
The RELATION command identifies a relation as the default relation for a specified dimension of the current object; or removes the default relation information from the current object. For more information on default relations, see "Using Related Dimensions in Expressions".
|
Note: Do not confuse the RELATION command with the RELATION statements in AGGMAP or ALLO.CMAP. |
Syntax
RELATION {dimension-name relation-name }| DELETE { ALL | dimension-name}
Parameters
The name of a previously-defined dimension. The dimension specified by the dimension-name argument must be a dimension of the currently considered object for which you want to specify or delete a default relation.
|
Note: The dimension specified by the dimension-name argument must be a dimension of the currently considered object. The current object is the object that has been most recently defined or considered during the current session. To make an object definition the current definition, use a CONSIDER statement. |
The name of a previously-defined relation that Oracle OLAP uses as the default relation for the dimension specified by dimension-name.
Specifies removal of previously-specified default relation information.
Removes all previously-defined default relation information.
Usage Notes
How Oracle OLAP Chooses Between Multiple Relations
When there are multiple relations between the two dimensions and you attempt to perform calculation on one of those dimension based on related dimensions, Oracle OLAP chooses the relation to use when executing the statement as follows:
Uses the relation specified in the statement, if any.
Uses the default relation for the dimension. Oracle OLAP determines the default relation as follows:
When you have specified a default relation using the RELATION command, Oracle OLAP recognizes that relation as the default relation.
When you have not specified a default relation using the RELATION command, Oracle OLAP recognizes the first relation that you defined as the default relation.
Identifying Default Relations
Use the OBJ function with the RELATION keyword to identify the default relation information for an object.
Multiple RELATION Commands Against the Same Object
Unlike other statements that operate against the most recently considered object (for example, an LD statement), a new RELATION command does not replace previously-issued RELATION commands. Instead, issuing multiple RELATION commands against the same object has a cumulative effect.
Examples
Example 10-95 Specifying a Default Relation Using the Relation Command
Assume that you defined the following analytic workspace objects (in the following order).
DEFINE CITY DIMENSION TEXT DEFINE DISTRICT DIMENSION TEXT DEFINE CITY_DISTRICT RELATION DISTRICT <CITY> DEFINE CITY_REDISTRICT_1 RELATION DISTRICT <CITY> REPORT city_district CITY CITY_DISTRICT -------------------- -------------------- Annapolis Southern Bethesda Southern Charlotte Southern Gettysburg Southern Greensboro Southern Raleigh Southern Reston Southern Rochester Southern Virginia Beach Southern Washington Capital REPORT city_redistrict_1 CITY CITY_REDISTRICT_1 -------------------- -------------------- Annapolis Capital Bethesda Capital Charlotte Southern Gettysburg Southern Greensboro Southern Raleigh Southern Reston Southern Rochester Southern Virginia Beach Capital Washington Capital
As the following OBJ statements illustrate, the city_district relation is the default relation between city and district since the city_district relation was the first relation defined between city and districtt and a default relation has not been specified using a RELATION statement.
SHOW OBJ (RELATION ACTUAL 'city' 'district') CITY_DISTRICT SHOW OBJ (RELATION SPECIFIED 'city' 'district') NA
Assume that you now issue the following statements to limit district to Washington and make the city_redistrict_1 relation the default relation.
LIMIT city TO district CONSIDER city RELATION city city_redistrict_1
As the following OBJ statements illustrate, now the city_redistrict_1 relation that you specified with the RELATION statement is the default relation between city and district.
SHOW OBJ (RELATION ACTUAL 'city' 'district') CITY_REDISTRICT_1 SHOW OBJ (RELATION SPECIFIED 'city' 'district') CITY_REDISTRICT_1
Also, as the following statements illustrate, when you limit city to district, you get the same results as limiting city to the city_redistrict_1 relation
LIMIT city TO district REPORT city CITY -------------------- Annapolis Bethesda Virginia Beach Washington LIMIT city to ALL LIMIT city to city_redistrict_1 REPORT city CITY -------------------- Annapolis Bethesda Virginia Beach Washington
The LOG command starts or stops the recording of a session to a disk file. All lines of input and output are recorded.
|
Note: Do not confuse the LOG command with the function of the same name which is a mathematical function. |
Syntax
LOG EOF | TRACEFILE | SAVE | {[APPEND] file-name}
Parameters
Stops recording of the session and closes any opened log record file.
Specifies that the session information should be directed the Oracle trace file, which is identified by the TRACEFILEUNIT option.
Forces Oracle OLAP to update the log file. Lines of input and output are not always written to disk as they are generated. Instead, the lines are stored temporarily then written to disk periodically. LOG SAVE effectively issues the LOG EOF and LOG APPEND file-name commands which ensures that all appropriate lines are written to disk by closing the log file and reopening it. Additional lines of input and output are appended to the file.
Specifies that the record of your session should be added to the end of an existing disk file. When you omit this argument, the new output replaces the current contents of the file.
A text expression that is the name of the file to which session information should be written. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Usage Notes
Automatic Closing of a Log File
When you use LOG file-name to start recording in a disk file, LOG closes any log record file that is currently open. LOG issues this close even when the new file is not actually opened (as when you specify an invalid file name in the LOG statement).
Examples
The ISNAN function returns a value that indicates if a the value of a numeric expression is the special NaN value.
|
See also: This function provides information similar provided by the SQL IS [NOT] NAN floating point condition as described in Oracle Database SQL Language Reference. |
Return Value
BOOLEAN
Returns TRUE when the expression is either +NaN (or -NaN when NOT is not specified); otherwise it returns FALSE.
|
Note: The OLAP DML converts+NaN or -NaN values to NA when it performs calculation. Consequently, this function can only possibly return TRUE when executed against data that has been imported into an analytic workspace from a SQL-populated database but not yet used in an OLAP DML calculation. |
Syntax
ISNAN(expression)
Parameters
A decimal expression.
The PROPERTY command adds or deletes properties to the most recently defined or considered object (see the DEFINE PROGRAM and CONSIDER commands). A property is a named value that is associated with a given definition. You can assign one or more properties to any type of definition. For example, you can assign a property to an object so you know how many decimal places to use when preparing a report on the object.
Syntax
PROPERTY { name value | DELETE {ALL | name} }
Parameters
A text expression that contains the name of the property. The property name can be from 1 to 256 bytes long.
|
Important: Do not create your own properties with names that begin with a$ (dollar sign). Properties with names beginning with a $ (dollar sign) are reserved for Oracle OLAP to use as "system" properties that Oracle OLAP interprets in predetermined ways. |
Property names have the TEXT data type, unless you include a Unicode escape sequence in the value you specify for the name, or unless you explicitly convert the value you specify to NTEXT (using the CONVERT or TO_NCHAR functions).
An expression that contains the value of the property. The property value can have one of the following data types: NUMBER, INTEGER, LONGINTEGER, DECIMAL, SHORTDECIMAL, TEXT, NTEXT, ID, BOOLEAN, DATE, or DATETIME. Oracle OLAP determines the data type based on the value that you specify. For example, when you specify YES, then Oracle OLAP assumes a type of BOOLEAN. When you specify a date value that is stored in a variable of type DATE, then Oracle OLAP assumes a type of DATE for the property.
Deletes either all of the properties of the object or only the property you specify for name. You can specify only one name at a time.
Usage Notes
Triggering Program Execution When PROPERTY Executes
Using the TRIGGER command, you can make a PROPERTY statement an event that automatically executes an OLAP DML program. See "Trigger Programs" for more information
Changing a Property Value
When you execute a PROPERTY statement that assigns a new value to an existing property name, then the new value overwrites the previous one.
Determining Property Values with OBJ
To use properties with OLAP DML statements, you must obtain the values by using the property-related keywords of the OBJ function. For example, suppose a property called decplace stores the number of decimal places to use when reporting an object. When you execute a REPORT statement, you can use the OBJ function with the PROPERTY keyword to obtain the value of the decplace property and use that value with the REPORT statement's DECIMAL attribute.
Listing Property Values with FULLDSC
You can list the properties of an object by using a FULLDSC statement. You can use the output from FULLDSC to create new objects. See the FULLDSC program for more information.
Examples
Example 10-83 Adding Properties to a Variable
The following statements add the properties decplace and prgname to the actual variable and assign the decimal 4 as the value for the decplace property and the text repprg as the value for the prgname property.
CONSIDER actual PROPERTY 'decplace' 4 PROPERTY 'prgname' 'repprg'
The ALLCOMPILE program compiles every compilable object in your current analytic workspace, one at a time. As it works, ALLCOMPILE sends to the current outfile messages that show the name of the object being compiled.
ALLCOMPILE uses the COMPILE command. Consequently, it checks for syntax errors as it compiles an object, and it records error messages in the current outfile as appropriate.
Syntax
ALLCOMPILE [n]
Parameters
An INTEGER expression with a value of zero or higher. The expression specifies the number of objects to be compiled before an UPDATE statement is executed. For example, when you specify 1, an UPDATE statement is executed after each object is compiled. When you specify 0 (zero), all the objects are compiled and an UPDATE statement is executed only at the end. When you omit the argument, no UPDATE statement is executed by ALLCOMPILE. Frequent updates during an ALLCOMPILE help ensure the most efficient use of space in the analytic workspace.
Examples
The EIFUPDBYTES option controls the frequency of updates when you are using the IMPORT (EIF) command with its UPDATE keyword. The value of EIFUPDBYTES has an effect only when the UPDATE keyword is specified in this command.
Data Type
INTEGER
Syntax
EIFUPDBYTES = n
Parameters
An INTEGER expression that specifies the minimum number of bytes to be read between updates, during an import. When EIFUPDBYTES has a value of 0, an update is triggered after each analytic workspace object is imported. When EIFUPDBYTES has a value greater than 0, an update is triggered each time the specified number of bytes is imported. The default is 0 (zero).
Examples
The COUNT function counts the number of TRUE values of a Boolean expression. It returns 0 (zero) when no values of the expression are TRUE.
Return Value
INTEGER
Syntax
COUNT(boolean-expression [CACHE] [dimension...])
Parameters
The Boolean expression whose TRUE values are to be counted.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of boolean-expression and another dimension that you want as a dimension of the result.
By default, COUNT returns a single YES or NO value. When you indicate one or more dimensions for the result, COUNT tests for TRUE values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of boolean-expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of boolean-expression, but, instead, is dimension that is related to a dimension of boolean-expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
The Effect of NASKIP on COUNT
COUNT is affected by the NASKIP option. When NASKIP is set to YES (the default), COUNT returns the number of TRUE values of the Boolean expression, regardless of how many other values are NA. When NASKIP is set to NO, COUNT returns NA when any value of the expression is NA. When all the values of the expression are NA, COUNT returns NA for either setting of NASKIP.
Examples
Example 7-55 Counting True Values by District
You can use COUNT to find the number of months in which each district sold more than 2,000 units of sportswear. To obtain a count for each district, specify district as the dimension for the result.
LIMIT product TO 'SPORTSWEAR' REPORT HEADING 'Count' COUNT(units GT 2000, district)
The preceding statement statements produce the following output.
DISTRICT Count -------------- ---------- Boston 0 Atlanta 23 Chicago 11 Dallas 24 Denver 7 Seattle 0
The GROWRATE function calculates the growth rate of a time-series expression, based on the first and last values of the series.
GROWRATE bases its calculation on the values of expression that correspond to the first and last values in the status of time-dimension. The intervening values of expression are ignored. GROWRATE uses the following calculation.
GROWRATE = ((last/first)**(1/(n-1))-1
In the exponent, n is the number of values in the status of the time dimension.
Return Value
DECIMAL
The result returned by GROWRATE is dimensioned by all the dimensions of expression except the dimension specified by time-dimension.
Syntax
GROWRATE(expression [time-dimension])
Parameters
A numeric expression for which you want to calculate the growth rate. The expression must be dimensioned by a time dimension.The following rules apply to the first and last values of expression:
The first value of expression cannot be zero. (This is to avoid a division by zero in the GROWRATE calculation.)
The first and last values of expression must both be positive or both negative. (Or the last value of expression can be zero, regardless of whether the first value is positive or negative.)
Neither the first value nor the last value of expression can be NA.
The name of the time dimension by which expression is dimensioned. When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional, unless loans has multiple time dimensions.
Examples
Example 7-107 Determining Growth Rate
The following statements limit the dimensions of the actual variable and produce a report.
LIMIT month TO 'Dec95' TO 'Mar96' LIMIT line TO 'net.income' REPORT DOWN division ACROSS month: actual
These statements produce the following report.
LINE: NET.INCOME
------------------ACTUAL-------------------
-------------------MONTH-------------------
DIVISION Dec95 Jan96 Feb96 Mar96
-------------- ---------- ---------- ---------- ----------
Camping 4,378.09 19,915.13 22,510.38 34,731.63
Sporting 6,297.02 13,180.29 17,429.17 18,819.14
Clothing 87,471.74 107,257.85 133,566.01 127,132.55
The statement REPORT W 20 GROWRATE(actual)produces a report that shows the growth rate of the actual net income in the demo workspace between December 1995 and March 1996.
--GROWRATE(ACTUAL)--
--------LINE--------
DIVISION NET.INCOME
-------------- --------------------
Camping 0.99
Sporting 0.44
Clothing 0.13
The PAGENUM option holds the current page number of output. You can use PAGENUM with PAGEPRG to produce the page number on each page of a report. The PAGENUM option is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and LISTNAMES.
Data Type
INTEGER
Syntax
PAGENUM = n
Parameters
An INTEGER expression that specifies the page number to use for the next page of output. The default is 1.
Usage Notes
Starting with Page 1
When you are sending output to the default outfile, set both PAGENUM and LINENUM to 1 whenever you want to produce a report starting on page 1. You can set these options in the initialization section of your report program. When you use an OUTFILE statement to send output to a file, PAGENUM is automatically set to 1.
Setting PAGENUM in Mid-Page
The value of PAGENUM is incremented automatically when the last line of output has been generated on a page. When you set PAGENUM when an output page is only partially full, the value of PAGENUM is incremented by 1 before the next page is produced. Consequently, you usually have to set PAGENUM to a value of one less than the number you want to show on the following page.
The Effect of PAGING on PAGENUM
When you set PAGING to NO, PAGENUM stops counting and keeps its last value. When you reset PAGING to YES, PAGENUM resumes counting at the page number where it left off.
The Effect of OUTFILE on PAGENUM
When you use an OUTFILE statement to direct output to a file, PAGENUM is set to 1 for the file. When you use an OUTFILE statement with the EOF keyword to redirect output to the default outfile, PAGENUM contains the number that it last held for the default outfile.
Examples
Example 5-84 Changing the Heading for Page 2
Suppose you want each page of a report to have a standard running page heading and a custom title, and pages after the first page to also have the heading "(Continued)". You can define a page heading program called report.head that uses the PAGENUM value to determine when to add the "(Continued)" heading.
DEFINE report.head PROGRAM PROGRAM STDHDR BLANK PAGING = YES HEADING WIDTH LSIZE CENTER 'Annual Sales Report' BLANK IF PAGENUM GT 1 THEN HEADING WIDTH LSIZE CENTER '(Continued)' BLANK END
In your report program, set the PAGEPRG option to use the report.head program.
PAGEPRG = 'report.head'
When you run the report program, each page after the first page starts with a heading such as the following.
15JAN95 15:05:16 Page 2
Annual Sales Report
(Continued)
The $VARCACHE property specifies whether Oracle OLAP stores or caches variable data that is the result of the execution of an AGGREGATE function or a $NATRIGGER expression.
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See also: "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data", "How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER", "What is an Oracle OLAP Session Cache?", and the description of the NA keyword of the CACHE statement for information on caching NA values calculated by the AGGREGATE function. |
Syntax
You add or delete a $VARCACHE property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$VARCACHE' value
To delete the property, issue the following statement.
PROPERTY DELETE '$VARCACHE'
Parameters
One of the following TEXT expressions that indicate where Oracle OLAP should place variable data that is the result of calculations performed when the AGGREGATE function or $NATRIGGER value executes:
VARIABLE specifies that Oracle OLAP populates the variable with data that is the result of the execution of the AGGREGATE function or $NATRIGGER property. When you specify this option, the data that is the result of the aggregation is permanently stored in the variable when the analytic workspace is updated and committed.
SESSION specifies that Oracle OLAP caches data that is the result of the execution of the AGGREGATE function or $NATRIGGER property in the session cache (See "What is an Oracle OLAP Session Cache?"). When you specify this option, the data that is the result of the execution of the AGGREGATE function or $NATRIGGER property is ignored during updates and commits and is discarded after the session.
|
Important: When SESSCACHE is set toNO, Oracle OLAP does not cache the data even when you specify SESSION. In this case, specifying SESSION is the same as specifying NONE. |
NONE specifies that Oracle OLAP calculates new variable data each time the AGGREGATE function or $NATRIGGER value executes; Oracle OLAP does not store or cache the data.
DEFAULT specifies that you do not want Oracle OLAP to use the $VARCACHE property when determining what to do with data that is calculated by the AGGREGATE function. (See "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data".)
Usage Notes
How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER
When a $NATRIGGER expression executes, what Oracle OLAP does with variable data that results from the execution of the expression is determined based on whether or not the variable that has the $NATRIGGER property also has a $STORETRIGGERVAL property and, if not, if the value of the $NATRIGGER property is an AGGREGATE function.
When a a $NATRIGGER expression executes, Oracle OLAP goes through the following process:
Does the variable with the $NATRIGGER property also have a $STORETRIGGERVAL property? If it does, then Oracle OLAP goes to step 1a. If it does not, then Oracle OLAP goes to step 2.
Is the value of the TRIGGERSTOREOK option, YES or NO? If it is YES, then Oracle OLAP goes to step 1b. If it is NO, then Oracle OLAP goes to step 2.
Is the value of the $STORETRIGGERVAL property, YES or NO? If it is YES, then Oracle OLAP stores the results of the $NATRIGGER expression and end decision-making process. If it is NO, then Oracle OLAP does not store the results of the $NATRIGGER expression and end decision-making process.
Is the $NATRIGGER expression an AGGREGATE function? If it is, then Oracle OLAP follows the steps described in "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data" to determine what to do with the result of $NATRIGGER expression execution. If it is not, then Oracle OLAP goes to step 3.
Does the variable with the $NATRIGGER property also have a $VARCACHE property? If it does, then Oracle OLAP goes to step 4. If it does not, then Oracle OLAP goes to step 5.
Does the $VARCACHE property have a value of DEFAULT? If it does, then go to step 5. If it does not, then Oracle OLAP uses the value of the $VARCACHE property (that is, STORE, CACHE, or NONE) to determine what happens to the variable data values that are the result of $NATRIGGER expression execution and end decision-making process.
Use the current setting of the VARCACHE option to determine what happens to the variable data values that are the result of $NATRIGGER expression execution and end decision-making process.
How Oracle OLAP Determines Whether to Store or Cache Aggregated Data
When an AGGREGATE command executes, Oracle OLAP always stores the results of the calculation directly in the variable in the same way it stores the results of an assignment statement. However, when an AGGREGATE function executes, Oracle OLAP sometimes stores the results of the calculation directly in the variable and sometimes caches it in the session cache. (See "What is an Oracle OLAP Session Cache?" for more information about the session cache.)
To determine where to place the data that is the result of AGGREGATE function execution, Oracle OLAP goes through the following process to determine whether to store or cache aggregated variable data:
Is there a CACHE statement in the specification for the aggmap that is being used by the current AGGREGATE function? If there is, then Oracle OLAP goes to step 2. If there is not, then Oracle OLAP goes to step 3.
Is the CACHE statement a CACHE DEFAULT statement? If it is, then Oracle OLAP goes to step 3. If it is not, then Oracle OLAP uses the CACHE statement in the aggregation specification to determine what to do with variable data that is the result of the calculation and ends the decision-making process.
Does the variable being aggregated have a $VARCACHE property? If it does, then Oracle OLAP goes to Step 4. If it does not, then Oracle OLAP goes to step 5.
Does the $VARCACHE property have a value of DEFAULT? If it does, then Oracle OLAP goes to step 5. If it does not, then Oracle OLAP uses the value of the $VARCACHE property determines what happens to the variable data calculated using the AGGREGATE function, and ends the decision-making process.
Use the current setting of the VARCACHE option to determine what happens to the variable data calculated using the AGGREGATE function. End decision-making process.
Examples
The FILECLOSE command closes an open file. When the file has not been opened, an error occurs.
Syntax
FILECLOSE fileunit
Parameters
An INTEGER fileunit number assigned to an open file by a previous call to the FILEOPEN function or by an OUTFILE command.
Usage Notes
LOG Command
You must use the LOG command with the EOF keyword, rather than FILECLOSE, to close a file that was opened with the LOG command.
Examples
Example 9-120 Program That Opens and Closes a File
Suppose you have a program called READFILE that takes a file name as its first argument. The following lines from the program open the file and then close it.
fil.unit = FILEOPEN(arg(1), read) ... (Commands to read and process data) FILECLOSE fil.unit
The AVERAGE function calculates the average of the values of an expression.
Return Value
DECIMAL
Syntax
AVERAGE(expression [CACHE] [dimension ...] )
Parameters
The expression whose values are to be averaged.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of expression and another dimension that you want as a dimension of the result.
By default, AVERAGE returns a single value. When you indicate one or more dimensions for the result, AVERAGE calculates values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of expression, but, instead, is dimension that is related to a dimension of expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
NA Values and AVERAGE
AVERAGE is affected by the NASKIP option in the same manner as other aggregate functions. When NASKIP is set to YES (the default), AVERAGE ignores NA values and returns the average of the values that are not NA. When NASKIP is set to NO, AVERAGE returns NA when any value of the expression is NA. When all the values of the expression are NA, AVERAGE returns NA for either setting of NASKIP.
Averaging Over a Dimension of Type DAY, WEEK, MONTH, QUARTER, or YEAR
When expression is dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other dimension that has one of these types as a related dimension. Oracle OLAP uses the implicit relation between the two dimensions. To control the mapping of one of these types of dimensions to another (for example, from weeks to months), you can define an explicit relation between the two dimensions and specify the name of the relation as the dimension argument to the AVERAGE function.
For each time period in the related dimension, Oracle OLAP averages the data for all the source time periods that end in the target time period. This method is used regardless of which dimension has the more aggregate time periods. To control the way in which data is aggregated or allocated between the periods of two dimensions, you can use the TCONVERT function.
Examples
Example 7-25 Calculating Average Monthly Sales
This example shows how to calculate the average monthly sales of sportswear for each sales district.
LIMIT product TO 'SPORTSWEAR' REPORT W 14 HEADING 'Average Sales' AVERAGE(sales district)
The preceding statements produce the following output.
DISTRICT Average Sales ----------- -------------- Boston 69,150.41 Atlanta 151,192.36 Chicago 95,692.99 Dallas 162,242.89 Denver 88,892.72 Seattle 54,092.32
You might also want to see the average monthly sales for each region. Since the region dimension is related to the district dimension, you can specify region instead of district as a dimension for the results of AVERAGE.
The OKNULLSTATUS option determines whether Oracle OLAP allows a dimension status list to be set to null. The default is to not allow an empty status list. When null status lists are not allowed, Oracle OLAP produces an error message when you execute a LIMIT command that would result in a null status list.
Data Type
BOOLEAN
Syntax
OKNULLSTATUS = {YES|NO}
Parameters
Indicates that null status lists are allowed. With this setting, when you execute a LIMIT command (without the IFNONE argument) that results in a dimension status list being null, the status list is set to null, and no error message is produced.
(Default) Indicates that null status lists are not allowed. With this setting, when you execute a LIMIT command (without the IFNONE argument and without the NULL keyword) that would result in a dimension status list being null, the status list is not changed and an error message is produced.
Usage Notes
Conditions When OKNULLSTATUS Has No Effect
The value of OKNULLSTATUS has no effect in the following situations.
When a LIMIT command includes an IFNONE argument.
When a LIMIT command uses the NULL keyword to set a dimension status list to null.
When a LIMIT command sets a valueset to null (unless the IFNONE argument is used). The valueset is set to null, and no error message is produced, even when OKNULLSTATUS is NO.
When a LIMIT function is specified to return a null dimension status list. The value returned is NA, and no error message is produced, even when OKNULLSTATUS is NO.
See the LIMIT command for more information about using null status in dimensions and valuesets.
Examples
The STATMAX function returns the latest value in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
The data type returned by STATMAX is either the data type of the dimension or dimension surrogate value or an INTEGER that indicates its position in the default status list of the dimension or surrogate. See "Automatic Conversion of Values Returned by STATMAX".
Syntax
STATMAX(dimension)
Parameters
A text expression whose value is the name of a dimension, dimension surrogate, or valueset.
Usage Notes
Automatic Conversion of Values Returned by STATMAX
The value that STATMAX returns is converted to a number or a text value as appropriate to the context. For example, suppose that the status of month is limited to Jun95 to Dec95 and that Dec95 is the twelfth month in the default status list. The value of STATMAX(month) can be assigned either to a text variable or a numeric variable.
The following statements
DEFINE textvar TEXT textvar = STATMAX(month) SHOW textvar
produce this output.
Dec95
In contrast, these statements
DEFINE intvar INTEGER intvar = STATMAX(month) SHOW intvar
produce this output.
12
Examples
Example 8-113 STATMAX Used in a Title
The following statements from a program use STATMAX to determine the latest of the 10 months with the highest total sales.
LIMIT month TO BOTTOM 10 BASEDON TOTAL(sales, month)
SHOW JOINCHARS(STATMAX(month) ' is the latest month -
of the ten months with the lowest sales.')
SHOW JOINCHARS('the months range from ' STATMIN(month) ' to '-
STATMAX(month))
These statements produce the following sales report.
Dec96 is the latest month of the ten months with the lowest sales. The months range from Jan95 to Dec96
When you used STATLAST instead of STATMAX, you could have produced a different value, because the LIMIT command arranged the month values by increasing sales rather than chronologically.
(Read-only) The EIFBYTES option holds the number of bytes read by the most recent IMPORT (EIF) command or written by the most recent EXPORT (EIF) command.
Data Type
INTEGER
Syntax
EIFBYTES
Examples
Example 5-27 Finding Out the Number of Bytes
To find out how many bytes of information were exported to an EIF file when you exported the dimensions of the demo workspace, you use the following statements.
LIMIT name TO OBJ(TYPE) EQ 'DIMENSION' EXPORT ALL TO EIF FILE 'myfile.eif' SHOW EIFBYTES
The SHOW statement produces the following output.
2,038
The POPLEVEL command (abbreviated PPL) restores all values saved with PUSH commands that were executed since the last POPLEVEL statement specifying the same marker.
You must use PUSHLEVEL to mark a starting point for a series of PUSH commands before you can use POPLEVEL to restore the saved values. POPLEVEL itself marks the end of the series. You can use POPLEVEL only within programs.
|
See also: "Considerations When Designing PUSHLEVEL and POPLEVEL Statements", POP, PUSH, PUSHLEVEL, and CONTEXT commands. |
Syntax
POPLEVEL marker-expression [DISCARD]
Parameters
A text value used as a marker. This value must be the same as the value used in the corresponding PUSHLEVEL statement to mark the start of a series of saved values being popped.
Specifies that the pushed values for that level are discarded when you issue a POPLEVEL statement. When you do not specify DISCARD, the values that were pushed are used to reset the pushed objects.
Usage Notes
Possible Uses for POP LEVEL Statement
Two possible uses for POPLEVEL statements are:
After a series of increasingly broadening or narrowing LIMIT commands, each with a corresponding PUSH.
After a single extremely long and complicated PUSH statement, or a series of short ones given throughout a program, that may need a lot of editing. PUSHLEVEL and POPLEVEL allow you to edit the arguments for a long and complicated PUSH statement without also having to edit a corresponding long and complicated POP statement.
Examples
To see a sample program using POPLEVEL, see the example for the PUSHLEVEL command.
The EVERSION function returns a text value that specifies the internal Oracle OLAP build number.
Return Value
TEXT
Syntax
EVERSION
Usage Notes
EVERSION and Major Releases
The build number in the output of the EVERSION function is not the Oracle Database version number. The EVERSION value does not change only with major releases of the Database.
Examples
The CHR function converts an integer value (or any value that can be implicitly converted to an integer value) into a character.
|
Note: Use of this function results in code that is not portable between ASCII- and EBCDIC-based architectures. |
Return Value
A text value. For single-byte character sets, if number > 256, the function returns the binary equivalent of number MOD 256. For multibyte character sets, number must resolve to one entire code point. Invalid code points are not validated, and the result of specifying invalid code points is indeterminate.
Syntax
CHR(number [ USING NCHAR_CS ])
Parameters
An integer value, or any value that can be implicitly converted to an integer value.
Specifies that the function returns the value in the national character set. When you do not specify this clause, the function returns the value in the database character set.
Examples
When an analytic workspace is attached in multiwriter mode, the RESYNC command drops private changes for the specified read-only objects and retrieves the data from the latest visible generations.
RESYNC resynthesized read-only objects. Use ACQUIRE to resynchronize acquired objects
Syntax
RESYNC objects
Parameters
A list of one or more variables, relations, valuesets, or dimension names, separated by commas, that you want to resynchronize. Oracle OLAP ignores any acquired objects in this list.
Use Name as a value in objects to specify that you want to resynchronize the newest objects defined by other users.
Usage Notes
Keeping Logical Relationship of Objects
When using RESYNC keep in mind the logical relationship of different objects to avoid losing the logical consistency of the data by promoting some objects, but not others to a new generation.
Resynchronizing Objects that Share a Composite Dimension
Objects that share a composite dimension can be resynchronized separately when all such objects that are not being resynchronized are either unchanged or acquired.
Examples
Example 10-105 Resynchronizing Objects
In this example, user A is periodically updating actuals, while user R needs to periodically check the latest view of the data. They could execute the following OLAP DML statements.
User A could execute the following OLAP DML statements.
AW ATTACH myworkspace MULTI ACQUIRE actuals ...make modifications UPDATE MULTI actuals COMMIT ...make modification UPDATE MULTI actuals COMMIT
At the same time, user R could execute the following OLAP DML statements.
AW ATTACH myworkspace MULTI ... RESYNC actuals ... RESYNC actuals ... RESYNC actuals ...
The DEPRDECL function calculates the depreciation expenses for a series of assets. DEPRDECL uses the declining balance method, as described in "Calculation Method Used by DEPRDECL", to depreciate the assets over the specified lifetime of the assets. The starting value and ending value are specified for the assets acquired in each time period.
|
Tip: The pure declining-balance method of depreciation used by DEPRDECL is not the most widely used form of the declining-balance method. For a more commonly used form of the declining-balance method, see the DEPRDECLSW function, which uses a combination of the declining-balance and straight-line methods. |
Return Value
DECIMAL
The return value is dimensioned by all the dimensions of start-exp.
Syntax
DEPRDECL(start-exp end-exp n [STATUS] [decline-factor [ {FULL|HALF|portion-exp}[time-dimension] ] ])
Parameters
A numeric expression that contains the starting values of the assets. The start-exp expression must be dimensioned by a time dimension. For each value of the time dimension, start-exp contains the initial value of the assets acquired during that time period. In addition to a time dimension, start-exp can also have non-time dimensions.
A numeric expression that contains the ending values of the assets. The end-exp expression must be dimensioned by the same dimensions as start-exp. For each value of the time dimension, end-exp contains the final (or salvage) value for the assets acquired during that time period. Each value of start-exp must have a corresponding end-exp value. For example, when the assets acquired in 1996 have a salvage value of $200, then the value of end-exp for 1996 is $200.
An INTEGER expression that contains the number of periods for the depreciation life of the assets. The n expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
Specifies that DEPRDECL should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the depreciation expenses. By default DEPRDECL uses the default status list.
A numeric expression that gives the declining balance rate to use for calculating the depreciation expenses. The decline-factor expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
A factor of 2 indicates a double declining balance. The default is 2.
(Default) Specifies that the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges the full amount to all of the assets in the series.
Specifies that half of the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges half the full amount to all of the assets in the series. When you specify HALF as the portion of depreciation expenses to charge to the period of acquisition, the HALF factor is applied to each period. Half of each period's full depreciation is rolled to the next period, and the final half period of depreciation takes place in the time period n + 1. You might want to use HALF when assets are acquired during the second half of the time period.
When you want to charge the full amount for some assets and half the amount for other assets, you can supply a portion-exp expression that is dimensioned by any of the non-time dimensions of start-exp. The portion-exp expression must be a text expression with values of FULL or HALF.
The name of the time dimension by which start-exp and end-exp are dimensioned. When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional.
Usage Notes
Calculation Method Used by DEPRDECL
DEPRDECL calculates the depreciation expense for a given time period as the sum of that period's depreciation expenses for all assets in the series that are not yet fully depreciated. The first period of depreciation for an asset is the period in which it was acquired.
For each time period, DEPRDECL calculates the declining balance depreciation expense by multiplying the current value of an asset by the decline-factor and dividing the result by the number of periods in the lifetime of an asset. However, when the calculation for a specific time period results in an asset's current value going below the ending value, then the depreciation expense is adjusted. In this instance, the depreciation expense is calculated as the current value minus the ending value.
Low Ending Value
When the ending value specified for an asset is low enough that the depreciation expense for the last period does not have to be adjusted, then the total depreciation expense over all the periods is typically less than the starting value minus the specified ending value.
High Ending Value
When the ending value specified for an asset is relatively high, then an asset might be totally depreciated in fewer periods than were specified for the lifetime of the depreciation. In this instance, when you want the depreciation expense applied across the specified lifetime of the depreciation, you can lower the decline-factor.
DEPRDECL and NA Values
When a value of start-exp is NA and the corresponding value of end-exp is not NA, an error occurs. Similarly, when a value of end-exp is NA and the corresponding value of start-exp is not NA, an error occurs.
DEPRDECL is affected by the NASKIP option when a value of start-exp and the corresponding value of end-exp are both NA. When NASKIP is YES (the default), DEPRDECL treats the values as zeros when calculating the depreciation expenses. When NASKIP is NO, DEPRDECL returns NA for all affected time periods.
Examples
Example 7-66 Using DEPRDECL to Calculate Depreciation Expenses for Assets Acquired in a Single Period
This example shows how to use DEPRDECL to calculate depreciation expenses for assets acquired in a single time period.
The following statements create two variables called assets and salvage.
DEFINE assets DECIMAL <year> DEFINE salvage DECIMAL <year>
Suppose you assign the following values to the variables assets and salvage.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 0.00 0.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00
The assets variable contains the starting value of the assets acquired in 1995. The salvage variable contains the ending value of the assets acquired in 1995.
The following statement reports asset and salvage values, along with depreciation expenses for the assets. Note that the call to DEPRDECL to calculate the depreciation expenses specifies an asset lifetime of 5 periods (in this case, years) and a decline factor of 2 (double-declining balance).
REPORT assets salvage W 12 HEADING 'Depreciation' - DEPRDECL(assets salvage 5 2 FULL year)
This statement produces the following output.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100.00 400.00 Yr96 0.00 0.00 240.00 Yr97 0.00 0.00 144.00 Yr98 0.00 0.00 86.40 Yr99 0.00 0.00 29.60 Yr00 0.00 0.00 0.00
In this example, the depreciation expense for 1999 is adjusted so that the current asset value does not fall below the salvage value. The current asset value is calculated by subtracting the accumulated depreciation expense from the starting asset value. For example, for 1998 the accumulated depreciation expense is $870.40 ($400.00 + $240.00 + $144.00 + $86.40 = $870.40). Thus, the current asset value for 1998 is $129.60 ($1,000.00 - $870.40 = $129.60). In this example, the depreciation expense is usually calculated by multiplying the current asset value by 2 and then dividing the result by 5. Now, if $129.60 is multiplied by 2, then divided by 5, the resulting depreciation expense is $51.84. If this depreciation expense is subtracted from the 1998 current asset value of $129.60, the current asset value for 1999 would be $77.76, which is below the salvage value of $100. Instead of letting the current asset value fall below the salvage value, the DEPRDECL function subtracts the salvage value ($100.00) from the current asset value ($129.60) to calculate the depreciation expense ($29.60).
Example 7-67 Using DEPRDECL to Calculate the Depreciation Expenses for Assets Acquired in Multiple Periods
You can also use DEPRDECL to calculate the depreciation expenses for a series of assets.
Suppose you change the values for the year 1997 in the variables assets and salvage to the values shown in the following report.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 500.00 50.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00 Yr01 0.00 0.00 Yr02 0.00 0.00
Now assets and salvage contain nonzero values for 1995 and for 1997
The following statement reports the values of assets and salvage, and uses DEPRDECL to calculate depreciation expenses for each year, specifying an asset lifetime of 5 years, and a decline factor of 2 (double declining balance).
REPORT assets SALVAGE W 12 HEADING 'Depreciation' - DEPRDECL(assets salvage 5 2 FULL year)
This statement produces the following output. (Notice that the depreciation expense increases in 1997 due to the assets acquired in that year.)
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100.00 400.00 Yr96 0.00 0.00 240.00 Yr97 500.00 50.00 344.00 Yr98 0.00 0.00 206.00 Yr99 0.00 0.00 101.00 Yr00 0.00 0.00 43.20 Yr01 0.00 0.00 14.80 Yr02 0.00 0.00 0.00
The LISTNAMES program produces a report that lists the names of the objects in an analytic workspace. You can limit the list to particular types of objects, and you can have the names for each type of object listed in alphabetical order.
Syntax
LISTNAMES [AW workspace|'*'] [objtype-list|ALL] -
[SORTED|UNSORTED] [LIKE 'pattern']
Parameters
Specifies the name of an attached workspace whose objects you want to list. When you omit the workspace name, LISTNAMES lists the objects in the current workspace. When you use the '*' (asterisk) argument instead of an analytic workspace name, LISTNAMES produces a separate report for each attached workspace.
Specifies one or more of the following types of objects whose names you want to list: AGGMAP, COMPOSITE, DIMENSION, FORMULA, MODEL, OPTION, PROGRAM, RELATION, VALUESET, VARIABLE, and WORKSHEET. You can include a trailing "S" on any object type, for example, DIMENSIONS. You can list these object types in any order. ALL (the default) specifies that the names of objects of all these types should be listed.
SORTED (the default, abbreviated SORT) specifies that the object names should be sorted alphabetically. UNSORTED (abbreviated UNSORT) specifies that the object names should not be sorted alphabetically.
Compares the names of the definitions in an analytic workspace to the text pattern you specify and lists the names that match. A definition name is like a text pattern when corresponding characters match. Besides literal matching, LIKE lets you use wildcard characters to match multiple characters in a string. An underscore (_) character in a pattern matches any single character. A percent (%) character in a pattern matches zero or more characters.
Usage Notes
NAME Dimension
NAME is a special dimension that is used by Oracle OLAP to organize the list of objects in an analytic workspace. Its values are the names of the objects defined in the current workspace. (
You cannot explicitly change the values of the NAME dimension. Instead the values are changed as DEFINE, DELETE, MOVE, or RENAME statements execute. Also, you cannot use a qualified object name to specify the NAME dimension of an analytic workspace that is not the current workspace.
Example 10-33 Listing Dimensions
Suppose you want a list of all the dimensions in an analytic workspace. First, use a LIMIT command and the OBJ function to limit the status of the NAME dimension. Then use a STATUS statement to produce a list of dimensions. Since the values returned by OBJ(TYPE) are always in uppercase, you must use 'DIMENSION' (not 'dimension') in the LIMIT statement to get a match. The statements
LIMIT NAME TO OBJ(TYPE) EQ 'DIMENSION' STATUS NAME
produce the following output.
The current status of NAME is: PRODUCT, DISTRICT, DIVISION, LINE, REGION, MARKETLEVEL, MARKET, MONTH, YEAR, QUARTER
Example 10-34 Listing Relations
Suppose you want to see the definitions of all the relations in an analytic workspace. Use the LIMIT command and the OBJ function to select these names. Then use DESCRIBE to produce a list of their definitions. The statements
LIMIT NAME TO OBJ(TYPE) EQ 'RELATION' DESCRIBE
produce the following output.
DEFINE REGION.DISTRICT RELATION REGION <DISTRICT> LD REGION for each DISTRICT DEFINE DIVISION.PRODUCT RELATION DIVISION <PRODUCT> LD DIVISION for each PRODUCT DEFINE MLV.MARKET RELATION MARKETLEVEL <MARKET> DEFINE MARKET.MARKET RELATION MARKET <MARKET> LD Self-relation for the Market Dimension
Examples
Example 10-35 Listing of DEMO Workspace Objects
This example lists the dimensions, variables, and relations in the current workspace. The statement
LISTNAMES dimension variable relation
produces the following output for the DEMO workspace.
10 DIMENSIONs 18 VARIABLEs 4 RELATIONs
---------------- ---------------- ----------------
DISTRICT ACTUAL DIVISION.PRODUCT
DIVISION ADVERTISING MARKET.MARKET
LINE BUDGET MLV.MARKET
MARKET DEMOVER REGION.DISTRICT
MARKETLEVEL EXPENSE
MONTH FCST
PRODUCT INDUSTRY.SALES
QUARTER NAME.LINE
REGION NAME.PRODUCT
YEAR NATIONAL.SALES
PRICE
PRODUCT.MEMO
SALES
SALES.FORECAST
SALES.PLAN
SHARE
UNITS
UNITS.M
The WEEKOF function returns an INTEGER in the range of 1 to 53, which gives the week of the year in which a specified date falls. The result has the same dimensions as the specified DATE expression.
Return Value
INTEGER
Syntax
WEEKOF(date-expression)
Parameters
An expression that has the DATE data type, or a text expression that specifies a date. The values of the text expression are converted automatically to DATE values, using the current setting of the DATEORDER option to resolve any ambiguity.
Usage Notes
Determining Week 1
The value of WEEKDSYSNEWYEAR specifies how many days of the new year there must be in the week for WEEKOF to consider it to be week 1 of the new year. For example, when January 1 is on a Wednesday, then the week of December 29 to January 4 has four days in the new year. WEEKDSYSNEWYEAR must therefore have a value of 4 or less for that week to be counted as week 1. This determination of week 1 affects the numbering of all weeks in the year.
Examples
The INFO function obtains information that has been produced by a FORECAST, PARSE, or REGRESS statement or that has been produced for a model in your analytic workspace.
Because the syntax of the INFO function is different depending on the type of information being obtained, four separate entries are provided:
The INFO (FORECAST) function obtains information produced by a FORECAST statement and stored internally by Oracle OLAP. Through the use of keywords, INFO lets you extract specific pieces of information about the forecast you have calculated.
|
Note: Before using INFO, familiarize yourself with FORECAST.REPORT that is a standard report of its results, which may give you all the information you need. INFO is useful primarily for creating customized reports or for performing further analysis on the results. |
When you try to extract information without having calculated a forecast, INFO produces an error. You can use the keyword AVAILABLE to determine whether any results are currently available.
Return Value
The return value depends on the keyword you use, as described in the tables in this entry. INFO returns NA when you use an index that is out of range or for any choice that does not apply to the forecasting method last used. For example, when your forecast formula has two coefficients and you request the twelfth one, INFO returns NA.
Syntax
INFO(FORECAST choice [index])
Parameters
Indicates that you want to obtain information produced by a FORECAST statement.
The specific information you want. The choices available for FORECAST are listed in Table 7-12, "Choices for All Methods", Table 7-13, "Choices for TREND and EXPONENTIAL Forecasts", and Table 7-14, "Choices for WINTERS Forecasts". Choices marked as indexed require the index argument.
An INTEGER expression that specifies which result you want for a choice that can have several different results. For example, a trend equation might have several coefficients. You would use index to specify which coefficient you want information about. When you omit index for a choice that requires it, an error occurs.
Table 7-12 Choices for All Methods
| Keyword | Type | Indexed? | Meaning |
|---|---|---|---|
|
AVAILABLE |
BOOL |
No |
Is there a computed forecast for which to obtain information? |
|
DEPENDENT |
TEXT |
No |
The variable or expression being forecast. |
|
METHOD |
TEXT |
No |
The forecast method. |
|
MAPE |
DEC |
No |
The mean absolute percent error (a measure of goodness of fit). |
|
LENGTH |
INT |
No |
The number of forecast periods calculated. |
|
TIME |
TEXT |
No |
The dimension along which forecasting is performed. |
|
FCNAME |
TEXT |
No |
The name of the variable that contains the fitted and forecasted values ( |
Table 7-13 Choices for TREND and EXPONENTIAL Forecasts
| Keyword | Type | Indexed? | Meaning |
|---|---|---|---|
|
FORMULA |
TEXT |
No |
The text of the forecasting equation. |
|
NUMCOEFS |
INT |
No |
The number of coefficients. |
|
COEFFICIENT |
DEC |
Yes |
The specified coefficient in the forecasting equation; index specifies which one you want. |
Table 7-14 Choices for WINTERS Forecasts
| Keyword | Type | Indexed? | Meaning |
|---|---|---|---|
|
PERIODICITY |
INT |
No |
The number of periods in a seasonal cycle. |
|
ALPHA |
DEC |
No |
The smoothing constant for the smoothed data series. |
|
BETA |
DEC |
No |
The smoothing constant for the seasonal index series. |
|
GAMMA |
DEC |
No |
The smoothing constant for the trend series. |
|
STSMOOTHED |
DEC |
No |
The starting value of the smoothed data series. |
|
STSEASONAL |
DEC |
Yes |
The starting values for the seasonal index series; index specifies which one you want. |
|
STTREND |
DEC |
No |
The starting value for the trend series. |
|
FCSMOOTHED |
TEXT |
No |
The variable that holds the smoothed data series. |
|
FCSEASONAL |
TEXT |
No |
The variable that holds the seasonal index series. |
|
FCTREND |
TEXT |
No |
The variable that holds the trend series. |
Examples
Example 7-111 Getting Forecast Information
In this example, suppose you forecasted sales.
The following statements limit the dimensions of the sales variable, then obtain the formula for your forecast.
LIMIT product TO 'Sportswear' LIMIT district TO 'Chicago' LIMIT month TO 'Jan95' TO 'Dec96' FORECAST LENGTH 12 METHOD EXPONENTIAL FCNAME fcst time - month sales SHOW INFO(FORECAST FORMULA)
These statements produce the following output.
87718.0009541865 * (1.005533834579 ** MONTH)
The next statement obtains the mean absolute percent error for your forecast.
SHOW INFO(FORECAST MAPE)
This statement produces the following output.
.17
The INFO (MODEL) function obtains information that is produced for the models in your analytic workspace and stored internally by Oracle OLAP. Through the use of keywords, INFO lets you extract specific pieces of information about the structure of a compiled model or the status of a model that you have run in your current session.
|
Note: Before using INFO, familiarize yourself with the reports created by MODEL.COMPRPT, MODEL.DEPRT, and MODEL.XEQRPT that might give you all the information you need. |
Use INFO with the keyword AVAILABLE to determine whether any model results are currently available. When you try to extract any other information without having considered or defined a model in your current session, INFO produces an error.
Return Value
The return value depends on the keyword you use, as described in the tables in this entry. INFO returns NA when you use an index that is out of range or when you request information that is not relevant. For example, if the model contains 5 statements and you request information about statement 6, INFO returns NA; or if you specify the DIMENSION REFERENCE choice when the assignment target is actually a variable, INFO returns NA.
Syntax
INFO(MODEL choice [index1 [index2 [index3]]])
where index is an argument specifies the result you want for a choice that can have several different results. Depending on the keyword choice, you can supply one or more of the following index arguments:
Parameters
Indicates that you want to obtain information about a model in your analytic workspace. INFO returns information about the model that you have most recently defined or considered in the current session (see the DEFINE MODEL and CONSIDER commands).
A keyword that specifies the information you want. The choices available for models are listed in the following tables that represent different informational categories:
Table 7-15, "INFO (MODEL) Choices to Retrieve General Information About the Model".
Table 7-16, "INFO (MODEL) Choices to Retrieve Information about the Structure of the Model".
Table 7-17, "INFO (MODEL) Choices to Retrieve Information about Target, Sources, and Dependencies". These choices provide information about statements that are equations. Equations have the form assignment target = expression. The expression can refer to one or more data sources. Assignment targets and data sources can be either variables or dimension values, and they can have qualifiers that affect their dimensionality.
Table 7-18, "INFO (MODEL) Choices to Retrieve Information About Execution Status". All of these choices (except XEQSTATUS) are relevant only after running a model with a simultaneous block. When the current model has not been compiled, Oracle OLAP returns an error when you use any choice except AVAILABLE or NAME.
Each table consists of four columns that provide the following information: keyword, data type of returned value; index argument associated with the keyword; and meaning.
Table 7-15 INFO (MODEL) Choices to Retrieve General Information About the Model
| Keywords | Data Type | Index Arguments | Meaning |
|---|---|---|---|
|
AVAILABLE |
BOOL |
(No arguments) |
Is there a model for which information is available? |
|
NAME |
TEXT |
[MODEL model-num] |
Without model-num (or with model-num equal to 0), the name of the current model. With model-num greater than 0, the name of the included model that is the specified model-num within the current model. |
|
COUNT STATEMENTS |
INT |
(No arguments) |
The number of statements in the current model. The count includes comments, equations, and DIMENSION and INCLUDE commands (if any), it but does not include the statements in an included model. |
|
STATEMENT |
TEXT |
stmnt-num |
The text of statement stmnt-num. |
|
SIMULTANEOUS |
BOOL |
(No arguments) |
Does the current model contain a simultaneous block? |
Table 7-16 INFO (MODEL) Choices to Retrieve Information about the Structure of the Model
| Keyword(s) | Data Type | Index Argument(s) | Meaning |
|---|---|---|---|
|
COUNT ELEMENTS |
INT |
[BLOCK block-num] |
Without block-num, the number of blocks in the current model. With block-num, the total number of statements and nested blocks within block block-num in the current model. When you request further information about a particular element (for example, with the TYPE ELEMENT choice), you always specify the block number to which the element belongs and the number of the element within that block. |
|
TYPE ELEMENT |
TEXT |
element-num BLOCK block-num |
Returns BLOCK or STATEMENT, depending on whether element element-num of block block-num is a nested block or a statement. |
|
NUMBER BLOCK |
INT |
element-num BLOCK block-num |
The block number of the nested block that is element element-num of block block-num. |
|
TYPE BLOCK |
TEXT |
block-num |
Returns SIMPLE, STEP-FORWARD, STEP-BACKWARD, or SIMULTANEOUS, depending on the execution type of block block-num. |
|
COUNT DIMS |
INT |
[BLOCK block-num] |
Without block-num, the number of model dimensions of the current model. With block-num, the number of step-forward, step-backward, or simultaneous dimensions of block block-num within the current model. |
|
DIMENSION |
TEXT |
dimension-num [BLOCK block-num] |
Without block-num, the name of model dimension dimension-num of the current model. With block-num, the name of the specified step-forward, step-backward, or simultaneous dimension of block block-num. |
|
NUMBER STATEMENT |
INT |
element-num BLOCK block-num |
The statement number of the statement that is element element-num of block block-num. The statement number refers to the position of the statement within its own model. To request further information about the statement (for example, with the HIDDEN choice), its model must be the model that you are currently considering. |
|
HIDDEN |
BOOL |
stmnt-num |
Has statement stmnt-num been masked by a subsequent statement? |
|
NUMBER MODEL |
INT |
element-num BLOCK block-num
|
The number of the included model from which the statement that is element element-num of block block-num is taken.
|
Table 7-17 INFO (MODEL) Choices to Retrieve Information about Target, Sources, and Dependencies
| Keyword(s) | Data Type | Index Argument | Meaning |
|---|---|---|---|
|
COUNT SOURCES |
INT |
STATEMENT stmnt-num |
The number of data sources in statement stmnt-num within the current model. |
|
TYPE REFERENCE |
TEXT |
STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the object type of the assignment target of statement stmnt-num. With source-num, the object type of data source source-num in statement stmnt-num. The object type is VARIABLE when the reference is to a variable. The type is DIMENSION when the reference is to the value of a dimension. |
|
VARIABLE REFERENCE |
TEXT |
STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the name of the variable that is the assignment target of statement stmnt-num. With source-num, the name of the variable that is data source source-num in statement stmnt-num. |
|
VALUE REFERENCE |
TEXT |
STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the dimension value that is the assignment target of statement stmnt-num. With source-num, the dimension value that is data source source-num in statement stmnt-num. |
|
DIMENSION REFERENCE |
TEXT |
STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the model dimension of the target dimension value in statement stmnt-num. With source-num, the model dimension of source dimension value source-num in statement stmnt-num. |
|
COUNT QUALIFIERS |
INT |
STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the number of qualifiers of the assignment target in statement stmnt-num. With source-num, the number of qualifiers of data source source-num in statement stmnt-num. |
|
TYPE QUALIFIER |
TEXT |
qualifier-num STATEMENT stmnt-num [SOURCE source-num] |
Without source-num, the qualifier type of qualifier qualifier-num of the target of statement stmnt-num. With source-num, the qualifier type of qualifier qualifier-num of data source source-num in statement stmnt-num. The qualifier type can indicate dimensional dependence: LAG (previous dimension values only), LEAD (later values only), BOTH (both previous and later values), and VARIABLE (either previous or later values, depending on the value of a variable when the model is run). The qualifier type can also be QDR (qualified data reference). |
|
DIMENSION QUALIFIER |
TEXT |
qualifier-num STATEMENT stmnt-num [SOURCE source-num] |
qualifier-num STATEMENT stmnt-num [SOURCE source-num] Without source-num, the dimension of qualifier qualifier-num of the assignment target in statement stmnt-num. With source-num, the dimension of qualifier qualifier-num of data source source-num in statement stmnt-num. |
Table 7-18 INFO (MODEL) Choices to Retrieve Information About Execution Status
| Keyword(s) | Data Type | Index Argument | Meaning |
|---|---|---|---|
|
XEQSTATUS |
TEXT |
[BLOCK block-num] |
Without block-num, the execution status of the model as a whole; when the model has not been run, the status is NOT EXECUTED. With block-num, the execution status of block block-num; when the model has not been run, an error is returned. When the model has been run, the status for the model as a whole or for a block can be SOLVED, DIVERGED, or FAILED TO CONVERGE. The status of an outer-level block can be EXECUTION INCOMPLETE when a nested block within it diverged or failed to converge. |
|
COUNT ITERATIONS |
INT |
BLOCK block-num |
The number of iterations that were performed for block block-num before it was solved or it diverged or failed to converge. |
|
DAMP |
DEC |
(No arguments) |
The value of the MODDAMP option when the model was run. (Relevant only when the solution method is GAUSS.) |
|
DIVERGSTMT |
INT |
BLOCK block-num |
The element number of the statement that diverged during the calculations for block block-num. |
|
GAMMA |
INT |
(No arguments) |
The value of the MODGAMMA option when the model was run. |
|
MAXITERS |
INT |
(No arguments) |
The value of the MODMAXITERS option when the model was run. |
|
OVERFLOW |
INT |
(No arguments) |
The value of the MODOVERFLOW option when the model was run. |
|
SIMULTYPE |
TEXT |
(No arguments) |
The value of the MODSIMULTYPE option when the model was run: AITKENS or GAUSS. |
|
TOLERANCE |
INT |
(No arguments) |
The value of the MODTOLERANCE option when the model was run. |
An INTEGER expression that specifies the block for which you want information. Block-num corresponds to the block numbers that are identified in the report produced by the MODEL.COMPRPT program.
An INTEGER expression that specifies the model dimension or block dimension for which you want information. For the model as a whole, the first dimension listed for the model is dimension-num 1, and so on. For example, assume that the MODEL.COMPRPT specifies the model dimensions as <line month>. In this case, line is dimension-num 1 and month is dimension-num 2. For a simultaneous block in the current model, the first dimension of the block is dimension-num 1, and so on. A step-forward or step-backward block has a single dimension, so the dimension of the block is always dimension-num 1. To see a list of the dimensions for the model as a whole and for each block of the model, you can run the MODEL.COMPRPT program.
An INTEGER expression that specifies the element for which you want information. When you request information about an element, you always specify the block number to which the element belongs. An element is either a statement in the specified block, or it is a nested block within the specified block. The element numbers correspond to the order of the statements and blocks in the compiled model. You can run the MODEL.COMPRPT program to see the list of elements in the compiled model.
For example, suppose the current model has the following compiled structure.
block 1 statement a block 2 statement b statement c END block 2 statement d END block 1
When you request information about block 1 in the preceding model, statement a is element-num 1; block 2 is element-num 2; and statement d is element-num 3. When you request information about block 2, statement b is element-num 1 and statement c is element-num 2.
For a hierarchy of included models, an INTEGER expression that specifies the model for which you want information. The model you are currently considering is model-num 0 (zero), the model it includes is model-num 1, and so on. The root model has the highest model number in the hierarchy.
An INTEGER expression that specifies the qualifier for which you want information. Qualifiers change the dimensionality of a variable or dimension value reference. The reference can be qualified by a function, such as LAG, LEAD, or TOTAL or by a qualified data reference (QDR). To see the qualifiers for a statement, you can run the MODEL.DEPRT program for the model that contains the statement.
For each equation in the model, the MODEL.DEPRT report lists the assignment target and its qualifiers on one line, followed by the data sources. Each data source is listed on a separate line, together with its qualifiers. The MODEL.DEPRTreport also specifies the type of each qualifier: LAG, LEAD, BOTH, VARIABLE, or QDR (see the TYPE QUALIFIER choice in the third group of INFO keyword choices).
For the target and each source, qualifier-num corresponds to the order in which the qualifiers are listed in the MODEL.DEPRT report.
An INTEGER expression that specifies the data source for which you want information. In a calculation, each reference to a variable or a dimension value is counted as a source of data for the assignment target. A constant value is not counted as a source.
To see the data sources in a statement, you can run the MODEL.DEPRT program for the model that contains the statement. For each equation in the model, the MODEL.DEPRT report lists the assignment target on one line, followed by its data sources. Each data source is listed on a separate line.
An INTEGER expression that specifies the statement for which you want information. Stmnt-num always refers to a statement from the model you are currently considering. It does not refer to a statement taken from an included model.
To see the statement numbers in the current model, you can run the MODEL.COMPRPT program. To the left of each statement, the report lists the model from which the statement is taken and the statement number within that model.
Examples
Example 7-112 Getting Qualifier Information
Assume that the following statement is statement 3 of a model called income.plan.
budget(line revenue) = LAG(actual(line revenue), 1, month) - + plan.factor
You can run the MODEL.DEPRPT program to see the qualifiers of the target and sources in this statement.
MODEL.DEPRPT income.plan
This statement produces the following output.
MODEL INCOME.PLAN
...
3 BUDGET(QDR <LINE>):
ACTUAL(LAG <MONTH>)(QDR <LINE>)
PLAN.FACTOR
...
This report shows that the assignment target, budget, has two data sources, actual and plan.factor.
Example 7-113 Checking Qualifier Information
The following statements make INCOME.PLAN the current model and check the number and type of the qualifiers of the assignment target of statement 3.
CONSIDER income.plan SHOW INFO(MODEL COUNT QUALIFIERS STATEMENT 3)
These statements produce the following output.
1
The OLAP DML statement
SHOW INFO(MODEL TYPE QUALIFIER 1 STATEMENT 3)
produces the following output.
QDR
Example 7-114 Checking Different Data Sources
The following statements check the number and type of the qualifiers of the two data sources in statement 3.
The OLAP DML statement
SHOW INFO(MODEL COUNT QUALIFIERS STATEMENT 3 SOURCE 1)
produces the following output.
2
The OLAP DML statement
SHOW INFO(MODEL TYPE QUALIFIER 1 STATEMENT 3 SOURCE 1)
produces the following output.
LAG
The OLAP DML statement
SHOW INFO(MODEL TYPE QUALIFIER 2 STATEMENT 3 SOURCE 1)
produces the following output.
QDR
The OLAP DML statement
SHOW INFO(MODEL COUNT QUALIFIERS STATEMENT 3 SOURCE 2)
produces the following output.
0
The INFO (PARSE) function obtains information produced by a PARSE statement and stored internally by Oracle OLAP. Through the use of keywords, INFO lets you extract specific pieces of information about the expression that you have parsed.
Return Value
The return value depends on the keyword you use, as described in Table 7-19. When you try to extract unavailable information or use an index that is out of range, INFO returns NA. For example, if you parse a phrase that contains four expressions and then ask for the twelfth FORMULA, INFO returns NA.
Syntax
INFO(PARSE choice [index])
Parameters
Indicates that you want to obtain information produced by a PARSE statement.
The specific information you want. The choices available for PARSE are listed in Table 7-19, "INFO PARSE Keywords". Choices marked as indexed can take the optional index argument.
An INTEGER expression that specifies which result you want for a choice that can have several different results. For example, when you parse text that contains three expressions, each expression has its own formula and data type. You would use index to specify which expression you are interested in.
When you omit index, INFO returns all the information as a multiline value.
Table 7-19 INFO PARSE Keywords
| Keyword | Type | Indexed? | Meaning |
|---|---|---|---|
|
PARSEABLE |
BOOL |
No |
Was Oracle OLAP able to parse the text? |
|
ERRORTEXT |
TEXT |
No |
The text of an error message when the expressions were not parsed. |
|
NUMFORMULAS |
INT |
No |
The number of expressions (formulas) that were parsed. |
|
NUMDIMS |
INT |
No |
The number of dimensions in the union of all the expressions that were parsed. |
|
FORMULA |
TEXT |
Yes |
The text (formula) of the specified expression; index specifies which one you want. |
|
DATA |
TEXT |
Yes |
The data type of the specified expression. |
|
TYPE |
TEXT |
Yes |
The type of object of the specified expression; when the expression is the name of an object, it returns the type; when the expression is a qualified data reference, it returns QDR; when the expression is anything else, it returns EXP. |
|
DIMENSION |
TEXT |
Yes |
The name of the specified dimension in the union of all dimensions of the expressions. |
Examples
Example 7-115 Getting Parsed Information
In a simple report program, you want to allow the user to specify the data to be reported as an argument to the program. You want to allow the user to specify an expression and the name of a data variable. You cannot process expression arguments with an ARGS statement, so you use PARSE and INFO to parse the program arguments and produce the report.
The following statements create a simple report program.
DEFINE report1 PROGRAM
PROGRAM
PUSH month product district DECIMALS
DECIMALS = 0
LIMIT month TO FIRST 2
LIMIT product TO ALL
LIMIT district TO 'Chicago'
PARSE ARGS
REPORT ACROSS month: WIDTH 8 <&INFO(PARSE FORMULA 1) -
WIDTH 13 &INFO(PARSE FORMULA 2)>
POP month product district DECIMALS
END
When users run the program, they can supply either the name of a variable (sales) or an expression (sales-expense) or both as arguments.
The following statement
REPORT1 sales sales-expense
produces the following output.
DISTRICT: CHICAGO
--------------------MONTH--------------------
--------Jan95--------- --------Feb95---------
PRODUCT SALES SALES-EXPENSE SALES SALES-EXPENSE
------------ -------- ------------- -------- -------------
Tents 29,099 1,595 29,010 1,505
Canoes 45,278 292 50,596 477
Racquets 54,270 1,400 58,158 1,863
Sportswear 72,123 7,719 80,072 9,333
Footwear 90,288 8,117 96,539 13,847
The INFO (REGRESS) function obtains information produced by an REGRESS statement and stored internally by Oracle OLAP. Through the use of keywords, INFO lets you extract specific pieces of information about the regression you have calculated.
|
Note: Before using INFO, familiarize yourself with REGRESS.REPORT that produces a standard report of its results, which might give you all the information you need. INFO is useful primarily for creating customized reports or for performing further analysis on the results |
Return Value
The return value depends on the keyword you use, as described in Table 7-20, "INFO REGRESS Keywords".
Syntax
INFO(REGRESS choice [index])
Parameters
Indicates that you want to obtain information produced by an REGRESS statement.
The specific information you want. The choices available for REGRESS are listed in Table 7-20, "INFO REGRESS Keywords". Choices marked as indexed require the index argument.
An INTEGER expression that specifies which result you want for a choice that can have several different results. For example, in a regression there may be multiple independent variables. You would use index to specify which independent variable you want information about. When you omit index for a choice that requires it, an error occurs.
Table 7-20 INFO REGRESS Keywords
| Keyword | Type | Indexed? | Meaning |
|---|---|---|---|
|
AVAILABLE |
BOOL |
No |
Is there a computed regression from which to extract information? |
|
DEPENDENT |
TEXT |
No |
The name of the dependent variable in the regression. |
|
NOINTERCEPT |
BOOL |
No |
Was the regression calculated with the intercept suppressed? |
|
WEIGHTED |
BOOL |
No |
Was the last regression weighted? |
|
WEIGHT |
TEXT |
No |
The expression used to weight the last regression. |
|
NUMCOEFS |
INT |
No |
The number of coefficients. |
|
INDEPENDENT |
TEXT |
Yes |
An independent variable; index specifies which one you want (Intercept to be first unless it was suppressed). |
|
COEFFICIENT |
DEC |
Yes |
An estimated coefficient; index specifies which one you want. |
|
STDERROR |
DEC |
Yes |
The standard error of an estimated coefficient; index specifies which one you want. |
|
TRATIO |
DEC |
Yes |
The t-ratio for an estimated coefficient; index specifies which one you want. |
|
NUMOBS |
INT |
No |
The number of observations that were used. |
|
FRATIO |
DEC |
No |
The F-ratio for the regression. |
|
RBSQ |
DEC |
No |
The corrected R-squared for the regression. |
|
FORMULA |
TEXT |
No |
The regression formula. |
|
STDERROREST |
DEC |
No |
The standard error of estimate for the regression |
|
RESET |
BOOL |
|
Use when you want to reset the original state of AVAILABLE back to |
Usage Notes
Determining Regression Results Availability
When you try to extract information without having performed a regression, INFO produces an error. You can use the keyword AVAILABLE to determine whether any results are currently available. Once a successful regression has run, AVAILABLE remains true even when one or more unsuccessful regressions follow, because the results of the previous successful regression are still available. AVAILABLE remains true until you use RESET to change the AVAILABLE state back to its original value of NO.
NA Results Due to Index
INFO returns NA when you use an index that is out of range. For example, when your regression has five independent variables and you request the coefficient of the twelfth one, INFO returns NA.
Examples
The AGGREGATE command calculates summary data in the variable that is specified as PRECOMPUTE in the specified aggmap. (For information about specifying precompute data, see the PRECOMPUTE and RELATION (for aggregation) statements of the AGGMAP command.) The aggregation is limited to those values that are currently in status.
Use the $AGGMAP property or the AGGREGATE function to calculate data that is not specified as precomputed data.
Syntax
AGGREGATE|AGGR { var [(PARTITION partition-name)]}... [USING aggmap] -
[FROM fromspec|FROMVAR textvar] [FORCEORDER] [FUNCDATA] [COUNTVAR countvar...]
Parameters
A variable whose data values are to be calculated. Every variable in a single AGGREGATE command must have the same dimensions in the same order.
Specifies that you want AGGREGATE to recalculate only the values in the specified partition of the specified variable. Frequently, the reason for aggregating only a single partition is to parallelize a build using multiwriter.
|
Note: Since the AGGREGATE command does not consider partition dependencies when aggregating individual partitions, aggregate only a set of non-dependent partitions within a single AGGREGATE command. |
The name of a previously-defined partition. See DEFINE PARTITION TEMPLATE
This keyword indicates that the aggregation is performed using the specified aggmap. When you do not include this phrase, the command uses the default aggmap for the variable as previously specified using an AGGMAP statement or the $AGGMAP property.
The name of a previously-defined aggmap that specifies how the data is aggregated. For information about aggmaps, see the DEFINE AGGMAP command.
This keyword indicates that the detail data is obtained from a different object.
A FROM clause is only one way in which you can specify the variable from which detail data should be obtained when performing aggregation. See "Ways of Specifying Where to Obtain Detail Data for Aggregation".
An arbitrarily dimensioned variable, formula, or relation from which the detail data for the aggregation is obtained.
This keyword indicates that the detail data is obtained from different objects to perform a capstone aggregation. (For an example of using the FROMVAR clause, see Example 9-32, "Capstone Aggregation".)
A FROMVAR clause is only one way in which you can specify the variable from which detail data should be obtained when performing aggregation. See "Ways of Specifying Where to Obtain Detail Data for Aggregation".
An arbitrarily dimensioned variable used to resolve any leaf nodes. Specify NA to indicate that a node does not need detail data to calculate the value.
Specifies that the calculation must be performed in the order in which the RELATION statements are listed in the aggmap. Use this option when you have changed some values calculated by the AGGREGATE command. Otherwise, the optimization methods used by the AGGREGATE command may cause the modified values to be ignored.
|
Note: You can also set an $AGGREGATE_FORCEORDER property on a variable to specify this behavior as the default aggregation behavior. In this case, you do not have to include the FORCEORDER keyword with the AGGREGATE command. |
Compiles the aggregation specification for future use by the AGGREGATE function. When you use FUNCDATA, you do not have to recompile the aggmap before using the AGGREGATE function, unless afterward you make changes to the aggmap, the relation hierarchies, or a composite.
When the variables have composite dimensions, the indexes (composite tuples) are created and saved for use by the AGGREGATE function. Otherwise, the indexes are re-created each time the AGGREGATE function is called. Refer to AGGINDEX for more information about composite indexes.
Indicates that Oracle OLAP should use the user-defined variable specified by countvar to store the non-NA counts of the number of leaf nodes that contributed to aggregate values calculated for RELATION statements that have an AVERAGE, HAVERAGE, HWAVERAGE, or WAVERAGE operator.
|
Note: Typically, you do not use a user-defined Countvar variable to store the counts for average aggregations. Instead, you use an Oracle OLAP-created Aggcount variable. You must use an Aggcount variable when the aggregation specification includes a RELATION statement with an average operator is for a compressed composite.For more information on Aggcount variables, see "Aggcount Variables". |
The countvar variable must be an INTEGER variable with the same dimensions in the same order as the dimensions of the variable specified by var. When you aggregate several variables together, you must define an INTEGER variable for each one to record the results.
Usage Notes
Effect of Status on AGGREGATE
The current status only affects dimension values at the lowest level of the hierarchy, that is, the leaf nodes. Only leaf-node dimension values that are currently in status are aggregated. The parent values of leaf nodes in status are calculated, whether the parent values are in status or not (unless you exclude the dimension values in those levels with a PRECOMPUTE clause in the AGGMAP command). Thus, when you want to aggregate all of the data specified in the aggmap, then be sure to set the status of the dimensions to ALL before performing the aggregation.
AGGREGATE uses the parent relation to distinguish among dimension values at different levels of the hierarchy. Alternatively, you can perform a partial aggregation of the data by limiting status. However, this must be done carefully when some data is aggregated at run time by the AGGREGATE function. See the notes in the AGGREGATE function topic for more information.
For example, suppose you use the area dimension and the area.area child-parent relation that supports one hierarchy for a geography dimension as illustrated in Table 9-2, "Geography Hierarchy".
Table 9-2 Geography Hierarchy
| Level | area Dimension | area.area Parent Relation |
|---|---|---|
|
1 |
|
|
|
2 |
|
|
|
2 |
|
|
|
3 |
|
|
|
3 |
|
|
|
3 |
|
|
Now suppose you change the data value for New York. When you then use AGGREGATE with only New York, the calculation occurs without including the child value for South (Atlanta), but still includes level 2 as it goes from level 3 to level 1 (TotalUS). When you want all the child values included in rolling up to TotalUS, use a LIMIT TO ALL statement before you execute the AGGREGATE command.
When the data has changed for some, but not all, of the child values in a hierarchy, you can set the status to calculate just the values that have changed. For example, when your embedded-total dimension is called d2, and its parent relation is called reld2, first limit d2 to the values that have changed.
To calculate the data for every hierarchy in a dimension, limit the dimension's hierarchy dimension to ALL before you execute the AGGREGATE command.
Controlling the Amount of Data That Is Calculated
You can control how much of the variable data is calculated by using the PRECOMPUTE keyword with the RELATION statement in the aggmap. Use the limit clause (after the PRECOMPUTE keyword) to set the status of the dimension.
When Users Modify Data
When users are able to change the data in a variable, then calculate aggregates on the fly using the AGGREGATE function, so that their changes are reflected in the aggregate data. See the AGGREGATE function for more information about run-time changes to the data.
Generation-Skipping Hierarchies
AGGREGATE automatically distinguishes between generations in the parent relation, even to the extent of allowing generation-skipping hierarchies. For example, you can have a four-level hierarchy (for example, neighborhoods, cities, states, and totalUS) that has a three-level branch (for example, Boston, Massachusetts, and totalUS).
Restrictions on Permissions
AGGREGATE does not work on variables that have cell-by-cell permissions; it immediately return an error. It also ignores the PERMITERROR option. However, AGGREGATE operates on variables with object level or dimension level permission. See the PERMIT command and PERMITERROR option.
Ways of Specifying Where to Obtain Detail Data for Aggregation
You can specify where to obtain detail data when aggregating data in the following ways:
Assign either an $AGGREGATE_FROM property or an $AGGREGATE_FROMVAR property to a variable.
|
Note: You can only assign one of these properties to a variable. A variable cannot have both the $AGGREGATE_FROM and $AGGREGATE_FROMVAR properties assigned to it. |
Include either a FROM or FROMVAR clause in the AGGREGATE command or AGGREGATE function that aggregates the data.
When performing an aggregation, Oracle OLAP determines where to obtain the detail data as follows:
When a location has been specified using a FROM or FROMVAR clause, Oracle OLAP uses the detail data at that location.
When a location has not been specified using a FROM or FROMVAR clause, Oracle OLAP checks to see if a location has been specified using an $AGGREGATE_FROM property or an $AGGREGATE_FROMVAR property. When a location has been specified using one of these properties, Oracle OLAP uses the detail data at that location.
When a location has not been specified using either FROM or FROMVAR clause or an $AGGREGATE_FROM property or an $AGGREGATE_FROMVAR property, Oracle OLAP performs the aggregation using the detail data in the variable itself.
Examples
This section contains several examples of using the AGGREGATE command. For additional aggregation examples, see the examples in the AGGMAP command.
Example 9-27 Precalculating Data in a Batch Job
Frequently, you generate precalculated aggregates in a batch window as part of maintaining the data in your Database. For example, you can use Job Manager to schedule batch jobs in Oracle Enterprise Manager, as described in Oracle OLAP User's Guide.
To generate precalculated aggregates, you use the AGGREGATE command. The AGGREGATE command aggregates the data for one or more variables according to the specifications provided in the aggmap.
Your batch job should include statements like the following.
POUTFILEUNIT=FILEOPEN('userfiles/progress.txt' WRITE)
AGGREGATE sales units USING gpct.aggmap
UPDATE
COMMIT
FILECLOSE POUTFILEUNIT
Example 9-28 Aggregating One Variable
Suppose your analytic workspace contains a variable named actuals, which has the following definition.
DEFINE actuals DECIMAL <time, SPARSE <product, customer, channel>>
The next step is to define an aggmap object, whose definition has the same dimensions in the same dimension order. Suppose you define an aggmap object named act.agg using DEFINE AGGMAP.
DEFINE act.agg AGGMAP <time, SPARSE <product, customer, channel>>
Suppose that the name of the hierarchy for the time dimension is time.r, the name of the product dimension is product.r, and so on Next, you use an AGGMAP statement to add the following text in the act.agg aggmap.
AGGMAP RELATION time.r RELATION product.r RELATION customer.r RELATION channel.r END
The preceding text specifies the name of each dimension's hierarchy for which data should be rolled up. Assuming that the current status of every dimension is ALL, data is calculated for every dimension value of every dimension in the definition of actuals. No data is calculated on the fly.
Use the following statements to calculate the actuals variable. (It is not necessary to compile the aggmap, because the compilation is included as part of the AGGREGATE command.)
AGGREGATE actuals USING act.agg
Example 9-29 Aggregating Multiple Variables
Suppose your analytic workspace contains a variable named actuals and a variable named forecast. As shown in the following variable definitions, these variables have the same dimensions in the same dimension order.
DEFINE actuals DECIMAL <time, SPARSE <product, customer, channel>> DEFINE forecast DECIMAL <time, SPARSE <product, customer, channel>>
The next step is to define an aggmap object, whose definition has the same dimensions in the same dimension order. Suppose you define the same aggmap object named act.agg, as described in "Aggregating One Variable". When you want the data for each variable to be rolled up in the same way, you can use the same aggmap to calculate both variables in a single statement.
Use the following statements to calculate the actuals and the forecast variables.
AGGREGATE actuals forecast USING act.agg
Because the aggmap specifies that all data for every dimension value in each dimension should be rolled up, this statement rolls up all of the data in actuals and all of the data in forecast.
Example 9-30 Using COUNTVAR with Multiple Variables
Suppose you plan to use one AGGREGATE command to aggregate the data for three variables: sales, units, and projected_sales. Each variable has the following dimensionality.
<month product geography>
To tally the results with COUNTVAR, you must define three INTEGER variables that have the same dimensionality as sales, units, and projected_sales.
DEFINE intsales INTEGER <month product geography> DEFINE intunits INTEGER <month product geography> DEFINE intprojsales INTEGER <month product geography>
You can then specify the INTEGER variables in the following statement.
AGGREGATE sales units projected_sales USING sales.agg - COUNTVAR intsales intunits inprojsales
Example 9-31 Performing a Partial Aggregation
This example limits the time dimension to the last two time periods, so that only newly loaded data is aggregated.
The tp2.agg aggmap specifies preaggregation for all detail data currently in status.
DEFINE TP2.AGG AGGMAP LD Full preaggregation AGGMAP RELATION time.parentrel PRECOMPUTE (ALL) RELATION product.parentrel PRECOMPUTE (ALL) END
For the aggregation, time is limited to the last two time periods and all product values are in status.
LIMIT time TO LAST 2 STATUS time product The current status of TIME is: Apr02, May02 LIMIT product TO ALL
The following AGGREGATE statement calculates units using the tp2.agg aggmap.
AGGREGATE units USING tp2.agg
The results of this aggregation show that parent values are calculated, regardless of their own status, when their children are in status.
LIMIT time TO '2002' 'Q1.02' 'Q2.02' 'Jan02' to 'May02' REPORT DOWN time units
-----------------------------------------UNITS----------------------------------------- ----------------------------------------PRODUCT---------------------------------------- TIME FOOD SNACKS DRINKS POPCORN COOKIES CAKES SODA JUICE ------- -------- -------- -------- -------- -------- -------- -------- -------- 2002 38 24 14 6 9 9 9 5 Q1.02 NA NA NA NA NA NA NA NA Q2.02 38 24 14 6 9 9 9 5 Jan02 NA NA NA 8 2 4 5 8 Feb02 NA NA NA 5 3 2 2 5 Mar02 NA NA NA 3 4 4 2 4 Apr02 21 13 8 2 7 4 6 2 May02 17 11 6 4 2 5 3 3
Example 9-32 Capstone Aggregation
Assume that your analytic workspace has the two hierarchical TEXT dimensions named geog.d and time.d with the following values.
GEOG.D -------------- Boston Medford San Diego Sunnydale Massachusetts California United States TIME.D -------------- Jan76 Feb76 Mar76 76Q1
Assume, also, that there are four variables with the following definitions
DEFINE sales_jan76 VARIABLE INTEGER <geog.d> DEFINE sales_feb76 VARIABLE INTEGER <geog.d> DEFINE sales_mar76 VARIABLE INTEGER <geog.d> DEFINE sales_capstone76 VARIABLE INTEGER <geog.d time.d>
Assume that you issue the following REPORT statements for the variables. The output of the reports show the detail data in the variables.
REPORT sales_jan76 sales_feb76 sales_mar76
REPORT DOWN geog.d sales_capstone76
GEOG.D SALES_JAN76 SALES_FEB76 SALES_MAR76
-------------- ------------ ------------ ------------
Boston 1,000 2,000 3,000
Medford 2,000 4,000 6,000
San Diego 3,000 6,000 9,000
Sunnydale 4,000 8,000 12,000
Massachusetts NA NA NA
California NA NA NA
United States NA NA NA
-----------------SALES_CAPSTONE76------------------
----------------------TIME.D-----------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- ------------ ------------ ------------ ------------
Boston NA NA NA NA
Medford NA NA NA NA
San Diego NA NA NA NA
Sunnydale NA NA NA NA
Massachusetts NA NA NA NA
California NA NA NA NA
United States NA NA NA NA
Define two aggmap objects with the following definitions.
DEFINE leaf_aggmap AGGMAP AGGMAP RELATION geog.parentrel OPERATOR SUM END DEFINE capstone_aggmap AGGMAP AGGMAP RELATION time.parentrel OPERATOR SUM END
Define a variable named capstone_source with the following definition to use to aggregate the data.
DEFINE capstone_source VARIABLE TEXT <time.d>
As the following output of a REPORT statement illustrates, for each value of time.d, you populate capstone_source with the name of the variable that contains the corresponding sales data.
TIME.D CAPSTONE_SOURCE -------------- ---------------------- Jan76 sales_jan76 Feb76 sales_feb76 Mar76 sales_mar76 76Q1 NA
Issue the following statements to aggregate the variables.
AGGREGATE sales_jan76 sales_feb76 sales_mar76 USING leaf_aggmap AGGREGATE sales_capstone76 USING capstone_aggmap FROMVAR capstone_source
After aggregating the variables, when you issue the REPORT statements, the variables are populated with the calculated data.
REPORT sales_jan76 sales_feb76 sales_mar76
REPORT DOWN geog.d sales_capstone76
GEOG.D SALES_JAN76 SALES_FEB76 SALES_MAR76
-------------- ------------ ------------ ------------
Boston 1,000 2,000 3,000
Medford 2,000 4,000 6,000
San Diego 3,000 6,000 9,000
Sunnydale 4,000 8,000 12,000
Massachusetts 3,000 6,000 9,000
California 7,000 14,000 21,000
United States 10,000 20,000 30,000
-----------------SALES_CAPSTONE76------------------
----------------------TIME.D-----------------------
GEOG.D Jan76 Feb76 Mar76 76Q1
-------------- ------------ ------------ ------------ ------------
Boston 1,000 2,000 3,000 6,000
Medford 2,000 4,000 6,000 12,000
San Diego 3,000 6,000 9,000 18,000
Sunnydale 4,000 8,000 12,000 24,000
Massachusetts 3,000 6,000 9,000 18,000
California 7,000 14,000 21,000 42,000
United States 10,000 20,000 30,000 60,000
The STATLEN function returns the number of values in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
INTEGER
Syntax
STATLEN(dimension)
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
Examples
The $AGGREGATE_FORCECALC property specifies the same behavior as that specified by the FORCECALC keyword in an AGGREGATE function. By adding an $AGGREGATE_FORCECALC property to a variable you can ensure this behavior when the variable is aggregated using an AGGREGATE function — even when it is aggregated by an AGGREGATE function does not include the FORCECALC keyword.
The behavior specified by both the $AGGREGATE_FORCECALC property and the FORCECALC keyword is that when an AGGREGATE function aggregates the variable, Oracle OLAP recalculates any value that is not specified in a PRECOMPUTE clause of a RELATION (for aggregation) statement in the aggmap of a variable — even when there is a value stored in the desired cell. Recalculating values that are not specified in a PRECOMPUTE clause is the desired behavior when you want users to be able to change detail data cells and see the changed values reflected in dynamically-computed aggregate cells.
Syntax
You add or delete an $AGGREGATE_FORCECALC property to the most recently defined or considered object (see DEFINE and CONSIDER commands) by issuing a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$AGGREGATE_FORCECALC'
To delete the property, issue the following statement.
PROPERTY DELETE '$AGGREGATE_FORCECALC'
The MONTHABBRLEN option specifies the number of characters to use for abbreviations of month names that are stored in the MONTHNAMES option. You can specify how many characters to use for abbreviating particular month names when you specify the <MT>, <MTXT>, and <MTXTL> formats with the DATEFORMAToption or a VNF (value name format) specified for a dimension of type dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR.
Data Type
TEXT
Syntax
MONTHABBRLEN = specification [;|, specification]...
where specification is a text expression that has the following form:
startpos [ - endpos] : length
Parameters
Numbers that represent the first and last months whose abbreviation length is defined by length. These numeric positions apply to the corresponding lines of text in the MONTHNAMES option. You can specify these ranges of values in reverse order, endpos [-startpos], if you prefer.
The MONTHNAMES option can have more than 12 lines, so you can specify startpos and endpos greater than 12 in the setting of MONTHABBRLEN. When you specify a range where neither startpos nor endpos has a corresponding text value in the MONTHNAMES option, MONTHABBRLEN has no text values to abbreviate for that range. When you later change your month names list so that startpos is valid, the specified abbreviation is applied.
A number that specifies the length in characters (not bytes) of abbreviated month names. When you do not specify an abbreviation length for a given position in the MONTHNAMES option, or when you explicitly set a given position to zero, the default abbreviation is used. The default abbreviations are one character for <MT> and three characters for <MTXT> and <MTXTL>. Abbreviations are never used when you have designated the full name specifications <MTEXT> and <MTEXTL>.
Usage Notes
Ambiguous Month Names
You can use MONTHABBRLEN to interpret ambiguous names, for example, whether A stands for April or August. When the MONTHABBRLEN for April was 1 and for August was 2, then A would always match April, and it would require at least Au to match August. This interpretation does not depend on the order of April and August in the year; it would work the same way when the two months were reversed. If, on the other hand, the MONTHABBRLEN for each of these was 2, then A would not match either one, and you would have to enter at least Ap or Au to get a match.
Examples
Example 5-64 Specifying Month Abbreviations
The following MONTHABBRLEN setting specifies that the first 10 months of the year are abbreviated to one character and the last 2 months are abbreviated to two characters.
MONTHABBRLEN = '1-10:1, 11-12:2'
SHOW CONVERT ('2 August 2005' DATE)
These statements product the following result, with August abbreviated to the letter A.
02A05
The ASCIISTR function takes a string in any character set and returns an ASCII version of that string.
Returns
NTEXT
Syntax
ASCIISTR(text-exp)
Parameters
A text expression.
Usage Notes
How ASCIISTR Converts Non-ASCII Characters
The ASCIISTR function converts non-ASCII characters to \xxxx, where xxxx represents a UTF-16 code unit.
|
See: Oracle Database Globalization Support Guide for information on Unicode character sets and character semantics. |
The LOAD command loads the definition of a program, formula, or model into memory. It is usually used in startup programs, to save time when a program is first used in a session.
Syntax
LOAD object. . .
Parameters
The name of a program, formula, or model.
Usage Notes
Definitions Loaded on First Use
All of the objects in an analytic workspace (except for programs, formulas, and models) are loaded into memory when the analytic workspace is attached. Programs, models, and formulas are loaded into memory when first used or when requested using the LOAD command. The time required for loading is small but perceptible, and an application builder fine-tuning a system might want to preload objects in a startup program so that the application runs up to speed from the beginning of a session.
Effect of Loading Many Objects
Loading too many objects into memory can cause Oracle OLAP to run out of memory when it processes a long statement. It is best to use LOAD sparingly, choosing the objects for maximum effect.
LOAD Does Not Compile Programs
When a program is not compiled, LOAD does not automatically compile it. For best performance, always compile the program and save the compiled code by updating your workspace. Then when you load the program in another session (for example, with an AUTOGO program), the program is ready to run. See the COMPILE command for more information about compilation.
Examples
(Read-only) The DECIMALCHAR option is the value specified for the NLS_NUMERIC_CHARACTERS option.
DECIMALCHAR only affects the way Oracle OLAP formats numbers in output. When you format numbers for input, use a period (.) for the decimal marker. To use a different decimal marker, enclose the value in single quotes and use the TO_NUMBER function to convert the value from text to a valid number.
Data Type
ID
Syntax
DECIMALCHAR
Examples
Example 5-18 Identifying the Decimal and Thousands Markers
The statements in this example show the DECIMALCHAR and THOUSANDSCHAR values.
The following statement might produce a comma as output.
SHOW THOUSANDSCHAR
The following statement might produce a period as output.
SHOW DECIMALCHAR
With these values, the following statement might produce the output that follows it.
SHOW TOTAL(sales) 63,181,743.50
The HIDE command hides the text of a program, so that you cannot display it using a DESCRIBE, EDIT, or OBJ statement. You can perform all other actions on the program, including executing, compiling, renaming, or exporting.
When you hide a program, you supply a seed expression, which Oracle OLAP uses to encode the program text. You can use this seed expression later using an UNHIDE statement to make the text visible.
|
Note: This command performs simple encoding. For information on using secure encryption and other security features in Oracle, see Oracle Database Security Guide. |
Syntax
HIDE prog-name seed-exp
Parameters
The name of the program whose text you want to hide. Do not enclose the program name in quotes.
A single-line text expression to be used as a seed value when encoding of the program text. Do not specify NA for this value.
Keep a record of this seed expression, so that you can use it later with an UNHIDE statement. The seed expression you specify in the UNHIDE statement must be byte-for-byte the same value as you used in this HIDE statement. Also, the seed expression is case-sensitive, so record uppercase and lowercase characters carefully.
Usage Notes
Exporting and Importing with the Seed
When you export and import a hidden program, the text remains hidden in the analytic workspace in which it is imported. It retains the same seed expression for use with the UNHIDE command.
Examples
The EIFVERSION option is used with the EXPORT (EIF) and IMPORT (EIF) commands to copy data between different versions of Express® Server or Oracle OLAP. The version from which the data is exported is referred to as the source. The version to which the data is imported is referred to as the target.
Before you use the EXPORT command to export data to an EIF file, you use the EIFVERSION option to specify the internal version or build number of the target. Then, when you use EXPORT to copy data from the source to an EIF file, the data is in a format that can be imported by the target. Generally, you can import data from an EIF file into any target that has a later version number than the one you specify for the EIF file with EIFVERSION. However, when you set EIFVERSION to a value that is lower than the default version (that is, the version number of the current process), and you try to export data that the earlier version cannot manage, an error is generated. For example, when you try to export an aggmap to a 6.2 version of Express Server, an error is generated because Express Server 6.2 cannot manage aggmap.
You can use the EVERSION function to determine the internal version or build number of the target.
Syntax
EIFVERSION = n
Parameters
The internal version or build number of an Express Server or Oracle OLAP process which is the target into which you want the data imported.
By default, EIFVERSION is set to the internal version or build number of the current process.
Examples
Example 5-32 Exporting and Importing Between Different Versions
This example shows how to use EIFVERSION when you want to export data from Oracle OLAP to an EIF file and then import it into Express Server version 6.2.0.
This statement (issued from the target 6.2.0 Express Server)
SHOW EVERSION
returns the following version and build information
Module Mgr, Version: 6.2.0.0.0, Build: 60232 OES Kernel, Version: 6.2.0.0.0, Build: 60232
The following statements export the data from Oracle OLAP (which has a higher build number than 60232) to an EIF file that can be read in Express 6.2.0
EIFVERSION = 60232 EXPORT ALL TO EIF FILE 'myeif.eif'
The AW_RENAME procedure changes the name of an analytic workspace.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_RENAME (
oldname IN VARCHAR2,
newname IN VARCHAR2 );
Parameters
Table B-16 AW_RENAME Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The current name of the analytic workspace. The analytic workspace cannot be attached to any session. |
|
|
The new name of the analytic workspace. |
Example
The following commands detach the DEMO analytic workspace and change its name to SALES_DEMO.
EXECUTE dbms_aw.aw_detach('demo');
EXECUTE dbms_aw.aw_rename('demo', 'sales_demo');
OLAP_EXPRESSION_TEXT is a SQL function that dynamically executes an OLAP DML text expression within the context of an OLAP_TABLE function. In addition to returning a custom measure, you can use this function in the WHERE and ORDER BY clauses to modify the result set of the query of the analytic workspace.
OLAP_EXPRESSION_TEXT returns character data. To return numeric, boolean, or date data, use OLAP_EXPRESSION, OLAP_EXPRESSION_BOOL, or OLAP_EXPRESSION_DATE SQL functions.
Before you use this function, you must specify a ROW2CELL clause in the limit map used by OLAP_TABLE. ROW2CELL identifies a RAW column that OLAP_TABLE populates with information used by the OLAP single-row functions.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
An evaluation of text_expression for each row of the table object returned by the OLAP_TABLE function.
Syntax
OLAP_EXPRESSION_TEXT(
r2c IN RAW(32),
text_expression IN VARCHAR2)
RETURN NUMBER;
Parameters
The name of a column specified by a ROW2CELL clause in the limit map. See "ROW2CELL Clause" of OLAP_TABLE
An OLAP DML expression that returns a text result.
Example
Refer to the examples in OLAP_EXPRESSION and OLAP_EXPRESSION_BOOL for examples of OLAP single-row functions.
The RUN procedure executes one or more OLAP DML commands and directs the output to a printer buffer. It is typically used to manipulate analytic workspace data within an interactive SQL session. In contrast to the EXECUTE Procedure, RUN stops processing commands when it gets an error.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON
If you are using a different program, refer to its documentation for the equivalent setting.
This procedure does not print the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
RUN (
olap_commands IN STRING,
silent IN BOOLEAN DEFAULT FALSE);
RUN (
olap_commands IN CLOB,
silent IN BOOLEAN DEFAULT FALSE);
RUN (
olap_commands IN STRING,
output OUT STRING);
RUN (
olap_commands IN STRING,
output IN OUT CLOB);
RUN (
olap_commands IN CLOB,
output OUT STRING);
RUN (
olap_commands IN CLOB,
output IN OUT CLOB);
Parameters
Table B-28 EXECUTE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semicolons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
|
|
A boolean value that signals whether the output from the OLAP DML commands should be suppressed. (Error messages from the OLAP engine are never suppressed, regardless of this setting.) |
|
|
Output from the OLAP engine in response to the OLAP commands. |
Example
The following sample SQL*Plus session attaches an analytic workspace named XADEMO, creates a formula named COST_PP in XADEMO, and displays the new formula definition.
EXECUTE dbms_aw.run('DESCRIBE time');
DEFINE TIME DIMENSION TEXT
The next example shows how RUN stops executing commands after encountering an error.
EXECUTE dbms_aw.run('SHOW DECIMALS'); 0 EXECUTE dbms_aw.run('CALL nothing; DECIMALS=4'); BEGIN dbms_aw.run('CALL nothing; DECIMALS=4'); END; * ERROR at line 1: ORA-34492: Analytic workspace object NOTHING does not exist. ORA-06512: at "SYS.DBMS_AW", line 58 ORA-06512: at "SYS.DBMS_AW", line 134 ORA-06512: at line 1 EXECUTE dbms_aw.run('SHOW DECIMALS'); 0
The SUBTOTAL function returns the value of one subtotal accumulated in a report. You normally use the SUBTOTAL function in a ROW command to include a subtotal or grand total in the report. Since Oracle OLAP maintains 32 running totals for each column, you can include up to 32 levels of subtotals
|
Note: In a REPORT statement, use the GRANDTOTALS and SUBTOTALS keywords to include rows of grand totals and subtotals. |
Return Value
DECIMAL
Syntax
SUBTOTAL(n)
Parameters
An INTEGER value that indicates the level of a running total for each numeric column in a report. For example, a "Total" may be a level 1 subtotal and a "Grand Total" may be a level 2 subtotal. Because it is possible to have up to 32 levels of running totals in a column, n must be an INTEGER between 1 and 32. SUBTOTAL returns the value of this subtotal for the current column and then resets the value of subtotal n to zero.
The numbers by which the 32 subtotals are referenced (1 to 32) have no intrinsic significance; all the subtotals are the same until you reference them.
Usage Notes
Resetting Subtotals Automatically
When you use the SUBTOTAL function in a ROW command to include a subtotal of the current column, the subtotal at that level is reset to zero.
Resetting Subtotals with ZEROTOTAL
When you use the ROW command to produce a report, you can use a ZEROTOTAL statement to reset any subtotal of any column to zero.Typically, use ZEROTOTAL this at the beginning of a report program to make sure all totals begin at zero.
NA Values and SUBTOTAL
SUBTOTAL ignores NA values. When all values are NA, SUBTOTAL returns zero.
Examples
Example 8-124 Calculating Subtotals and Grand Totals in a Report
In a sales report, suppose you want to show a subtotal for each region. You also want to see a grand total of all sales at the end of the report. You can use SUBTOTAL(1) to produce the subtotal for each region. This subtotal is reset to 0 each time you use it, so it provides a separate subtotal for each region. At the end of the report you can use SUBTOTAL(2) to produce the grand total. Since you have not yet used it in your report, it holds a total of the sales figures for all regions.
LIMIT month TO FIRST 3
LIMIT region TO ALL
ZEROTOTAL ALL
FOR region
DO
ROW region
LIMIT DISTRICT TO region
FOR district
DO
ROW INDENT 5 district ACROSS month: sales
DOEND
ROW INDENT 5 'Total' ACROSS month: OVER '-' SUBTOTAL(1)
BLANK
DOEND
ROW 'Grand Total' ACROSS month: OVER '=' SUBTOTAL(2)
The program produces the following output.
East
Boston 32,153.52 32,536.30 43,062.75
Atlanta 40,674.20 44,236.55 51,227.06
---------- ---------- ----------
Total 72,827.72 76,772.85 94,289.81
Central
Chicago 29,098.94 29,010.20 39,540.89
Dallas 47,747.98 50,166.81 67,075.44
---------- ---------- ----------
Total 76,846.92 79,177.01 106,616.33
West
Denver 36,494.25 33,658.24 45,303.93
Seattle 43,568.02 41,191.28 51,547.23
---------- ---------- ----------
Total 80,062.27 74,849.52 96,851.16
========== ========== ==========
Grand Total 229,736.91 230,799.38 297,757.30
The COMPILEWARN option controls whether Oracle OLAP records a warning message in the current outfile when a compilable object, such as a program or a model, is being compiled automatically. (When you use the COMPILE command to explicitly compile an object, Oracle OLAP does not display the COMPILEWARN message.)
A compilable object is automatically compiled in the following cases:
The first time it is executed after being edited.
The first time it is executed in a session when it was compiled in a previous session after the last time the analytic workspace was updated and committed.
After an analytic workspace object referred to in the code has been renamed or deleted. When the object name in the code has not been redefined, you receive an error message.
When the code refers to objects in another analytic workspace and the objects in the currently attached analytic workspace do not have the same object type (variable, relation, and so on), data type (INTEGER, TEXT, and so on), or dimensions as the objects available when the code was previously compiled.
Data Type
BOOLEAN
Syntax
COMPILEWARN = {YES|NO}
Parameters
Oracle OLAP records a message warning you that a compilable object is being compiled automatically. The message explains why the compilation was necessary.
(Default) Oracle OLAP does not record a message warning you that an object is being compiled automatically.
Examples
The DESCRIBE command produces a report that shows the definition of one or more workspace objects. An object definition that you see in the output from a DESCRIBE command might include a description (LD), a value name format (VNF) for a time dimension, an expression associated with a FORMULA, permission specified a PERMIT statements, or the contents of a calculation specification (for example, the contents of a program). You can use DESCRIBE to show the definition of an object even when you do not have permission to access the object or to change its permission. Some parts of some object definitions are not reported on as described in "What's Not in the Report Output by DESCRIBE".
Syntax
DESCRIBE [names]
Parameters
The names of one or more workspace objects, separated by spaces or commas. When you omit this argument, DESCRIBE shows the definition of all objects in the current status of the NAME dimension. Consequently, when you omit this argument you can use a LIMIT command in combination with DESCRIBE to report the definitions of a particular group of objects in your workspace, as illustrated in Example 9-109, "Describing All Relations".
Usage Notes
What's Not in the Report Output by DESCRIBE
Some parts of the object definitions do not appear in the output of DESCRIBE:
When a PERMIT statement denies you the right to change the permission of an object, DESCRIBE does not include the permission associated with the definition of the object.
For a worksheet definition, the DESCRIBE report does not include the default dimensions, WKSCOL and WKSROW. However, it does include user-defined dimensions when they have been used to define a worksheet. See Example 9-110, "Describing a Worksheet".
Properties and triggers associated with objects are not displayed. To see the properties and triggers associated with an object, you must use the FULLDSC program.
When you define a composite or conjoint has the default index type, that information is not displayed.
Dimensioned BOOLEAN variables that are in older 1 or 2 byte formats are listed as WIDTH 1 and WIDTH 2. The width of BOOLEAN variables created in single-bit format is not listed.
Creating Objects with DESCRIBE Output
You can use the output from the DESCRIBE command to create objects in other workspaces, because each line of the output is a valid statement. For example, you can execute an OUTFILE statement to send subsequent output to a file, and then execute a DESCRIBE command. You can then access another workspace and use an INFILE statement to read the DESCRIBE output. The same object is created in that workspace.
Examples
Example 9-108 Describing Variables
This example produces a report of the definitions of the two variables, sales and price. The statement
DESCRIBE sales price
produces the following output.
DEFINE SALES VARIABLE DECIMAL <MONTH PRODUCT DISTRICT> LD Sales Revenue DEFINE PRICE VARIABLE DECIMAL <MONTH PRODUCT> LD Wholesale Unit Selling Price
Example 9-109 Describing All Relations
Suppose you want to look at the definitions of all the relations in your workspace. First limit the NAME dimension, using the OBJ function. After limiting NAME, use DESCRIBE with no arguments to produce a report of the definitions. The following statements produce a description of the relations in the analytic workspace.
LIMIT NAME TO OBJ(TYPE) EQ 'RELATION' DESCRIBE
DEFINE REGION.DISTRICT RELATION REGION <DISTRICT> LD REGION for each DISTRICT DEFINE DIVISION.PRODUCT RELATION DIVISION <PRODUCT> LD DIVISION for each PRODUCT DEFINE MLV.MARKET RELATION MARKETLEVEL <MARKET> DEFINE MARKET.MARKET RELATION MARKET <MARKET> LD Self-relation for the Market Dimension
Since the values returned by OBJ(TYPE) are always in uppercase, you have to use 'RELATION' rather than 'relation' in your LIMIT command to obtain a match.
Example 9-110 Describing a Worksheet
The dimensions of a worksheet appear in the description only when they are user-defined dimensions. The default dimensions WKSCOL and WKSROW are not included in the description. The statements
DEFINE work1 WORKSHEET DEFINE columns DIMENSION INTEGER DEFINE rows DIMENSION INTEGER DEFINE work2 WORKSHEET <columns rows> DESCRIBE work1 work2
produce the following output.
DEFINE WORK1 WORKSHEET DEFINE WORK2 WORKSHEET <COLUMNS ROWS>
The STATFIRST function returns the first value in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
The data type returned by STATFIRST is either the data type of the dimension or dimension surrogate value or an INTEGER that indicates its position in the default status list of the dimension.The dimension value returned by STATFIRST is converted to a number or a text value, as appropriate to the context. See Example 8-107, "Assigning value of STATFIRST to Variables of Different Types".
Syntax
STATFIRST(dimension)
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
Examples
Example 8-107 Assigning value of STATFIRST to Variables of Different Types
The following statements
DEFINE textvar TEXT textvar = STATFIRST(month) SHOW textvar
produce this output.
Jun95
In contrast, these statements
DEFINE intvar INTEGER intvar = STATFIRST(month) SHOW INTVAR
produce this output.
6
Example 8-108 STATFIRST with KEEP
The following line from a program uses STATFIRST to limit month to all values in the status up to a value that has been stored previously in a variable called onemonth. The keyword KEEP means the new status is always a subset of the old status.
LIMIT month KEEP STATFIRST(month) TO onemonth
STATFIRST is used here, rather than a particular month value, so that the limit can work on any status list.
The LAG function returns the values of a dimensioned variable or expression at a specified offset of a dimension before the current value of that dimension. Typically, you use the LAG function to retrieve values for a previous time period.
Return Value
The data type of the variable argument or NA when you try to lag before the first period of a time dimension.
Syntax
LAG(variable n, dimension, [STATUS|NOSTATUS|limit-clause])
Parameters
A variable or expression that is dimensioned by dimension.
The offset (that is, the number of dimension values) to lag. LAG uses this value to determine the number of values that LAG should go back in dimension to retrieve the value of variable.
Typically, n is a positive INTEGER that indicates the number of time periods (or dimension values) before the current one. When you specify a negative value for n, it indicates the number of time periods after the current o ne. In other words, using a negative value for n turns LAG into a LEAD function.
|
Note: When using LAG in a model, see "Ensuring One-Way Dimensional Dependence" for information on how to code a value forn so that Oracle OLAP does not use simultaneous blocks when solving the model. |
The dimension along which the lag occurs. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR.
When variable has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want LAG to use that dimension, you can omit the dimension argument.
Specifies that LAG should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the lag.
(Default) Specifies that LAG should use the default status (that is, a list all the dimension values in their original order) when computing the lag.
Specifies that LAG should use the default status limited by limit-clause when computing the lag.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
To specify that LAG should use the current status limited by limit-clause when computing the lag, specify a LIMIT function for limit-clause.
Usage Notes
Assigning Results to a Time-Series Variable
Use care when assigning the results of LAG back into the time-series variable. Results are assigned one cell at a time, so you can overwrite the whole array with the first value returned, instead of moving all the values over n positions. You can, however, use LAG to calculate a series of values based on the initial value.
Examples
Example 8-1 Using LAG
Assume that you have the following definitions in your analytic workspace.
DEFINE time DIMENSION TEXT DEFINE timelevels DIMENSION TEXT DEFINE timelevelrel RELATION timelevels <time> DEFINE product DIMENSION TEXT DEFINE district DIMENSION TEXT DEFINE sales VARIABLE DECIMAL <time product district>
Assume also that those object have the values shown in the following reports.
REPORT timelevelrel TIME TIMELEVELREL -------------- ---------- AllYears AllYears 2004 Years 2005 Years 2006 Years Jan2005 Months Feb2005 Months Mar2005 Months Apr2005 Months ... ... Oct2006 Months Nov2006 Months Dec2006 Months
REPORT product PRODUCT -------------- TVs DVDs Computers REPORT district DISTRICT -------------- All Districts Mass Conn Boston Springfield Hartford New Haven
Now assume that you issue the following LIMIT statements to limit product, district, and time.
LIMIT product TO 'TVs' LIMIT district TO 'Hartford' LIMIT time TO 'Jan2006' 'Feb2006' 'Mar2006' 'Apr2006' 'May2006' 'Jun2006' 'Jul2006' 'Aug2006' 'Sep2006' 'Oct2006' 'Nov2006' 'Dec2006'
You can issue a REPORT statement with LAG to show the value of sales for months in both 2006 and for 2005.
REPORT DOWN time HEADING 'Sales 2006' sales HEADING 'Sales 2005' LAG(sales, 12, time, RELATION timelevelrel)
DISTRICT: Hartford
-------PRODUCT-------
---------TVs---------
TIME Sales 2006 Sales 2005
-------------- ---------- ----------
Jan2006 1,542.91 1,627.51
Feb2006 1,786.07 1,100.13
Mar2006 1,794.43 1,667.61
Apr2006 1,942.92 1,346.66
May2006 1,530.08 1,509.51
Jun2006 1,613.60 1,242.47
Jul2006 1,666.35 1,307.17
Aug2006 1,413.79 1,033.93
Sep2006 1,526.98 1,773.96
Oct2006 1,112.85 1,103.78
Nov2006 1,193.41 1,132.39
Dec2006 1,851.19 1,543.62
The WRITABLE function returns TRUE when the user has WRITE permission for the object and FALSE when the user does not or when the object is not a variable, worksheet object, relation, or valueset.
Return value
BOOLEAN
The result has the same dimensions as expression.
Syntax
WRITABLE (expression)
Parameters
An expression that is the name or QDR of an object that has values (that is, a variable, relation, valueset, or worksheet object).
The YYOF function returns an INTEGER in the range of 1000 to 9999, giving the year in which a specified date falls. The result returned by YYOF has the same dimensions as the specified date expression.
Return Value
INTEGER
Syntax
YYOF(date-expression)
Parameters
An expression that has the DATE data type, or a text expression that specifies a date. The values of the text expression are converted automatically to DATE values, using the current setting of the DATEORDER option to resolve any ambiguity.
Usage Notes
Commas in Year Values
When the COMMAS option is set to YES when you display the value returned by YYOF, the year is displayed with a comma separating the thousands (for example, 1,996). To avoid this, you can set the COMMAS option to NO before displaying the year.
Examples
The NULLIF function compares one expression with another and returns NA when the expressions are equal, or the base expression when they are not.
Return Value
NA when the expressions are equal, or the base expression when they are not.
Syntax
NULLIF (expr1 , expr2)
Parameters
An expression. The base expression for the comparison
An expression to compare to expr1.
Examples
The REPLCHARS function replaces one or more characters in a text expression.
|
Tip: When you are using a multibyte character set, you can use the REPLBYTES function instead of the REPLCHARS function. Also, you can use the CHANGECHARS function to change one or more occurrences of a specified string in a text value to another string. |
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
REPLCHARS(text-expression characters [start])
Parameters
The expression in which characters are to be replaced. When the characters to be replaced from text-expression contain embedded line breaks, these breaks are removed. Other line breaks are preserved. Removed line breaks are not counted toward the total number of characters replaced. Line breaks in the replacement expression are retained in the output of REPLCHARS, but are likewise not counted.
A text expression that contains one or more characters that replaces existing characters in text-expression.
An INTEGER that represents the character position at which to begin replacing characters. The position of the first character in text-expression is 1. When you omit this argument, REPLCHARS starts with the first character. REPLCHARS replaces as many characters of text-expression as are required for the specified new characters. When the value of start is greater than the length of text-expression, REPLCHARS simply returns text-expression.
Examples
Example 8-78 Replacing Text Characters
This example shows how to replace a portion of the text value Hello there, Joe.
The statement
SHOW REPLCHARS('Hello there, Joe', 'Jane', 14)
produces the following output.
Hello there, Jane
Example 8-79 How REPLCHARS Handles Line Breaks
This example shows how REPLCHARS preserves but ignores line breaks.
var1 = JOINLINES('Hello' 'there' 'Joe')
var2 = JOINLINES('Hi' 'Jane')
The statement
show REPLCHARS(var1 var2)
produces the following output.
Hi Janehere Joe
REPLCHARS has replaced the first 6 characters of var1 (Hellot of HellothereJoe) with the 6 characters of var2 (HiJane). It has preserved the line breaks following Hi (from var2) and there (from var1).
To replace all 13 characters in var1, you must specify 13 replacement characters; for example, you can add 7 spaces after Jane.
var2 = JOINLINES('Hi' 'Jane ')
The statement
SHOW REPLCHARS(var1 var2)
produces the following output.
Hi Jane
The ADVISE_PARTITIONING_LEVEL function returns the level used by the Sparsity Advisor for partitioning over a dimension. It returns NULL if the Sparsity Advisor did not partition the cube, and raises an exception if the dimension hierarchy is not level-based.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_PARTITIONING_LEVEL (
cubename IN VARCHAR2,
sources IN dbms_aw$_dimension_sources_t,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Parameters
Table B-7 ADVISE_PARTITIONING_LEVEL Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a table created by the |
Example
The following program fragment shows the ADVISE_PARTITIONING_LEVEL function being used to query the results after using the Sparsity Advisor.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_output.put_line('Partitioning Level: ' ||
dbms_aw.advise_partitioning_level('units_cube', dimsources,
'aw_sparsity_advice'));
END;
/
The program uses DBMS_OUTPUT to display the partitioning level, which in this case is YEAR.
Partitioning Level: year
For expressions dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the ENDDATE function returns the final date of the last time period in the dimension status for which the expression has a non-NA value. For example, when an expression is dimensioned by a dimension of type MONTH, and when DEC98 is the last dimension value for which the expression has a non-NA value, ENDDATE returns the date December 31, 1998.
Return Value
DATE-only or text
Syntax
ENDDATE(expression)
Parameters
The expression must have exactly one dimension that has the type of DAY, WEEK, MONTH, QUARTER, or YEAR. When all the values of the expression are NA, ENDDATE returns NA.
Examples
Example 7-75 Finding the End Date
The following statements limit the values of the dimensions of the units variable, then sends the last date associated with a non-NA value to the current outfile.
LIMIT month TO ALL LIMIT product TO 'Tents' LIMIT district TO 'Chicago' SHOW ENDDATE(units)
These statements produce the following output.
31DEC96
The LTRIM function removes characters from the left of a text expression, with all the leftmost characters that appear in another text expression removed. The function begins scanning the base text expression from its first character and removes all characters that appear in the trim expression until reaching a character that is not in the trim expression and then returns the result.
To trailing characters, use RTRIM. To trim both leading or trailing characters, use TRIM.
Return Value
TEXT or NTEXT based on the data type of the first argument.
Syntax
LTRIM (text-exp [, trim-exp])
Parameters
A text expression that you want trimmed.
A text expression that is the characters to trim. The default value of trim-exp is a single blank.
Examples
The MODGAMMA option specifies a value to use in testing how much an equation in a simultaneous block of a model is changing between iterations. MODGAMMA controls the degree to which the test compares the absolute amount of the change between iterations versus the proportional change. MODGAMMA is especially important in testing equations that result in very small values.
|
See: "Model Options" for descriptions of all of the options that control the solution of simultaneous blocks. |
Data Type
INTEGER
Syntax
MODGAMMA = {n|1}
Parameters
An INTEGER value to use in testing for convergence and divergence. As Oracle OLAP calculates each equation in a simultaneous block, it constructs a comparison value that is based on the results of the equation for the current iteration and the previous iteration. When the comparison value passes a tolerance test, the equation is considered to have converged. When the comparison value meets an overflow test, the equation is considered to have diverged.
The comparison value that is tested is as follows.
(thisResult - prevResult) DIVIDED BY (prevResult PLUS MODGAMMA)
where thisResult is the result of this iteration and prevResult is the result of the previous iteration.
Oracle OLAP calculates the absolute value of the enclosed expression. The default value of MODGAMMA is 1.
Usage Notes
Testing Convergence
In the test for convergence, the MODTOLERANCE option determines how closely the results of an equation must match between successive iterations. With the default value of 3 for MODTOLERANCE, the equation is considered to have converged when the comparison value is less than 0.001.
Testing Divergence
In the test for divergence, the MODOVERFLOW option determines how dissimilar the results of an equation must be in successive iterations. With the default value of 3 for MODOVERFLOW, the equation is considered to have diverged when the comparison value is greater than 1000.
Comparison Value
The comparison value that Oracle OLAP evaluates in tests of convergence and divergence is fundamentally a proportional value. It expresses the change between iterations as a proportion of the previous results. In the test for convergence, the change between iterations must be small in proportion to the previous results. In the test for divergence, the change between iterations must be large in proportion to the previous results. By testing a proportional value, rather than testing the absolute amount of change, Oracle OLAP can apply the same test criteria to all equations, regardless of the magnitude of the equation results.
However, the comparison value that Oracle OLAP tests is not strictly proportional. When the results of an equation are very close to zero, the denominator of a strictly proportional comparison value would also be very close to zero, and thus the comparison value itself would generally be large. Therefore, the test for convergence would be difficult to satisfy, while the test for divergence would be easy to meet. To solve this problem, Oracle OLAP adds the value of MODGAMMA to the denominator of the comparison value. When the default value of 1 is used for MODGAMMA, the effect of MODGAMMA is as follows:
When the equation results are close to zero, the denominator is close to one and the test is essentially a test of the absolute change between iterations.
When the equation results are very large, the effect of adding MODGAMMA to the denominator is negligible, and the test is close to being a strictly proportional test.
Controlling Test Sensitivity
For equation values close to zero, you can control the sensitivity to the tests for convergence and divergence by changing the value of MODGAMMA. When equation values are very small, you essentially scale the changes in model values between iterations when you change the value of MODGAMMA. For example, when you change MODGAMMA from 1 to 2, the comparison value is essentially cut in half. As a consequence, you reduce the likelihood that divergence occurs.
Ways to Increase Speed of Convergence of Model Equations
The default value of MODGAMMA is appropriate in most situations. When you increase the value of MODGAMMA, the model equations converge more quickly, but the results are less precise. The smaller the equation value, the more pronounced is the effect of increasing MODGAMMA; convergence is attained relatively more quickly for small model values, while more precision is lost.
You can also force the simultaneous blocks of a model to converge more quickly by decreasing the value of MODTOLERANCE and thereby relaxing the test for convergence. However, when you do this, you sacrifice the precision of all the results, not just the results of equations with small values.
Therefore, when a model contains some equations with large values and some equations with very small values, it might be preferable to increase MODGAMMA rather than decreasing MODTOLERANCE. By increasing MODGAMMA, you might be able to force equations with small values to converge more quickly while retaining the precision of equations with large values.
Examples
Example 5-53 Using the Default MODGAMMA Value
The following statements specify a trace for a model called income.bud, specify that the Gauss-Seidel method should be used for solving simultaneous blocks, limit a dimension, and run the model.
MODTRACE = YES MODSIMULTYPE = 'GAUSS' LIMIT division TO 'Camping' income.bud budget
These statements produce the following output.
(MOD= INCOME.BUD) BLOCK 1: SIMULTANEOUS
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 16) = 0.026243533
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 17) = 0.024054312
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 18) = 0.025788293
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 19) = 0.024390642
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 20) = 0.025501664
...
(MOD= INCOME.BUD) BUDGET (LINE NET.INCOME MONTH 'JAN97' ITER 21) = 0.024608562
In the trace, you can see the results that were calculated for the NET.INCOME line item in the final six iterations over a block of simultaneous equations.
The value of MODTOLERANCE is its default value of 3. Consequently, for an equation to pass the convergence test, its comparison value must be less than .001.
MODGAMMA is set to its default value of 1. The equation for the NET.INCOME line item passed the convergence test in the twenty-first iteration. The comparison value for Net.Income in the twenty-first iteration was calculated as follows.
(0.024608562967 - 0.025501664970 = 0.00087) / (0.025501664970 + 1)
Example 5-54 Setting MODGAMMA to Speed up the Convergence of a Model
The following statements change the MODGAMMA setting and run the income.bud model.
MODGAMMA = 2 income.bud budget
With MODGAMMA set to 2, the equation for Net.Income converges in the eighteenth iteration. The comparison value for Net.Income in the eighteenth iteration is calculated as follows.
(0.025788293304 - 0.024054312748 = 0.00086) / (0.024054312748 + 2)
The ECHOPROMPT option determines if input lines and error messages should be echoed to the current outfile. When ECHOPROMPT is set to YES and you have specified a debugging file with DBGOUTFILE, the input lines and error messages are echoed to the debugging file instead of the current outfile.
Data Type
BOOLEAN
Syntax
ECHOPROMPT = {YES|NO}
Parameters
Input lines and error messages are echoed to the current outfile or the debugging file specified by DBGOUTFILE.
(Default) Input lines and error messages do not appear in the current outfile or in the debugging file.
Examples
Example 5-26 Using ECHOPROMPT
Suppose you want to have all input lines and error messages included in the disk file that contains your output. Set ECHOPROMPT to YES before issuing an OUTFILE statement that sends the output to the disk file. In the following statements, the disk file is in the current directory object.
ECHOPROMPT = YES OUTFILE 'newcalc.dat'
The LARGEST function returns the largest value of an expression. You can use this function to compare numeric values or date values.
Return Value
The data type of the expression. It can be INTEGER, LONGINT, DECIMAL, or DATE.
Syntax
LARGEST(expression [CACHE] [dimension...])
Parameters
The expression whose largest value is to be returned.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of expression and another dimension that you want as a dimension of the result.
By default, LARGEST returns a single value. When you indicate one or more dimensions for the result, LARGEST tests for values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of expression, but, instead, is dimension that is related to a dimension of expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
NA Values and LARGEST
LARGEST is affected by the NASKIP option in the same manner as other aggregate functions. When NASKIP is set to YES (the default), LARGEST ignores NA values and returns the largest value or values that are not NA. When NASKIP is set to NO, LARGEST returns NA when any value of the expression is NA. When all the values of the expression are NA, LARGEST returns NA for either setting of NASKIP.
Using LARGEST With an Expression Dimensioned by a DWMQY Dimension
When expression is dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other DAY, WEEK, MONTH, QUARTER, or YEAR dimension as a related dimension. Oracle OLAP uses the implicit relation between the dimensions. To control the mapping of one DAY, WEEK, MONTH, QUARTER, or YEAR dimension to another (for example, from weeks to months), you can define an explicit relation between the two dimensions and specify the name of the relation as the dimension argument to the LARGEST function.
For each time period in the related dimension, Oracle OLAP finds the largest data value in any source time period that ends in the target time period. This method is used regardless of which dimension has the more aggregate periods.
Examples
Example 8-4 Finding the Largest Monthly Sales
This example uses the LARGEST function to find the largest monthly sportswear sales for each district during the first half of 1996. To see the largest sales figure for each district, specify district as the dimension of the results.
LIMIT product TO 'Sportswear' LIMIT month TO 'Jan96' TO 'Jun96' REPORT HEADING 'Largest Sales' LARGEST(sales district)
The preceding statements produce the following output.
Largest
DISTRICT Sales
-------------- ----------
Boston 79,630.20
Atlanta 177,967.49
Chicago 112,792.78
Dallas 175,716.31
Denver 97,236.88
Seattle 60,322.88
The CUMSUM function computes cumulative totals over time or over another dimension. When the data being totaled is one-dimensional, CUMSUM produces a single series of totals, one for all values of the dimension. When the data has dimensions other than the one being totaled over, CUMSUM produces a separate series of totals for each combination of values in the status of the other dimensions.
Return Value
DECIMAL
Syntax
CUMSUM(cum-expression [STATUS] total-dim [reset-dim] [INSTAT])
Parameters
A numeric variable or calculation whose values you want to total, for example UNITS.
When cum-expression is multidimensional, CUMSUM creates a temporary variable to use while processing the function. When you specify the STATUS keyword, CUMSUM uses the current status instead of the default status of the dimensions for calculating the size of this temporary variable. When the dimensions of the expression are limited to a few values and are physically fragmented, you can improve the performance of CUMSUM by specifying STATUS.
When you use CUMSUM with the STATUS keyword in an expression that requires going outside of status for results (for example, with the LEAD or LAG functions or with a qualified data reference), the results outside of status are returned as NA.
|
Note: When you specify the STATUS keyword when the data being totaled is one-dimensional, an error results |
The dimension of cum-expression over which you want to total.
Specifies that the cumulative totals in a series should start over with each new reset dimension value, for example at the start of each new year. The reset dimension can be any of the following:
Any dimension related to total-dim through an explicitly defined relation.
Any dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR, when total-dim also has a type of DAY, WEEK, MONTH, QUARTER, or YEAR. CUMSUM uses the implicit relation between the two dimensions, so they do not have to be related through an explicit relation. See "Overriding an Implicit Relation".
A relation dimensioned by total-dim. CUMSUM uses the related dimension as the reset dimension which enables you to choose which relation is used when there are multiple relations.
Specifies that CUMSUM uses only the values of total-dim that are currently in status. When you do not specify INSTAT, CUMSUM produces a total for all the values of total-dim, independent of its current status. See "INSTAT Ignores Current Status By Default".
Usage Notes
Overriding an Implicit Relation
When you specify dimensions with a type of DAY, WEEK, MONTH, QUARTER, or YEAR for both the total-dim argument and the reset-dim argument, CUMSUM uses the implicit relation between the two dimensions even when an explicit relation exists. However, you can override the default and use the explicit relation by specifying the name of the relation for the reset-dim argument.
INSTAT Ignores Current Status By Default
Unless you specify the INSTAT keyword, CUMSUM ignores the current status in calculating totals. Suppose MONTH is the dimension being totaled over (and INSTAT has not been specified). The CUMSUM total for a given month uses the values for all preceding months, even when some are not in the status. When a reset dimension is specified, the total for a given month uses the values for all preceding months that correspond to the same value of the reset dimension (for example, all preceding months in the same year). To calculate year-to-date totals, specify YEAR as the reset dimension.
Examples
Example 7-56 Multiple CUMSUM Calculations
This example shows cumulative units totals for tents and canoes in the Atlanta district for the first six months of 1996. The report shows the units figures themselves, year-to-date totals calculated using year as the reset dimension, and totals calculated with no reset dimension using all preceding months. Assume that you issue the following statements.
LIMIT district TO 'Atlanta' LIMIT product TO 'Tents' 'Canoes' LIMIT month TO 'Jan96' TO 'Jun96' REPORT DOWN month units CUMSUM(units, month year) - CUMSUM(units, month)
The following report is displayed.
DISTRICT: ATLANTA
------------------------PRODUCT------------------------
---------TENTS------------- ---------CANOES------------
CUMSUM(UNI CUMSUM(UNI
TS, MONTH CUMSUM(UNI TS, MONTH CUMSUM(UNI
MONTH UNITS YEAR) TS, MONTH) UNITS YEAR) TS, MONTH)
----- -------- --------- ---------- ------- --------- ----------
Jan96 279 279 5,999 281 281 5,162
Feb96 305 584 6,304 309 590 5,471
Mar96 356 940 6,660 386 976 5,857
Apr96 537 1,477 7,197 546 1,522 6,403
May96 646 2,123 7,843 525 2,047 6,928
Jun96 760 2,883 8,603 608 2,655 7,536
The totals for CUMSUM(UNITS, MONTH) include values for all months beginning with the first month, JAN95. The totals for CUMSUM(UNITS, MONTH YEAR) include only the values starting with JAN96.
Example 7-57 Resetting for a Quarter
This example shows cumulative totals for the same products and district, for the entire year 1996. Because quarter is specified as the reset dimension, totals start accumulating at the beginning of each quarter. The cumulative totals for Jan96, Apr96, Jul96, and Oct96 are the same as the units figures for those months. Assume that you issue the following statements.
LIMIT district TO 'Atlanta' LIMIT product TO 'Tents' 'Canoes' limit month TO year 'Yr96' REPORT DOWN month units CUMSUM(units, month quarter)
A report displays.
DISTRICT: ATLANTA
------------------PRODUCT------------------
--------TENTS-------- -------CANOES--------
CUMSUM(UNI CUMSUM(UNI
TS, MONTH TS, MONTH
MONTH UNITS QUARTER) UNITS QUARTER)
------------ ---------- ---------- ---------- ----------
Jan96 279 279 281 281
Feb96 305 584 309 590
Mar96 356 940 386 976
Apr96 537 537 546 546
May96 646 1,183 525 1,071
Jun96 760 1,943 608 1,679
Jul96 852 852 626 626
Aug96 730 1,582 528 1,154
Sep96 620 2,202 520 1,674
Oct96 554 554 339 339
Nov96 380 934 309 648
Dec96 284 1,218 288 936
The ISDATE program determines whether a text expression represents a valid date. ISDATE only tests a text expression to see if it can be converted to a DATE-only value; it does not actually make the conversion. You must use CONVERT to make the conversion.
Return Value
BOOLEAN
YES when the text expression represents a valid date; NO when it does not.
Syntax
ISDATE(test-date)
Parameters
A single-line ID or TEXT expression to be examined to see if it represents a valid date, as defined by the DATE-only data type. For a description of the valid styles for entering dates, see "Date-only Input Values".
Examples
The SET_INCLUDED_MODEL program adds an INCLUDE model statement to a previously-defined cube dimension's model, or deletes an INCLUDE model statement from a previously-defined cube dimension's model. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
Syntax
CALL SET_INCLUDED_MODEL(logical_dim, model_name, custom_model)
Parameters
Since SET_INCLUDED_MODEL is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name of the logical model that is associated with the cube dimension.
A text expression that is the OLAP DML-created model for which you want to add an INCLUDE statement.
To remove an INCLUDE statement, specify NA.
Examples
Example 10-118 Creating Static and Dynamic Models for an OLAP Cube
Assume that you have created an OLAP cube dimension named my_time that dimensions an OLAP cube named my_cube. Within my_cube there are two measures: sales and moving_sales. Now you want to create static and dynamic models for my_cube.
To create a static model, execute the following PL/SQL statement that executes a user-written OLAP DML program named setup_pre_model.
exec dbms_aw.execute('call my_util_aw!setup_pre_model');
As you can see from the following definition of the setup_pre_model program, the model is actually defined using the SET_INCLUDED_MODEL program and added using the ADD_CUBE_MODEL program, both of which are provided with the OLAP DML.
DEFINE SETUP_PRE_MODEL PROGRAM
PROGRAM
VARIABLE _pre_model text
VARIABLE _aw_dim text
_pre_model = 'my_aw!my_pre_model'
_aw_dim = OBJORG(DIM 'my_time')
DEFINE &_pre_model model
CONSIDER &_pre_model
MODEL JOINLINES(JOINCHARS('dimension ' _aw_dim) -
JOINCHARS(_aw_dim '(\'L3_3\')=10') -
'end')
CALL SET_INCLUDED_MODEL('my_time', 'pre_model', _pre_model)
CALL ADD_CUBE_MODEL('my_cube', 'my_time', 'pre_model', YES)
END
Load the my_time dimension and load and solve my_cube by executing the following the PL/SQL statement.
exec dbms_cube.build('MY_CUBE');
You can now report on the initial values of sales and moving sales with the static model by issuing the following statement.
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2) from my_cube_view order by my_time asc; MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2) -------------------------------------------------------------------- L1_1 14 14 L2_1 12 12 L2_2 2 14 L3_1 1 1 L3_2 1 2 L3_3 10 11 L3_4 1 11 L3_5 1 2 8 rows selected.
To create a dynamic model where L1_2 = (L2_2' * 2) execute the following PL/SQL statement that calls a user-written OLAP DML program named SETUP_POST_MODEL.
exec dbms_aw.execute('call my_util_aw!setup_post_model');
As you can see from the definition of the user-written setup_post_model program shown below, the model is actually defined using the SET_INCLUDED_MODEL program and added using the ADD_CUBE_MODEL program, both of which are provided with the OLAP DML.
DEFINE SETUP_POST_MODEL PROGRAM
PROGRAM
VARIABLE _post_model text
VARIABLE _aw_dim text
VARIABLE _start_date text
VARIABLE _timespan text
VARIABLE _member text
_post_model = 'my_aw!my_post_model'
_aw_dim = OBJORG(DIM 'my_time')
_start_date = OBJORG(ATTRIBUTE 'my_time' 'start_date')
_timespan = OBJORG(ATTRIBUTE 'my_time' 'timespan')
_member = 'L1_0'
DEFINE &_post_model model
CONSIDER &_post_model
MODEL JOINLINES( -
JOINCHARS('dimension ' _aw_dim) -
JOINCHARS(_aw_dim '(\'' _member '\')=' _aw_dim '(\'L2_2\')*2') -
'end')
CALL SET_INCLUDED_MODEL('my_time', 'post_model', _post_model)
CALL ADD_CUBE_MODEL('my_cube', 'my_time', 'post_model', NO)
" Add _member to the dimension
CALL ADD_DIMENSION_MEMBER(_member, 'my_time', NA, 'L1', NA, NO)
CALL UPDATE_ATTRIBUTE_VALEU(_member, 'my_time', 'start_date', -
&_start_date(&_aw_dim 'L1_1')-365, NO)
CALL UPDATE_ATTRIBUTE_VALUE(_member, 'my_time', 'timespan', -
&_timespan(&_aw_dim 'L1_1'))
UPDATE
COMMIT
END
Execute the following statement to report on the new values of my_time, sales and moving_sales.
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2)
from my_cube_view
order by my_time asc;
MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2)
--------------------------------------------------------------------
L1_0 4 4
L1_1 14 18
L2_1 12 12
L2_2 2 14
L3_1 1 1
L3_2 1 2
L3_3 10 11
L3_4 1 11
L3_5 1 2
9 rows selected.
The FLOOR function returns the largest whole number equal to or less than a specified number.
Return Value
NUMBER
Syntax
FLOOR(n)
Parameters
A number.
Examples
Example 7-99 Displaying the Largest Integer Equal to or Less Than a Number
The following statements show results returned by the FLOOR function.
The following SHOW FLOOR statement produces the result that follows it.
SHOW FLOOR(15.7) 15
The following SHOW FLOOR statement produces the result that follows it.
SHOW FLOOR(4) 4
The following SHOW FLOOR statement produces the result that follows it.
SHOW FLOOR(-6.457) -7
The INSTAT function checks whether a dimension or dimension surrogate value is in the current status list or whether a dimension value is in a valueset.
Return Value
BOOLEAN
YES if the value is in the current status list or in a valueset and NO if it is not.
Syntax
INSTAT(dimension, value)
Parameters
The name of the dimension, dimension surrogate, or valueset.
The dimension or dimension surrogate value you want to test, either a text literal (enclosed in single quotes) or an expression that specifies the value. To specify the value of a conjoint dimension or a concat dimension, enclose the value in angle brackets. For a conjoint dimension, separate the base dimension values with a comma and space. For a concat dimension, separate the base dimension and its value with a colon and a space.
Usage Notes
Checking an Invalid Value
When you specify a dimension name and value in an INSTAT statement, Oracle OLAP tells you whether that value is in the current status list for that dimension. Conversely, the ISVALUE function tells you whether an item is a value of a dimension, regardless of whether it is in the status. INSTAT produces an error when value is not a dimension value, but ISVALUE simply returns a value of FALSE.
Examples
Example 7-123 Using INSTAT With a Valueset
Assume that within your analytic workspace you have a geog dimension with the following definition and values.
DEFINE geog TEXT DIMENSION GEOG -------------- Austria Belgium Canada
Assume, also, that you define a mygeogs valueset and identify a value for that valueset using the following statements.
DEFINE mygeogs VALUESET geog LIMIT mygeogs TO 'Belgium'
You cannot issue a REPORT on a valueset. If you attempt to, Oracle OLAP issues an error message.
REPORT mygeogs ORA-34104: INSTATTEST!MYGEOGS is not a type of object that contains data values.
However, you can use the INSTAT function to display which values of a dimension are in a valueset.
REPORT INSTAT (mygeogs, geog) GEOG INSTAT (MYGEOGS, GEOG) -------------- ------------------------ Austria no Belgium yes Canada no
Example 7-124 Checking Current Status
In the following example, a program accepts a value of the month dimension as an argument. The first lines of the program use INSTAT to check whether the dimension value that was passed as an argument is in the current status for month. When it is, the program calls a report program. When it is not, the program branches to its error-handling section.
ARGUMENT onemonth month IF INSTAT(month onemonth) THEN sales_report ELSE GOTO error ...
Example 7-125 Using INSTAT When the Dimension is a Conjoint Dimension
When the dimension that you specify is a conjoint dimension, then the entire value must be enclosed in single quotes. For example, suppose the analytic workspace has a region dimension and a product dimension. The region dimension values include East, Central, and West. The product dimension values include Tents, Canoes, and Racquets.
The following statements define a conjoint dimension, and add values to it.
DEFINE reg.prod DIMENSION <geography product> MAINTAIN reg.prod ADD <'East', 'Tents'> <'West', 'Canoes'>
To specify base positions, use a statement such as the following.
SHOW INSTAT(reg.prod '<1, 1>') YES
To specify base text values, use a statement such as the following.
SHOW INSTAT(reg.prod '<\'East\', \'Tents\'>') YES
Example 7-126 Using INSTAT When the Dimension is a Concat Dimension
When the dimension that you specify is a concat dimension, then you must enclose the entire <component dimension: dimension value> pair in single quotes. The following statement defines a concat dimension that has as its base dimensions region and product.
DEFINE reg.prod.ccdim DIMENSION CONCAT(region product)
A report of reg.prod.ccdim returns the following.
REG.PROD.CCDIM ---------------------- <region: East> <region: Central> <region: West> <product: Tents> <product: Canoes> <product: Racquets>
To specify a base dimension position, use a statement such as the following.
SHOW INSTAT(reg.prod.ccdim '<product: 3>') yes
To specify base dimension text values, use a statement such as the following.
SHOW INSTAT(reg.prod.ccdim '<product: Tents>') YES
The MODE function returns the mode (the most frequently occurring value) of a numeric expression. When there are no duplicate values in the data, then MODE returns NA.
Return Value
DECIMAL
Syntax
MODE(expression [CACHE} [dimensions])
Parameters
The numeric expression whose mode is to be calculated.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The dimensions of the result. When you do not specify any dimensions, MODE calculates the mode over all the dimensions of expression and it returns a single value. When you specify one or more dimensions (but fewer than all of the dimensions of expression) in the dimension argument, then MODE calculates the mode for each value of the dimensions that you specified and returns an array of values. Each dimension must be a dimension of expression.
Usage Notes
The Effect of NASKIP on MODE
MODE is not affected by the NASKIP option.
More Than One Set of Duplicate Values
When multiple values qualify as having the greatest number of occurrences in the expression, then MODE sorts the values and returns the lowest one. For example, for the data series {4,5,2,3,7,4,6,2,1}, the mode for the series is 2 even though 2 and 4 both occur twice.
Examples
Example 8-27 Reporting the Mode
These examples use the following geography and items dimensions and sales2 variable.
DEFINE geography DIMENSION TEXT MAINTAIN geography ADD 'g1' 'g2' 'g3' DEFINE items DIMENSION TEXT MAINTAIN items ADD 'Item1' 'Item2' 'Item3' 'Item4' 'Item5' DEFINE sales2 DECIMAL <geography items>
Assume the sales2 variable has the following data values.
-------------SALES2-------------
-----------GEOGRAPHY------------
ITEMS G1 G2 G3
-------------- ---------- ---------- ----------
Item1 30.00 15.00 12.00
Item2 10.00 20.00 18.00
Item3 15.00 20.00 24.00
Item4 30.00 25.00 25.00
Item5 NA 7.00 21.00
This statement reports the mode that is calculated over the geography dimension.
REPORT W 22 MODE(sales2, geography)
The preceding statement produces the following output.
MODE(SALES2,
GEOGRAPHY GEOGRAPHY)
-------------- ----------------------
g1 30.00
g2 20.00
g3 NA
This statement reports the mode that is calculated over the items dimension.
REPORT W 18 MODE(sales2, items)
The preceding statement produces the following output.
MODE(SALES2,
ITEMS ITEMS)
-------------- ------------------
Item1 NA
Item2 NA
Item3 NA
Item4 25.00
ITEM5 NA
This statement reports the mode that is calculated over all of the dimensions of the sales2 variable.
REPORT MODE(sales2)
The preceding statement produces the following output.
Mode ---- 15
Specifies the default aggmap for a variable.
|
Note: You can also use an $AGGMAP property to specify the default aggregation specification for a variable or the $ALLOCMAP property to specify the default allocation specification for a variable. |
Syntax
AGGMAP SET aggmap AS DEFAULT FOR variables
Parameters
The name of a previously defined aggmap object.
A text expression that is the name of one or more variables for which the specified aggmap is the default aggmap. When you specify a literal value, separate the names of the variables with commas.
Examples
Example 9-26 Using AGGMAP SET to Specify a Default Aggmap
Example 4-3, "Using the $AGGREGATE_FROM Property" illustrates how the AGGREGATE command shown in Example 9-13, "Using a CACHE Statement in an Aggregation Specification" can be simplified to the following statement.
AGGREGATE sales_by_revenue USING revenue_aggmap
You can further simplify the AGGREGATE command if you make revenue_aggmap the default aggmap for the sales_by_revenue variable. You can do this either by defining an $AGGMAP property on the sales_by_revenue variable or by issuing the following statement.
AGGMAP SET revuienue_aggmap AS DEFAULT FOR sales_by_revenue
Now you can aggregate the data by issuing the following AGGREGATE command that does not include a USING clause.
AGGREGATE sales_by_revenue
The NLS_TERRITORY option specifies current territory for the session.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_TERITORRY = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS database parameters.
Examples
Example 5-79 Effects of Changing NLS_TERRITORY
In this example, the NLS_LANG option is initially set to:
AMERICAN_AMERICA.WE8ISO8859P1
The thousands marker is a comma (,), and the decimal marker is a period (.).
SHOW TO_NUMBER('12345')
12,345.00
A change to the territory setting:
NLS_TERRITORY = 'FRANCE'
changes the value of NLS_LANG to
AMERICAN_FRANCE.WE8ISO8859P1
The thousands marker is now a period (.), and the decimal marker is a comma (,).
SHOW TO_NUMBER('12345')
12.345,00
The NLS_CALENDAR option specifies the calendar for the session.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_CALENDAR = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
Examples
Within an OLAP DML program, the SLEEP command suspends the program execution for at least the specified number of seconds.
|
Note: SLEEP is rarely used in Oracle OLAP programs, because there is seldom a need to suspend program execution. |
Syntax
SLEEP n
Parameters
A numeric expression that specifies the number of seconds for Oracle OLAP to "sleep." Program execution is suspended for at least this number of seconds.
Examples
The IRR function computes the internal rate of return associated with a series of cash flow values. Each value of the result is calculated to be the discount rate for each period that makes the net present value of the corresponding cash flows equal to zero.
Return Value
DECIMAL (For example, n 8.25 percent internal rate of return produces a result value of .0825.)
The result returned by the IRR function is dimensioned by all the dimensions of cashflows except its time dimension. When cashflows is dimensioned only by the time dimension, IRR returns a single value.
Syntax
IRR(cashflows, [time-dimension])
Parameters
A numeric expression dimensioned by time-dimension, that specifies the series of cash flow values.
|
Note: All the cash flows used to compute a result value are assumed to occur at the same relative point within the period with which they are associated. Cash flows that corresponds to out-of-status dimension positions are ignored |
A name that specifies the time dimension. When cashflows has a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional since IRR automatically uses the DAY, WEEK, MONTH, QUARTER, or YEAR dimension of cashflows when you do not specify a value for time-dimension.
Usage Notes
Multiple Discount Rates
Some series of cash flows have multiple discount rates, which make the net present value equal to zero. In such cases, IRR finds and returns only one of these discount rates as the internal rate of return. When there is only a single solution and it is between -99.9 percent and 10,000 percent, the IRR function finds it. When IRR cannot calculate an internal rate of return, the corresponding value in the result is NA.
Examples
Example 7-131 Calculating the Internal Rate of Return
The following statements create a dimension called project, add values to it, and create a variable called cflow, which is dimensioned by year and project.
DEFINE project DIMENSION TEXT MAINTAIN project ADD 'a' 'b' 'c' 'd' 'e' DEFINE cflow VARIABLE DECIMAL <project year>
Once you have assigned the following values to CFLOW,
------------------------CFLOW----------------------
-----------------------PROJECT---------------------
YEAR a b c d e
-------------- ---------- ---------- ---------- ---------- -------
Yr95 -200.00 -200.00 -300.00 -100.00 -200.00
Yr96 100.00 150.00 200.00 25.00 25.00
Yr97 100.00 400.00 200.00 100.00 200.00
then the following statement
REPORT IRR(cflow, year)
produces the following report of the internal rate of return.
IRR(CFLOW,
PROJECT YEAR)
-------------- ----------
a 0.00
b 0.84
c 0.22
d 0.13
E 0.06
The CHARLIST function transforms an expression into a multiline text value with a separate line for each value of the original expression.
Return Value
NTEXT when the expression is NTEXT; otherwise, TEXT.
Syntax
CHARLIST(expression [dimensions])
Parameters
The expression to be transformed into a multiline text value. When the expression has a data type other than TEXT or NTEXT, CHARLIST automatically converts the expression to TEXT.
The dimensions of the return value. When you do not specify a dimension, CHARLIST returns a single value. When you provide one or more dimensions for the return value, CHARLIST returns a multiline text value for each value in the current status list of the specified dimension. Each dimension must be an actual dimension of the expression; it cannot be a related or base dimension.
Examples
Example 7-41 Deleting Workspace Objects
You can use CHARLIST with the NAME dimension to create lists of workspace objects. Suppose you want to delete all objects of a certain type in your workspace, for example, all worksheets. You can use CHARLIST and an ampersand (&) to do this.
LIMIT NAME TO OBJ(TYPE) EQ 'WORKSHEET' DELETE &CHARLIST(NAME)
Example 7-42 Creating a List of Top Sales People
Assume you have stored the names of the sales people who sold the most for each product in product.memo, a text variable with the dimensions of product and . You then want to create a list of top sales people broken out by product. To do this, you can created a variable dimensioned by product and then use CHARLIST with the product to create a separate list of all of the top sales people for each product.
DEFINE topsales VARIABLE TEXT <product> topsales = CHARLIST(product.memo product)
For a given expression, the WIDTH_BUCKET function returns the bucket number into which the value of this expression would fall after being evaluated.
Return Value
An INTEGER.
Syntax
WIDTH_BUCKET (expr , min_value , max_value , num_buckets)
Parameters
The expression for which the histogram is being created. This expression must evaluate to a number or a datetime value. When expr evaluates to NA, then the expression returns NA.
An expression that resolves to the minimum end point of the acceptable range for expr. This expression must evaluate to number or datetime values, and cannot evaluate to NA.
An expression that resolves to the maximum end point of the acceptable range for expr. This expression must evaluate to number or datetime values, and cannot evaluate to NA.
An expression that resolves to a constant indicating the number of buckets. This expression must evaluate to a positive INTEGER.
Usage Notes
Underflow and Overflow Buckets
WIDTH_BUCKET also creates (when needed) an underflow bucket numbered 0 and an overflow bucket numbered num_buckets+1. These buckets handle values less than min_value and more than max_value and are helpful in checking the reasonableness of endpoints.
Constructing Equiwidth Histograms
WIDTH_BUCKET lets you construct equiwidth histograms, in which the histogram range is divided into intervals that have identical size. (Compare this function with NTILE, which creates equiheight histograms.) Ideally each bucket is a "closed-open" interval of the real number line. For example, a bucket can be assigned to cores between 10.00 and 19.999... to indicate that 10 is included in the interval and 20 is excluded. A bucket of this size is sometimes denoted as (10, 20).
Examples
Example 8-168 Grouping Values Into a Ten-Bucket Histogram
The following example limits the customers to those customers who have a customer_id of 825 through 853 and, then, creates a ten-bucket histogram on the credit_limit variable for those customer. It uses the credit_group formula to calculate the bucket number for each customer. Customers with credit limits greater than the maximum value are assigned to the overflow bucket, 11.
DESCRIBE
DEFINE customer_id DIMENSION INTEGER
DEFINE cust_last_name VARIABLE TEXT <customer_id>
DEFINE credit_limit VARIABLE INTEGER <customer_id>
DEFINE credit_group FORMULA INTEGER <customer_id>
EQ WIDTH_BUCKET(credit_limit, 100, 5000, 10)
LIMIT customer_id to 825 TO 853
REPORT cust_last_name, credit_limit, credit_group
CUSTOMER_ID CUST_LAST_NAME CREDIT_LIMIT CREDIT_GROUP
-------------- ---------------- ---------------- ----------------
825 Dreyfuss 500 1
826 Barkin 500 1
827 Siegel 500 1
828 Minnelli 2,300 5
829 Hunter 2,300 5
830 Dutt 3,500 7
831 Bel Geddes 3,500 7
832 Spacek 3,500 7
833 Moranis 3,500 7
834 Idle 3,500 7
835 Eastwood 1,200 3
836 Berenger 1,200 3
837 Stanton 1,200 3
838 Nicholson 3,500 7
839 Johnson 3,500 7
840 Elliott 1,400 3
841 Boyer 1,400 3
842 Stern 1,400 3
843 Oates 700 2
844 Julius 700 2
845 Fawcett 5,000 11
846 Brando 5,000 11
847 Streep 5,000 11
848 Olmos 1,800 4
849 Kaurusmdki 1,800 4
850 Finney 2,300 5
851 Brown 2,300 5
852 Tanner 2,300 5
853 Palin 400 1
The TO_BINARY_FLOAT function converts a text or numeric expression to a SHORTDECIMAL numeric expression.
Return Value
SHORTDECIMAL
Syntax
TO_BINARY_FLOAT(expr [, fmt [, nlsparam ] ])
Parameters
A text or a numeric expression. When expr is a text expression, the function converts the following case-insensitive values to particular values:
INF to positive infinity
-INF to negative infinity
NaN to NaN (not a number)
A text expression that specifies a number format model. This argument is valid only when expr is a text expression.
The default number format model uses the decimal and thousands group markers identified by NLS_NUMERIC_CHARACTERS.
|
Note: You cannot use a floating-point number format element (F, f, D, or d) in a text expression. |
A text expression that specifies how the function uses the thousands group marker, decimal marker, and currency symbols when converting a text expression. This argument is valid only when expr is a text expression. This expression contains one or more of the following parameters, separated by commas:
NLS_CURRENCY symbol
NLS_ISO_CURRENCY territory
NLS_NUMERIC_CHARACTERS dg
The $ALLOCMAP property specifies the default aggmap for allocation for a variable which is the aggmap that Oracle OLAP uses when the variable is the target variable of an ALLOCATE statement that does not include a USING phrase.
Syntax
You add or delete an $ALLOCMAP property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$ALLOCMAP' aggmap-name
To delete the property, issue the following statement.
PROPERTY DELETE '$AALLOCMAP'
Parameters
A TEXT expression that specifies the name of a previously defined ALLOCMAP type aggmap object.
Examples
Example 4-5 Using $ALLOCMAP to Specify a Default Allocation Specification
Example 9-35, "Recursive Even Allocation with a Lock" uses the following statement to allocated data in the projbudget variable using the projbudgmap allocation specification.
ALLOCATE projbudget USING projbudgmap
You can specify that projbudgmap is the default allocation specification for the projbudget variable by issuing the following statements.
CONSIDER projbudget PROPERTY '$ALLOCMAP' "projbugmap'
Now, by issuing the following statement, you can allocate data in the projbudget variable using the projbudgmap allocation specification.
ALLOCATE projbudget
The TRACKPRG command tracks the performance cost of every program that runs while you have tracking turned on. To get meaningful information from TRACKPRG, your session must be the only one running in Oracle OLAP. Furthermore, the accuracy of the results of TRACKPRG decreases as more processes are started on the host computer.
You turn TRACKPRG on, run the programs you want to track, and use TRACKPRG again to obtain the results. Each time each program is executed, TRACKPRG stores its cost data as one entry in its tracking list. When you execute another program, a new entry is added to the list, which is maintained in Oracle OLAP memory (free storage).
A program or line of code is considered to have a high performance cost when it takes a long time to execute. Use TRACKPRG to identify programs that have relatively high costs and then use a MONITOR statement to identify the time-consuming lines within those programs. When you want, you can use both commands simultaneously.
Syntax
TRACKPRG {ON|OFF|file|INIT}
where file has the following syntax:
Parameters
Starts looking for programs to be run so it can gather their timing data in a tracking list. (Continues the current tracking process without interruption when tracking is already on, or resumes with a gap when tracking is off.)
Stops tracking programs and freezes any timing data currently in the tracking list which allows you to send the list to the current outfile or to a text file either immediately, or later in your session.
Specifies where to send the tracking list. TRACKPRG FILE has no effect on the tracking list, so you can send the same list repeatedly to different destinations.
Specifies that Oracle OLAP adds the tracking list to the contents of the file indicated by file-name instead of replacing it.
A text expression to which Oracle OLAP sends the data. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
When you omit file-name, Oracle OLAP sends the timing data currently in the tracking list to the current outfile
Discards the timing data in the current tracking list and releases the Oracle OLAP memory that was used for that list (useful when you want the memory for other purposes). Also, when tracking is on, resumes waiting for you to run programs so it can gather their data into a completely new tracking list.
Usage Notes
Single Execution
Each entry (that is, line) in the tracking list focuses on a single execution of a single program.
Depth of the Call
Each entry records the depth of the call, if any, to the current program; that is, how many program calls it has taken to get to the program reported on the current line. In TRACKPRG output, the depth of the call is indicated by the indentation of the program name. For each indented program, TRACKPRG also records the name of the program that called it at the end of the entry.
Types of Timing Data
In each entry, TRACKPRG records two types of timing data:
Exclusive cost -- The time spent in this program, excluding the time spent on any programs that are called by this one.
Inclusive cost -- The time spent in this program, including the time spent on any programs that are called by this one.
This gives you the option of generating a report on both types of cost.
Entry Sections
In TRACKPRG output, each entry (line) is divided into the following four sections:
Program name, in character columns 1 through 38
Exclusive time, in columns 39 through 49
Inclusive time, in columns 50 through 60
Name of calling program, in columns 61 through 77
Here is a sample of TRACKPRG output (for the MAIN program) with column numbers included for reference.
1234567890123456789012345678901234567890123456789012345678901234567890
MAIN 39.6198425 225.551453
COMM 43.793808 185.93161 MAIN
_C.SYS.INFO .112533569 .112533569 COMM
_C.SYS.INFO .087173462 .087173462 COMM
_C.MAIN 61.414505 141.938095 COMM
_C.CON 66.7147064 80.5235901 _C.MAIN
_C.SYS.DORETURN .032287598 .032287598 _C.CON
TRACKREPORT Program
When you want to use Oracle OLAP reporting capabilities to produce a report from the timing data in the text file that is created by TRACKPRG, you can use the TRACKREPORT program. It has the following syntax.
TRACKREPORT textfile-name
The textfile-name argument is the file name of the text file created by TRACKPRG from which you want to generate a report. TRACKREPORT uses a FILEREAD statement to read the data into an Oracle OLAP variable, and then it uses Oracle OLAP reporting capabilities to produce a report like the following sample.
Exclusive Inclusive Number of
Program name cost cost calls
____________________ __________ __________ __________
COMM 43.793808 185.93161 1
MAIN 39.6198425 225.551453 1
_C.CON 66.7147064 80.5235901 1
_C.ENV.PUTOPTS 1.15296936 1.15296936 1
_C.ENV.XLATEIN 6.32765198 6.32765198 1
_C.MAIN 61.414505 141.938095 1
_C.SYS.DORETURN .032287598 .032287598 1
_C.SYS.INFO .289932251 .289932251 3
_C.SYS.NOF10 .038269043 .038269043 1
_CONNECT 5.3609314 6.16748047 1
_CONNNONE .806549072 .806549072 1
When you want to further process the data from a TRACKPRG file, you can write your own program using the TRACKREPORT program as a model.
Excluded Subprograms
When you do not want separate performance data on all the subprograms called by the program you are timing, you can, within the overall program, turn tracking off before calling any subprograms you want to exclude and then turn it back on before calling any you want to include. You can do this repeatedly. Remember, however, that the time taken by any excluded subprograms is assigned to the total "exclusive" time for the overall program and to its "inclusive" time, since TRACKPRG has not individually tracked the excluded subprograms.
Using TRACKPRG with Very Small Programs
You might not be able to reproduce the results exactly for very small programs. When the CPU interrupts processing to do other tasks, that time is a greater percentage of the total execution time.
Unit of Measure for TRACKPRG
The MONITOR and TRACKPRG commands use milliseconds as the unit for recording execution time. The execution time does not include time spent on I/O and time spent waiting for the next statement.
Examples
Example 10-154 Collecting Timing Data USING TRCKPRG
In this example, timing data on the mybjt program and all the programs it calls is collected in a file called mybjttim.dat.
TRACKPRG ON mybjt TRACKPRG OFF TRACKPRG FILE mybjttim.dat TRACKPRG INIT TRACKREPORT mybjttim.dat
Example 10-155 Using the INIT Keyword and TRACKREPORT
In this example, tracking is turned on to collect timing data about the execution of prog1 and the data is sent to a file named prog1.trk. Then, the INIT keyword is used to discard the existing tracking list so the data for a second program can be collected and sent to a file. Throughout the procedure, tracking remains on. Finally, after tracking is turned off and the INIT keyword is used to release the memory that was used for the tracking list, the TRACKREPORT program is called to produce two reports generated from the data stored in the two files.
TRACKPRG ON prog1 TRACKPRG FILE prog1.trk TRACKPRG INIT prog2 TRACKPRG FILE prog2.trk TRACKPRG OFF TRACKPRG INIT TRACKREPORT prog1.trk TRACKREPORT prog2.trk
The DEFINE command adds a new object to the analytic workspace. This entry describes the DEFINE command in general. The following entries discuss the use of the DEFINE command for creating specific types of object:
Syntax
DEFINE name object-type attributes [AW workspace] [SESSION]
Parameters
A TEXT expression that is the name for the new object. Follow these guidelines when specifying a value for name:
The name must consist of 1 to 64 characters. When you are using a multibyte character set, you can still specify 64 characters even when this requires more than 64 bytes. Each character may be a letter (A-Z), a number (0-9), an underline (_), or a dot (.). However, the following restrictions apply to the use of these characters:
The name cannot consist of a single dot (.) character or a single underscore (_) character.
The name cannot duplicate a reserved word. For more information on identifying reserved words, see the RESERVED function.
The first character in the name cannot be a number.
The first character cannot be a dot (.) when the second character is a number.
By default Oracle OLAP creates the definition in the current workspace. To create the definition in a different attached workspace, you can specify a qualified object name for name or you can use the AW argument to specify the workspace. Do not use both.
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Caution: Oracle OLAP does not warn you when you create an object that has the same name as an existing object in another attached workspace. |
The type of object being defined. The default is VARIABLE. The object types are discussed in the subsections for the DEFINE command.
Attributes are different for each type of object. The attributes are listed in the entry for each object type.
The name of an attached workspace in which you want to define the object. You can also specify a noncurrent attached workspace using a qualified object name for name. Do not use this phrase when qualified object name for name.
Specifies that the object exists only in the current session. The object is created in the EXPRESS analytic workspace to which you have read-only access. When you close the current session, the object no longer exists.
Usage Notes
Triggering Program Execution When DEFINE Executes
Using a TRIGGER_DEFINE program, you can make the DEFINE command an event that automatically executes an OLAP DML program. See "Trigger Programs" for more information.
Effect of DEFINE on the Status of the NAME Dimension
When you execute a DEFINE command with the NAME dimension limited to less than all its values, the status of NAME is automatically limited to ALL.
Viewing Session Objects
Objects created with the SESSION keyword are stored in the analytic workspace named EXPRESS instead of the current analytic workspace. Therefore, statements that operate against the current analytic workspace (such as LISTNAMES) do not list session objects unless you do one of the following:
Specify the EXPRESS analytic workspace in the statement (such as LISTNAMES AW EXPRESS)
Make the EXPRESS analytic workspace the current analytic workspace by issuing an AW ATTACH EXPRESS statement.
The DEFINE command with the AGGMAP keyword adds a new aggmap object to an analytic workspace. An aggmap object is a specification for how Oracle OLAP allocates or aggregates variable data.
Defining an aggmap merely creates an aggmap object in the analytic workspace; it does not define the calculation specification. The aggmap specification can either specify how to aggregate or how to allocate data:
For information on coding an aggregation specification, see the AGGMAP command.
For information on coding an allocation specification, see the ALLOCMAP command.
Syntax
DEFINE aggname AGGMAP [<dims...>][AW workspace][SESSION]
Parameters
The name of the object that you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining an aggmap.
(Optional; retained for compatibility with earlier software versions.) When defining an aggmap object for aggregation (that is, an AGGMAP-type aggmap), the names of the dimensions. You cannot specify a conjoint dimension as a base dimension in the definition or specification for the aggmap.
The name of an attached workspace in which you want to define the object. For more about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. For more information about this argument, see the main entry for the DEFINE command.
Examples
Example 9-78 Creating an Aggmap for Aggregation
Suppose you define a sales variable with the following statement.
DEFINE sales VARIABLE <time, product, geography>
Assume also that you have defined an aggmap named sales.agg with the following definition and specification.
DEFINE sales.agg AGGMAP <time, product, geography> AGGMAP RELATION time.r PRECOMPUTE (time NE 'Year99') RELATION product.r PRECOMPUTE (product NE 'All') RELATION geography.r CACHE STORE END
The sales.agg aggregation specification contains the preceding three RELATION statements and a CACHE statements. In this example, you are specifying that all of the data for the time.r hierarchy of the time dimension should be aggregated, except for any data that has a time dimension value of Year99. All of the data for the product.r hierarchy of the product dimension should be aggregated, except for any data that has the product dimension value of ALL. (In this example, the product dimension has a dimension value named ALL that represents all products in the hierarchy.) All geography dimension values are aggregated. The CACHE STORE statement specifies that any data that is rolled up on the fly should be calculated just once and stored in the cache for other access requests during t he same session.
Note that users should not have write access to the analytic workspace when CACHE STORE is set, because the data calculated during the session may be saved inadvertently.
In this example, any data value that dimensioned by a Year99 time value or an ALL product dimension value is calculated on the fly.
You can now use the sales.agg aggmap with an AGGREGATE command, such as the following.
AGGREGATE sales USING sales.agg
Example 9-79 Creating an Aggmap for Allocation
Suppose you have a sales variable that you defined with the following statement.
DEFINE sales VARIABLE <time, product, geography>
To allocate data from a source to cells in the sales variable that are specified by the time and product dimension hierarchies, you have created an ASCII disk file called salesalloc.txt, which contains the following aggmap definition and specification.
DEFINE sales.alloc AGGMAP ALLOCMAP RELATION time.r OPERATOR EVEN RELATION product.r operator EVEN NAOPERATOR HEVEN SOURCEVAL ZERO CHILDLOCK DETECT END
To include the sales.alloc aggmap in your workspace, execute the following statement.
INFILE 'salesalloc.txt'
The sales.alloc aggmap is now defined, and it contains the preceding two RELATION statements, the SOURCEVAL statement and the CHILDLOCK statement. You end the entry of statements into the aggmap with the END statement. In this example, you are specifying that the first allocation of source values occurs down the time dimension hierarchy and that the source value is divided evenly between the target cells at each level of the allocation. The second allocation occurs down the product dimension hierarchy, with the source value again divided evenly between the target cells at each level of the allocation, and when the allocation encounters a deadlock, the source values is divided evenly between the target cells of the hierarchy including cells that have a basis value of NA. With the SOURCEVAL statement you specify that after the allocation, ALLOCATE sets the value of each source cell to zero. With the CHILDLOCK statement you specify that ALLOCATE detects the existence of locks on both a parent and a child element of a dimension hierarchy.
You can now use the sales.alloc aggmap with an ALLOCATE command, such as the following.
ALLOCATE sales USING sales.alloc
The preceding statement does not specify a basis or a target object so ALLOCATE uses the sales variable as the source, the basis, and the target of the allocation.
The DEFINE command with the COMPOSITE keyword adds a new named composite to an analytic workspace. Conceptually, you can think of a composite consisting of two structures:
The composite object itself. The composite contains the dimension-value combinations (that is, a composite tuples) that Oracle OLAP uses to determine the structure of any variables dimensioned by the composite.
An index between the composite values and its base dimension values.
For a variable that is dimensioned by composite, Oracle OLAP creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; it does not create a cell for every value in the base dimensions. Data for the variable is stored in order, cell by cell, for each tuple in the composite. From the perspective of data storage, each combination of base dimension values in a composite is treated like the value of a regular dimension. Consequently, when you define a variable with one regular dimension and one composite, the data for the variable is stored as though it was a two-dimensional variable. Using composites to reduce the number of elements created for a variable results in more efficient data storage.
Syntax
DEFINE name COMPOSITE <dims...> [AW workspace] [index-algorithm] [SESSION]
where index-algorithm specifies the algorithm that Oracle OLAP uses to create an index that relates the composite values to its base dimension values. When you omit this optional argument, Oracle OLAP uses the value specified by the SPARSEINDEX option. Valid values for index-algorithm are:
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a named composite.
The names of two or more dimensions that you want to be the base dimensions of the composite. When you specify COMPRESSED as the value of index-algorithm, at least one dimension must be a hierarchal dimension.
The order of the dimensions in dims varies by the value you specify for index-algorithm:
For b-tree or hash composites, specify the dimensions in fastest to slowest-varying order as discussed in "Effect of Dimension Order on Variable Storage and Statement Looping".
For compressed composites, it does not matter in which order you specify the dimensions. Oracle OLAP selects the order in which to store the values unless you override this optimization by specifying FORCEORDER in an AGGREGATE command or AGGREGATE function. To see the optimized order chosen by Oracle OLAP, view the POUTFILELOG.
You must define all the dimensions and named composites used in the list before defining the composite. DEFINE automatically creates any unnamed composites in the list for you.
The name of an attached workspace in which you want to define the object. For more information about this argument, see the main entry for the DEFINE command.
Specifies the creation of a b-tree index to relate composite values to base dimension values. BTREE is the standard indexing method for composites. For a variable that is dimensioned by a BTREE composite, Oracle OLAP creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; it does not create a cell for every value in the base dimensions.
Specifies the creation of a highly-scalable b-tree index to relate composite values to base dimension values. For a variable that is dimensioned by a BTREE64 composite, like a BTREE composite, Oracle OLAP creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; it does not create a cell for every value in the base dimensions. However, unlike a BTREE composite, a BTREE64 composite supports b-trees greater than 2 gigabytes.
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Note: Typically, you define a BTREE64 composite when you want to use it to dimension a variable which you populate from a relational table that is larger than 2 gigabytes. |
Specifies the creation of a compressed index to relate composite values to base dimension values. You specify COMPRESSED only when you want to create a composite for a variable that has at least one hierarchical dimension is specified in dims and that is aggregated.
A compressed composite contains one composite tuple for each set of base dimension values that identifies non-NA detail data in the variables that use it. Additionally, for variables dimensioned by compressed composite Oracle OLAP reduces redundancy in the variable, composite, and composite index by creating a physical position in the composite only for those tuples that represent a parent with multiple descendants. Oracle OLAP then creates an index between this composite structure and the base dimensions and uses this composite structure as the dimension of the variable. Since the actual structure of a compressed composite is smaller than that of a b-tree or hash composite, a variable dimensioned by a compressed composite is also smaller than a variable dimensioned by a b-tree or hash composite. Also, since the index for a compressed composite only has nodes for parents with multiple descendants, the index of a compressed composite has fewer levels and is smaller than the index of a b-tree composite. Although performance varies depending on the depth of the hierarchies and the order of the dimensions in the composite, aggregating variables defined with compressed composites is typically much faster than aggregating variables defined with b-tree or hash composites.
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Note: Oracle OLAP compresses the data in variables dimensioned by compressed composites using the "intelligence" of the AGGREGATE command or AGGREGATE function. Consequently, there are special considerations that apply when aggregating a variable dimensioned by one or more compressed composites. See "Aggregating Variables Dimensioned by Compressed Composites" for more information. |
Specifies the creation of a hash index to relate composite values to base dimension values. HASH is rarely used and, then, typically, only when the composite has two or three dimensions. For a variable that is dimensioned by a b-tree or hash composite, Oracle OLAP creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; it does not create a cell for every value in the base dimensions.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
Shared Composites
You can use the same b-tree or hash composite to dimension several variables. (Compressed composites cannot be shared in this manner.) The actual sparsity of a variable dimensioned by a b-tree or hash composite varies depending on whether or not the composite is an unshared composite or a shared composite:
An unshared composite is a composite that is used to dimension only one variable. All types of composites (that is, b-tree, hash, and compressed composites) can be unshared composites. An unshared composite is populated only when the variable that uses it is populated. Consequently, an unshared composite perfectly reflects the sparsity of the variable that it is used to dimension. It only has the dimension value combinations for each non-NA value in that variable.
A shared composite is a composite that is used to dimension multiple variables. A shared composite can be either a b-tree or hash composite; it cannot be a compressed composite. A shared composite is populated when any of the variables that use it are populated. A shared composite has all of the dimension value combinations for non-NA values for all of the variables that it dimensions. A shared composite reflects the sparsity of all of the variable that it is used to dimension. Typically, therefore, variables dimensioned by shared composites are not perfectly sparse variables.
When the size of variables is important, or when you have variables that are sparse along the same dimensions but with significantly different patterns of sparsity, define different composites for the different variables.
Examples
This section contains a simple example of creating a named b-tree composite. For examples of using composites to dimension variables, see Example 9-99, "Defining a Variable Dimensioned by an Uncompressed Composite" and Example 9-100, "Defining a Variable Dimensioned by a Compressed Composite".
Example 9-80 Creating a Named b-Tree Composite
Assume that the value of SPARSEINDEX is BTREE. The following statements define two objects: a named composite that has a b-tree index and base dimensions of market and a variable called expenses that is dimensioned by the month dimension and the market.product composite.
DEFINE market.product COMPOSITE <market product> DEFINE expenses DECIMAL <month market.product <market product>>
The DEFINE command with the DIMENSION keyword adds a new dimension object to an analytic workspace. A dimension is a list of values that provides an index to the data.
Because the syntax of the DEFINE DIMENSION command is different depending on the type of the dimension that you are defining, four separate entries are provided:
DEFINE DIMENSION (simple) for defining a dimension with unique values of the same data type.
DEFINE DIMENSION (DWMQY) for defining a non-hierarchical dimension whose values represent a time period (day, week, month, quarter, or year).
DEFINE DIMENSION (conjoint) for defining a dimension over two or more other base dimensions when the base dimensions do not contain duplicate values or have different data types and when you want to explicitly specify the dimension value combinations.
DEFINE DIMENSION CONCAT for defining a dimension over two or more other base dimension when the base dimensions contain duplicate values or different data types or when you want Oracle OLAP to automatically populate the dimension value combinations.
DEFINE DIMENSION ALIASOF for defining an alias for a simple dimension.
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Note: Defining a dimension in the analytic workspace merely adds the definition of the dimension to the analytic workspace; it does not populate the dimension. To populate dimensions using the OLAP DML, you can issue OLAP DML SQL, FILEREAD, or MAINTAIN statements. |
The DEFINE DIMENSION (simple) command defines a simple dimension. When a variable is dimensioned by regular dimensions, Oracle OLAP creates an array element for each set of its dimension values. The values of a simple dimension must be unique data values with the same data type. A simple dimension can be a flat dimension or a hierarchical dimension that contains values from different levels of a hierarchy.
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Tip: To create a hierarchical dimension using duplicate values or values of different data types, use a concat dimension as described in DEFINE DIMENSION CONCAT. |
Syntax
DEFINE name DIMENSION type [TEMP] [AW workspace] [SESSION]
where type is the data type of the dimension. The syntax of type varies depending on the data type:
TIMESTAMP [( truncation-code )]TIMESTAMP_TZ [( truncation-code )]TIMESTAMP_LTZ [( truncation-code )]Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a dimension.
Specifies that the values of the dimension have the TEXT data type which is equivalent to the CHAR and VARCHAR2 data types in Oracle Database. This data type stores up to 4,000 bytes for each line in the database character set.
Specifies that the values of the dimension have the NTEXT data type which is equivalent to the NCHAR and NVARCHAR2 data types in the Oracle Database. This data type stores up to 4,000 bytes for each line in UTF-8 character encoding.
Specifies a special text data type that stores up to 8 single-byte characters for each line in the database character set.
For TEXT or NTEXT dimensions, the width, in bytes, of the storage area of each value of an object. Valid width values are 1 th rough 4000. Specify a fixed width only when you are certain that the values of a particular dimension are of similar size. When a value exceeds the specified width, it is truncated.
Specifies that the values of the dimension have the INTEGER data type. The data type for a dimension with values that are identified by their numeric position (1, 2, and so on). A data type of INTEGER means that the dimension has no character values. For ease of use, use a text or time period data type, when possible.
Specifies that the values of the dimension have the NUMBER data type. A NUMBER dimension differs from other dimensions in that its values cannot be specified by position, only by value. To specify the values of a NUMBER dimension by position, you can define an INTEGER type dimension surrogate for the NUMBER dimension.
The total number of digits a value of type NUMBER can have.
The number of digits a value of type NUMBER can have to the right of a decimal point. For example, when you specify a precision of 7 and a scale of 2, then the highest value that the dimension can have is 99999.99. When you specify a precision value, but do not specify a scale value, then the scale is 0.
Specifies that the values of the dimension have the DATETIME data type.
Specifies that the values of the dimension have the TIMESTAMP data type.
Specifies that the values of the dimension have the TIMESTAMP_TZ data type.
Specifies that the values of the dimension have the TIMESTAMP_LTZ data type.
A text expression that specifies a format model shown in Table 8-13, "Datetime Format Templates for the ROUND and TRUNC Date Functions". A format model indicates how the date and time number should be truncated.
Indicates that the dimension's values are only temporary and only for the current session. The dimension has a definition in the current workspace and can contain values during the current session. However, when you update and commit, only the definition of the dimension is saved. When you leave end your session or switch to another workspace, the data values are discarded. Each time you start the workspace, the values of a temporary dimension are NA.
The name of an attached analytic workspace in which you want to define the dimension. Any objects dimensioned by the dimension must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
NA Values in Variables Dimensioned by Simple Dimensions
When a variable is dimensioned by regular dimensions, Oracle OLAP creates an array element for each set of its dimension values. When an array element is empty, then the element is said to contain an NA value. In some cases, this can result in a sparse variable—that is, a variable in which a relatively high percentage of array elements that are empty. There are two types of sparsity:
Controlled sparsity occurs when a range of one or more dimensions has no data; for example, a new variable dimensioned by month for which you do not have data for past months.
Random sparsity occurs when some combinations of dimension values never have any data. For example, a district might only sell certain products and never have data for other products. Other districts might sell some of those products and other ones, too.
When a sequence of array elements contain enough NA values to fill up an analytic workspace page, Oracle OLAP does not actually store any of the NA values and, instead, keeps tracks of the values internally. However, when an analytic workspace page contains both regular values and NA values, then Oracle OLAP stores all of the values. You can reduce the number of array elements with NA values by dimensioning a variable with one or more composites or conjoint dimensions. See the DEFINE COMPOSITE and DEFINE DIMENSION (conjoint) commands.
Examples
Example 9-81 Defining a Simple Dimension
This example adds the dimension city to an analytic workspace. You can attach a description to the object immediately after defining it. (You can also add the description later when you use CONSIDER and LD statements.) After defining the dimension city, you can give it values with a MAINTAIN statement.
The statements
DEFINE city DIMENSION ID LD List of cities MAINTAIN city ADD 'Boston' 'Chicago' 'Dallas' 'Seattle' DESCRIBE city
produce the following definition.
DEFINE city DIMENSION ID LD List of cities
The DEFINE DIMENSION (DWMQY) command defines a DWMQY dimension (that is a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR) whose values represent time periods. After defining a DWMQY dimension, you can use a VNF statement to add a value name format to the dimension's definition. The VNF command controls the format for entering dimension values and the format for showing them in output.
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Note: When you want to aggregate over time do not define the time dimension as a DWMQY dimension since you cannot aggregate over dimensions of this type. Instead, define the time dimension as a hierarchical dimension of typeTEXT or NTEXT. |
Syntax
DEFINE name DIMENSION dwmqy [TEMP] [AW workspace] [SESSION]
where dwmqy is the time period of the dimension. The valid types for dwmqy are DAY, WEEK, MONTH, QUARTER, and YEAR. Each type indicates the span of the time period represented by the individual dimension values of the dimension. The syntax of dwmqy varies depending on the type:
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a dimension.
For the WEEK and MONTH types, specifies time periods that span a multiple number of weeks or months. With the WEEK keyword, multiple can be an INTEGER from 2 to 52. With the MONTH keyword, multiple can be 2, 3, 4, or 6.
Specifies the beginning or ending phase of a WEEK, MONTH, QUARTER, or YEAR dimension:
For single weeks, phase can be a day of the week (corresponding to a name in the DAYNAMES option) or a date.
For multiple weeks, phase must be a date.
For months, quarters, or years, phase must be a month, expressed as a month name (corresponding to a name in the MONTHNAMES option) or as a date.
When you specify phase as a date, you give the month, day, and year, enclosed in single quotes, using any of the input styles that are valid for variable values with a data type of DATE. When you specify a date with an ambiguous meaning (such as '03 05 97'), the date is interpreted according to the current setting of the DATEORDER option.
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Note: When you define a multiple-period dimension of type WEEK but you do not specify a BEGINNING or an ENDING argument, DEFINE automatically supplies a phase that begins with the date'31DEC1899'. |
Indicates that the dimension's values are only temporary and only for the current session. The dimension has a definition in the current workspace and can contain values during the current session. However, when you update and commit, only the definition of the dimension is saved. When you leave end your session or switch to another workspace, the data values are discarded. Each time you start the workspace, the values of a temporary dimension are NA.
The name of an attached analytic workspace in which you want to define the dimension. Any objects dimensioned by the dimension must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
Implicit Relations Between DWMQY Dimensions
When you define two or more dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR, Oracle OLAP automatically defines implicit relations between the values of the dimensions. For example, when you define a dimension of type MONTH and a dimension of type YEAR, Oracle OLAP automatically defines a relation that associates all the MONTH values that fall within a particular year with the corresponding value of the YEAR dimension.
Using BEGINNING or ENDING Phase to Organize Data by Fiscal Calendar
For dimensions of type MONTH, QUARTER, and YEAR, the BEGINNING phase or ENDING phase argument is especially useful for data organized on a fiscal-year calendar.
By specifying a phase for a dimension of type MONTH or QUARTER, you identify the time period that is the first or last period within a year. For example, when you define a dimension of type MONTH with an ending phase of June, then June is identified as the twelfth month of the year. When a dimension of type QUARTER has an ending phase of June, the quarter ending in June is identified as the fourth quarter of the year. When you give a dimension a VNF that includes a period code, you can enter or report dimension values according to their period within the year.
By default, the single or multiple weeks in a dimension of type WEEK end on Saturday. The BEGINNING phase or ENDING phase argument lets you specify the day of the week on which each period begins or ends. For multiple-week periods, the phase argument also controls the starting or ending date for grouping the weeks into periods. By default, the starting point for grouping multiple weeks is December 31, 1899 (a Sunday).
However, the phase argument does not determine the period that is counted as the first period within a year. For dimensions of type WEEK, Period 1 in a given calendar year is always the first period that ends in that year. For example, suppose you specify a dimension of type WEEK with a four-week period ending on June 7, 1997. DEFINE works backward and forward from this date, forming weeks into four-week periods. For 1997, Period 1 is the period beginning on December 22, 1996 and ending on January 18, 1997.
Examples
Example 9-82 Defining a YEAR Dimension
The following statement defines a dimension of type YEAR that holds values for fiscal years that end on June 30.
DEFINE fyear DIMENSION YEAR ENDING june
After defining the dimension, you can give it a description and a VNF (value name format). You can use a MAINTAIN statement to give values to the dimension.
LD Fiscal years ending June 30 VNF 'FY<ff>' MAINTAIN fyear ADD 'FY97' 'FY00'
Example 9-83 Using the Default Phrase for Date in an ENDING Phrase
This example illustrates how DEFINE automatically supplies a phase that begins with the date '31DEC1899' when you define a multiple-period dimension of type WEEK but you do not specify a BEGINNING phase or an ENDING phase argument. Assume that you issue the following statements
DEFINE twoweek DIMENSION 2 WEEK DESCRIBE TWOWEEK
When you issue a DESCRIBE statement for twoweek, the following output is produced.
DEFINE twoweek DIMENSION 2 WEEK ENDING '13Jan1900'
The DEFINE DIMENSION (conjoint) command defines a conjoint dimension.
Conceptually, you can think of a conjoint dimension consisting of two structures:
The dimension object itself. The values of the dimension are combinations of values of two or more other dimensions (that is, a conjoint tuples) that Oracle OLAP uses to determine the structure of any variables dimensioned by the conjoint dimension.
An index between the conjoint dimension values and its base dimension values.
Composites are another object that you can use to dimension a variable using a list of dimension value combinations. See "Differences Between Conjoint Dimensions and Composites" for a discussion of the major differences between composites and conjoint dimensions.
Syntax
DEFINE name DIMENSION <dims. . .> index-algorithm [AW workspace] [SESSION]
where index-algorithm specifies the algorithm that Oracle OLAP uses to create the index into the conjoint dimension. Valid values for index-algorithm are:
Parameters
The name of the conjoint dimension you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a conjoint dimension.
One or more previously defined dimensions that are the base dimensions of the conjoint dimension. Specify the dimensions in fastest to slowest-varying order as discussed in "Effect of Dimension Order on Variable Storage and Statement Looping". You must enclose the dimension list in angle brackets.
Typically, a base dimension of a conjoint dimension is a simple dimension, but it can also be another conjoint dimension. However, when you do have a simple dimension for one value of dims, you cannot also specify for dims a conjoint or concat dimension that has same simple dimension as one of its bases.
Specifies the creation of a b-tree index to relate conjoint values to base dimension values. Typically, you specify BTREE as the index algorithm for a conjoint dimension.
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Tip: When you are unsure whether to specify BTREE or NOHASH, use NOHASH, since you can always use a CHGDFN statement to change a NOHASH conjoint into a BTREE conjoint, while you can use a CHGDFN statement to change a BTREE conjoint into a NOHASH conjoint only when the conjoint was originally defined as a NOHASH conjoint |
Specifies that Oracle OLAP does not create an index for the conjoint dimension, but instead uses internal structures to relate conjoint values to base dimension values. Because no index is created for NOHASH, NOHASH decreases the number of structures associated with the conjoint dimension; and, in many cases, decreases the time it takes to load and access conjoint dimension values. However, NOHASH is used infrequently, as it is a complicated algorithm that, on occasion, can result in unpredictable performance.
(Default, but not recommended.) Specifies the creation of a has index to relate conjoint values to base dimension values.
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Tip: Even though HASH is the default, typically, you specify BTREE as the index algorithm for a conjoint dimension. When your conjoint dimension has more than 3 base dimensions, for best performance, use BTREE instead of HASH. |
The name of an attached analytic workspace in which you want to define the dimension. Any objects dimensioned by the dimension must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
Differences Between Conjoint Dimensions and Composites
You can use either a composite or a conjoint dimension to dimension a variable with a list of dimension value combinations. Keep the following points in mind when deciding on which type of object to use:
Object population maintenance—Conjoint dimensions offer the most control, while composites provide the greatest ease of use:
Oracle OLAP determines the dimension value combinations stored in a composite. Oracle OLAP populates a composite automatically when a variable dimensioned by composite is populated.
You determine the dimension value combinations that are stored in a composite. You must explicitly populate and maintain a conjoint dimension using MAINTAIN statements the same way you populate and maintain other dimensions.
Dimension operations —You can perform dimension operations on conjoint dimensions, but not composites; however, you can only perform dimension operations on the base dimensions of composites. For example, you can LIMIT conjoint dimensions, but you must limit the base dimensions of a composite to limit your view to a subset of composite values; and you can define relations using conjoint dimensions, but not composites.
For more information on composites, see the DEFINE COMPOSITE command.
Relationship of Conjoint Dimensions to Base Dimensions
The values of the conjoint dimension are related to the base dimensions. You can specify data in a variable dimensioned by the conjoint dimension using the conjoint value combinations, the individual values of the base dimensions, or other dimensions related to either of the base dimensions of the conjoint dimension.
Defining a Subset of a Dimension's Values
You can have a conjoint dimension with only one base dimension, which enables you to create a subset of that dimension's values. You must still enclose that one base dimension within angle brackets.
Using Conjoint Dimension Values in Expressions
To refer to the value of a conjoint dimension in an expression, specify the value following these guidelines:
Enclose the entire dimension value specification in angle brackets and then enclose this entire specification in single quotes; do not enclose the individual values in single quotes.
Use the exact upper- and lowercase spellings for the base dimension values.
When the specification includes a text value with an embedded blank, you must separate the dimension values with commas.
For example, when item.org is a conjoint dimension with base dimensions item and org, use the following format to refer to values of item.org.
'<Expenses, Direct Sales>'
Examples
Example 9-84 Defining a Conjoint Dimension
Assume that you have defined and populated the simple dimensions city, state, and region and that they have the following values.
CITY STATE REGION --------- ---------- ------ Princeton New Jersey East Newark New Jersey Central Patterson New York New York Illinois Chicago Indiana
To define a conjoint dimension named cityandstate and add values to it use the following OLAP DML statements.
DEFINE cityandstate DIMENSION <city state> MAINTAIN cityandstate add <'Princeton' 'New Jersey'> MAINTAIN cityandstate add <'Newark' 'New Jersey'> MAINTAIN cityandstate add <'Patterson' 'New Jersey'> MAINTAIN cityandstate add <'New York' 'New York'> MAINTAIN cityandstate add <'Chicago' 'Illinois'> MAINTAIN cityandstate add <'Princeton' 'Indiana'>
The DEFINE DIMENSION CONCAT commands defines a concat dimension. A concat dimension is a dimension that groups a set of base dimensions with duplicate values or different data types into one dimension.
When there are duplicate data values, you create a non-unique concat dimensions. For example, you would create a nonunique dimension for a geography hierarchy when "New York" is both the value at the city level and at the state level. When all of the data values in all of the base dimensions are unique, you can create a unique concat dimension.
|
Tip: The way that you specify the values of concat dimension varies depending on whether the concat dimension is a unique or nonunique concat dimension. See "Specifying a Value of a CONCAT Dimension" for more information. |
Syntax
DEFINE name DIMENSION CONCAT(basedimlist. . .)[UNIQUE] [TEMP] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a concat dimension.
One or more previously-defined dimensions that are the base dimensions of the concat dimension. Specify the dimensions in fastest to slowest-varying order as discussed in "Effect of Dimension Order on Variable Storage and Statement Looping". You must enclose the dimension list in parenthesis.
The types of dimensions that can be base dimensions varies depending on whether you are defining a unique or nonunique concat dimension:
When defining a non-unique concat dimension, a base dimension can be a simple dimension of any data type, a conjoint dimension, or another concat dimension.
When defining a unique concat dimension, a base dimension can be a simple dimension of type TEXT or ID, or another unique concat dimension if the data values of all of the base dimensions are unique and not duplicated in any of the base dimensions.
A composite cannot be the base dimension of a concat dimension.
Simple dimensions and conjoint dimensions are the bottom-level components of a concat dimension. When you specify a concat dimension as a base dimension when defining a concat, then the base dimensions of that inner concat are component dimensions of the outer concat.
The same dimension cannot appear more than once in the component dimensions of a concat dimension. However, in a concat, a conjoint dimension is an indivisible unit and Oracle OLAP does not consider the base dimensions of a conjoint in the definition of the concat. Therefore, a simple dimension can be a base dimension of a conjoint and that conjoint and the same simple dimension can be base dimensions (or components) of a concat dimension.
For example, the following definitions are permissible.
DEFINE conjointdim.a DIMENSION <simpledim.b, simpledim.c> DEFINE conjointdim.b DIMENSION <simpledim.a, simpledim.b> DEFINE conjointdim.c DIMENSION <simpledim.a, conjointdim.a> DEFINE concatdim.a DIMENSION CONCAT (simpledim.a, conjointdim.a) DEFINE concatdim.b DIMENSION CONCAT (simpledim.a, conjointdim.b) DEFINE concatdim.c DIMENSION CONCAT (simpledim.b, conjointdim.b) DEFINE concatdim.d DIMENSION CONCAT (simpledim.a, concatdim.c)
In the definition of concatdim.a, the base dimensions are simpledim.a and conjointdim.a. In the definition of concatdim.d, the base dimensions are simpledim.a and concatdim.c. The component dimensions of concatdim.d are simpledim.a, simpledim.b, and conjointdim.b. simpledim.a and simpledim.b appear only once as component dimensions even though they are the base dimensions of conjointdim.b because the base dimensions of a conjoint are not component dimensions of a concat.
However, the following definition is not permitted because the same simple dimension is a base dimension of concatdim.e and a component of concatdim.e because it is a base dimension of concatdim.b.
DEFINE concatdim.e DIMENSION CONCAT (simpledim.a, concatdim.b)
|
Note: The simple dimensions in the basedimlist argument, and the simple dimensions that are base dimensions of any conjoint dimensions or concat dimensions in basedimlist, cannot have an INTEGER data type. |
Specifies that the text values of the base dimensions are unique. When you specify this keyword, the dimensions listed in basedimlist must be either simple text or ID dimensions or unique concat dimensions.
Indicates that the dimension's values are only temporary and only for the current session. The dimension has a definition in the current workspace and can contain values during the current session. However, when you update and commit, only the definition of the dimension is saved. When you leave end your session or switch to another workspace, the data values are discarded. Each time you start the workspace, the values of a temporary dimension are NA.
The name of an attached analytic workspace in which you want to define the dimension. Any objects dimensioned by the di mension must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Examples
Example 9-85 Defining a CONCAT Dimension
Assume that you have defined and populated the simple dimensions city, state, and region and that they have the following values.
CITY STATE REGION --------- ---------- ------ Princeton New Jersey East Newark New Jersey Central Patterson New York New York Illinois Chicago Indiana
You define a concat dimension based on these dimensions using the following OLAP DML statement.
DEFINE geog DIMENSION CONCAT(region cityandstate)
The values of geog are the following.
<REGION: East> <REGION: Central> <CITYANDSTATE: <Princeton New Jersey>> <CITYANDSTATE: <Newark New Jersey>> <CITYANDSTATE: <Patterson New Jersey>> <CITYANDSTATE: <New York New York>> <CITYANDSTATE: <Chicago Illinois>> <CITYANDSTATE: <Princeton Indiana>>
The DEFINE DIMENSION ALIASOF command defines a dimension alias for a simple dimension. An alias dimension has the same type and values as its base dimension. Typically, you define an alias dimension when you want to dimension a variable by the same dimension twice.
Additionally, You can use a LIMIT statement to limit alias dimensions and define variables and relations using an alias dimension. However, you cannot maintain an alias dimension directly; instead you maintain its base dimension using MAINTAIN.
Syntax
DEFINE name DIMENSION ALIASOF dimension [TEMP] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a dimension. Indicates that the dimension being defined is an alias for another dimension.
The name of a simple dimension for which you want to define an alias. This dimension cannot be a concat or conjoint dimension, composite, or surrogate.
Indicates that the dimension's values are only temporary and only for the current session. The dimension has a definition in the current workspace and can contain values during the current session. However, when you update and commit, only the definition of the dimension is saved. When you leave end your session or switch to another workspace, the data values are discarded. Each time you start the workspace, the values of a temporary dimension are NA.
The name of an attached analytic workspace in which you want to define the dimension. Any objects dimensioned by the dimension must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Examples
Example 9-86 Defining an Alias Dimension
Assume that your department has multiple projects that employees participate in and that an employee may be a leader of one project and a participant in another. Assume also that you want to track the hours that each employee participates in a project as either a leader or a participant. To keep track of this information, you can design a variable that is dimensioned by the time you want to track by (in this example, year), project, and two dimensions for employee—one dimension named employee for employee as participant and another dimension named leader for employee as leader. The following definitions support this structure.
DEFINE year DIMENSION TEXT DEFINE project DIMENSION TEXT DEFINE employee DIMENSION TEXT DEFINE leader DIMENSION ALIASOF employee DEFINE hours VARIABLE INTEGER <year project employee leader>
The following statements populate all of the dimensions.
MAINTAIN year ADD '2001' '2002' '2003' MAINTAIN project ADD 'projA' 'projB' MAINTAIN employee add 'Adams' 'Baker' 'Charles'
Note that you do not have to explicitly populate the alias dimension (that is, leader). When you populate the employee dimension, Oracle OLAP also populates its alias dimension leader.
EMPLOYEE -------------- Adams Baker Charles LEADER -------------- Adams Baker Charles
You can limit a dimension without limiting its alias; or limit an alias without limiting the dimension for which it is an alias. For example, when you issue the following statements to limit employee to Adams for project ProjA in year 2001, a report displays all of the leaders of the projects that Adams participates in.
LIMIT year TO '2001'
LIMIT employee TO 'Adams'
LIMIT project TO 'projA'
REPORT DOWN leader ACROSS employee: hours
PROJECT: projA
YEAR: 2001
--HOURS---
-EMPLOYEE-
LEADER Adams
-------------- ----------
Adams 1
Baker 2
Charles 1
On the other hand, when you limit leader to Adams for project ProjA in year 2001, a report displays all of the employees of the projects that Adams leads.
LIMIT employee TO ALL
LIMIT leader TO 'Adams'
LIMIT project TO 'projA'
REPORT DOWN leader ACROSS employee: hours
PROJECT: projA
YEAR: 2001
-------------HOURS--------------
------------EMPLOYEE------------
LEADER Adams Baker Charles
-------------- ---------- ---------- ----------
Adams 1 3 3
The DEFINE command with the FORMULA keyword adds a new formula object to an analytic workspace. You define a formula to save an expression. A formula can take the place of an expression you use repeatedly. The name of the formula takes the place of the text of the expression. Oracle OLAP does not store the data for a formula in a variable; instead it is calculated at run time each time it is requested.
Syntax
DEFINE name FORMULA {expression | [ datatype ][<dimensions...>]} [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a formula.
The calculation to be performed to produce values when you use the formula. It can be any valid expression, including a constant or the name of a variable as described in Chapter 2, "OLAP DML Expressions".
You can specify an expression for a formula when you define it or after you define using an EQ statement. When you define a formula without specify an expression, a formula returns NA with the specified data type.
|
Note: Oracle OLAP does not automatically convert text in a formula to uppercase. |
The intended data type for the formula when you do not specify a value for expression. You can use any of the data types that apply to variables. If you do not specify a value, the data type is determined at run time.
When you include an expression in the formula definition, DEFINE automatically determines the data type for a formula defined using expression. Later, when you add the expression using an EQ statement, its data type should match the type you specify now. When it does not, DEFINE converts the output to the specified type.
The dimensions of the formula. Enclose the list in angle brackets. The dimensions argument is optional. When the formula is a single-cell value, you do not specify any dimensions. Also, when you include an expression in the definition, you do not specify a value. DEFINE automatically determines the dimensions.
However, when you do not include an expression in the definition, you must specify the dimensions. When you add the expression later using an EQ statement, the expression must have the same dimensions as the formula definition. When it does not, DEFINE forces the output to have the specified dimensions.
|
Restriction: You cannot define a formula that is dimensioned by a composite. |
The name of an attached workspace in which you want to define the formula. When the formula is dimensioned, it must be defined in the same workspace as its dimensions. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
Effect of Changing the Characteristics of Objects Used by a Formula
When you change the name, data type, or dimensions of any of the objects used by a formula, the formula is not automatically updated. The formula causes an error when objects it refers to have been deleted or are now the wrong data type.
Storing Complex Expressions and Calculations
To define a very complex calculation, you can define a program that uses a RETURN statement to return a value. You can then use the program as a function wherever you would use an expression or formula.
Examples
Example 9-87 Defining a Formula
This example adds a formula named sales.diff to an analytic workspace. This formula calculates the percent difference between total sales for the current year and last year.
The statements
DEFINE sales.diff FORMULA LAGPCT(TOTAL(actual year) 1 year) DESCRIBE sales.diff
produce the following definition.
DEFINE sales.diff FORMULA DECIMAL <year> EQ lagpct(TOTAL(actual year) 1 year)
The DEFINE command with the MODEL keyword adds a new model object to an analytic workspace. A model is a set of interrelated equations. The calculations in an equation can be based either on variables or on dimension values. You can assign the results of the calculations directly to a variable or you can specify a dimension value for which data is being calculated. For example, in a financial application, all the equations might be based on the values of a line item dimension, and data would be calculated for line items such as total expenses and net income.
|
Note: Defining a model merely creates a model object in the analytic workspace. You must also code a specification for the model, as described in MODEL. |
Syntax
DEFINE name MODEL [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a model.
The name of an attached workspace in which you want to define the object. For more information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Examples
Example 9-88 Defining a Simple Model
This example shows a simple model named income.calc that calculates the line items in an income statement. The model equations are based on the line dimension in the demo workspace. First, define the model and give it an LD.
DEFINE income.calc MODEL LD Model for calculating Income Statement items
Then use a MODEL statement to enter the specification for the model. For this example, you can enter model lines such as the ones in the following model description.
DEFINE income.calc MODEL LD Model for calculating Income Statement items MODEL dimension line net.income = opr.income - taxes opr.income = gross.margin - (marketing+selling+r.d) gross.margin = revenue - cogs END
To solve the model for the actual variable, enter data in actual for the input line items (Revenue, Cogs, Marketing, Selling, R.D, and Taxes). Then execute the following statement.
income.calc actual
The DEFINE command with the PARTITION TEMPLATE keywords adds a new partition template object to an analytic workspace. A partition template is a specification for the partitions of a partitioned variable. A partitioned variable is stored as multiple rows in the relational table of LOBs that is the analytic workspace—each partition is a row in the table. You define both partitioned and unpartitioned variables using DEFINE VARIABLE statements. Before you can define a partitioned variable you must first define a partition template object.
Syntax
DEFINE name PARTITION TEMPLATE <dimlist> PARTITION BY
{RANGE|LIST} (dims_partitioned_by) ([partition_definition_statement...]) [AW workspace]
where partition_definition_statement defines a partition. The syntax varies depending on whether you specify RANGE or LIST:
For RANGE:
PARTITION partition-name VALUES LESS THAN const-exp <partition-dimlist>
For LIST:
PARTITION partition-name VALUES ([valuelist)] <partition-dimlist>
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
A list of all of the logical dimensions for the variable that you are partitioning. You must enclose the names of the dimensions in a single set of angle brackets (< >). You must define a dimension before you can include it in the definition of a partition template.
The subset of dimensions specified by dimlist that actually specify the partitions of the variable. For range and list partitioning (that is, when you specify either the RANGE or LIST keywords), you can specify only one dimension for dims_partitioned_by. You cannot partition a variable along an INTEGER dimension.
The name of the partition.
Indicates that you are specifying a RANGE partition by comparing values.
A constant expression that has the same data type as the data type of the dimension specified for dims_partitioned_by.
A list of all of the dimensions of the partition template object (although the dimensions may be members of a composite). You must enclose the names of the dimensions in a single set of angle brackets (< >). Use this argument to specify the composite (if any) used to dimension the partitions that correspond to partition-name. When you do not specify a value then the partition is dimensioned densely by all of the dimensions of the partition template object.
Indicates that you are specify a LIST partition by specifying values.
A list of dimension values, separated by commas. You must surround text values with single quotes (for example, 'mytext'). Specify values of conjoints by specify the values of the base dimensions, separated by a comma, in a single set of angle brackets (for example, <'Value1', 'Value2'>). Specify values of nonunique concat dimensions by specify the values of the base dimensions, separated by a colon, in a single set of angle brackets (for example, <'Value1': 'Value2'>).
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Tip: I f you want to use a valueset object to specify values, do not specify values for valuelist. Instead, omit valuelist from the partition template definition and use a MAINTAIN ADD TO PARTITION statement to specify values for the partition. |
Examples
See Example 9-101, "Defining a Variable with Partitions".
The DEFINE command with the PROGRAM keyword adds a new OLAP DML program object to an analytic workspace. An OLAP DML program is a collection of OLAP DML statements that helps you accomplish some workspace management or analysis task. Defining a program merely creates a program object in the analytic workspace. You must also code the actual lines of the program.
Syntax
DEFINE name PROGRAM [datatype|dimension] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a program.
The data type of the value to be returned by the program when it is called as a function. You can use any of the data types that apply to variables.
The name of a dimension, whose value the program returns when it is called as a function. The return value is a single value of the dimension, not a position (INTEGER). The dimension must be defined in the same workspace as the program.
The name of an attached workspace in which you want to define the program. When the program returns a dimension, the program must be defined in the same workspace as the dimension. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists.
Usage Notes
Returning Values
Use a RETURN statement in a program when you want it to return a value. The argument to the RETURN statement is an expression that specifies the value to return. When the expression does not match the declared data type or dimension, the value is converted (if possible) to the declared data type or dimension value.
When you do not specify a data type or dimension in the definition of a program, its return value is treated as worksheet data and Oracle OLAP converts any return value to the data type required by the calling context which may lead to unexpected results.
For a program to return a value, you must call the program as a function. That is, you must use it as an expression in a statement. In the following example, the program isrecent is being treated as a function. It is an argument to the REPORT command.
REPORT isrecent(actual)
When the program returns values of a dimension, the program is in the output of the LISTBY function, and OBJ(ISBY) is TRUE for the dimension.
See the entries for the ARGUMENT, CALL, and RETURN commands for more information about programs as user-defined functions.
Examples
Example 9-89 Basing Program Flow on Test Results
The saleseval program tests whether total sales for a month exceeds total planned sales for the month. The program executes different statements based on the results of the test.
DEFINE SALESEVAL PROGRAM
PROGRAM
ARGUMENT onemonth MONTH
VARIABLE excess DECIMAL
ALLSTAT
LIMIT month TO onemonth
IF TOTAL(sales, month) GT TOTAL(sales.plan, month)
THEN DO
excess = (TOTAL(sales, month) -
- TOTAL(sales.plan, month)) -
/ TOTAL(sales.plan, month) * 100
SHOW JOINCHARS('Sales exceeded plan by ' excess '%.')
DOEND
ELSE SHOW JOINCHARS('We\'re not meeting plan. ' -
'Let\'s get working!')
REPORT DOWN product W 10 ACROSS district: sales - sales.plan
END
When total sales for the month exceeds total planned sales for the month, the THEN statement lines are executed. The program calculates the percentage by which actual sales exceeds planned sales and places the result in a numeric variable called excess. The program then sends the results to the current outfile. The JOINCHARS function is used to combine the calculated expression excess with the text expression "Sales exceeded plan by" in the output.
When total sales does not exceed planned sales, the ELSE statement line is executed and a different message is produced.
After the THEN or ELSE statement lines are executed, control flows to the next line in the program, and a report of sales in excess of plan is produced.
The DEFINE command with the RELATION keyword adds a new relation object to an analytic workspace. A relation describes a correspondence between the values of two or more dimensions. It can have dimensions, just like a variable, but the values of the relation must be values from the related dimension.
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Note: Defining a relation merely adds the definition of the relation to the analytic workspace; it does not populate the relation. To populate relations using the OLAP DML, you can issue OLAP DML SQL, FILEREAD, SET, or SET1 statements. |
Syntax
DEFINE name RELATION related-dim [<dimensions...>] [TEMP] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a relation.
Specifies the dimension to which one or more dimensions are related. A relation is normally used to store information about the relationship between two dimensions; for example, the cities that belong in each region.
In the definition, the dimension having fewer values is normally specified as the related dimension (for example, regions). The dimension having more values is normally specified as a dimension of the relation (for example, cities).
The names of the dimensions of the relation. You must enclose the names of the dimensions in a single set of angle brackets (< >). You must define a dimension before including it in the definition of a relation. Do not include composites in the dimension list.
|
Restriction: Oracle OLAP does not support the use of composites as dimensions for relations. Do not attempt to define them. |
|
Tip: When defining two relations between the same dimensions, use the RELATION command to identify which relation is the default relation. |
Indicates that the values of the relation are only temporary. The relation is defined in the current workspace and can contain values during the current session. However, when you update and commit the workspace, only the definition of the relation is saved. When you end the session or switch to another workspace, the data values are discarded. Each time you start the workspace, the values of a temporary relation are NA.
The name of an attached workspace in which you want to define the relation. The relation must be defined in the same workspace as its dimensions. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When the session ends, the object no longer exists. The behavior specified by the SESSION keyword differs from the behavior specified by the TEMP keyword which is that the values are temporary, but the object definition remains in the workspace in which you create it.
Examples
Example 9-90 Creating, Populating, and Totaling by a Relation
The following example defines a relation between division and product, stores the values of the relation, and then totals units by division, even though units is dimensioned by product. The following statement defines the div.prod relation.
DEFINE div.prod RELATION division <product>
The following statements store values of division in div.prod.
LIMIT product TO 'Tents' 'Canoes' div.prod = 'Camping' LIMIT product TO 'Racquets' div.prod = 'Sporting' LIMIT product TO 'Sportswear' 'Footwear' div.prod = 'Clothing'
You can use a REPORT statement to see the values stored in div.prod.
report div.prod
This statement produces the following output.
PRODUCT DIV.PROD ------------- ---------- Tents Camping Canoes Camping Racquets Sporting Sportswear Clothing Footwear Clothing
The div.prod relation lets you look at division totals in a report, even though the data is dimensioned by product.
REPORT TOTAL(units division)
The DEFINE command with the SURROGATE keyword adds a a new dimension surrogate object to an analytic workspace. A surrogate provides an alternative set of values for a dimension. You can use a surrogate rather than a dimension in a model, in a LIMIT command, in a qualified data reference, or in data loading with statements such as FILEREAD, FILEVIEW, SQL FETCH, and SQL IMPORT.
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Note: Defining a surrogate merely adds the definition of the dimension surrogate to the analytic workspace; it does not populate the surrogate. To populate surrogates using the OLAP DML, you can issue OLAP DML SQL, FILEREAD, SET, or SET1 statements. |
Syntax
DEFINE name SURROGATE targetname type [AW workspace] [SESSION]
where type has the following syntax:
[TEXT|NTEXT] [WIDTH n]|ID|INTEGER|NUMBER (precision[, scale] | datatime-datatype)
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a dimension surrogate.
The name of the dimension for which you are creating a surrogate. See "Restrictions on the Use of Surrogates" for points to keep in mind when determining the target.
The data type for a dimension surrogate with text values. When all the values of a dimension surrogate are eight single-byte characters or less, give it a data type of ID. When one or more dimension values has more than eight single-byte characters, you must give it a data type of TEXT or NTEXT. For greater efficiency and ease of use, give dimensions a data type of ID whenever possible.
For TEXT or NTEXT dimension surrogate, the width, in bytes, of the storage area of each value of an object. Valid width values are 1 through 4000. Specify a fixed width only when you are certain that the values of a particular dimension surrogate are of similar size. When a value exceeds the specified width, Oracle OLAP truncates it.
The data type for a dimension surrogate with values that are the ordinal positions (1, 2, and so on) of the values in its dimension. You might create an INTEGER type dimension surrogate for a NUMBER type dimension so that you can specify dimension values by position instead of by the value of the dimension. When you define an INTEGER type dimension surrogate, Oracle OLAP automatically assigns an INTEGER value to the surrogate for each of the positions in the dimension.
Specifies that the dimension surrogate has a data type of NUMBER. See "Numeric Data Types" for more information.
Specifies the total number of characters in the value of a dimension surrogate of type NUMBER.
Specifies the number of characters that can be to the right of a decimal point of a dimension surrogate of type NUMBER.
Specifies a datetime data type (that is, DATETIME , TIMESTAMP, TIMESTAMP_TZ, or TIMESTAMP-LTZ). See "Datetime and Interval Data Types" for more information.
The name of an attached workspace in which you want to define the dimension surrogate. The dimension for which you define the surrogate must be defined in the same workspace. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When you close the current session, the object no longer exists. Use this keyword when the definition of the targetname dimension includes SESSION.
Usage Notes
Restrictions on the Use of Surrogates
Keep the following restrictions in mind when determining a target for your surrogate:
You cannot create a surrogate for a dimension that has a type of DAY, WEEK, MONTH, QUARTER, or YEAR or for a composite.
When you create a surrogate for a conjoint, you cannot convert the conjoint to a composite.
You cannot specify a dimension surrogate as the dimension or related dimension argument when you define a concat dimension, a formula, a program, a relation, a valueset, or a variable. Additionally, in data loading you cannot create new dimension values using a dimension surrogate
Examples
Example 9-91 Creating an INTEGER Dimension Surrogate
The following statement creates an INTEGER type dimension surrogate for the store_id dimension.
DEFINE storepos SURROGATE store_id INTEGER
Example 9-92 Creating a NUMBER Dimension Surrogate
The following statement creates an NUMBER type dimension surrogate for the product dimension, which is a TEXT dimension that has product names as values. The precision argument to the NUMBER keyword specifies that a value in prodnum can have no more than seven characters and the scale argument specifies that no more than three characters can be to the right of the decimal point.
DEFINE prodnum SURROGATE product NUMBER(7, 3)
The following statement sets the first value of prodnum to 1083.375.
prodnum(product 1) = 1083.375
The DEFINE command with the VALUESET keyword adds a new valueset object to an analytic workspace. A valueset is a list of dimension values for one or more dimensions. You use a valueset to save dimension status lists across sessions.
|
Note: Defining a valueset adds the definition of the valueset to the analytic workspace and sets all of its values to null (NA). To assign values to a valueset use the LIMIT command. You can also use a STATUS statement and the STATFIRST, INSTAT, and VALUES functions to work with a valueset. |
Syntax
DEFINE name VALUESET dimension [<dims...>] [TEMP] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a valueset.
The name of the previously-defined dimension whose values you want to store in the valueset.
When defining a multi-dimensional valueset, the names of the previously-defined dimensions by which you want the valueset dimensioned.
Indicates that the valueset's values are only temporary. The valueset has a definition in the current workspace and can contain values during the current session. However, when you update and commit, only the definition of the valueset is saved. When you end the session or switch to another workspace, the values are discarded. Each time you start the workspace, the value of a temporary valueset is null.
The name of an attached workspace in which you want to define the valueset. The valueset must be defined in the same workspace as its dimensions. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When the session ends, the object no longer exists. The behavior specified by SESSION is different from the behavior specified by the TEMP keyword which is that the values are temporary but the object definition remains in the workspace in which you create it.
Examples
Example 9-93 Creating and Assigning Values to a Valueset
This example adds the valueset named lineset to the demonstration workspace. The lineset valueset is dimensioned by line, and therefore it can be limited by the current values of the line dimension. The LD statement attaches a description to the object.
The following statements 1) limit the line dimension and display the values in status, 2) create a valueset named lineset by defining valueset and limiting the valueset to those values currently in status for the line dimension, and 3) display the values of the lineset.
LIMIT line TO FIRST 2 STATUS line
The current status of LINE is: REVENUE, COGS " Define the valueset and specify a long description for it
DEFINE lineset VALUESET line LD Valueset for LINE dimension values " Assign the values that are currently in status for line " as the values of valueset LIMIT lineset TO line UPDATE SHOW lineset
Revenue Cogs
Example 9-94 Creating and Assigning Values to a Multidimensional Valueset
Assume that your analytic workspace has the variables and dimensions with the following definitions.
DEFINE geography DIMENSION TEXT DEFINE product DIMENSION TEXT DEFINE sales VARIABLE DECIMAL <geography product> DEFINE salestax VARIABLE DECIMAL <geography>
Assume also that the analytic workspace contains the following dimensions whose values are the names of variables and dimensions within the workspace.
DEFINE all_variables DIMENSION TEXT MAINTAIN all_variables ADD 'sales' 'salestax' DEFINE all_dims DIMENSION TEXTMAINTAIN all_dims ADD 'geography' 'product'
The following statements create and populate a valueset for the values of all_variables and all_dims, and then report the values of that valueset.
DEFINE variables_dims VALUESET all_dims <all_variables>
" Assign all values of all_dims and all_variables to the valueset
LIMIT variables_dims TO ALL
REPORT variables_dims
ALL_VARIABLES VARIABLES_DIMS
---------------- ------------------------------
sales geography
product
salestax geography
product
To create a multidimensional valueset that has the correct dimensions related to the variables that use them, you issue the following statement that uses a QDR to limit the all_dims values for the salestax value of all_variables.
LIMIT variables_dims(all_variables 'salestax') TO 'geography'
REPORT variables_dims
ALL_VARIABLES VARIABLES_DIMS
---------------- ------------------------------
sales geography
product
salestax geography
The DEFINE command with the VARIABLE keyword adds a new variable object to an analytic workspace. Variables store one type of data, which can be numeric, text, Boolean, or dates. Beside the data type of a variable, the definition that you create for a variable also determines the following characteristics of the variable:
The number of elements that are actually created in the array that is the variable.
The logical order of the variable's elements.
Whether the variable's data is stored permanently or is only available for the session.
The number of LOBs that Oracle OLAP creates for the variable's data.
You can also define local program variables using a VARIABLE command. These variables exist only when the program is running.
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Note: Defining a variable merely adds the definition of the variable to the analytic workspace; it does not populate the variable. To populate variables using the OLAP DML, you can issue OLAP DML SQL, FILEREAD, SET, or SET1 statements. |
Syntax
DEFINE name [VARIABLE] datatype [<dims...>] [WITH NULLTRACKING] [WITH AGGCOUNT] -
[PERMANENT | TEMP ] -
[ RANSPACE64] [(partition-instance...)] [WIDTH n] [AW workspace] [SESSION]
where:
dims are the dimensions of the variable separated by commas. For a dimension of a variable you can specify a dimension object, a partition template object, a named uncompressed composite, a compressed composite, or an unnamed uncompressed composite using one of the following:
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Note: The order in which you list the dims of a variable is the default order of the dimensions and behavior of a variety of statements (such as REPORT and UNRAVEL) and affects how the data for the variable is stored (as discussed in "Effect of Dimension Order on Variable Storage and Statement Looping". Also, when you define multiple objects with the same dimensions, most operations work much more efficiently when you list the dimensions in the same order in each definition. |
partition-instance are the partitions of the variable separated by commas. Use the following syntax to specify a partition.
PARTITION partition-name INTERNAL [TEMP | PERMANENT]
Parameters
The name of the variable you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a variable. You do not have to include the word VARIABLE, because it is the default.
The data type of the data to be stored in the variable. The data types, their abbreviations, and the range of acceptable values are shown in Table 2-1, "Summary of OLAP DML Data Types".
The name of a simple, concat, conjoint, or alias dimension that you have previously defined using a DEFINE DIMENSION statement. In this case, you specify the name of the dimension.
When defining a TEXT, NTEXT, or RAW variable, specify this keyword to increase the maximum number of characters for the values of the variable from nearly 2**32 to nearly 2**64.
The name of a partition template object that you have previously defined using a DEFINE PARTITION TEMPLATE statement. For dims, specify the names of the dimensions of the partition template object. These dimensions must be the same dimensions as those used to define the partition template object.
The name of an uncompressed composite previously defined using a DEFINE COMPOSITE statement. For the optional basedims argument, specify the names, separated by commas, of the dimensions used to define the composite.
The name of a compressed composite previously defined using a DEFINE COMPOSITE statement. For the optional basedims argument, specify the names, separated by commas, of the dimensions used to define the composite.
When defining a variable that is dimensioned by a compressed composite, keep the following points in mind:
A compressed composite can dimension only one variable or one partition of a variable. A compressed composite cannot be a shared composite.
The compressed composite must be the last dimension in the variable's dimension list of the DEFINE VARIABLE statement that defines the variable.
Indicates that you want Oracle OLAP to create an unnamed composite and use it when dimensioning the variable. For the basedims argument, specify the names of the dimensions, separated by commas, for which the unnamed composite is created.
When the variable is dimensioned by a composite, specifies that Oracle OLAP create NA2 bits for the cells of the variable.
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See also: For more information on:
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Specifies that Oracle OLAP automatically creates an INTEGER variable in which it stores the non-NA counts of the number of leaf nodes that contributed to aggregate values calculated for RELATION statements that have an AVERAGE, HWAVERAGE, or WAVERAGE operator. You must include this phrase to calculate average aggregations for a variable dimensioned by a compressed composite. For more information on Aggcount variables, see "Aggcount Variables".
Specifies that a variable or a partition of a variable is either permanent or temporary. After you update and commit, the definition of both permanent and temporary variables and partitions is always saved between sessions. Specifying permanent or temporary determines whether or not the values of a variable or partition of a variable are saved or discarded, after you update and commit, when you leave end your session or switch to another workspace:
Permanent variables and partitions—Oracle OLAP saves the data values or a permanent variable or permanent partitions. When you start the workspace, the data values or a permanent variable or permanent partitions are the same as they were at the last commit.
Temporary variables and partitions—Oracle OLAP discards the data values of a temporary variable or temporary partition. Each time you start the workspace, the values of a temporary variable or temporary partition are NA.
Keep the following points in mind when specifying the PERMANENT and TEMP keywords:
By default, a variable is permanent.
Temporary variables can be dimensioned by partition template objects or by temporary dimensions.
By default, a top-level partition of a variable has the same permanence as the variable that contains it. Specifically, a partition of a temporary variable is a temporary partition unless you use the PEMANENT keyword to make it a permanent partition, and a partition of a permanent variable is a permanent partition unless you use the TEMPORARY keyword to make it a temporary partition. To indicate different behavior, use either the PERMANENT or TEMP keyword.
By default, a subpartition has the same permanence as its parent partition. To indicate different behavior, use either the PERMANENT or TEMP keyword.
(You can abbreviate WIDTH as W.) The width, in bytes, of the storage area for each value of a variable. When you are using a multibyte character set, be sure to specify the number of bytes, not characters.
You specify fixed widths to create faster and more compact data storage formats. You can specify fixed widths for dimensioned TEXT, NTEXT, and INTEGER variables only, as described in the following list:
For dimensioned TEXT and NTEXT variables, you can specify a width from 1 byte through 4,000 bytes. Specify a fixed width for such variables only when you are certain that the values of a particular variable are of similar size. You cannot assign a width to a scalar variable.
For dimensioned INTEGER variables, you can specify a width of 1 byte only. Define a fixed width INTEGER variable only when you are certain that all the values for that variable are between -128 and 127.
The default widths for variables are: 2 bytes for SHORTINTEGER, 4 bytes for DATE, INTEGER, and SHORTDECIMAL, and 8 bytes for DECIMAL and ID. TEXT and NTEXT variables that do not have fixed widths are stored on two sets of pages. The first set contains 4-byte cells, each of which points to the actual text value that is stored in the other set of pages. The default width of 4 bytes for TEXT and NTEXT variables is for these 4-byte cells.
Specifies a partition of the variable where partition-name is the name of the partition.
When defining the partitions of a variable dimensioned by a compressed composite, keep the following points in mind:
A compressed composite can dimension only one partition.
The partitions of a variable dimensioned by a compressed composite must respect the parent-child relationships of the hierarchical dimensions. When an AGGREGATE command executes, data cannot be aggregated across partitions. To verify if a variable is partitioned correctly, use the PARTITIONCHECK function.
The name of an attached workspace in which you want to define the variable. When the variable is dimensioned, it must be defined in the same workspace as its dimensions. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When the session ends, the object no longer exists. The behavior specified by SESSION is different than the be3havior specified by the TEMP keyword which is that the values are temporary but the object definition remains in the workspace in which you create it.
Usage Notes
Aggcount Variables
When you include the WITH AGGCOUNT phrase in a DEFINE VARIABLE statement, Oracle OLAP automatically creates the variable specified in the DEFINE statement and a secondary variable (often called the Aggcount variable). The Aggcount variable is an INTEGER variable that Oracle OLAP uses when performing average aggregations for the defined variable. When resolving RELATION statements that have an AVERAGE, HAVERAGE, WAVERAGE, or HWAVERAGE operator and that do not have a COUNT NO phrase, Oracle OLAP stores the non-NA counts of the number of leaf nodes that contribute to the average aggregate values in the Aggcount variable.
Most statements that maintain a variable also automatically maintain an associated Aggcount variable. For example, an EXPORT statement exports both a variable and its associated Aggcount variable, and a CLEAR statement clears both the variable and the related portions of the associated Aggcount variable. Additionally, some OLAP DML statements are specific to the use of Aggcount objects. Table 9-6, "OLAP DML Statements for Aggcount Variables" lists these statements.
Table 9-6 OLAP DML Statements for Aggcount Variables
| Statement | Keywords | Description |
|---|---|---|
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WITH AGGCOUNT |
Defines a variable and an associated Aggcount variable. |
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Retrieves the values of the Aggcount variable associated with the specified variable. | |
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ADD|DROP AGGCOUNT |
Adds or drops an Aggcount variable for the specified variable. |
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HASAGGCOUNT |
Returns a |
NA2 Bits and Null Tracking
Relational fact tables sometimes have null facts (that is, facts that have a null value). Typically, when OLAP DML creates a variable dimensioned by a composite, it does not create a composite tuple for an NA (or null) value. Given this typical behavior, OLAP DML variables would not correspond to their base relational fact table because the variables would eliminate the null facts.
To support OLAP DML composite-dimensioned variables that correspond to relational fact tables with null facts, OLAP has a special NA bit called an NA2 bit. These NA2 bits tracks whether or not each cell of the variable has null value because the underlying relational table has a null fact. When the corresponding fact table has a null fact, you want Oracle OLAP to intentionally include an NA value in the composite tuples for the variable and NA2 bits are used by Oracle OLAP to do just that. NA2 bits are used by Oracle OLAP when it populates variables using the SQL IMPORT command, the AGGREGATE command, and variables that were created as materialized views. It is also used by Oracle OLAP when it populates a relational table using the OLAP_TABLE SQL function. Additionally, Oracle OLAP recognizes NA2 values when evaluating expressions using arithmetic and Boolean operators.
The OLAP DML provides the following statements for working with variables that have NA2 bits:
To create a variable with NA2 bits, use the DEFINE VARIABLE statement with the NULLTRACKING phrase.
To add NA2 bits to a variable that does not have NA2 bits, use the CHGDFN statement with the NULLTRACKING phrase.
To remove NA2 bits from a variable that has NA2 bits, use the CHGDFN statement with the DROP NULLTRACKING phrase.
For testing and debugging purposes, use the NA2 function to set one or more of the NA2 bit of a variable to TRUE. Use the NAFLAG function to identify if one or more values of a variable are NA values and, if so, if the NA value is just the typical NA values that OLAP should ignore or both the typical NA value and also an NA2 value.
Defining Very Large Variables
Theoretically, a variable can contain up to 2**63 cells and a TEXT or NTEXT variable can contain up to 2 billion bytes. However, the page size determines if a variable can be stored entirely on a page or how many variables can be stored on a page. To calculate the maximum number of values for a variable of a given width that fit on one page, use the VALSPERPAGE program.
Effect of Dimension Order on Variable Storage and Statement Looping
The order in which you list the dimensions of a variable definition determines the order in which the elements of the variable are stored and, consequently, how the data is accessed. The first dimension in the variable definition is the fastest-varying dimension, and the last dimension is the slowest-varying dimension.
For example, assume your analytic workspace has an opcosts variable that contains the operating costs, by month, of each city in which you have offices. In the following definition for the opcosts variable, month is the fastest-varying dimension and city is the slowest-varying dimension.
DEFINE opcosts VARIABLE DECIMAL <month city>
The data for a multidimensional variable is stored as a linear stream of values, in which the values of the fastest-varying dimension are clustered. For example, for the opcosts variable, the values for Boston for all the months are stored in a sequence, and then it stores the values for Chicago for all the months in a sequence, and so on. Thus the month values vary fastest in the opcosts variable, as shown in the following table.
When you define variables and other dimensioned objects, and when you write programs that loop over multidimensional expressions in nested loops, always try to maximize performance by matching the fastest-varying dimension with the inner loop.
Unnamed Composites
Oracle OLAP automatically defines an unnamed composite when a DEFINE VARIABLE statement with a SPARSE <dimlist> phrase executes. An unnamed composite can have either a b-tree or hash index. The type of index is determined by the value of the SPARSEINDEX option when Oracle OLAP defines an unnamed composite.
Once Oracle OLAP has created a definition for an unnamed composite for a certain dimension list, it uses that composite any time you define a variable with the same SPARSE <dimlist> phrase. Thus all variables that are defined with the same SPARSE <dimlist> phrase share the same unnamed composite. For more information on sharing composites, see "Shared Composites".
Variable Segments
Within a partition, variable data is stored in analytic workspace segments. An analytic workspace segment is a group of logically contiguous analytic workspace pages. By default, the segment sizes of a variable are automatically determined by Oracle OLAP. Each segment is the exactly the number of analytic workspace pages needed to store the values assigned by the one OLAP DML statement. You can explicitly specify a segment size for a variable using the SEGWIDTH keyword of the CHGDFN command. In this case, when you assign values to a variable, Oracle OLAP stores the data assigned by multiple OLAP DML statements into a segment until the segment is full.
Examples
Example 9-95 Defining an INTEGER Variable with One Regular Dimension
This example adds the variable population to an analytic workspace. It is dimensioned by city, which has already been defined in the workspace. The LD Statement attaches a description to the object. The statements
DEFINE population INTEGER <city> LD Population in each city DESCRIBE population
produce the following description.
DEFINE POPULATION VARIABLE INTEGER <CITY> LD Population in each city
Example 9-96 Defining a Single-Cell Variable
The following is a definition for a variable named newdata which is a single Boolean value. It has no dimensions. An application might set it to YES when new data is added to the workspace and to NO after a user views the data.
DEFINE newdata BOOLEAN newdata = YES
Example 9-97 Defining NUMBER Variables
The following statement defines a NUMBER variable named sales and dimensioned by product and geography with a precision of 16 digits and a scale of 4 digits.
DEFINE sales VARIABLE NUMBER (16,4) <product, geography>
The following statements define a NUMBER variable named numvar with 5 significant digits and 2 decimal places. The number 1234567 is out of its range.
DEFINE numvar VARIABLE NUMBER (5, 2) numvar = 1234567 SHOW numvar NA
A negative scale defines a NUMBER variable named numnegvar with 5 significant digits and 2 rounded digits to the left of the decimal point. The number 1,234,567 is rounded up.
DEFINE numnegvar VARIABLE NUMBER (5, -2) numnegvar = 1234567 SHOW numnegvar 1,234,600.00
Example 9-98 Defining a Variable Dimensioned by Two Regular Dimensions
Assume that you have an analytic workspace that contains the following definitions for dimensions, relations, and aggmaps.
DEFINE GEOG_CITY DIMENSION TEXT DEFINE GEOG_STATE DIMENSION TEXT DEFINE GEOG_AREA DIMENSION TEXT DEFINE GEOG_CONT DIMENSION TEXT DEFINE GEOG DIMENSION CONCAT (GEOG_CITY GEOG_STATE GEOG_AREA GEOG_CONT) DEFINE PROD_UPC DIMENSION TEXT DEFINE PROD_FAMILY DIMENSION TEXT DEFINE PROD_DIV DIMENSION TEXT DEFINE PROD_TOP DIMENSION TEXT DEFINE PROD DIMENSION CONCAT (PROD_UPC PROD_FAMILY PROD_DIV PROD_TOP) DEFINE GEOGLEVEL DIMENSION TEXT DEFINE PRODLEVEL DIMENSION TEXT DEFINE GEOG.PARENT RELATION GEOG <GEOG> DEFINE PROD.PARENT RELATION PROD <PROD> DEFINE GEOG.LEVELREL RELATION GEOGLEVEL <GEOG> DEFINE PROD.LEVELREL RELATION PRODLEVEL <PROD> DEFINE GEOG.FAMILYREL RELATION GEOG <GEOG GEOGLEVEL> DEFINE PROD.FAMILYREL RELATION PROD <PROD PRODLEVEL> DEFINE SALES_DIMS_REG VARIABLE NUMBER (12,0) <PROD GEOG> DEFINE SALES_AGGMAP AGGMAP AGGMAP RELATION geog.parent RELATION prod.parent END
The two parent relations (prod.parent and geog.parent) have the following values.
PROD PROD.PARENT ------------------------- ------------------------- <PROD_UPC: ColorTV> <PROD_FAMILY: TV> <PROD_UPC: BWTV> <PROD_FAMILY: TV> <PROD_UPC: StndVCR> <PROD_FAMILY: VCR> <PROD_UPC: StrVCR> <PROD_FAMILY: VCR> <PROD_FAMILY: VCR> <PROD_DIV: VideoDiv> <PROD_FAMILY: TV> <PROD_DIV: VideoDiv> <PROD_DIV: VideoDiv> <PROD_TOP: Total Prod> <PROD_TOP: Total Prod> NA GEOG GEOG.PARENT ------------------------- ------------------------- <GEOG_CITY: Canberra> <GEOG_STATE: ACT> <GEOG_CITY: Sydney> <GEOG_STATE: NSW> <GEOG_CITY: Darwin> <GEOG_STATE: NT> <GEOG_CITY: Brisbane> <GEOG_STATE: QLD> <GEOG_CITY: Adelaide> <GEOG_STATE: SA> <GEOG_CITY: Hobart> <GEOG_STATE: TAS> <GEOG_CITY: Melbourne> <GEOG_STATE: VIC> <GEOG_CITY: Perth> <GEOG_STATE: WA> <GEOG_STATE: ACT> <GEOG_AREA: Aust Terr> <GEOG_STATE: NSW> <GEOG_AREA: Aust State> <GEOG_STATE: NT> <GEOG_AREA: Aust Terr> <GEOG_STATE: QLD> <GEOG_AREA: Aust State> <GEOG_STATE: SA> <GEOG_AREA: Aust State> <GEOG_STATE: TAS> <GEOG_AREA: Aust State> <GEOG_STATE: VIC> <GEOG_AREA: Aust State> <GEOG_STATE: WA> <GEOG_AREA: Aust State> <GEOG_AREA: Aust State> <GEOG_CONT: Australia> <GEOG_AREA: Aust Terr> <GEOG_CONT: Australia> <GEOG_CONT: Australia> NA
Assume that you aggregate sales_dims_reg using sales_aggmap). Now assume that you issue the following REPORT statement for a report of the sales_dims_reg variable.
REPORT sales_dims_reg->REPORT sales_dims_reg
As you can see from the output of the REPORT statement, the sales_dims_reg variable is a sparsely populated variable with 152 cells, many of which contain NA values.
----------------------------SALES_DIMS_REG-----------------------------
---------------------------------PROD----------------------------------
<PROD_DI
<PROD_UP <PROD_UP <PROD_UP <PROD_FA <PROD_FA V: <PROD_TO
C: <PROD_UP C: C: MILY: MILY: VideoDiv P: Total
GEOG ColorTV> C: BWTV> StndVCR> StrVCR> VCR> TV> > Prod>
------------------------- -------- -------- -------- -------- -------- -------- -------- --------
<GEOG_CITY: Canberra> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_CITY: Sydney> NA NA NA NA NA NA NA NA
<GEOG_CITY: Darwin> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_CITY: Brisbane> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_CITY: Adelaide> NA NA NA NA NA NA NA NA
<GEOG_CITY: Hobart> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_CITY: Melbourne> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_CITY: Perth> NA NA NA NA NA NA NA NA
<GEOG_STATE: ACT> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_STATE: NSW> NA NA NA NA NA NA NA NA
<GEOG_STATE: NT> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_STATE: QLD> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_STATE: SA> NA NA NA NA NA NA NA NA
<GEOG_STATE: TAS> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_STATE: VIC> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_STATE: WA> NA NA NA NA NA NA NA NA
<GEOG_AREA: Aust State> 66,779.0 22,000.0 67,111.0 73,065.0 140,176 88,779.0 228,955 228,955
<GEOG_AREA: Aust Terr> 36,460.0 NA 60,460.0 36,111.0 96,571.0 36,460.0 133,031 133,031
<GEOG_CONT: Australia> 103,239 22,000.0 127,571 109,176 236,747 125,239 361,986 361,986
Because the sales_dims_reg variable is dimensioned by two regular dimensions (rather than by composites or concat dimensions), the values of all of its cells (even those with an NA value) are stored in variable. You can confirm the number of physical values stored in the workspace by issuing the following statement.
SHOW OBJ(NUMVALS 'sales_dims_reg') 152.00
The result of the statement is that the value 152.00 displays which indicates that every value in the 152 cells of the sales_dims_reg variable (even the NA values) are stored as part of the variable.
Example 9-99 Defining a Variable Dimensioned by an Uncompressed Composite
Assume that you have created an analytic workspace with the same dimensions, relations, and aggmap as those in Example 9-98, "Defining a Variable Dimensioned by Two Regular Dimensions". Now assume that you define a composite and a variable dimensioned by that composite by issuing the following statements.
DEFINE COMP_PROD_GEOG COMPOSITE <PROD GEOG> DEFINE SALES_DIMS_COMPOSITE VARIABLE NUMBER (12,2) <COMP_PROD_GEOG <PROD GEOG>>
Assume that you populate sales_dims_composite with the same base values as you did sales_dims_reg in Example 9-98, "Defining a Variable Dimensioned by Two Regular Dimensions", and that you aggregate sales_dims_composite using the same aggmap (that is, sales_aggmap) and issue the following. REPORT statement for the sales_dims_composite variable.
REPORT sales_dims_composite
A report for the sales_dims_composite variable displays the same 152 cells as the report for the sales_dims_reg variable.
-------------------------SALES_DIMS_COMPOSITE--------------------------
---------------------------------PROD----------------------------------
<PROD_DI
<PROD_UP <PROD_UP <PROD_UP <PROD_FA <PROD_FA V: <PROD_TO
C: <PROD_UP C: C: MILY: MILY: VideoDiv P: Total
GEOG ColorTV> C: BWTV> StndVCR> StrVCR> VCR> TV> > Prod>
------------------------- -------- -------- -------- -------- -------- -------- -------- --------
<GEOG_CITY: Canberra> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_CITY: Sydney> NA NA NA NA NA NA NA NA
<GEOG_CITY: Darwin> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_CITY: Brisbane> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_CITY: Adelaide> NA NA NA NA NA NA NA NA
<GEOG_CITY: Hobart> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_CITY: Melbourne> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_CITY: Perth> NA NA NA NA NA NA NA NA
<GEOG_STATE: ACT> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_STATE: NSW> NA NA NA NA NA NA NA NA
<GEOG_STATE: NT> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_STATE: QLD> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_STATE: SA> NA NA NA NA NA NA NA NA
<GEOG_STATE: TAS> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_STATE: VIC> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_STATE: WA> NA NA NA NA NA NA NA NA
<GEOG_AREA: Aust State> 66,779.0 22,000.0 67,111.0 73,065.0 140,176 88,779.0 228,955 228,955
<GEOG_AREA: Aust Terr> 36,460.0 NA 60,460.0 36,111.0 96,571.0 36,460.0 133,031 133,031
<GEOG_CONT: Australia> 103,239 22,000.0 127,571 109,176 236,747 125,239 361,986 361,986
However, because the sales_dims_comp variable is dimensioned by a composite, the 65 cells that display as NA values are not stored in variable. You can confirm the number of physical values stored in the workspace by issuing the following statement that calls the OBJ function with the NUMVALS keyword on sales_dims_composite.
SHOW OBJ(NUMVALS 'sales_dims_composite') 87.00
The result of the statement is that the value 87.00 displays which indicates that only the 87 non-NA values are stored as part of the sales_dims_composite variable.
Example 9-100 Defining a Variable Dimensioned by a Compressed Composite
Assume that you have created an analytic workspace with the same dimensions, relations, and aggmap as those in Example 9-98, "Defining a Variable Dimensioned by Two Regular Dimensions". Now assume that you define a composite and a variable dimensioned by that composite by issuing the following statements.
DEFINE CC_COMP_PROD_GEOG COMPOSITE <PROD GEOG> COMPRESSED DEFINE SALES_DIMS_COMP_COMPOSITE VARIABLE NUMBER (12,0) <CC_COMP_PROD_GEOG <PROD GEOG>>
Assume that you populate sales_dims_composite with the same base values as you did sales_dims_reg in Example 9-98, "Defining a Variable Dimensioned by Two Regular Dimensions", and that you aggregate sales_dims_comp_composite using the same aggmap (that is, sales_aggmap). Now you issue the following statement.
REPORT sales_dims_comp_composite
A report for the sales_dims_comp_comp_composite variable displays the same 152 cells as the report for the sales_dims_reg variable.
-----------------------SALES_DIMS_COMP_COMPOSITE-----------------------
---------------------------------PROD----------------------------------
<PROD_DI
<PROD_UP <PROD_UP <PROD_UP <PROD_FA <PROD_FA V: <PROD_TO
C: <PROD_UP C: C: MILY: MILY: VideoDiv P: Total
GEOG ColorTV> C: BWTV> StndVCR> StrVCR> VCR> TV> > Prod>
------------------------- -------- -------- -------- -------- -------- -------- -------- --------
<GEOG_CITY: Canberra> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_CITY: Sydney> NA NA NA NA NA NA NA NA
<GEOG_CITY: Darwin> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_CITY: Brisbane> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_CITY: Adelaide> NA NA NA NA NA NA NA NA
<GEOG_CITY: Hobart> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_CITY: Melbourne> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_CITY: Perth> NA NA NA NA NA NA NA NA
<GEOG_STATE: ACT> 11,592.0 NA 38,356.0 3,444.00 41,800.0 11,592.0 53,392.0 53,392.0
<GEOG_STATE: NSW> NA NA NA NA NA NA NA NA
<GEOG_STATE: NT> 24,868.0 NA 22,104.0 32,667.0 54,771.0 24,868.0 79,639.0 79,639.0
<GEOG_STATE: QLD> 49,556.0 NA 48,239.0 24,285.0 72,524.0 49,556.0 122,080 122,080
<GEOG_STATE: SA> NA NA NA NA NA NA NA NA
<GEOG_STATE: TAS> 17,223.0 NA 18,872.0 48,780.0 67,652.0 17,223.0 84,875.0 84,875.0
<GEOG_STATE: VIC> NA 22,000.0 NA NA NA 22,000.0 22,000.0 22,000.0
<GEOG_STATE: WA> NA NA NA NA NA NA NA NA
<GEOG_AREA: Aust State> 66,779.0 22,000.0 67,111.0 73,065.0 140,176 88,779.0 228,955 228,955
<GEOG_AREA: Aust Terr> 36,460.0 NA 60,460.0 36,111.0 96,571.0 36,460.0 133,031 133,031
<GEOG_CONT: Australia> 103,239 22,000.0 127,571 109,176 236,747 125,239 361,986 361,986
However, because the sales_dims_comp_comp variable is dimensioned by a compressed composite not all of values in all of the cells are stored in the variable. The 65 cells that display as NA values are not stored in variable, Also, the values that are "passed up" the hierarchy are stored only once — at the lowest level of the hierarchy.
You can confirm the number of physical values stored in the workspace by issuing the following statement that calls the OBJ function with the NUMVALS keyword on sales_dims_comp_composite.
SHOW OBJ(NUMVALS 'sales_dims_comp_composite') 38.00
The result of the statement is that the value 38.00 displays which indicates that only 38 values are stored as part of the sales_dims_comp_composite variable. These values are shown in the following table.
| GEOG | PROD_UPC:ColorTV | PROD_UPC:BWTV | PROD_UPC:StandVCR | PROD_UPC:StrVCR | PROD_FAMILY: VCR | PROD_FAMILY: TV | PROD_DIV: VideoDiv |
|---|---|---|---|---|---|---|---|
| GEOG_CITY: Canberra | 11,592.0 | 38,356.0 | 3,444.00 | 41,800.0 | 53,392.0 | ||
| GEOG_CITY: Darwin | 24,868.0 | 22,104.0 | 32,667.0 | 54,771.0 | 79,639.0 | ||
| GEOG_CITY: Brisbane | 49,556.0 | 48,239.0 | 24,285.0 | 72,524.0 | 122,080 | ||
| GEOG_CITY: Hobart | 17,223.0 | 18,872.0 | 48,780.0 | 67,652.0 | 84,875.0 | ||
| GEOG_CITY: Melbourne | 22,000.0 | ||||||
| GEOG_AREA: Aust State | 66,779.0 | 67,111.0 | 73,065.0 | 140,176 | 88,779.0 | 228,955 | |
| GEOG_AREA: Aust Terr | 36,460.0 | 60,460.0 | 36,111.0 | 96,571.0 | 133,031 | ||
| GEOG_Cont: Australia | 103,239 | 127,57 | 109,176 | 236,747 | 125,239 | 361,986 |
Example 9-101 Defining a Variable with Partitions
Assume that you want to define a sales variable that is dimensioned by product and time and that is partitioned so that each year's data is in a separate partition.
Assume that the analytic workspace contains a products dimension, a time dimension that is a simple hierarchical dimension with three levels of data (day, month, and year), and a time_parentrel relation that represents the child-parent relationships between the values of time.
DEFINE TIME DIMENSION TEXT DEFINE PRODUCT DIMENSION TEXT DEFINE TIME_PARENTREL RELATION TIME <TIME>
For simplicity's sake, in this example the time and product dimensions are only partially populated and have only the following values.
TIME -------------- 2003 2002 Dec2003 Jan2003 Dec2002 Jan2002 31Dec2003 01Dec2003 31Jan2003 01Jan2003 31Dec2002 01Dec2002 31Jan2002 01Jan2002 PRODUCT ------- 00001 00002
To create the partitioned variable, take the following steps:
Define a partition template that defines one partition for each year's data.
DEFINE partition_sales_by_year PARTITION TEMPLATE <time product> -
PARTITION BY LIST (time)(-
PARTITION time_2003 VALUES ('2003', 'Dec2003', 'Jan2003', '31Dec2003', '01Dec2003', '31Jan2003', '01Jan2003') <time product>-
PARTITION time_2002 VALUES ('2002', 'Dec2002', 'Jan2002', '31Dec2002', '01Dec2002', '31Jan2002', '01Jan2002') <time product>)
(note that for simplicity's sake, only some of each year's dimension values are specified for each partition in this example. Typically, when you want to specify a large number of values for a partition, you do not do so within the DEFINE PARTITION STATEMENT statement. Instead, you define the partition without specifying any values, and then later specify the values using MAINTAIN ADD TO PARTITION or MAINTAIN MOVE TO PARTITION statements as illustrated in Example 10-53, "Specifying the Values of a Partition Using Valuesets".)
Define a partitioned sales variable with the partitions defined by the partition template named partition_sales_by_year.
DEFINE sales DECIMAL <partition_sales_by_year<time product>>
After you populate sales with day values, you can issue the following REPORT statement to see which sales values are in which partition.
REPORT DOWN PARTITION(partition_sales_by_year) time product sales PARTITION(PARTITION_SALES_BY_YEAR) TIME PRODUCT SALES ----------------------------------- ---------- ---------- ---------- TIME_2003 2003 00001 NA TIME_2003 Dec2003 00001 NA TIME_2003 Jan2003 00001 NA TIME_2003 31Dec2003 00001 14.78 TIME_2003 01Dec2003 00001 15.52 TIME_2003 31Jan2003 00001 13.61 TIME_2003 01Jan2003 00001 10.39 TIME_2003 2003 00002 NA TIME_2003 Dec2003 00002 NA TIME_2003 Jan2003 00002 NA TIME_2003 31Dec2003 00002 16.05 TIME_2003 01Dec2003 00002 12.27 TIME_2003 31Jan2003 00002 10.83 TIME_2003 01Jan2003 00002 11.07 TIME_2002 2002 00001 NA TIME_2002 Dec2002 00001 NA TIME_2002 Jan2002 00001 NA TIME_2002 31Dec2002 00001 18.80 TIME_2002 01Dec2002 00001 13.64 TIME_2002 31Jan2002 00001 12.41 TIME_2002 01Jan2002 00001 16.97 TIME_2002 2002 00002 NA TIME_2002 Dec2002 00002 NA TIME_2002 Jan2002 00002 NA TIME_2002 31Dec2002 00002 17.47 TIME_2002 01Dec2002 00002 16.58 TIME_2002 31Jan2002 00002 18.94 TIME_2002 01Jan2002 00002 18.36
Example 9-102 Defining a Fixed-Width TEXT Variable
The following statement defines a TEXT variable named lastname dimensioned by employee. Values in lastname are limited to 20 characters, so that longer values are truncated.
DEFINE lastname TEXT <employee> WIDTH 20
Example 9-103 Defining a Variable That Uses a Named B-Tree Composite
Assume that you have the following dimensions in your analytic workspace.
DEFINE month DIMENSION TEXT DEFINE product DIMENSION TEXT DEFINE region DIMENSION TEXT
When your company does promotional marketing for certain products in some but not all regions, then your variable data is sparse along the product and region dimensions. Therefore, suppose you define a composite named proddist, whose base dimensions are product and region. There are dimension-value combinations in the composite only for those values that have data. For example, when you run a promotion for tents but not skis, then the composite includes the tents and region combinations, but not the skis and region combinations.
The following statement creates a b-tree composite named proddist whose base dimensions are product and district, and a variable called promo that is dimensioned by month and proddist.
DEFINE proddist COMPOSITE <product region> DEFINE promo VARIABLE INTEGER <month proddist <product district>>
For simplicity's sake assume that you have only stored the following dimension data in your analytic workspace.
PRODUCT -------------- Tents Skis REGION -------------- Northeast Southwest MONTH -------------- Jan2003 Feb2003 Mar2003 Apr2003 May2003 Jun2003 Jul2003 Aug2003 Sep2003 Oct2003 Nov2003 Dec2003
You decide to run a promotional sales for skis in the Northeast region in the month of September, 2003 at a cost of $5,000. Once you populate promo with this, promo contains only 12 cells—each cell is dimensioned by a value of month and the composite tuple value of <'Skis' 'Northeast'> for proddist. The cell for September 2003 contains the value $5,000, and all of the other cells contain NA. No other NA values are stored in promo; there are no cells are created for any other values of product or region.
Example 9-104 Defining a Variable with Null Tracking
Assume that you have the following objects defined in your analytic workspace.
DEFINE GEOG DIMENSION TEXT LD A dimension with a simple hierarchy for geography DEFINE geog_levellist DIMENSION TEXT LD List of Levels in in the hierarchy of the geog dimension DEFINE GEOG_PARENTREL RELATION GEOG <GEOG> LD Self-relation for geog showing parents of each value in the hierarchy DEFINE GEOG_LEVELREL RELATION GEOG_LEVELLIST <GEOG> LD Level of each dimension member for geog DEFINE product DIMENSION TEXT LD A nonhierarchical dimension DEFINE time DIMENSION TEXT LD A hierarchical text dimension for time DEFINE time_levellist DIMENSION TEXT LD List of Levels in hierarchy of the time dimension DEFINE time_parentrel RELATION time <time> LD A self-relation for time show parents of each value in the hierarchy DEFINE TIME_LEVELREL RELATION TIME_LEVELLIST <TIME> LD Level of each dimension member for time DEFINE prod_geog COMPOSITE <product geog> COMPRESSED
Now assume that you define a sales variable that you want to have dimensioned by time and the prod_geog composite. You want this variable to have null tracking because you eventually populate it using SQL IMPORT and you know that some facts in the fact table have null values. To do this you issue the following statement that includes the WITH NULLTRACKING phrase.
DEFINE sales VARIABLE DECIMAL <time prod_geog<product geog>> WITH NULLTRACKING
For testing purposes, you populate the variable using the RANDOM function. After you populate the variable in this way, you issue a report on it that shows the NA values in the variable.
REPORT DOWN time ACROSS geog: sales
PRODUCT: TVs
-----------------------SALES-----------------------
-----------------------GEOG------------------------
TIME Boston Springfield Hartford All Places
-------------- ------------ ------------ ------------ ------------
2007 NA NA NA NA
2008 NA NA NA NA
All years NA NA NA NA
Jan07 NA NA NA NA
Feb07 NA NA NA NA
Mar07 NA NA NA NA
Apr07 NA NA NA NA
May07 NA NA NA NA
Jun07 NA NA NA NA
Jul07 NA NA NA NA
Aug07 NA NA NA NA
Sep07 NA NA NA NA
Oct07 NA NA NA NA
Nov07 NA NA NA NA
Dec07 NA NA NA NA
Jan08 NA NA NA NA
Feb08 NA NA NA NA
Mar08 NA NA NA NA
Apr08 NA NA NA NA
May08 NA NA NA NA
Jun08 NA NA NA NA
Jul08 NA NA NA NA
Aug08 NA NA NA NA
Sep08 NA NA NA NA
Oct08 NA NA NA NA
Nov08 NA NA NA NA
Dec08 NA NA NA NA
PRODUCT: Radios
-----------------------SALES-----------------------
-----------------------GEOG------------------------
TIME Boston Springfield Hartford All Places
-------------- ------------ ------------ ------------ ------------
2007 NA NA NA NA
2008 NA NA NA NA
All years NA NA NA NA
Jan07 24.59 23.70 33.12 28.65
Feb07 22.78 21.42 26.28 37.06
Mar07 25.74 32.08 22.75 24.62
Apr07 22.23 23.21 20.79 28.68
May07 20.51 29.71 30.35 33.05
Jun07 34.43 35.96 33.85 39.34
Jul07 24.86 38.02 36.78 31.22
Aug07 39.05 21.08 35.80 33.81
Sep07 34.38 21.69 25.04 33.40
Oct07 33.82 39.27 20.28 24.39
Nov07 25.48 23.03 32.45 39.94
Dec07 25.14 30.66 33.75 23.37
Jan08 NA NA NA NA
Feb08 NA NA NA NA
Mar08 NA NA NA NA
Apr08 NA NA NA NA
May08 NA NA NA NA
Jun08 NA NA NA NA
Jul08 NA NA NA NA
Aug08 NA NA NA NA
Sep08 NA NA NA NA
Oct08 NA NA NA NA
Nov08 NA NA NA NA
Dec08 NA NA NA NA
For testing purposes, you also generate a report using the NAFLAG function to retrieve the type of NAs that are in the variable. As the following report shows, because it was populated using RANDOM, all of the NAs are the typical NA values; they are not NA2 values.
REPORT DOWN time ACROSS geog: NAFLAG(sales)
PRODUCT: TVs
-------------------NAFLAG(SALES)-------------------
-----------------------GEOG------------------------
TIME Boston Springfield Hartford All Places
-------------- ------------ ------------ ------------ ------------
2007 1 1 1 1
2008 1 1 1 1
All years 1 1 1 1
Jan07 1 1 1 1
Feb07 1 1 1 1
Mar07 1 1 1 1
Apr07 1 1 1 1
May07 1 1 1 1
Jun07 1 1 1 1
Jul07 1 1 1 1
Aug07 1 1 1 1
Sep07 1 1 1 1
Oct07 1 1 1 1
Nov07 1 1 1 1
Dec07 1 1 1 1
Jan08 1 1 1 1
Feb08 1 1 1 1
Mar08 1 1 1 1
Apr08 1 1 1 1
May08 1 1 1 1
Jun08 1 1 1 1
Jul08 1 1 1 1
Aug08 1 1 1 1
Sep08 1 1 1 1
Oct08 1 1 1 1
Nov08 1 1 1 1
Dec08 1 1 1 1
PRODUCT: Radios
-------------------NAFLAG(SALES)-------------------
-----------------------GEOG------------------------
TIME Boston Springfield Hartford All Places
-------------- ------------ ------------ ------------ ------------
2007 1 1 1 1
2008 1 1 1 1
All years 1 1 1 1
Jan07 0 0 0 0
Feb07 0 0 0 0
Mar07 0 0 0 0
Apr07 0 0 0 0
May07 0 0 0 0
Jun07 0 0 0 0
Jul07 0 0 0 0
Aug07 0 0 0 0
Sep07 0 0 0 0
Oct07 0 0 0 0
Nov07 0 0 0 0
Dec07 0 0 0 0
Jan08 1 1 1 1
Feb08 1 1 1 1
Mar08 1 1 1 1
Apr08 1 1 1 1
May08 1 1 1 1
Jun08 1 1 1 1
Jul08 1 1 1 1
Aug08 1 1 1 1
Sep08 1 1 1 1
Oct08 1 1 1 1
Nov08 1 1 1 1
Dec08 1 1 1 1
Again, for testing purposes, you use the NA function to set an NA2 bit on the variable cells dimensioned by the months of 2008. The following code shows the result of issuing a SHOW of the NA2 function and using that function to set the NA2 bit on the cells dimensioned by the months in 2008.
SHOW NA2 NA LIMIT time TO 'Jan08' 'Feb08' 'Mar08' 'Apr08' 'May08' 'Jun08' 'Jul08' 'Aug08' 'Sep08' 'Oct08' 'Nov08' 'Dec08' saleswithnull= NA2
For brevity's sake assume that your test now issues the following three LIMIT statements and then reports on the sales variable and the NAFLAG function against the sales variable. As the NAFLAG report illustrate, the value Jan08 which is a month to which an NA2 value was assigned returns the value of 2 for NAFLAG, while the NAFLAG report still returns the value of 1 for the year 2008.
LIMIT product to 'Radios'
LIMIT time TO 'Jan08' '2008'
LIMIT geog TO 'Boston' 'All Places'
REPORT DOWN time ACROSS geog: sales
PRODUCT: Radios
----------SALES----------
----------GEOG-----------
TIME Boston All Places
-------------- ------------ ------------
Jan08 NA NA
2008 NA NA
REPORT DOWN time ACROSS geog: NAFLAG(sales)
PRODUCT: Radios
------NAFLAG(SALES)------
----------GEOG-----------
TIME Boston All Places
-------------- ------------ ------------
Jan08 2 2
2008 1 1
Now assume that you issue the following code to remove the NA2 bits from the sales variable.
CHGDFN sales DROP NULLTRACKING
A DESCRIBE of the sales variable shows that it no longer has the WITH NULLTRACKING phrase in its definition while a report of the results of NAFLAG show that the NA values are now just the typical NA values without an NA2 bit.
DESCRIBE sales
DEFINE SALES VARIABLE DECIMAL <TIME PROD_GEOG <PRODUCT GEOG>>
REPORT DOWN time ACROSS geog: sales
PRODUCT: Radios
----------SALES----------
----------GEOG-----------
TIME Boston All Places
-------------- ------------ ------------
Jan08 NA NA
2008 NA NA
"Report on the type of NA values in the sales variable
REPORT DOWN time ACROSS geog: NAFLAG(sales)
PRODUCT: Radios
------NAFLAG(SALES)------
----------GEOG-----------
TIME Boston All Places
-------------- ------------ ------------
Jan08 1 1
2008 1 1
The DEFINE command with the WORKSHEET keyword adds a new worksheet object to an analytic workspace. A worksheet, like a spreadsheet, is a two-dimensional object that is dimensioned by a worksheet row and a worksheet column. It can temporarily store data that you want to transfer between spreadsheet packages and workspace dimensions and variables.
When you first define a worksheet, it does not contain any values. You can populate a worksheet with values from an existing spreadsheet by using an IMPORT (spreadsheet) statement or add or delete values from worksheet row and a worksheet column dimensions with a MAINTAIN statement.
Syntax
DEFINE name WORKSHEET [<column-dim row-dim>] [TEMP] [AW workspace] [SESSION]
Parameters
The name of the object you are defining. For general information about this argument, see the main entry for the DEFINE command.
The object type when you are defining a worksheet.
The names of the dimensions of the worksheet. When you supply this argument, you must give the names of two INTEGER dimensions for column-dim and row-dim. When you omit this argument, the worksheet is dimensioned automatically by WKSCOL and WKSROW. See "Worksheet Dimensions" for more information
Indicates that the worksheet is only temporary. The worksheet is defined in the specified workspace and can contain values during the current session. However, when you update and commit, only the definition of the worksheet is saved. When you end your session or switch to another workspace, the data values are discarded.
The name of an attached workspace in which you want to define the worksheet. The worksheet must be defined in the same workspace as its dimensions. For general information about this argument, see the main entry for the DEFINE command.
Specifies that the object exists only in the current session. When the session ends, the object no longer exists. The behavior specified by SESSION is different than the behavior specified by the TEMP keyword which is that the values are temporary but the object definition remains in the workspace in which you create it.
Usage Notes
Worksheet Dimensions
A worksheet must always dimensioned by two dimensions that represent a worksheet row and a worksheet column. The worksheet row and a worksheet column dimensions can either be automatically created by Oracle OLAP or explicitly created by you:
When you have not created worksheet row and a worksheet column dimensions and specified their names in the column-dim and row-dimt arguments of DEFINE WORKSHEET, Oracle OLAP automatically creates the following dimensions:
For the worksheet row, an INTEGER dimension named WKSROW with values from 1 to 63.
For the worksheet column, an INTEGER dimension named WKSROW with values from 1 to 63.
|
Note: WhenWKSCOL and WKSROW already exist in any attached workspace, Oracle OLAP cannot create them in the current worksheet. In this case, the DEFINE WORKSHEET command fails to create a worksheet with these default dimensions. (Note, also, that WKSCOL and WKSROW do not appear in a worksheet description generated using DESCRIBE.) |
You create worksheet row and a worksheet column dimensions the same way you create any other simple dimension by issuing the following statements:
Create two simple INTEGER dimensions using a DEFINE DIMENSION (simple) statement. One dimension is for row numbers and the other for column numbers.
Using MAINTAIN statements, populate one dimension with integers that represent row numbers and populate with integers that represent column numbers.
Examples
Example 9-105 Defining a Worksheet
These statements define a temporary worksheet named travelexp, which is dimensioned by columns and rows.
DEFINE itemsheet WORKSHEET DEFINE columns INT DIMENSION MAINTAIN columns ADD 5 DEFINE rows INT DIMENSION MAINTAIN rows ADD 10 DEFINE travelexp WORKSHEET <columns rows> TEMPORARY
Example 9-106 Importing Spreadsheet Data
You can import data from a spreadsheet to a worksheet. When all the cells contain the same type of data, you can use UNRAVEL to transfer the data to a variable with one statement. You can also limit the worksheet dimensions to a smaller group of cells and use UNRAVEL to transfer each group to a separate variable. To transfer imported data from a worksheet named itemsheet to a variable named items, you might use the following statements.
DEFINE itemsheet WORKSHEET IMPORT itemsheet FROM dif FILE 'file name' LIMIT WKSCOL TO FIRST 3 LIMIT WKSROW TO FIRST 10 items = UNRAVEL(itemsheet)
The VNF command assigns a value name format (VNF) to the definition of a object with DATE -only data type, including dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR. A VNF is a template that controls the input and display format for DATE -only values. The template can include format specifications for any of the components that identify a time period (day, month, calendar year, fiscal year, and period within a fiscal year).
|
Important: You can only use this statement with dimensions that have a data type ofDATE (that is, dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR).You cannot use this statement for time dimensions that have a datetime data type that corresponds to a SQL datetime data type or dimensions that are implemented as hierarchical dimensions of type TEXT. |
To assign a VNF to a definition, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
Syntax
VNF [template]
Parameters
A text expression that specifies the format for entering and displaying the values of the current dimension. When template is omitted, any existing VNF for the current definition is deleted and the default VNF is used (see Table 2-5, "Default VNFs for DWMQY Dimensions").
|
Note: When you enter a dimension value that does not conform to the VNF, Oracle OLAP attempts to interpret the value as a date. See "Entering Dimension Values as Dates" |
A template contains a code for each component that you use to describe a time period in the current dimension. The code for each component must be preceded by a left angle bracket and followed by a right angle bracket. Basic information about coding a template is provided in Table 10-12, "Basic Codes for Components in VNF Templates", Table 10-13, "Component Combinations Allowed in VNF Templates", and Table 10-14, "Format Styles for Day Available in VNF Templates".
Table 10-12, "Basic Codes for Components in VNF Templates" lists the basic codes for the components of time periods. It uses a sample dimension called MYQTR, which is a QUARTER dimension that ends in June. The examples are from the quarter July 1, 1995 through September 30, 1995. The period code (P) specifies the numeric position of a time period within a fiscal year. You can use the P code with any dimension, but only when you use it along with the FF or FFB code. The B code specifies the beginning period.
Table 10-12 Basic Codes for Components in VNF Templates
| Code | Meaning | Sample Values |
|---|---|---|
|
|
Day of the month on which the period ends |
|
|
|
Month in which the period end |
|
|
|
Calendar year in which the period ends |
|
|
|
Fiscal year that contains the period; the fiscal year is identified by the calendar year in which the fiscal year ends |
|
|
|
Day of the month on which the period begins |
|
|
|
Month in which the period begins |
|
|
|
Calendar year in which the period begins |
|
|
|
Fiscal year that contains the period; the fiscal year is identified by the calendar year in which the fiscal year begins |
|
|
|
The period's numeric position within the fiscal year |
|
|
|
Name of the dimension |
|
Table 10-13, "Component Combinations Allowed in VNF Templates" lists the component combinations you can combine in a VNF for each type of dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR. Notice that you can use the fiscal year codes (FF or FFB) in a template for any dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. However, the fiscal year codes have a special meaning for WEEK dimensions and for phased MONTH, QUARTER, and YEAR dimensions. For other dimensions, the fiscal year is identical to the calendar year. See "Fiscal Years for a Dimension of Type WEEK", "Fiscal Years for Dimensions of Type MONTH, QUARTER, or YEAR", and "Fiscal Years for Dimensions of Type DAY".
Table 10-13 Component Combinations Allowed in VNF Templates
| Type of Dimension | Component Combinations | Sample Values |
|---|---|---|
|
DAY, WEEK, MONTH, QUARTER, YEAR |
|
|
|
MONTH, QUARTER, YEAR |
|
|
|
YEAR |
|
|
Notice that instead of the basic codes listed in Table 10-13, "Component Combinations Allowed in VNF Templates", you can substitute any of the format styles listed in Table 10-14, "Format Styles for Day Available in VNF Templates". You can also include the <NAME> component with any of the component combinations listed in Table 10-13.
You cannot specify a template that includes too few or too many components. The VNF must allow you to input dimension values without ambiguity. See "Coding VNFs to Prevent Ambiguity".
However, if you include only the component combinations that are allowed for a particular type of dimension, and if the VNF permits unambiguous interpretation of input, you have considerable flexibility in specifying a VNF template:
You can specify the components in any order.
You can include text before, after, and between the components.
Instead of the basic codes for the day, month, calendar year, fiscal year, and period that were listed in Table 10-13, "Component Combinations Allowed in VNF Templates", you can substitute the format styles listed in Table 10-14, "Format Styles for Day Available in VNF Templates", Table 10-15, "Format Styles for Month Available in VNF Templates", Table 10-16, "Format Styles for Year Available in VNF Templates", and Table 10-17, "Format Styles for Period Available in VNF Templates".
Table 10-14 Format Styles for Day Available in VNF Templates
| Format | Meaning | Jan 3, 1995 | Nov 12, 2051 |
|---|---|---|---|
|
|
One digit or two digits |
|
|
|
|
Two digits |
|
|
|
|
Space-padded, two digits |
|
|
Table 10-15 Format Styles for Month Available in VNF Templates
| Format | Meaning | Jan 3, 1995 | Nov 12, 2051 |
|---|---|---|---|
<M> | One digit or two digits | 1 | 11 |
<MM> | Two digits | 01 | 11 |
<MS> | Space-padded, two digits | 1 | 11 |
<MTXT> | First three letters, uppercase | JAN | NOV |
<MTXTL> | First three letters, lowercase | jan | nov |
<MTEXT> | Full name, uppercase | JANUARY | NOVEMBER |
|
|
Full name, lowercase |
|
|
Note that for MTXT, MTXTL, MTEXT, and MTEXTL, the actual value displayed depends on the value specified for the MONTHNAMES option:
For MTXT and MTEXT, when the name in the MONTHNAMES option is all lowercase, the entire name is converted to uppercase. Otherwise, the first letter is converted to uppercase and the second and subsequent letters remain in their original case.
For MTXTL and MTEXTL, when the name in the MONTHNAMES option is all uppercase, the entire name is converted to lowercase. Otherwise the first letter is converted to lowercase and the second and subsequent letters remain in their original case.
Usage Notes
Discarding a VNF
When you want to discard a VNF for a dimension and return to using the default VNF, use a CONSIDER statement to make the dimension's definition the current one, and then use a VNF statement with no argument.
Specifying Angle Brackets as Text in a VNF Template
To include an angle bracket as additional text in a template, specify two additional angle brackets for each angle bracket to be included as text (for example, to display the entire value in angle brackets, specify <<<D> <M> <YY>>>).
Month Names
The names used in the month component for the MTXT, MTXTL, MTEXT, and MTEXTL formats are drawn from the current setting of the MONTHNAMES option.
Fiscal Year Codes
You can use a fiscal year code (FF or FFB) in a template for any dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR.
Fiscal Years for a Dimension of Type WEEK
For a dimension of type WEEK, a fiscal year starts on the beginning date of the first period (single-week or multiple-week) that ends in a new calendar year. The fiscal year ends on the final date of the final period that is wholly contained in the calendar year.
This definition holds true, regardless of any beginning or ending date you specify for a WEEK dimension when you define it. However, the fiscal year does take into account the beginning or ending day of the week that you specify (either as a day of the week or as a date).
For example, suppose you define a dimension of type WEEK, named myweek, with single-week periods ending on June 2, 1995 (a Friday). The fiscal year that contains June 2, 1995 begins on December 31, 1994 (a Saturday) and ends on December 29, 1995 (a Friday). When the VNF for myweek has the FF code, this fiscal year is identified as 1995. When the VNF has the FFB code, the fiscal year is identified as 1994.
Fiscal Years for Dimensions of Type MONTH, QUARTER, or YEAR
For a dimension of type MONTH, QUERTER, or YEAR with no beginning or ending phase, the fiscal year is identical to the calendar year.
For a MONTH, QUARTER, or YEAR dimension with a beginning or ending phase, each fiscal year for that dimension begins with the beginning month of the phase and ends with the ending month of the phase.
For example, assume you define a dimension of type MONTH, mymonth, with four-month periods ending in March, each fiscal year begins on April 1 and ends on March 31. When you use the FF code in a VNF for MYMONTH, the fiscal year that starts on April 1, 1995 and ends on March 31, 1996 is m identified as 1996. When you use the FFB code, this fiscal year is identified as 1995.
Fiscal Years for Dimensions of Type DAY
For a dimension of type DAY, the fiscal year is identical to the calendar year.
Out-of-Range Years in a VNF
When a VNF specifies a YY, YYB, FF, or FFB format, and a year outside the range of 1950 to 2049 is to be displayed, the year is displayed in four digits. You must also supply all four digits when you enter the year as input.
Coding VNFs to Prevent Ambiguity
A VNF template must allow you to input dimension values unambiguously. To prevent ambiguity, you must observe the following restrictions when you code a VNF template:
You cannot place a letter (either in a component code or in literal text) immediately after a text component of unspecified length (for example, <MTEXT>, which specifies a full month name of any length).
You cannot place a digit (either in a component code or in literal text) immediately after a numeric component of unspecified length (for example, <M>, which can be one digit or two digits, or <YY>, which can be two digits or four digits).
Coding VNFs for Model Dimensions
When you define a model that contains equations based on a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the VNF for the that dimension must specify dimension values with these format characteristics: the value must start with a letter, and it can contain only letters, digits, underscores, and periods.
Entering Dimension Values
Once you have assigned a VNF to a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you cannot use the default VNF for entering values for that dimension. You must enter values in the format of your VNF or as dates.
Entering Dimension Values in VNF Format
When you enter dimension values in a VNF format, you have the following flexibility:
Letters (either in a component or in literal text) can be either uppercase or lowercase, rather than matching the exact capitalization indicated by the VNF.
When the template specifies <MTXT> or <MTXTL>, which indicate the first three letters of the month name, you can include as much of the month name as you want, from the first three letters to the full month name. When the template specifies <MTEXT> or <MTEXTL>, which indicate a month name of indeterminate length, you can include as much of the name as you want, from the first letter to the full month name. In all cases, however, you must provide enough letters to uniquely match a name in the MONTHNAMES option. For example, to distinguish April from August, you must type at least the first two letters of these names.
You can include as many or as few spaces as you want between components or between text elements in a dimension value.
When the template contains date components that are not essential for identifying a time period for a particular dimension, you can specify any date that falls within the desired time period. For example, the <DD> component of the template <DD><MTXT><YY> is not essential for identifying a period in a MONTH dimension. Therefore, for June 1995 you can specify any date from 01JUN95 through 30JUN95.
Entering Dimension Values as Dates
When you enter a value of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR as a date, you can use any of the input styles listed in the DATEORDER entry. When you specify a full date, Oracle OLAP uses the DATEORDER option to resolve any ambiguities. However, you must specify only the date components that are relevant for the type of dimension you are using:
For a DAY or WEEK dimension, you must enter all the components (day, month, and year).
For a MONTH or QUARTER dimension, you must only enter the month and year components. When you enter an ambiguous value, such as '0106', Oracle OLAP uses the first two characters of the DATEORDER option to resolve the ambiguity. Therefore, the DATEORDER option must be MYD or YMD in this situation.
For a YEAR dimension, you must only enter the year.
Overriding a VNF
For additional flexibility in displaying the values of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can override the dimension's VNF (and the default VNF when the dimension has no VNF of its own) by using the CONVERT function with a VNF argument.
The VNF argument to CONVERT enables you to include all the template codes that are permitted in the template for a VNF statement, but it does not prevent you from specifying too few components or more components than are necessary for identifying a value. In addition, the VNF argument enables you to use additional codes that are not allowed in the VNF template.
Examples
Example 10-173 Assigning a VNF for a Dimension of Type MONTH
The following statements provide a VNF for the existing dimension of type MONTH named month.
CONSIDER month VNF <mtextl>, <yyyy>
Example 10-174 Adding Values to a Dimension of Type Month
The following statements add dimension values in the style of the new VNF, using just enough letters to distinguish the month names rather than the full names that the <MTEXTL> code in the VNF specifies.
MAINTAIN month ADD 'JA, 1995' 'MAR, 1995' Limit month TO LAST 3 REPORT month
These statements produce the following output.
MONTH -------------- January, 1995 February, 1995 March, 1995
Note that Oracle OLAP automatically adds the time periods between the ones you specify in the MAINTAIN statement.
Example 10-175 Assigning a VNF for WEEK
The following statements define a dimension of type WEEK named week, add a VNF to the week definition, and add values to the week dimension.
DEFINE week DIMENSION WEEK VNF Week <p>.<ff> MAINTAIN week ADD '01JAN95' '30JAN95' REPORT week
These statements produce the following output.
WEEK -------------- Week 1.95 Week 2.95 Week 3.95 Week 4.95 Week 5.95
When you use a MAINTAIN statement to add values to the week dimension, you can specify the new values as dates rather than as values that conform to the VNF. However, the VNF is used for displaying output in the desired format.
The AW_COPY procedure copies the object definitions and data from one analytic workspace into a new analytic workspace.
AW_COPY detaches the original workspace and attaches the new workspace first with read/write access.
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Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_COPY (
oldname IN VARCHAR2,
newname IN VARCHAR2,
tablespace IN VARCHAR2 DEFAULT NULL,
partnum IN NUMBER DEFAULT 8);
Parameters
Table B-12 AW_COPY Procedure Parameters
| Parameter | Description |
|---|---|
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The name of an existing analytic workspace that contains object definitions. The workspace cannot be empty. |
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A name for the new analytic workspace that is a copy of oldname. |
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The name of a tablespace in which newname is stored. If this parameter is omitted, then the analytic workspace is created in the user's default tablespace. |
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The number of partitions that are created for the |
Example
The following commands create an analytic workspace named GLOBAL_TRACKING and copies the contents of GLOBAL into it. The workspace is stored in a table named AW$GLOBAL_TRACKING, which has three partitions and is stored in the user's default tablespace.
EXECUTE dbms_aw.aw_attach('global');
EXECUTE dbms_aw.aw_copy('global', 'global_tracking', NULL, 3);
The NUMTOYMNTERVAL function converts a number to a YMINTERVAL literal.
Syntax
NUMTOYMINTERVAL (number, interval_unit)
Parameters
Any NUMBER value or an expression that can be implicitly converted to a NUMBER value.
A text value that specifies the unit of number and must resolve to one of the following string values: YEAR or MONTH.
interval_unit is case insensitive. Leading and trailing values within the parentheses are ignored. By default, the precision of the return is 9.
The PRGTRACE option controls whether each line of a program is recorded in the current outfile or in a debugging file during execution of the program. PRGTRACE is primarily used as a debugging tool to uncover problems by tracing the execution of a program.
OLAP DML programs provided as OLAP DML statements are not traced unless EXPTRACE is set to YES.
When you have used a DBGOUTFILE statement to specify a debugging file, Oracle OLAP sends PRGTRACE output to the debugging file instead of the current outfile.
Data Type
BOOLEAN
Syntax
PRGTRACE = {YES|NO}
Parameters
Oracle OLAP records each line in a program before it is executed.
(Default) Oracle OLAP does not record each line in a program.
Usage Notes
PRGTRACE Output
PRGTRACE records the name of the current program at the beginning of each program line. It includes an equals sign to indicate a compiled line.
(PRG= SALESREP) . . .
It includes a colon to indicate an uncompiled line.
(PRG: SALESREP) . . .
A compiled line is a line that has been translated into an efficient internal form, whereas an uncompiled line has not. Oracle OLAP ordinarily stores lines in compiled form to make programs work more efficiently, especially programs that contain loops.
Uncompiled Program Lines
Oracle OLAP compiles a program before running it. Therefore, the only lines that are marked as uncompiled in the PRGTRACE output are lines that cannot be compiled, such as lines that include ampersand substitution.
Examples
Example 5-93 Tracing Program Execution
Suppose you have a program called salesrep that produces a simple budget report.
DEFINE salesrep PROGRAM PROGRAM PUSH month division line TRAP ON cleanup LIMIT month TO &ARGS LIMIT division TO ALL LIMIT line TO FIRST 1 REPORT DOWN division across month: dec 0 budget cleanup: POP month division line END
When you want to debug this program, you can trace the execution of each of its lines by turning on PRGTRACE and executing the program.
PRGTRACE = yes salesrep FIRST 3
PRGTRACE produces the following output in the current outfile or debugging file.
(PRG= SALESREP) push month division line
(PRG= SALESREP) trap on cleanup
(PRG: SALESREP) limit month to &args
(PRG= SALESREP) limit division to all
(PRG= SALESREP) limit line to first 1
(PRG= SALESREP) report down division across month: dec0 budget
LINE: REVENUE
-------------BUDGET-------------
-------------MONTH--------------
DIVISION JAN95 FEB95 MAR95
-------------- ---------- ---------- ----------
CAMPING 679,149 707,945 780,994
SPORTING 482,771 517,387 525,368
CLOTHING 983,888 1,016,528 992,331
(PRG= SALESREP) cleanup:
(PRG= SALESREP) pop month division line
The LAGABSPCT function returns the percentage difference between the value of a dimensioned variable or expression at a specified offset of a dimension before the current value of that dimension and the current value of the dimensioned variable or expression.
Unlike the LAGPCT function, which always uses the sign of the previous period value in calculating the result, LAGABSPCT uses the absolute value of the previous period value and therefore provides the direction of the percentage difference.
Return Value
DECIMAL value that corresponds to a percent difference or NA when you try to lag before the first period of a time dimension.
Syntax
LAGABSPCT(variable, n, dimension, [STATUS|NOSTATUS|limit-clause] )
Parameters
A variable or expression that is dimensioned by dimension.
The offset (that is, the number of dimension values) to lag. LAGABSPCT uses this value to determine the number of values that LAGABSPCT should go back in dimension to retrieve the value of variable.
Typically, n is a positive INTEGER that indicates the number of time periods (or dimension values) before the current one. When you specify a negative value for n, it indicates the number of time periods after the current one. In this case, LAGABSPCT compares the current value of the time series with a subsequent value.
The dimension along which the lag occurs. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR.
When variable has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want LAGABSPCT to use that dimension, you can omit the dimension argument.
Specifies that LAGABSPCT should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the lag.
(Default) Specifies that LAGABSPCT should use the default status (that is, a list all the dimension values in their original order) when computing the lag.
Specifies that LAGABSPCT should use the default status limited by limit-clause when computing the lag.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
To specify that LAG should use the current status limited by limit-clause when computing the lag, specify a LIMIT function for limit-clause.
Usage Notes
Formula Used by LAGABSPCT
To obtain its results, LAGABSPCT uses the following formula.
(currentvalue - previousvalue) / ABS(previousvalue)
When the Previous Value of the Time Series Used by LAGABSPCT is Zero
When the previous value of the time series used by LAGABSPCT is zero, the result LAGABSPCT returns is determined by the DIVIDEBYZERO option. When DIVIDEBYZERO is set to NO, an error occurs. When DIVIDEBYZERO is set to YES, LAGABSPCT returns NA.
Examples
Example 8-2 Using LAGDIF and LAGABSPCT
Suppose you have a variable called sales that is dimensioned by a hierarchical dimension named time, and dimensions called district and products. Assume also that there is a dimension named timelevels that contains the names of the levels of the time dimension (that is, Month and Year) and a relation named timelevelrel that is dimensioned by time and that has values from timelevels (that is, the related dimension of timelevelrel is timelevels).
You want to compare sales for racquets in Dallas for the January, 2000 and the previous year. You can use the LAG function to display sales from the previous years. You can use the LAGABSPCT function to calculate the percentage difference between the two months and indicate the direction of the change. For example, when sales increase, the percentage difference LAGABSPCT returns is positive. When sales decrease, the percentage difference LAGABSPCT returns is negative.
You can also use the LAGPCT function to calculate the percentage difference between two years. You can multiply the values returned by LAGABSPCT by 100 to display them as percentage points.
The following statements
ALLSTAT
LIMIT product TO 'Racquets'
LIMIT district TO 'Dallas'
LIMIT time TO 'Jan2000'
REPORT DOWN time sales -
HEADING 'Last Jan' LAG(sales, 12, time, time LEVELREL timelevelrel)-
HEADING 'Lagdif' LAGDIF(sales, 12, time, time LEVELREL timelevelrel)-
HEADING 'Lagabspct' rset '%' d 0 LAGABSPCT(sales, 12, time, -
time LEVELREL timelevelrel) * 100
produce this report.
DISTRICT: Dallas
------------------PRODUCT------------------
-----------------Racquets------------------
TIME SALES Last Jan Lagdif Lagabspct
-------------- ---------- ---------- ---------- ----------
Jan2000 125,879.86 118,686.75 7,193.11 6%
The TRIGGERMAXDEPTH option determines the maximum number of $NATRIGGER property expressions that Oracle OLAP can execute simultaneously.
Data Type
INTEGER
Syntax
TRIGGERMAXDEPTH = n
Parameters
An INTEGER expression that specifies the maximum number of $NATRIGGER property expressions that can execute simultaneously. The default value is 50.
Usage Notes
About the $NATRIGGER Property
The TRIGGERMAXDEPTH option works with the $NATRIGGER property of a variable.
Recursive Triggers
While a $NATRIGGER expression is executing, it cannot be invoked again by a formula, program, or other $NATRIGGER expression that it invokes unless the RECURSIVE option is set to YES. The TRIGGERMAXDEPTH option governs the depth of recursion of $NATRIGGER expressions and prevents infinite recursions or excessively deep recursions, which can cause Oracle OLAP to malfunction.
Examples
Example 5-108 Setting the Maximum Trigger Depth
This example sets the maximum trigger depth, exceeds it, then sets the depth to a higher value. Usually the TRIGGERMAXDEPTH value would be much higher than 2, which is used in this example. The default value is 50.
DEFINE d1 INTEGER DIMENSION MAINTAIN d1 ADD 2 DEFINE v1 DECIMAL <d1> PROPERTY '$NATRIGGER' 'v2 + 1' DEFINE v2 DECIMAL <d1> PROPERTY '$NATRIGGER' 'v3 + 1' DEFINE v3 DECIMAL <d1> PROPERTY '$NATRIGGER' 'v4 + 1' DEFINE v4 DECIMAL <d1> v4(d1 1) = 333.3 RECURSIVE = YES TRIGGERMAXDEPTH = 2 SHOW v1
The preceding statements produce the following output.
ERROR: Depth of NA trigger calls exceeds allowable (maximum depth 2)
The following statements set the maximum trigger depth to a higher value and show the value of the variable.
TRIGGERMAXDEPTH = 3 SHOW v1
The preceding statements produce the following output.
336.3
The LENGTH functions return the length of a text expression including trailing blanks. LENGTH calculates length using characters as defined by the input character set. LENGTHB uses bytes instead of characters. LENGTHC uses Unicode complete characters.
Return Value
NUMBER or NA if the expression is an empty string or NA
Syntax
{ LENGTH | LENGTHB | LENGTHC}(char)
Parameters
A text expression.
The LINENUM option contains the current line number of the output. Its value is incremented automatically as output lines are produced. The LINENUM option is meaningful only when PAGING is set to YES and only for output from commands such as REPORT and LISTNAMES.
Data Type
INTEGER
Syntax
LINENUM = n
Parameters
An INTEGER expression. Normally you do not want to set LINENUM explicitly, but just want to check its current value.
Usage Notes
Starting a New Page
When PAGING is set to YES, LINENUM increases by 1 after each line of output. When LINENUM equals PAGESIZE minus BMARGIN, a new page automatically begins.
At the beginning of each new page, LINENUM is automatically reset to 1.
LINENUM Compared to PAGESIZE
Since the lines in the bottom margin are included in PAGESIZE, LINENUM can never reach PAGESIZE when BMARGIN is set to a number greater than 0 (zero).
The Effect of PAGING on LINENUM
When PAGING is set to NO (its default), the value of the LINENUM option continues to increment as more output lines are produced. When you set PAGING to YES, LINENUM is set to 1 and it begins counting lines on the current page.
The Effect of OUTFILE on LINENUM
When you use an OUTFILE statement to direct output to a file, LINENUM is set to 1 for the file. When you use OUTFILE with the EOF keyword to redirect output to the default outfile, LINENUM contains the value that it last held for the default outfile.
Sending LINENUM in Output
When you produce output that contains the value of LINENUM, and a new page is created by this output, the value of LINENUM is recorded as 1 when your output consists of a single line. However, when the output is a multiline value, the value of LINENUM may be recorded as a value that is larger than PAGESIZE.
Examples
Example 5-46 Keeping the Heading Size Constant
Suppose you have a heading that varies between one and two lines from page to page. Regardless of this variation, you want to draw a line across the page at a constant position below the heading. Include the following statement in the page heading program that you use with your report program.
WHILE LINENUM LT 5 BLANK ROW W LSIZE ROW CENTER '--------------------------------'
The UNRAVEL function is used with an assignment statement to copy the values of an expression into the cells of a variable when the dimensions of the expression are different from the dimensions of the variable.
An assignment statement created using an assignment statement assigns the values obtained from UNRAVEL by looping over the status of the dimensions of the target variable. The first dimension listed in the variable's definition varies the fastest. UNRAVEL obtains the values of the expression in the same way, looping over the status of the dimensions of the expression with the first dimension varying the fastest. You can alter the order in which UNRAVEL obtains its values by specifying the dimensions over which to loop.
Return Value
The data type returned by UNRAVEL is the data type of the values specified by the expression.
Syntax
UNRAVEL(expression [dimension1...])
Parameters
The expression whose values are to be copied.
Specifies one or more dimensions over which to loop; the dimension specified first varies fastest as the data is unraveled.
Specifying dimensions in UNRAVEL overrides the default looping order and the extent to which the expression is unraveled. By default, unraveling extends through all the dimensions of the expression. However, when you specify some but not all the dimensions of the expression, any dimensions you have not specified do not unravel. Instead, the unraveled values include only the first value of each of the omitted dimensions.
Usage Notes
Moving Worksheet Data
One common use of UNRAVEL is to move data from a worksheet to a variable, because the worksheet usually does not have the same dimensions as the variable. See Example 8-157, "Copying Data from a Worksheet to a Variable".
Filling Extra Target Cells
When there are still more cells in the target for the assignment statement (created using an assignment statement) to fill after it has used the last value from the expression, UNRAVEL starts over at the first value again.
Setting Status
Since the order in which unraveled values are assigned depends on the current status of the dimensions of both the variable and the expression, ensure that the appropriate LIMIT commands have been given so that the cells match up correctly.
Assigning Data Values
See SET for information on how data values are assigned.
Examples
Example 8-157 Copying Data from a Worksheet to a Variable
In an analytic workspace, you have imported some product price data from a spreadsheet into a worksheet. You now want to transfer that data to a variable called newprice. You can produce a report of a worksheet, called pricedata, with these statements.
LIMIT wksrow TO 1 TO 6 LIMIT wkscol TO 1 2 3 REPORT pricedata
This is the report.
-----------PRICEDATA------------
-------------WKSCOL-------------
WKSROW 1 2 3
-------------- ---------- ---------- ----------
1 Jan95 Jan96
2 Tents 191.39 194.00
3 Canoes 279.92 300.00
4 Racquets 83.34 85.00
5 Sportswear 107.90 110.00
6 Footwear 183.18 195.00
As you can see, row 1 contains month labels, while column 1 contains product labels. The variable newprice is dimensioned by month and product, as shown in its definition.
DEFINE newprice VARIABLE DECIMAL <month product> LD Wholesale Unit Selling Price
Even though the worksheet has different dimensions (wkscol and wksrow) than newprice, the data contained in it is well organized for transferring to the variable.
However, you do not want to take data from all the rows and columns in the worksheet, so limit wkscol and wksrow to the rows and columns that contain the price data itself.
LIMIT wkscol TO 2 3 LIMIT wksrow TO 2 TO 6
Also, you only want to set values into the variable newprice for January 1995 and January 1996. So first limit month to these values, then type an assignment statement using UNRAVEL to move the values from the worksheet to the variable.
LIMIT month TO 'Jan95' 'Jan96' newprice = UNRAVEL(pricedata)
You do not have to specify dimensions in the UNRAVEL function because wkscol is the fastest varying dimension. Consequently, both months unravel for the first product, then both months for the second product. Since the fastest-varying dimension of the variable is month, SET assigns values to the variable in the same order.
A report of newprice looks like this.
------NEWPRICE-------
--------MONTH--------
PRODUCT Jan95 Jan96
-------------- ---------- ----------
Tents 191.39 194.00
Canoes 279.92 300.00
Racquets 83.34 85.00
Sportswear 107.90 110.00
Footwear 183.18 195.00
The PERMIT command lets you grant or deny read-only and read/write access permission for workspace objects and for specific values of dimensions and dimensioned objects. You can also use PERMIT to grant or deny permission to maintain dimensions and to change permission for workspace objects.
In general, access permissions that you set for a dimension are meaningful not only for that dimension, but also for the objects dimensioned by that dimension as explained more fully in "How Dimension Permission Interacts with Permissions for Other Objects". Access permissions that you set for other objects are limited in scope to that particular object. Various conditions determine when permission changes take effect as discussed in "When Permission Changes Take Effect"
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See also: "Important Considerations Before You Change the Permissions of an Object", "Startup Programs", "Permission Programs", PERMITERROR option, and PERMITRESET command. |
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Tip: The PERMIT command assigns permission to the object most recently defined or considered. When the definition of the object is not the current one, first use a CONSIDER statement before issuing PERMIT commands for the object |
Syntax
PERMIT {READ|WRITE|MNT|PERMIT} [WHEN permission-condition...]
Parameters
Depending on the permission conditions, grants or restricts permission to read all of the values of an object or only certain values in a dimension or dimensioned object.
Note that restricting read permission for a dimension also restricts maintain permission for that dimension. Also, when you grant read permission for an object, write permission is also allowed for the values you can read, unless you deny it with an explicit PERMIT WRITE statement.
Depending on the permission conditions, grants or restricts permission to modify any of the values of an object or only certain values of a dimensioned object.
Restricting write permission for an object does not necessarily mean that the object is totally unavailable. For example, when you have restricted write access to a calculation specification (that is, an aggmap object, program, model, or formula, you can still execute the object— you just cannot edit the contents of the calculation specification.
Oracle OLAP does not prevent you from granting write permission for values that you cannot read within a dimensioned object. When you have both a PERMIT READ and a PERMIT WRITE statement for a dimensioned object, and some values which satisfy the permission conditions for write do not fall within the subset of values which satisfy the permission conditions for read, then those values may be modified but not seen.
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Tip: Write permission is not meaningful for dimensions— except to provide write access to objects dimensioned by the dimension. To grant or restrict the ability to add values to a dimension, issue PERMIT MNT statements for the dimension instead. |
Depending on the permission conditions, grants or restricts permission to maintain a dimension.
Note that you cannot grant maintain permission to a dimension for which you have restricted read permission. Oracle OLAP automatically denies maintain permission for a dimension when there is restricted read permission for that dimension.
Depending on the permission conditions, grants or restricts permission to use the PERMIT command to change the read, write, maintain, or permit permission for the object.
Note that unless explicitly you explicitly deny permit permission for an object, permit permission is allowed for an object no matter what other permissions are set for that object.
When you omit the WHEN clause and execute a PERMIT READ, PERMIT WRITE, or PERMIT MNT statement, Oracle OLAP restores full read, write, or maintain permission to the object.
When you include the WHEN clause, the conditions for granting read, write, maintain, or permit permission consist of one or more Boolean expressions depending on whether or not the object has dimensionality, the type of permission you are setting and, for read and write permissions, whether or not the object has dimensionality:
When you are specifying permit permission, maintain permission, or read or write permission that applies to an object without dimensionality or when you want the read or write permissions to apply to all the values of a dimensioned object, specify the permission condition as a Boolean expression that evaluates to a single value. (Not that if you do specify a dimensioned Boolean expression to specify permissions for an object without dimensionality or when you are specifying permit or maintain permission, then PERMIT uses the first value in status.)
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Tip: Avoid specifying a Boolean value as a permission condition (for example,YES or NO) for a PERMIT PERMIT statement. Instead specify the permission condition as a Boolean variable, a function that returns a Boolean result, or a Boolean value calculated by comparison operators. In this way, when permit permission has been denied, you can restore it by setting the value of the Boolean and executing a PERMITRESET statement. If you ever do lock up an object and are unable to modify its permission, you can specify permit permission for it in the workspace permission program for that workspace, then detach and reattach the workspace. |
If you are specifying read or write permission that applies to individual dimension values or to slices of a dimensioned object, specify one permission condition for each dimension of interest. In this case, the WHEN clause has the following syntax and each dimensioned permission condition consists of a Boolean expression dimensioned by a dimension of the object.
Use the UNION phrase to efficiently access the union of several symmetric subcubes of a multidimensional variable.
Note that if a Boolean expression for a dimensioned permission condition has any extra dimensions in addition to an object dimension, PERMIT takes the first value in status to determine which column of Boolean values to use. The intersection of the YES values for each dimension (a logical AND of the conditions) is the subset of values within the object to which the permission applies. When any of the object dimensions are not represented by a dimensioned permission condition, then Oracle OLAP assumes YES for all those dimension values.
Usage Notes
Important Considerations Before You Change the Permissions of an Object
Keep the following important considerations in mind before you change the permissions of an object:
You must have permit permission for an object to issue PERMIT commands against it.
Do not lock out the DBA user, who must always have access to everything in the workspace.
Issuing PERMIT statements against an INTEGER dimension may result in undesired behavior. Dimensions with an INTEGER data type have values identified by their numeric position. PERMIT renumbers INTEGER dimensions to keep the normal sequence of INTEGER values (1, 2, 3, ...). When you must use PERMIT to change the default access rights for an INTEGER dimension and this behavior is not desirable, redefine the dimension with a different, non-integer data type.
When Permission Changes Take Effect
Within PERMIT_READ and PERMIT_WRITE programs, permissions ares only evaluated when you issue an explicit PERMIT or PERMITRESET statement and then reference the targeted object.
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Note: AW ATTACH automatically executes a PERMITRESET immediately after executing an analytic workspace permission program. Executing PERMITRESET causes the workspace to be attached with all permission implemented |
Once an analytic workspace is attached and any PERMIT_READ and PERMIT_WRITE programs have executed, permission changes specified by a PERMIT statement take effect:
When a PERMITRESET statement executes.
When you are targeting any object (except a dimension), and the permission condition consists of a single Boolean variable, any changes to that Boolean variable affect the permission immediately. (You never have to execute a PERMITRESET in this case.)
In other situations, if you do not issue a PERMITRESET statement, permission are evaluated upon next reference to the object.
|
Note: The OBJ function is an exception to this rule. Because OBJ does not load the object into memory, it does not reflect any changes to the object's permission since the last time it was loaded. When you want OBJ to provide information based on new permission criteria, execute a LOAD statement before the OBJ statement. |
When the only PERMIT Statement for an Object is a PERMIT WRITE Statement
When the only PERMIT statement for an object is a PERMIT WRITE, then read permission is provided by default for the object. The default read permission is provided independent of the value of the permission condition(s) for the PERMIT WRITE statement. Consequently, a PERMIT WRITE with a single-cell permission condition which evaluates to NO provides read-only access to an nondimensional object or to all the values of a dimensioned object.
When the only PERMIT statement for an object is a PERMIT WRITE with dimensioned permission conditions, it designates some values for read/write access and the remaining values for read-only access. See Example 10-73, "Variable Permission".
How Dimension Permission Interacts with Permissions for Other Objects
All dimensioned data is affected by the read permission on its dimensions. The dimension values that satisfy the read permission condition determine the default status for the dimension. The values of dimensioned objects that correspond to dimension values without read permission are inaccessible.
However, in order for write permission associated with a dimension to apply to other objects dimensioned by it, there must be at least one PERMIT statement associated with the dimensioned object.
When you want a dimensioned object to inherit write permission from its dimensions, but you do not want it to have permission of its own, which could interact with the dimension permission, you can simply use a PERMIT READ with a single-cell permission condition that evaluates to YES.
When you want a dimensioned object to inherit write permission from its dimensions, and you also want it to have permissions of its own, understand how dimension permission interacts with individual object permissions before setting them.
Dimension permission interacts with permission for most of the objects dimensioned by it in the following ways:
The access permissions of a dimension apply to all dimension surrogates defined for that dimension. You cannot use a PERMIT statement on a dimension surrogate.
When there is read or write permission associated with a dimension, but no permission restriction associated with an object dimensioned by that dimension, then the permission for the dimensioned object is the same as the dimension permission.
When there is read permission associated with both the dimension and the dimensioned object, Oracle OLAP determines the values with read permission in the object by taking the intersection of the values with read permission in the dimension and the values with read permission in the object.
When there is write permission associated with both the dimension and the dimensioned object, Oracle OLAP determines the values with write permission in the object by taking the intersection of the values with read permission in the dimension, the values with write permission in the dimension, and the values with write permission in the object.
However, this is not the case for relations and valuesets. When there is restricted write permission for a dimension of a relation or a valueset, it does not affect relations and valuesets dimensioned by that dimension.
Determining Permission
The permission associated with an object is provided, like an LD, when you describe it using a DESCRIBE statement. The only exception is when you are denied permit permission for the object. In this case, no permission is provided when you describe it.
Advantages of PERMIT Over LIMIT as a Tool for Scoping
As a tool for scoping within application programs, PERMIT has several advantages over the LIMIT command. To restrict the scope of a dimensioned object according to a Boolean expression, you have to use two LIMIT statements, a LIMIT and a LIMITKEEP. You only need one PERMIT statement to do the same thing. Moreover, application users cannot change the restricted scope set by PERMIT commands in application programs. Application users can easily change the scope set by LIMIT commands in application programs simply by executing more LIMIT commands.
Handling Permission Violations
You can use the PERMITERROR option to control the way Oracle OLAP handles attempted violations of the permission established by PERMIT commands for variables. The default value of PERMITERROR is YES, meaning that Oracle OLAP signals an error when a user attempts to access a value for which permission is denied. When you set PERMITERROR to NO, Oracle OLAP simply denies access without signaling an error condition which is useful when you want to do a report of a dimensioned variable for which you have partial permission without limiting the dimensions to the permitted values up front. With PERMITERROR set to NO, values for which you do not have read permission appear as NA values in the report.
Examples
Example 10-73 Variable Permission
For a variable sales dimensioned by month, product, and district, you might have three dimensioned permission conditions in the form of three variables as illustrated in the following report.
MONTH.BOOL<MONTH> PROD.BOOL<PRODUCT> DISTRICT.BOOL<DISTRICT> ----------------- ------------------ ----------------------- Jan95 NO Tents YES Boston NO Feb95 YES Canoes YES Atlanta NO Mar95 NO Racquets NO Chicago YES ... ... ... ... ... ...
When the YES values shown in the preceding example are the only YES values in the permission conditions, the following PERMIT statement provides read/write access to sales data for tents and canoes sold in Chicago in Feb95. In the absence of a PERMIT READ statement for sales, Oracle OLAP provides read-only permission for all the other values of sales.
PERMIT WRITE WHEN district.bool BY prod.bool BY month.bool
You can restore full write permission with the following PERMIT statement.
PERMIT WRITE
When there is no restricted write permission for sales, the following PERMIT statement provides read/write access to sales data for tents and canoes sold in Chicago in Feb95, and it causes all other values of sales to be invisible.
PERMIT READ WHEN district.bool BY prod.bool BY month.bool
Example 10-74 Dimensioned Permission Condition
To restrict access to the product dimension you need a permission condition dimensioned by product. However, when the permission condition has a second dimension, say authority, PERMIT selects the BOOLEAN values that pertain to product based on the first value in status of authority. When you restrict read permission on the authority dimension to one value, PERMIT uses that value to determine the BOOLEAN values of the permission condition for product. The REPORT commands produce the output that follows them.
DEFINE authority DIMENSION TEXT
MAINTAIN authority ADD OTHER DBA
DEFINE prod_authority VARIABLE BOOLEAN <product authority>
...
" Assign values to the variable
...
REPORT prod_authority
-----------------PROD_AUTHORITY------------------
--------------------PRODUCT----------------------
AUTHORITY Tents Canoes Racquets Sportswear Footwear
--------- ----- ------ -------- ---------- --------
Other NO NO YES YES YES
Dba YES YES YES YES YES
CONSIDER product
PERMIT READ WHEN prod_authority
PERMITERROR = NO
RPEPORT product
PRODUCT
-------------
Racquets
Sportswear
Footwear
CONSIDER authority
PERMIT READ WHEN AUTHORITY EQ 'dba'
PERMITRESET
Report product
PRODUCT
-------------
Tents
Canoes
Racquets
Sportswear
Footwear
Example 10-75 User-Defined Boolean Function
In the following example, usercheck is a user-defined Boolean function that checks the current value of the variable thisuser against a list of user IDs. usercheck returns NO when the current value of thisuser is not in the list. The following PERMIT statement applied to the sales variable provides read-only access to all values of sales when usercheck returns NO. It provides read/write access to all values of sales when usercheck returns YES.
PERMIT WRITE WHEN usercheck(thisuser)
The following PERMIT statement, applied to the variable price, provides full access to all values of price when usercheck returns YES. When it returns NO, it denies all access to the price variable.
PERMIT READ WHEN usercheck(thisuser)
Example 10-76 Individual Cells
When you want to prevent access to one particular sales figure, say for racquets in Boston in March of 1997, you can create a Boolean variable and use it in a PERMIT statement as illustrated in the following statements.
DEFINE sales.bool VARIABLE BOOLEAN <month product district> sales.bool = yes LIMIT month TO 'Mar97' LIMIT product TO 'Racquets' LIMIT district TO 'Boston' sales.bool = no CONSIDER sales PERMIT READ WHEN sales.bool
Example 10-77 Individual Dimension Values
The following PERMIT commands applied to the district dimension prevent access to all dimension values except Boston and Atlanta. They provide read/write access for all data related to Boston and read-only access for all data related to Atlanta. They also prevent anyone with a user ID not allowed by the function usercheck (see Example 10-75, "User-Defined Boolean Function") from modifying the permission for district.
PERMIT READ WHEN district EQ 'Boston' OR district EQ 'Atlanta' PERMIT WRITE WHEN district EQ 'Boston' PERMIT PERMIT WHEN usercheck(thisuser)
The MONTHNAMES option holds the list of valid names for months that is used in handling values with a DATE-only data type and values of dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR. The list of names is used to interpret dates that are entered and to format dates that are displayed or converted to text values.
The MONTHNAMES list is used when you enter a date that includes a month name or abbreviation. See the DATEFORMAT option for a discussion of methods for entering DATE-only values. The MONTHNAMES list is also used when you display or convert a date using the <MT>, <MTXT>, <MTXTL>, <MTEXT>, or <MTEXTL> formats. These formats are specified in the DATEFORMAT option. When you have multiple sets of month names, Oracle OLAP chooses the synonym whose number of characters and capitalization pattern best match the DATEFORMAT specification.
Data Type
TEXT
Syntax
MONTHNAMES = name-list
Parameters
A multiline text expression that lists the names of the 12 months of the year. Each month name occupies a separate line. Regardless of which month you are treating as the first month of the year, the list must begin with the name for January. The default value is the list of English month names, all in capital letters.
You can include more than 1 set of 12 names in your list. Any name in the list is considered a valid name for input. The thirteenth name is a synonym for the first name, the fourteenth name is a synonym for the second name, and so on.
Examples
Example 5-65 Specifying Two Sets of Month Names
The following statement creates two sets of month names, one in uppercase English and the second in lowercase French.
MONTHNAMES = - 'JANUARY - ... DECEMBER - janvier - ... decembre'
Example 5-66 Specifying English Month Names
The following statements define a DATE-only variable, assign a value to that variable, assign a setting to DATEFORMAT, and send the output to the current outfile. The DATEFORMAT value includes <MTEXT>, which specifies uppercase, so the English month names are used.
DEFINE datevar DATE datevar = '27feb98' DATEFORMAT = '<MTEXT> <D>, <YYYY>' SHOW datevar
These statements produce the following output.
FEBRUARY 27, 1998
Example 5-67 Specifying French Month Names
The following statements assign a new setting to DATEFORMAT and send the output to the current outfile. The DATEFORMAT value includes <MTEXTL>, which specifies lowercase, so the French month names are used.
DATEFORMAT = 'le <D> <MTEXTL> <YYYY>' SHOW datevar
These statements produce the following output.
le 27 fevrier 1998
The LOCALTIMESTAMP function returns the current date and time in the session time zone as a value of data type TIMESTAMP.
When you want to retrieve the current date and time in the session time zone as a TIMESTAMP_TZ value, use the CURRENT_TIMESTAMP function.
Return Values
TIMESTAMP
Syntax
LOCALTIMESTAMP [ (timestamp-precision) ]
ARGUMENTS
Specifies the fractional second precision of the time value returned
Examples
The REMOVE_DIMENSION_MEMBER program removes an OLAP cube dimension member from one or more hierarchies, or entirely removes an OLAP cube dimension member from a cube dimension.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL REMOVE_DIMENSION_MEMBER(member_id, logical_dim, hier_list, [ auto_compile ])
Parameters
Since REMOVE_DIMENSION_MEMBER is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the member that you want to remove from the cube dimension hierarchies.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A multi-line text expression consisting of the Oracle data dictionary names of all of the hierarchies from which you want to remove the cube dimension member. Specify one hierarchy name per line.
To entirely remove a member from the dimension, specify NA.
A Boolean expression that specifies whether or not you want related analytic workspace objects (for example, changes to the parent relation) to be updated immediately.
The default value is TRUE in which case all of the changes to the analytic workspace that are needed to remove the cube dimension member happen now.
Specify FALSE only when, for performance reasons, you want to make a bulk set of changes before issuing a compile. In this case, you need to explicitly compile the cube dimension before the values of the analytic workspace objects take effect as described in "Explicitly Compiling a Cube Dimension".
|
Note: Regardless of the value that you specify for this argument, the new member is always immediately removed from the dimension -- even when an error is signaled during compilation. |
Examples
Example 10-98 Removing OLAP Cube Dimension Members From a Hierarchy
Execute the following SQL statement that reports on the values of the my_time cube dimension.
select dim_key||' '||level_name||' '||parent from my_time_lvl_hier_view order by dim_key asc;
The values this statement returns are shown below.
DIM_KEY||''||LEVEL_NAME||''||PARENT ------------------------------------------------------------------------------- L1_0 L1 L1_1 L1 L1_2 L1 L2_1 L2 L1_1 L2_2 L2 L1_1 L2_3 L2 L1_2 L3_1 L3 L2_1 L3_2 L3 L2_1 L3_3 L3 L2_2 L3_4 L3 L2_2 L3_5 L3 L2_2 L3_6 L3 L2_3 12 rows selected.
Execute the following SQL statement that calls a user-written program named remove_12_1 OLAP DML program.
exec dbms_aw.execute('call my_util_aw!remove_l2_1');
The contents of the user-written remove_12_1 program are shown below.
|
Note: The program uses:
|
DEFINE REMOVE_L2_1 PROGRAM
PROGRAM
VARIABLE _aw_dim text
VARIABLE _parentrel text
VARIABLE _members text
VARIABLE _member text
VARIABLE _i integer
" Removes L2_1 and descendants
_aw_dim = OBJORG(DIM 'my_time')
_parentrel = OBJORG(PARENTREL 'my_time')
LIMIT &_aw_dim TO 'L2_1'
LIMIT &_aw_dim ADD DESCENDANTS USING &_parentrel
_members = VALUES(&_aw_dim)
_i = 1
WHILE _i LE NUMLINES(_members)
DO
_member = EXTLINES(_members, _i, 1)
_i = _i + 1
CALL REMOVE_DIMENSION_MEMBER(_member, 'my_time', NA, NO)
DOEND
UPDATE
COMMIT
END
Execute the following SQL statement (the same statement as in Step 1) that shows the values of the my_time cube dimension after removal.
select dim_key||' '||level_name||' '||parent
from my_time_lvl_hier_view
order by dim_key asc;
The values after removal are shown below.
DIM_KEY||''||LEVEL_NAME||''||PARENT -------------------------------------------------------------------------------- L1_0 L1 L1_1 L1 L1_2 L1 L2_2 L2 L1_1 L2_3 L2 L1_2 L3_3 L3 L2_2 L3_4 L3 L2_2 L3_5 L3 L2_2 L3_6 L3 L2_3 9 rows selected.
The ANY function returns YES when any values of a Boolean expression are TRUE, or NO when none of the values of the expression are TRUE.
Return Value
BOOLEAN.
Syntax
ANY(boolean-expression [CACHE] [dimension ...] )
Parameters
The Boolean expression to be evaluated
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of boolean-expression and another dimension that you want as a dimension of the result.
By default, ANY returns a single YES or NO value. When you indicate one or more dimensions for the result, ANY tests for TRUE values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of boolean-expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of boolean-expression, but, instead, is dimension that is related to a dimension of boolean-expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
The Effect of NASKIP on ANY
ANY is affected by the NASKIP option. When NASKIP is set to YES (the default), ANY ignores NA values and returns YES when any of the values of the expression that are not NA are TRUE and returns NO when none of the values are TRUE. When NASKIP is set to NO, ANY returns NA when any value of the expression is NA. When all the values of the expression are NA, ANY returns NA for either setting of NASKIP.
Data with a Type of DAY, WEEK, MONTH, QUARTER, or YEAR
When boolean-expression is dimensioned by a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other dimension of this type as a related dimension. Oracle OLAP uses the implicit relation between these dimensions. To control the mapping of one of these dimension to another (for example, from weeks to months), you can define an explicit relation between the dimensions and specify the name of the relation as the dimension argument to the ANY function.
For each time period in the related dimension, Oracle OLAP tests the data values for all the source time periods that end in the target time period. This method is used regardless of which dimension has the more aggregate time periods.
Examples
Example 7-14 Testing for Any True Values by District
Suppose you want to find out which districts had at least one month with sales greater than $150,000 for sportswear. You use the ANY function to determine whether the Boolean expression (sales GT 150000) is TRUE for any month. To have the result dimensioned by district, specify district as the second argument in the ANY function.
LIMIT product TO 'SPORTSWEAR' REPORT HEADING 'High Sales' ANY(sales GT 150000, district)
The preceding statements produce the following output.
DISTRICT High Sales -------------- ---------- Boston NO Atlanta YES Chicago NO Dallas YES Denver NO Seattle NO
Example 7-15 Testing for Any True Values by Region
You might also want to find out which regions had at least one month in which at least one district had sportswear sales greater than $150,000. Since the region dimension is related to the district dimension, you can specify region instead of district as a dimension for the results of ANY.
report heading 'High Sales' any(sales gt 150000, region)
The preceding statement produces the following output.
REGION High Sales -------------- ---------- East YES Central YES west NO
This function returns the session log from the last execution of the INTERP or INTERPCLOB functions in this package.
To print the session log returned by this function, use the DBMS_AW.PRINTLOG procedure.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
GETLOG()
RETURN CLOB;
Returns
The session log from the latest call to INTERP or INTERPCLOB.
Example
The following example shows the session log returned by a call to INTERP, then shows the identical session log returned by GETLOG.
EXECUTE dbms_aw.printlog(dbms_aw.interp('AW ATTACH global; REPORT units_cube')); UNITS_CUBE -------------- TIME CUSTOMER PRODUCT CHANNEL EXECUTE dbms_aw.printlog(dbms_aw.getlog()); UNITS_CUBE -------------- TIME CUSTOMER PRODUCT CHANNEL
The FILEOPEN function opens a file, assigns it a fileunit number (an arbitrary INTEGER), and returns that number. You use the fileunit number, rather than a file name, in any further references to the file. When Oracle OLAP cannot open the file, an error occurs.
Return Value
INTEGER
Syntax
FILEOPEN(file-name {READ|WRITE|APPEND} [BINARY]) [NLS_CHARSET charset-exp]
Parameters
A text expression specifying the name of the file you want to open. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the Database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
(Abbreviated R) Opens the file for reading.
(Abbreviated W) Opens the file for writing. File access begins at the top of the file. Therefore, opening an existing file in WRITE mode erases its contents completely even before anything is written to the file.
Opens the file for writing. File access begins at the end of the file, and data is added to the existing contents.
Opens a binary-format file (a file with packed or binary data). When you specify BINARY, Oracle OLAP considers every character in the file to be data. Rather than using newline characters to tell when records end, it assumes records of a fixed length, which you can set with FILESET(...LSIZE). The default record length is 80.
Specifies the character set that Oracle OLAP uses when reading data from the file specified by file-name. When this argument is omitted, then Oracle OLAP handles the data in the file as having the database character set, which is recorded in the NLS_LANG option.
Usage Notes
Multiple File Units
You can open as many files at the same time as your operating system allows.
Access Modes
The mode of access, READ, WRITE, or APPEND, must be appropriate to the file.
Examples
The REMOVE_MODEL_DIMENSION program removes aDIMENSION (in models) statement from a cube dimension's model. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
Syntax
CALL REMOVE_MODEL_DIMENSION(logical_dim, model_name, explicit_dim)
Parameters
Since REMOVE_MODEL_DIMENSION is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name of the logical model that is associated with logical_dim.
A text expression that is the identifier of the dimension that you want to remove from the cube dimension's model.
The PAGING option controls the production of paged output in Oracle OLAP. When you set PAGING to YES, output from statements such as DESCRIBE, REPORT, ROW command, HEADING, SHOW, and LISTNAMES is produced in a page-oriented format. Output is produced in page-size segments with standard top and bottom margins and headings. You can use a variety of paging-related options to change the size of the page, the size of the margins, and the headings on each page.
Paging is useful primarily for making output more attractive when you plan to print output that you send to a file. However, you can also send paged output to the default outfile. Normally you would set the PAGING option in the initialization section of a report program to turn paging on for your report.
Data Type
BOOLEAN
Syntax
PAGING = {YES|NO}
Parameters
Produces output with page breaks, top and bottom margins, and page headings.
(Default) Produces output that contains no page breaks, top and bottom margins, or page headings. Output is continuous, one line after another.
Usage Notes
Setting PAGING for a File
To set PAGING for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set PAGING to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, PAGING returns to its default value of NO for the file.
When you set PAGING for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE commands that send output to a file. That is, the value of PAGING is automatically saved for the default outfile.
Paging-Related Options
Oracle OLAP uses default values for page length, page headings, and top and bottom margins. You can change these values by setting the PAGESIZE, PAGEPRG, TMARGIN, and BMARGIN options. Other paging options that become meaningful when PAGING is set to YES are LINENUM, LINELEFT, and PAGENUM.
The value of PAGING for the current outfile determines whether the paging-related options are used. You must set PAGING to YES for the current outfile to make the paging options take effect.
Toggling PAGING On and Off
Toggling PAGING on and off, has the following effect on paging options:
When you toggle PAGING from on (YES) to off (NO):
The value of the LINENUM option continues to increment as more output lines are produced.
The LINELEFT option is set to PAGESIZE.
The PAGENUM option stops counting and retains its current value
When you toggle PAGING from off (NO) to on (YES):
LINENUM is set to 1 and it begins counting lines on the current page.
LINELEFT begins counting the lines left on the current page.
PAGENUM resumes counting at the page number where it left off.
Changing Outfiles
When you use an OUTFILE statement to direct output to a file, all the paging-related options are set to their default values for the file. When you use an OUTFILE statement with the EOF keyword to redirect output to the default outfile, the paging-related options contain the values that they last held for the default outfile.
Examples
Example 5-88 Setting Paging Options
Suppose you are writing a report program and you want to control page breaks and the top margin. You can include the following lines in the initialization section of your program. These lines send output to a file named repfile.txt, turn the PAGING option on, and change the page size and top margin.
OUTFILE 'repfile.txt' PAGING = YES PAGESIZE = 84 TMARGIN = 6
The ADD_DIMENSION_SOURCE procedure populates a table type named DBMS_AW$_DIMENSION_SOURCES_T with information about the dimensions of a cube. This information is analyzed by the ADVISE_SPARSITY procedure.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADD_DIMENSION_SOURCE (
dimname IN VARCHAR2,
colname IN VARCHAR2,
sources IN OUT dbms_aw$_dimension_sources_t,
srcval IN VARCHAR2 DEFAULT NULL,
dimtype IN NUMBER DEFAULT NO_HIER,
hiercols IN columnlist_t DEFAULT NULL,
partby IN NUMBER DEFAULT PARTBY_DEFAULT);
Parameters
Table B-2 ADD_DIMENSION_SOURCE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
A name for the dimension. For clarity, use the logical name of the dimension in the analytic workspace. |
|
|
The name of the column in the fact table that maps to the dimension members for dimname. |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a dimension table, or a SQL statement that returns the columns that define the dimension. If this parameter is omitted, then colname is used. |
|
|
One of the following hierarchy types: DBMS_AW.HIER_LEVELS Level-based hierarchyDBMS_AW.HIER_PARENTCHILD Parent-child hierarchyDBMS_AW.MEASURE Measure dimensionDBMS_AW.NO_HIER No hierarchy |
|
|
The names of the columns that define a hierarchy. For level-based hierarchies, list the base-level column first and the topmost-level column last. If the dimension has multiple hierarchies, choose the one you predict will be used the most frequently; only list the columns that define the levels of this one hierarchy. For parent-child hierarchies, list the child column first, then the parent column. For measure dimensions, list the columns in the fact table that becomes dimension members. |
|
|
A keyword that controls partitioning. Use one of the following values:
|
Example
The following PL/SQL program fragment provides information about the TIME dimension for use by the Sparsity Advisor. The source data for the dimension is stored in a dimension table named TIME_DIM. Its primary key is named MONTH_ID, and the foreign key column in the fact table is also named MONTH_ID. The dimension hierarchy is level based as defined by the columns MONTH_ID, QUARTER_ID, and YEAR_ID.
The program declares a PL/SQL variable named DIMSOURCES with a table type of DBMS_AW$_DIMENSION_SOURCES_T to store the information.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
dbms_aw.add_dimension_source('time', 'month_id', dimsources,
'time_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('month_id', 'quarter_id', 'year_id'));
.
.
.
END;
/
The LOG function computes the logarithm of an expression.
|
Note: Do not confuse the LOG function with the function of the same name which creates a log file. |
Return Value
DECIMAL
Syntax
LOG([base,] expression)
Parameters
The base by which to compute the logarithm. When you do not specify a value, the function computes the natural logarithm of the expression by using e for the base where e equals 2.718281828459.
A numeric expression which is greater than zero. When the value is equal to or less than zero, LOG returns an NA value.
Examples
The STATMIN function returns the earliest value in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
Either a dimension or surrogate value or an INTEGER that indicates the position of the value in the default status list of the dimension or surrogate. The return value varies depending on the dimension argument and the object receiving the return value. See "Automatic Data Type Conversion of Values Returned by STATMIN".
Syntax
STATMIN(dimension)
Parameters
A text expression whose value is the name of a dimension, dimension surrogate, or valueset.
Usage Notes
Automatic Data Type Conversion of Values Returned by STATMIN
The dimension value that STATMIN returns is converted, if necessary, to a number or a text value. For example, suppose the status of month is limited to Jun95 to Dec95, and Jun95 is the sixth month value in the default status list. The value of STATMIN(month) can be assigned either to a text variable, a numeric variable, or DATE variable.
The following statements
DEFINE textvar TEXT textvar = STATMIN(month) SHOW textvar
produce this output.
Jun95
In contrast, these statements
DEFINE intvar INTEGER intvar = STATMIN(month) SHOW intvar
produce this output.
6
Examples
Example 8-114 Using STATMIN in a Title
The following statements from a program use STATMIN to determine the earliest of the 10 months with the highest total sales.
LIMIT month TO TOP 10 BASEDON TOTAL(sales, month) SHOW JOINCHARS(STATMIN(month) ' is the earliest of the - ten months with the highest sales.') SHOW JOINCHARS( 'The months range from ' statmin(month) ' TO '- statmax(month) )
The preceding statements produce the following sales report.
May95 is the earliest of the ten months with the highest sales. The months range from May95 to Sep96
Example 8-115 Comparing to STATFIRST
In the following example, you can see the difference between STATMIN and STATFIRST, which returns the first value in the current status list.
Assume that you issue the following statements.
LIMIT month TO TOP 10 BASEDON TOTAL(sales, month) REPORT WIDTH 20 TOTAL(sales, month)
When the proceeding statements execute, the following report is produced.
MONTH TOTAL(SALES, MONTH) -------------- -------------------- Jul96 3,647,085.39 Jun96 3,458,438.30 Jul95 3,414,210.05 Aug96 3,246,601.97 Jun95 3,228,824.80 Sep96 3,215,883.93 May96 3,112,854.59 Aug95 3,044,694.29 Sep95 3,006,242.58 May95 2,908,539.45
Notice that the month values in this report are arranged by decreasing sales rather than chronologically, and this is now the order in which they occur in the status list:
STATMIN gives the chronologically first value in the status (though it is positionally last) as illustrated in the following statement and output.
SHOW STATMIN(month) May95
STATFIRST gives the value that is positionally first in the status (though it is chronologically eighth) as illustrated in the following statement and output.
SHOW STATFIRST(month) Jul96
The PUSHLEVEL command marks the start of a series of PUSH commands. You can then use a corresponding POPLEVEL statement to restore all the values saved by PUSH commands that are executed after PUSHLEVEL. POPLEVEL must specify the same marker as the PUSHLEVEL statement that starts the series. You can use PUSHLEVEL only within programs.
|
See also: "Considerations When Designing PUSHLEVEL and POPLEVEL Statements", POP, PUSH, POPLEVEL, and CONTEXT commands. |
Syntax
PUSHLEVEL marker-expression
Parameters
A text value to mark the start of a series of PUSH commands all of whose saved values are to be popped at once. A POPLEVEL statement that specifies the exact same marker-expression restores the whole series of saved values.
Usage Notes
Considerations When Designing PUSHLEVEL and POPLEVEL Statements
Keep the following points in mind when coding pushlevel statements:
You can nest PUSHLEVEL/POPLEVEL pairs, if you specify a different marker for each pair, as illustrated in the following code.
PUSHLEVEL 'firstlevel' PUSH PAGESIZE DECIMALS < saves values in FIRSTLEVEL ... PUSHLEVEL 'secondlevel' PUSH month product < Saves values in SECONDLEVEL ... POPLEVEL 'secondlevel' < Restores values in SECONDLEVEL ... POPLEVEL 'firstlevel' < Restores values in FIRSTLEVEL
You do not normally need multiple levels in a single program. However, Oracle OLAP automatically creates nested levels when one program calls another program and each program contains a set of PUSHLEVEL and POPLEVEL commands.
When you specify the same marker for two or more PUSHLEVEL commands, a POPLEVEL statement specifying that same marker restores values that were saved only since the most recent PUSHLEVEL statement.
When you specify a different marker for two or more PUSHLEVEL commands, a POPLEVEL statement that specifies the marker of any PUSHLEVEL statement restores all the values that were saved since that statement, including values that were saved after later PUSHLEVEL commands.
Examples
Example 10-85 Creating Level Markers
You can use a PUSHLEVEL statement to establish a level marker called firstlevel, and then use PUSH to save the current values.
PUSHLEVEL 'firstlevel' PUSH month DECIMALS ZSPELL
The level marker can be any text that is enclosed in single quotation marks. It can also be the name of a single-cell ID or TEXT variable, whose value becomes the name of the level marker. In the exit sections of the program, you can then use a POPLEVEL statement to restore all the values you saved since establishing the firstlevel marker.
POPLEVEL 'firstlevel'
Example 10-86 Nesting PUSHLEVEL and POPLEVEL Commands
You can nest PUSHLEVEL and POP LEVEL commands to save certain groups of values in one place in a program and other groups of values in another place in a program. The next example shows two sets of nested PUSHLEVEL and POPLEVEL commands.
PUSHLEVEL 'firstlevel'
PUSH PAGESIZE DECIMALS "Saves values in FIRSTLEVEL
...
PUSHLEVEL 'secondlevel'
PUSH month product "Saves values in SECONDLEVEL
...
POPLEVEL 'secondlevel' "Restores values in SECONDLEVEL
...
POPLEVEL 'firstlevel' "Restores values in FIRSTLEVEL
Normally, you do not use multiple sets of PUSHLEVEL and POPLEVEL commands in a single program. However, the nesting feature comes into play automatically when one program calls another program, and each program contains a set of PUSHLEVEL and POPLEVEL commands.
Example 10-87 One-Step Restoration and Nested Levels
The following program uses PUSHLEVEL 'rpt1' to mark for one-step restoration the original value of DECIMALS and the original status of month, product, and district, even though these are pushed separately in the program.
To demonstrate nesting, the program includes a nested PUSHLEVEL-POPLEVEL pair with 'rpt2' as its marker and some STATUS commands at various points. You can compare the program's output with the program to see how the status is affected.
DEFINE sales.RPT PROGRAM PROGRAM STATUS month product district PUSHLEVEL 'rpt1' PUSH DECIMALS month DECIMALS = 0 LIMIT month TO 'Jan96' REPORT WIDTH 8 DOWN district WIDTH 9 ACROSS product: expense PUSH product LIMIT product TO 'Racquets' 'Sportswear' REPORT DOWN district ACROSS product: advertising PUSHLEVEL 'rpt2' PUSH district LIMIT district TO 'Atlanta' 'Dallas' 'Chicago' REPORT DOWN district ACROSS product: sales BLANK STATUS month product district BLANK POPLEVEL 'rpt2' STATUS month product district BLANK POPLEVEL 'rpt1' STATUS month product district END
The sales.rpt program produces the following output.
The current status of MONTH is:
ALL
The current status of PRODUCT is:
ALL
The current status of DISTRICT is:
ALL
MONTH: JAN96
---------------------EXPENSE---------------------
---------------------PRODUCT---------------------
DISTRICT Tents Canoes Racquets Sportswear Footwear
-------- --------- --------- --------- ---------- ----------
Boston 31,299 67,527 52,942 49,668 80,565
Atlanta 41,139 53,186 57,159 108,047 99,758
Chicago 27,768 45,621 53,756 65,055 81,639
Dallas 47,063 34,072 118,807 113,629 19,785
Denver 33,177 42,975 89,144 63,380 36,960
Seattle 41,043 64,009 26,719 38,970 46,900
Month: JAN96
-----ADVERTISING-----
-------PRODUCT-------
DISTRICT RAcquets Sportswear
-------------- ---------- ----------
Boston 3,784 3,352
Atlanta 4,384 9,509
Chicago 3,351 5,283
Dallas 8,700 8,340
Denver 6,215 4,654
Seattle 2,344 3,726
MONTH: Jan96
--------SALES--------
-------PRODUCT-------
DISTRICT Racquets Sportswear
-------------- ---------- ----------
Atlanta 61,895 129,616
Dallas 125,880 128,115
Chicago 58,649 77,490
The current status of MONTH is:
JAN96
The current status of PRODUCT is:
RACQUETS, SPORTSWEAR
The current status of DISTRICT is:
ATLANTA, DALLAS, CHICAGO
The current status of MONTH is:
JAN96
The current status of PRODUCT is:
RACQUETS, SPORTSWEAR
The current status of DISTRICT is:
ALL
The current status of MONTH is:
ALL
The current status of PRODUCT is:
ALL
The current status of DISTRICT is:
ALL
The NORMAL function returns a random value from a normal distribution with a specified mean and standard deviation. The result returned by NORMAL is dimensioned by all the dimensions of the mean and standard deviation expressions.
Return Value
DECIMAL
Syntax
NORMAL(mean standard-deviation)
Parameters
A numeric expression that represents the mean of a normal distribution. When mean is NA, NORMAL returns NA.
A numeric expression that represents the standard deviation of a normal distribution. When standard-deviation is NA, NORMAL returns the mean.
Examples
Example 8-39 Showing Random Values
Each of the following examples shows a random number that might be returned from a normal distribution with a mean of 0 and a standard deviation of 1.
The first time you execute the following statement,
SHOW NORMAL(0 1)
it might produce the following result.
-0.75
However, when you execute the same statement again, it might produce the following result.
0.87
You use the COMPILEMESSAGE option to specify whether you want Oracle OLAP to send to the current outfile non-irrecoverable error messages during execution of the COMPILE command. Non-irrecoverable error messages are those indicating errors that do not prevent a program from compiling.
Data Type
BOOLEAN
Syntax
COMPILEMESSAGE = {YES|NO}
Parameters
(Default) Indicates that Oracle OLAP should record non-irrecoverable error messages during execution of the COMPILE command.
Indicates that Oracle OLAP should suppress non-irrecoverable error messages during execution of the COMPILE command.
Examples
The MOVINGAVERAGE function (abbreviated MVAVG) computes a series of averages for the values of a dimensioned variable or expression over a specified dimension. For each dimension value in status, MOVINGAVERAGE computes the average of the data in the range specified, relative to the current dimension value.
When the data being averaged has only one dimension, MOVINGAVERAGE produces a single series of averages, one for each dimension value in status. When the data has dimensions other than the one being averaged over, MOVINGAVERAGE produces a separate series of averages for each combination of values in the status list of the other dimensions.
Return Value
DECIMAL when the data type of expression is DECIMAL or SHORT; otherwise, NUMBER.
Syntax
MOVINGAVERAGE(expression, start, stop, step, -
[dimension [STATUS|limit-clause]])
Parameters
A numeric variable or calculation whose values you want to average; for example, units or sales-expense.
Integer values that specify the range of values over which you want to average. The value of start specifies the beginning of the range. The value of stop specifies the end of the range. Specify the values of start and stop relative to the current value of dimension. To specify a negative position for start or stop preceed the value with a comma. Thus, you specify zero (0) for the current dimension value, and -1 for the value preceding the current value. (See also "How the Moving Functions Handle Out-of-Range and NA Values".)
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Note: By default this function uses the default status list when identifying the range of values to average. You can specify either the STATUS or limit-clause phrase to change this behavior. |
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Tip: When you want to range to the end of status, for convience and to document your intent, specify the value of stop as OBJ function with the DIMMAX keyword |
A positive whole number that specifies whether to average over every value in the range, every other value, every third value, and so on. A value of 1 for step means average over every value. A value of 2 means average over the first value, the third value, the fifth value, and so on. For example, when the current month is Jun96 and the start and stop values are -3 and 3, a step value of 2 means average over Mar96, May96, Jul96, and Sep96.
The dimension over which the moving average is calculated. The data type of dimension can be of any type, but typically, is a time dimension.
When expression has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want the function to use that dimension, you can omit the dimension argument.
Specifies that MOVINGAVERAGE should use the current status list (that is, only the dimension values currently in status in their current status order) when calculating the moving average.
Specifies that MOVINGAVERAGE uses the values specified by a LIMIT function or those specified with the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
Usage Notes
How the Moving Functions Handle Out-of-Range and NA Values
As a moving function loops through the values, at each step in the loop, if the in-loop dimension position is NA or out of range, then the function considers expression as an NA value. The function treats these NA values in the manner specified by the setting of the NASKIP option (by default, as NA) so, typically, the function ignores out-of-range (NA) values and does not evaluate the expression for that step in the loop.
Examples
Example 8-31 Calculating a Moving Average
Suppose you have a variable called sales that is dimensioned by a hierarchical dimension named time, a dimension named product, a dimension named timelevelnames that contains the names of the levels of time (for example, Quarter and Year), and a relation named time.levelrels that relates the values of time to the values of timelevelnames. Assume also that using the following statements you limit product to Womens - Trousers and time to quarters from Q4-1999 to present.
LIMIT product TO 'Womens - Trousers' LIMIT timelevelnames TO 'Quarter' LIMIT time TO time.levelrels LIMIT time REMOVE 'Q1-1999' 'Q2-1999' 'Q3-1999'
After you have limited product and sales, you issue the following report statement.
REPORT DOWN time sales -
HEADING 'Running Yearly\nTotal' MOVINGTOTAL(sales, -4, 0, 1, time, -
LEVELREL time.levelrels) -
HEADING 'Minimum\nQuarter' MOVINGMIN(sales, -4, 0, 1, time, -
LEVELREL time.levelrels) -
HEADING 'Maximum\nQuarter' MOVINGMAX(sales, -4, 0, 1, time, -
LEVELREL time.levelrels) -
HEADING 'Average\nQuarter' MOVINGAVERAGE(sales, -4, 0, 1, time, -
LEVELREL time.levelrels)
The following report was created by the preceding statement.
-----------------------PRODUCT------------------------
------------------Womens - Trousers-------------------
Running
Yearly Minimum Maximum Average
TIME SALES Total Quarter Quarter Quarter
-------------- ---------- ---------- ---------- ---------- ----------
Q4-1999 416 1,386 233 480 346.50
Q1-2000 465 1,851 233 480 370.20
Q2-2000 351 1,969 257 480 393.80
Q3-2000 403 2,115 351 480 423.00
Q4-2000 281 1,916 281 465 383.20
Q1-2001 419 1,919 281 465 383.80
Q2-2001 349 1,803 281 419 360.60
Q3-2001 467 1,919 281 467 383.80
Q4-2001 484 2,000 281 484 400.00
Q1-2002 362 2,081 349 484 416.20
Q2-2002 237 1,899 237 484 379.80
Q3-2002 497 2,047 237 497 409.40
Q4-2002 390 1,970 237 497 394.00
The UPCASE function converts all alphabetic characters in a text expression into uppercase. When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
Return Value
TEXT or NTEXT
Syntax
UPCASE(text-expression)
Parameters
The text expression whose characters are to be converted.
Examples
Example 8-158 Converting Part of a Text Expression to Uppercase
Suppose you get some new data to add to a mailing list. In the existing mailing list, people's names have the first letter capitalized. In the new data, however, the whole name is in lowercase. You can use UPCASE to make the new data correspond to the current data with a statement similar to the following.
lastname = JOINCHARS(UPCASE(EXTCHARS(lastname, 1, 1)), -
EXTCHARS(lastname, 2, NUMCHARS(lastname)))
The MODTRACE option controls whether each equation in a model is recorded in a file during execution of the model. MODTRACE is used primarily as a debugging tool to uncover problems by tracing the execution of a model.
|
Tip: The INFO function lets you obtain specific items of information about the structure of the compiled model and the solution status of a model you have run. See INFO (MODEL). |
Data Type
BOOLEAN
Syntax
MODTRACE = {YES|NO}
Parameters
Oracle OLAP sends the text of each model equation to the current outfile before calculating the model equation, and then sends the results of the calculation to the current outfile.
When you have used a DBGOUTFILE statement to specify a debugging file, Oracle OLAP sends MODTRACE output to the debugging file instead of the current outfile.
(Default) Oracle OLAP does not send the text of model equations and results to a file while a model executes.
Usage Notes
Previewing the Solution Order
MODTRACE sends the equations of a model to the current outfile in the order in which they are being solved. Before you run the model, you might want to use the MODEL.COMPRPT program to get a preview of the solution order. A preview can be especially helpful when the model is large and complex. The MODEL.COMPRPT program, which you can run after compiling a model, produces a report that shows how the compiler has organized the model equations into blocks and the order in which the blocks and equations are solved.
Understanding Trace Information
MODTRACE shows the name of the current model on each line of the trace. The trace includes the following types of lines.
Block. A block line gives the block number and block type of the block that is about to be executed. The type of block can be simple, step-forward, step-backward, or simultaneous. For a step-forward or step-backward block, the block line specifies the dimension being stepped over. For a simultaneous block with a cross-dimensional dependency, the block line specifies the dimensions involved in the dependency. See MODEL command for information on blocks in a model.
Iteration. These lines occur in simultaneous blocks and specify the number of the iteration that is about to be performed for the current block. When you are using the Aitkens solution method, the next-guess iterations are identified. (The MODSIMULTYPE option determines the solution method being used.)
Equation. The equation that is about to be calculated.
Results. A results line follows each equation line and shows the results assigned by the equation. It shows the variable to which the results were assigned and the current value of each model dimension. In a simultaneous block, it also shows the current iteration number. For example, when actual is the solution variable and the model dimensions are line and month, a results line in a simultaneous block might look like the following one.
(MOD= INCOME.CALC) ACTUAL (LINE OPR.INCOME MONTH 'JAN96' ITER 1) = 108.9600000
Using MODTRACE with Dimension-Based Equations
When you run a model that contains dimension-based equations, Oracle OLAP automatically loops over all the dimensions of the solution variable. In the trace, the results lines show the current value of each dimension listed in a DIMENSION statement, but they do not show the current values of extra dimensions that are not listed in DIMENSION statement. See DIMENSION (in models) for more information about using DIMENSION statements.
Thus, when the model dimensions are line and month, and when the solution variable is dimensioned by line, month, and division, the current value of division is not shown in the results lines. Oracle OLAP executes the entire model for the first value in the status of division, then for the second value in the status, and so on.
When you run a model that assigns values to variables, Oracle OLAP automatically loops over all the dimensions (or bases of a composite) of those variables. In this case, the current value of each of the variable's dimensions is shown in the trace.
Examples
Example 5-63 Debugging a Model with MODTRACE
The following statements define a model named income.budget.
DEFINE income.budget MODEL LD Model for estimating budget items MODEL DIMENSION line month Opr.Income = Gross.Margin - Marketing Gross.Margin = Revenue - Cogs Revenue = LAG(Revenue, 1, month) * 1.02 Cogs = LAG(Cogs, 1, month) * 1.01 Marketing = LAG(Opr.Income, 1, month) * 0.20 END
This model estimates budget line items on an income statement. The model equations are based on a line dimension. The following statements compile the model and run the MODEL.COMPRPT program.
COMPILE income.budget MODEL.COMPRPT income.budget
The MODEL.COMPRPT statement produces the following compilation report.
MODEL INCOME.BUDGET <LINE MONTH>
BLOCK 1 (SIMPLE)
INCOME.BUDGET 4: revenue = lag(revenue, 1, month) * 1.02
INCOME.BUDGET 5: cogs = lag(cogs, 1, month) * 1.01
INCOME.BUDGET 3: gross.margin = revenue - cogs
BLOCK 2 (STEP-FORWARD <MONTH>)
INCOME.BUDGET 6: marketing = lag(opr.income, 1, month) * 0.20
INCOME.BUDGET 2: opr.income = gross.margin - marketing
END BLOCK 2
END BLOCK 1
When you want to debug this model, you can trace its execution, line by line, by turning on MODTRACE before running the model.
The following statements limit dimensions, specify tracing, and run the model.
LIMIT month TO 'Jan97' TO 'Mar97' LIMIT division TO 'Camping' MODTRACE = YES income.budget budget
These statements produce the following line-by-line results.
(MOD= INCOME.BUDGET) BLOCK 1: SIMPLE (MOD= INCOME.BUDGET) revenue = lag(revenue, 1, month) * 1.02 (MOD= INCOME.BUDGET) BUDGET (LINE REVENUE MONTH 'JAN97') = 744491.1966 (MOD= INCOME.BUDGET) BUDGET (LINE REVENUE MONTH 'FEB97') = 759381.020532 (MOD= INCOME.BUDGET) BUDGET (LINE REVENUE MONTH 'MAR97') = 774568.64094264 (MOD= INCOME.BUDGET) cogs = lag(cogs, 1, month) * 1.01 (MOD= INCOME.BUDGET) BUDGET (LINE COGS MONTH 'JAN97') = 382386.2323 (MOD= INCOME.BUDGET) BUDGET (LINE COGS MONTH 'FEB97') = 386210.094623 (MOD= INCOME.BUDGET) BUDGET (LINE COGS MONTH 'MAR97') = 390072.19556923 (MOD= INCOME.BUDGET) gross.margin = revenue - cogs (MOD= INCOME.BUDGET) BUDGET (LINE GROSS.MARGIN MONTH 'JAN97') = 362104.9643 (MOD= INCOME.BUDGET) BUDGET (LINE GROSS.MARGIN MONTH 'FEB97') = 373170.925909 (MOD= INCOME.BUDGET) BUDGET (LINE GROSS.MARGIN MONTH 'MAR97') = 384496.44537341 (MOD= INCOME.BUDGET) BLOCK 2 STEP-FORWARD <MONTH> (MOD= INCOME.BUDGET) marketing = lag(opr.income, 1, month) * 0.20 (MOD= INCOME.BUDGET) BUDGET (LINE MARKETING MONTH 'JAN97') = 39938.192 (MOD= INCOME.BUDGET) opr.income = gross.margin - marketing (MOD= INCOME.BUDGET) BUDGET (LINE OPR.INCOME MONTH 'JAN97') = 322166.7723 (MOD= INCOME.BUDGET) marketing = lag(opr.income, 1, month) * 0.20 (MOD= INCOME.BUDGET) BUDGET (LINE MARKETING MONTH 'FEB97') = 64433.35446 (MOD= INCOME.BUDGET) opr.income = gross.margin - marketing (MOD= INCOME.BUDGET) BUDGET (LINE OPR.INCOME MONTH 'FEB97') = 308737.571449 (MOD= INCOME.BUDGET) marketing = lag(opr.income, 1, month) * 0.20 (MOD= INCOME.BUDGET) BUDGET (LINE MARKETING MONTH 'MAR97') = 61747.5142898 (MOD= INCOME.BUDGET) opr.income = gross.margin - marketing (MOD= INCOME.BUDGET) BUDGET (LINE OPR.INCOME MONTH 'MAR97') = 322748.93108361 (MOD= INCOME.BUDGET) END BLOCK 2 (MOD= INCOME.BUDGET) END BLOCK 1
In Block 1, which is a simple block, Oracle OLAP solved the equations one at a time, looping over the three values in the status of month as it solved each equation. In Block 2, which is a step-forward block over the month dimension, Oracle OLAP stepped over the values in the status of month, solving all the equations in the block for each month in turn.
The SQLFETCH function retrieves one or more rows of a column in a relational text.
Return value
TEXT
Syntax
SQLFETCH (cursorname [COLUMN column-number} {STOPAFTER number-of-rows])
Parameters
A TEXT expression that is the name of the SQL cursor. The cursor must be opened and closed by the caller.
An INTEGER value that is the number of the column. (Default is 1.)
The number of rows to read. (Default is all remaining rows).
The TCONVERT function converts time-series data from one dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR to another dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. You can specify an aggregation method or an allocation method to use in the conversion.
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Important: You can only use this function with dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR.You cannot use this function for time dimensions that are implemented as hierarchical dimensions of type TEXT. |
Return Value
The value returned by the TCONVERT function depends on the type of conversion you specify and the type of the dimension being converted.
Syntax
TCONVERT(expression time-dimension method [method])
where the syntax for method varies by method type:
Parameters
An expression whose values you want to convert. Expression must be dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. This dimension is referred to as the source dimension. Usually expression is numeric, but with some conversion methods you can also convert text data. See "Converting Text Data".
The DAY, WEEK, MONTH, QUARTER, or YEAR dimension to which you want to convert the expression. This dimension is referred to as the target dimension.
The method to use for converting data from the source dimension to the target dimension. You can specify an aggregation method or an allocation method:
Aggregation methods are SUM, AVERAGE, and LAST. They are typically used to convert data from smaller time periods to larger time periods (for example, months to years).
Allocation methods are SPLIT, REPEAT, and INTERPOLATE. They are typically used to convert data from larger to smaller time periods (for example, years to quarters). The allocation methods all use the full default status of the source dimension to determine the periods that contribute to the allocation.
Except for a case in which the source dimension and target dimension have overlapping periods of equal length (as with a calendar year and a fiscal year), you can specify both an aggregation method and an allocation method. See "Compatible Aggregation and Allocation Methods" and "Using Both Aggregation and Allocation".
For all methods, results are calculated for the values in the current status of the target dimension.
The results you obtain depend on the method you specify and on whether you convert data between dimensions with periods of equal length or unequal length. See "Using Both Aggregation and Allocation", "Overlapping Periods of Equal Length", and "Substituting a Compatible Method".
Aggregates data to a target period by totaling the data of the contributing source periods. For each target period, SUM BY PERIOD returns the total for all the source periods that end in the target period. SUM uses the implicit relation between the source and target dimensions.
Weights each source value according to the portion of target days it represents. For each target period, SUM BY DAY multiplies each contributing source period value by a weighting factor that has this form where source-days-in-target is the Number of source-period days that actually fall in target period and total-days-in-period is the total number of days in source period:
source-days-in-target / total-days-in-period
SUM BY DAY then returns the total of these weighted source values. When you use SUM BY DAY, the value of an individual source period may be apportioned across adjacent target periods.
For example, suppose you convert weekly data to monthly data. When three days of a week fall in January and four fall in February, then SUM BY DAY adds 3/7 of the data for that week to the January total and 4/7 to the February total. In contrast, SUM BY PERIOD adds the entire data value for the week to the February total (since the week ends in February).
As another example, suppose you want to convert calendar year data to a fiscal year ending in June. Calendar year 1996 (Cal96) is the only calendar year that ends in fiscal year 1997 (Fy97). The SUM BY PERIOD method assigns the value for Cal96 to Fy97. In contrast, SUM BY DAY apportions the Cal96 value to the fiscal years Fy96 and Fy97, according to the number of calendar days that fall in each fiscal year. Of the 366 days of Cal96, 182 days (January 1 - June 30) fall in Fy96 and 184 days (July 1 - December 31) fall in Fy97. Therefore, for the CAL96 data, SUM BY DAY uses a weighting factor of 182/366 for Fy96 and a factor of 184/366 for Fy97.
Aggregates data to a target period by averaging the data of the contributing source periods. For each target period, AVERAGE BY PERIOD adds up the data from all the source periods that end within the target period and divides this total by the number of source periods. AVERAGE BY PERIOD uses the implicit relation between the two time dimensions.
Weights the value of each contributing source period by the portion of target days it represents. For each target period, AVERAGE BY DAY multiplies the value of each source period by the number of days of that source period that actually fall within the target period. The average is then calculated by adding these weighted source values and dividing by the total number of days in the target period. When you use AVERAGE BY DAY, the value of a single source period may be apportioned across adjacent target periods.
For each target period, LAST BY PERIOD returns the data value from the last source period that ends within the target period. It uses the implicit relation between the source and target dimensions.
Has the same effect as LAST BY PERIOD, provided you are converting data from smaller periods to larger periods. See "Substituting a Compatible Method".
Indicates that the current status of the source dimension is used. It is the default for the SUM and AVERAGE methods.
Indicates that the full default status of the source dimension is used. It is the default for the LAST method.
Allocates data to target periods by splitting the data from the source periods. SPLIT BY PERIOD divides a source value evenly among the target periods that end in that source period. SPLIT BY PERIOD uses the implicit relation between the two DAY, WEEK, MONTH, QUARTER, or YEAR dimensions.
Weights each source value according to the portion of target days it represents. For each target period, SPLIT BY DAY multiplies each contributing source period value by a weighting factor that has this form where target-days-in-source is the Number of target-period days that actually fall in source period and total-period-days is the total number of days in source period:
target-days-in-source / total-period-days
SPLIT BY DAY then returns the total of these weighted source values. When you use SPLIT BY DAY, the value of an individual source period may be apportioned across adjacent target periods.
For each target period, REPEAT returns the value of a source period. The target periods are the periods that end within the source period. REPEAT uses the implicit relation between the source and target dimensions. REPEAT BY DAY has the same effect as REPEAT BY PERIOD, provided you are converting data from larger time periods to smaller time periods. See "Substituting a Compatible Method".
The INTERPOLATE method allocates data to target periods by first calculating the difference between the values of the current and previous source periods, and then splitting the result incrementally over the target periods. INTERPOLATE divides the difference between the current and previous source period values by the number of target periods that end in the source period, and it increments each target period by this amount.
For each target period, adds the value of the previous source period to a value that is calculated as follows where end-days is the number of days from end of previous source period to end of current target period and period-days is the total number of days in current source period:
(end-days / period-days) * (current-source-value - previous-source-value)
When a target period has days that fall in multiple source periods, a similar calculation is made for each source period.
Usage Notes
Dimensions of the Result Returned by TCONVERT
The results returned by TCONVERT are dimensioned by the target DAY, WEEK, MONTH, QUARTER, or YEAR dimension and by all of expression dimensions that are not DAY, WEEK, MONTH, QUARTER, or YEAR dimensions.
Status Used with Allocation
The STATUS and NOSTATUS keywords have no effect with the allocation methods. The allocation methods always use the full default status of the source dimension to determine the contributing periods.
Compatible Aggregation and Allocation Methods
Except for a case in which the source dimension and the target dimension have overlapping periods of equal length, you can specify both an aggregation method and an allocation method. However, the two methods must be compatible. Table 8-15, "Compatible Aggregation and Allocation Methods" shows the compatible methods.
Table 8-15 Compatible Aggregation and Allocation Methods
| Aggregation | Compatible Allocation |
|---|---|
|
SUM |
SPLIT |
|
AVERAGE |
REPEAT |
|
LAST |
INTERPOLATE |
When you specify both an aggregation method and an allocation method, you can specify BY PERIOD or BY DAY with either method. When you specify BY PERIOD (explicitly or by default) for one method and BY DAY for the other method, BY DAY takes precedence.
Using Both Aggregation and Allocation
When you specify both an aggregation method and a compatible allocation method, Oracle OLAP handles this as follows:
When you convert data from smaller periods to larger periods, Oracle OLAP uses the aggregation method (with BY DAY, if specified for either method).
When you convert data from larger periods to smaller periods, Oracle OLAP uses the allocation method (with BY DAY, if specified for either method).
When you convert data between dimensions that have non-overlapping periods of equal length, such as a quarter ending in March and a quarter ending in June, the results of the aggregation and allocation methods are identical.
Overlapping Periods of Equal Length
When you convert data between two dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR that have overlapping periods of equal length, such as a calendar year and a fiscal year, or a quarter ending in March and a quarter ending in April, you must specify either an aggregation method or allocation method, but not both. For these dimensions, the compatible aggregation and allocation methods may yield different results.
For example, when you convert data from a calendar year dimension to a fiscal year dimension that ends in June, the SUM and SPLIT methods return different results:
The SUM method totals up the data from the source periods that end in the target period. Since the calendar year 1996 ends in fiscal year 1997, the SUM method assigns the value for calendar year 1996 to fiscal year 1997.
The SPLIT method allocates a source data value to the target periods that end in the source period. Since the fiscal year 1996 ends in calendar year 1996, the SPLIT method assigns the value for calendar year 1996 to fiscal year 1996.
Substituting a Compatible Method
When you specify a single conversion method, and you use an aggregation method to convert data from a larger period to a smaller period (for example, from months to weeks) Oracle OLAP automatically uses the compatible allocation method instead of the specified aggregation method. Similarly, when you use an allocation method to convert data from a smaller period to a larger period, Oracle OLAP automatically uses the compatible aggregation method. See "Compatible Aggregation and Allocation Methods".
Data Type of the Result
When possible, TCONVERT returns results that have the same data type as expression. When expression is DECIMAL, the results are always DECIMAL. When expression is INTEGER, the results are INTEGER when the required calculations do not involve division. For example, when two dimensions are aligned (that is, they have the same phase and are based on the same periods, such as a calendar year dimension and a quarter dimension ending in December), the result is INTEGER when you use the REPEAT method to convert an INTEGER expression from larger periods to smaller periods. Similarly, the result is INTEGER when you use the SUM or LAST method to convert the expression from smaller to larger periods.
Converting Text Data
You can also use TCONVERT to convert the values of a text expression when no numeric calculations are needed for the conversion. For aligned dimensions, for example, you can use the LAST method to convert text values from smaller periods to larger periods, and you can use the REPEAT method to convert text values from larger periods to smaller periods. You can also use the LAST and REPEAT methods to convert text data between dimensions that have periods of equal length. When you attempt to convert a text expression with a method that requires numeric calculations, you receive an error message.
Methods for Financial Data
When you work with financial data, you can use an appropriate conversion method for each type of data. Table 8-16, "Examples of Conversion Methods for Different Types of Financial Data" gives some examples.
Table 8-16 Examples of Conversion Methods for Different Types of Financial Data
| Type of Financial Data | Conversion | Conversion Method |
|---|---|---|
|
Revenue or expenses |
Month to year |
SUM |
|
Stock quotations |
Day to quarter |
AVERAGE |
|
Balance sheet items |
Month to quarter |
LAST |
|
Quarterly tax payment |
Year to quarter |
SPLIT BY PERIOD |
|
Money supply |
Year to quarter |
INTERPOLATE |
How TCONVERT Handles NA Values
TCONVERT is affected by the NASKIP option. When NASKIP is set to NO, TCONVERT returns an NA value for any target period that receives contributions from a source period with an NA value.
Examples
Example 8-133 Splitting Data Across Quarters
This example shows the effects of using the SPLIT method and the SPLIT BY DAY method to allocate an annual budget revenue figure of $120,000 across the quarters of the year 1996. An existing year dimension is the source dimension and an existing quarter dimension is the target dimension.
The following statements
DEFINE budget.revenue DECIMAL <year> budget.revenue(year 'Yr96') = 120000 LIMIT quarter TO year 'Yr96' REPORT W 12 HEADING 'Split Evenly' - TCONVERT(budget.revenue quarter SPLIT) - W 12 HEADING 'Split by Day' - TCONVERT(budget.revenue quarter Split by day)
produce this report.
QUARTER Split Evenly Split by Day -------------- ------------ ------------ Q1.96 30,000.00 29,836.07 Q2.96 30,000.00 29,836.07 Q3.96 30,000.00 30,163.93 Q4.96 30,000.00 30,163.93
Example 8-134 Aggregating Weekly Data to Monthly Using TCONVERT
This example aggregates weekly data to monthly data. First, define a week dimension named week and add weeks that include the dates January 1, 1996 and June 30, 1996 (Oracle OLAP automatically adds the intervening weeks).
DEFINE week DIMENSION WEEK MAINTAIN week ADD '01Jan96' '30Jun96'
Next, define a variable named weekvar, dimensioned by week, and assign a value of 7 to each week.
DEFINE weekvar DECIMAL <week> weekvar = 7
The following statements show that December 31, 1995 is the beginning date of the first week for which weekvar contains non-NA data and that July 6, 1996 is the ending date of the final week for which weekvar contains non-NA data.
SHOW BEGINDATE(weekvar) SHOW ENDDATE(weekvar)
The statements produce this output.
31Dec95 06Jul96
With these beginning and ending dates, when the data is converted to monthly data, it is aggregated over the months Dec95 through Jul96. The following statements show the effects of using the SUM method and the SUM BY DAY method to convert the weekly weekvar data to monthly data.
LIMIT month TO 'Jan96' TO 'Jul96' REPORT HEADING 'Sum' TCONVERT(weekvar month SUM) - HEADING 'Sum by Day' - TCONVERT(weekvar month SUM BY day)
These statements produce the following report.
MONTH Sum Sum by Day -------------- ---------- ---------- Jan96 28.00 31.00 Feb96 28.00 29.00 Mar96 35.00 31.00 Apr96 28.00 30.00 May96 28.00 31.00 Jun96 35.00 30.00 Jul96 7.00 6.00
Within a model, the AGGREGATION function allows you to create a model that represents a custom aggregate. Such an aggmap can be used for dynamic aggregation with the AGGREGATE function.
|
Note: Because the AGGREGATION function is intended only for dynamic aggregation, a model that contains such a function cannot be used with the AGGREGATE command. |
Syntax
AGGREGATION(dimval-list)
Parameters
A list of one or more dimension values to include in the custom aggregation. The specified values must belong to the same dimension to which the target dimension value belongs. You must specify each dimension value as a text literal. That is, they cannot be represented by a text expression such as a variable.
Examples
Example 7-9 Using the AGGREGATION Function to Create a Custom Aggregate
The following lines of code from a program perform these steps:
Add the new dimension value my_time to the time dimension.
MAINTAIN time ADD 'My_Time'
Define the model mytime_custagg and set the specification of the model using the AGGREGATION function.
DEFINE mytime_custagg MODEL
MODEL JOINLINES('DIMENSION time' 'My_Time = AGGREGATION(\'23\' \'24\')')
(Note that backslash escape characters are required to include quotation marks within a quoted string.)
Define the sales_aggmap aggmap.
DEFINE sales_aggmap AGGMAP <time cpc <customer product channel> > AGGMAP RELATION prntrel.time RELATION prntrel.chan RELATION prntrel.prod RELATION prntrel.cust END
Add the model mytime_custagg to sales_aggmap.
AGGMAP ADD mytime_custagg TO sales_aggmap
Limit the dimensions to the values of interest and run a report.
" Run a report LIMIT time TO 'My_Time' '23' '24' LIMIT channel TO '5' LIMIT product TO '70' LIMIT customer TO '114' REPORT DOWN time AGGREGATE(sales USING sales_aggmap)
The report generates the following output.
CHANNEL: 5
PRODUCT: 70
--AGGREGATE(SALES---
USING SALES_AGGMAP)-
------CUSTOMER------
TIME 114
-------------- --------------------
my_time 682,904.34
23 84,982.92
24 597,921.42
(Read-only) The LINESLEFT option contains the number of lines left on the current page. The LINESLEFT option is meaningful only when PAGING is set to YES and only for output from commands such as REPORT and LISTNAMES.
Data Type
INTEGER
Syntax
LINESLEFT
Usage Notes
Controlling Page Breaks
LINESLEFT is used primarily in report programs to check the number of lines left on a particular page. When the number of lines left is less than that required for a part of the report that you do not want interrupted by a page break, you can then use a PAGE statement to skip to a new page.
The Effect of PAGESIZE on LINESLEFT
When you change the value of PAGESIZE, the value of LINESLEFT is adjusted accordingly. First, LINESLEFT is subtracted from the old value of PAGESIZE, which gives the lines already used. This result is then subtracted from the new value of PAGESIZE which gives the new value of LINESLEFT. When LINESLEFT becomes less than 1, a new page is started at the next output line.
The Effect of PAGING on LINESLEFT
When you set PAGING to NO, LINESLEFT is set to the value of PAGESIZE, and it keeps this value until PAGING is set to YES. When you set PAGING to YES, LINESLEFT begins counting the lines on the current page.
The Effect of OUTFILE on LINESLEFT
When you use an OUTFILE statement to direct output to a file, LINESLEFT is set to 66 for the file, to match the default value of PAGESIZE. When you set PAGESIZE to a new value for the current outfile, LINESLEFT is adjusted accordingly. For example, assume that you direct output to a file and then set PAGESIZE to 40. In this case, Oracle OLAP sets LINESLEFT to 40 for the file which ensures that the first line of output to the file triggers a new page when PAGING is set to YES.
When you use an OUTFILE statement with the EOF keyword to redirect output to the default outfile, LINESLEFT contains the value that it last held for the default outfile.
Sending LINESLEFT in Output
When you produce output that contains the value of LINESLEFT, the lines that contain this value are never included in the value recorded for LINESLEFT.
Examples
Example 5-47 Including a Footnote
In a report, you want a one-line footnote preceded by two blank lines at the bottom of a page. Use the following statements to generate the footnote when three lines remain on the page.
IF LINESLEFT EQ 3 THEN DO BLANK 2 ROW W 50 'Subject To Change Without Notice.' DOEND
(Read-only) The OUTFILEUNIT option holds the file unit number of the current OUTFILE destination, set by the last OUTFILE statement. The first time you redirect output to a given file, OUTFILE assigns that file an arbitrary INTEGER as a file unit number.
Data Type
INTEGER
Syntax
OUTFILEUNIT
Usage Notes
OUTFILE and OUTFILEUNIT
You automatically change the setting of OUTFILEUNIT whenever you specify a different file with an OUTFILE statement. For example, after the statement OUTFILE myfilename, the value of OUTFILEUNIT is the file unit number assigned to myfilename.
Examples
Example 5-83 Using OUTFILEUNIT with FILEQUERY
Suppose you have saved the file unit number for a file in a variable called filenum. Your current outfile is another disk file. You want to set the value of PAGEPRG for the first file to the value that it has for the current outfile. Because the file unit number for the current outfile is contained in the OUTFILEUNIT option, you can use FILEQUERY with the OUTFILEUNIT number to get the PAGEPRG setting for the current outfile.
FILESET filenum PAGEPRG FILEQUERY(OUTFILEUNIT PAGEPRG)
The $GID_DEPTH property, which is automatically created and set when a GROUPINGID command populates a grouping id relation, specifies the number of levels of grouping ids in the grouping id relation to which it is added.
Syntax
You cannot explicitly define a $GID_DEPTH property. Oracle OLAP automatically creates a $GID_DEPTH property on a grouping id relation when the execution of a GROUPIONGID command creates the relation.
$GID_DEPTH = intlevels
Parameters
An INTEGER value that specifies the number of levels of grouping ids.
Examples
See Example 9-145, "Using GROUPINGID Command to Populate a Relation with Grouping Ids".
This chapter contains the following topics:
One topic for each of the OLAP DML functions that begins with the letters A - K, beginning with ABS.
Reference topics for the remaining OLAP DML functions appear in alphabetical order in Chapter 8, "OLAP DML Functions: L - Z".
For other OLAP DML reference topics, see Chapter 4, "OLAP DML Properties", Chapter 5, "OLAP DML Options", Chapter 9, "OLAP DML Commands: A-G", and Chapter 10, "OLAP DML Commands: H-Z".
OLAP functions work in much the same way as functions work in other programming languages. They initiate action and return a value. The one exception is the looping nature of OLAP DML functions as discussed in "OLAP DML Statements Apply to All of the Values of a Data Object".
Most of the OLAP DML functions are standard text and calculation functions. Other OLAP DML functions return more complex information. For example, the OLAP DML provides the AW and OBJ functions that you can use to retrieve many different types of information about an analytic workspace and its objects and the AGGREGATE function that you can use to calculate aggregate data on-the-fly at user request.
Additionally, you can augment the functionality of the OLAP DML by writing an OLAP DML program for use as a function.
|
Tip: Many OLAP DML statements can be coded as a 3-character abbreviation that consists of the first letter of the statement plus the next two consonants. |
A B C D E F G H I J K L M N O P Q R S T U V W Y
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Y
The OLAP DML provides the typical numeric and text functions:
It also has functions that are unique to its data model:
Analytic workspace and object information functions
Aggregation, allocation, and model specification functions
Conversion functions
System and Database information functions
Datetime functions
Date-only functions
Financial functions
File management functions
NA functions
Numeric (general) functions
Numeric aggregation functions
Object value retrieval functions
Program argument and context functions
Reporting functions
Statistical and forecasting functions
Status manipulation functions
Text functions
Time-series functions
The RTRIM function removes characters from the right of a text expression, with all the rightmost characters that appear in another text expression removed. The function begins scanning the base text expression from its last character and removes all characters that appear in the trim expression until reaching a character that is not in the trim expression and then returns the result.
Return Value
TEXT or NTEXT based on the data type of the first argument.
Syntax
RTRIM (text-exp [, trim-exp])
Parameters
A text expression that you want trimmed.
A text expression that is the characters to trim. The default value of trim-exp is a single blank.
Examples
The CREATE_LOGICAL_MODEL program creates a new model for an OLAP cube dimension, and adds that definition to the Oracle data dictionary. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
Syntax
CALL CREATE_LOGICAL_MODEL ( logical_dim, model_name)
Parameters
Since CREATE_LOGICAL_MODEL is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name that the model will have in the Oracle data dictionary.
This procedure sends a session log returned by the INTERP, INTERPCLOB, or GETLOG functions of this package to the print buffer, using the DBMS_OUTPUT package in PL/SQL.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON SIZE 1000000
The SIZE clause increases the buffer from its default size of 4K.
If you are using a different program, refer to its documentation for the equivalent setting.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
PRINTLOG (
session-log IN CLOB);
Parameters
Example
The following example shows the session log returned by the INTERP function.
SET serverout ON size 1000000 EXECUTE dbms_aw.printlog(dbms_aw.interp('REPORT W 30 all_dimensions')); ALL_DIMENSIONS ------------------------------ TIME.DIMENSION CUSTOMER.DIMENSION PRODUCT.DIMENSION CHANNEL.DIMENSION
The IMPORT command transfers data to an analytic workspace from a text file, a spreadsheet, or another analytic workspace from an EIF file.
Because the syntax of the IMPORT command is different depending on where the data to be imported is located, separate topics are provided for different types of source files:
You can use the IMPORT (from EIF) command to copy data and definitions into your Oracle OLAP analytic workspace from an EIF file. IMPORT also copies any dimensions of the imported data that do not already exist in your workspace, even when you do not specify them in the command.
|
Tip: Several options that determine how EIF files are imported and exported. These options are listed in "EIF Options". |
IMPORT (from EIF) is commonly used with EXPORT (EIF) to copy parts of one Oracle OLAP analytic workspace to another; you export objects from the source workspace to an EIF file and then import the objects from the EIF file into the target workspace. The source and target workspaces can reside on the same platform or on different platforms. When you transfer an EIF file between computers, you use a binary transfer to overcome file-format incompatibilities between platforms. The EIF file must have been created with the EIFVERSION set to a version that is less than or equal to the version number of the target workspace. Use EVERSION to verify the target version number.
You can also use IMPORT to store information in the EIFNAMES and EIFTYPES options.
Syntax
IMPORT import_item FROM EIF FILE file-id [INTO workspace] -
[MATCH [STATUS]|APPEND|REPLACE [DELETE]] [LIST [ONLY]] [DATA] -
[DFNS] [UPDATE] [NOPROP] [NASKIP] [NLS_CHARSET charset-exp] -
[API | NOAPI]
where import_item is one of the following:
Parameters
The name of an analytic workspace object to be imported from an EIF file to an attached workspace. You cannot specify a qualified object name for the object, because the object is not yet in any workspace. You can list multiple names at a time. See the INTO workspace argument for information about where the object is imported.
AS newname can be used to rename any type of object being imported except dimensions.
When you have exported a multidimensional object as separate variables, list all the variable names. (See the SCATTER AS keyword in the EXPORT (EIF).)
(Default) Indicates that you want to import all the objects contained in the EIF file. See the INTO workspace argument for information about where the objects is imported.
an analytic workspace name that identifies the attached workspace into which objects is imported. When the objects exist in the specified workspace, then their data is overwritten by the imported data. When the objects do not already exist, IMPORT creates them it in the specified workspace. IMPORT ignores identically named objects when they exist in other attached workspaces.
When you do not specify this argument, then Oracle OLAP does the following:
When you have not previously defined the objects being imported in an attached workspace, then IMPORT defines them automatically in the current workspace.
When the objects already exist in any attached workspace, then IMPORT overwrites the data they contain with the imported data.
Identifies the file you want to import. File-id is a text expression that represents the name of the file. The name must be in a standard format for a file identifier.
Indicates that the IMPORT command should bring in only the data associated with dimension values that match those already in the target workspace. For dimensions other than time dimensions, ensure that corresponding dimension values are spelled and capitalized identically in the EIF file and your target workspace when you want them to match; for example, Tents does not match TENTS. For time dimensions, Oracle OLAP identifies dimension values by the dates they represent rather than by the way they are displayed. Therefore, time dimension values in the EIF file automatically matches time dimension values in your workspace when they represent the same time periods. When you specify MATCH STATUS, IMPORT only imports data associated with the values included in the current status of that dimension. When the dimension is limited in the target workspace, Oracle OLAP ignores any data in the EIF file associated with the values excluded from the status.
(Default) Indicates that the IMPORT command should bring in all the dimension values, along with associated data, regardless of whether or not the dimension values match those already present in the target workspace. APPEND adds those that do not match to those already present; it adds new values to the end of the list of dimension values. For time dimensions, APPEND also adds dimension values to fill in any gaps between the dimension values in your target workspace and the new ones.
Indicates that, for objects already defined in the workspace, IMPORT should keep the existing dimension values that match the dimension values in the EIF file. IMPORT deletes dimension values (and their data) that do not match dimension values in the EIF file. IMPORT replaces the associated data for the dimension values kept as part of the new dimension when the associated data variables are included in the EIF file. For text dimensions, the order of the dimension values in the EIF file is also adapted.
When you specify REPLACE DELETE, no matching takes place. Before importing a dimension, Oracle OLAP performs a MAINTAIN DELETE ALL, which discards all data associated with the existing dimension and the dimension values.
|
Important: Be careful when using the REPLACE keyword. When you replace the values of a dimension, all variables and relations in the target workspace dimensioned by it are affected. When a variable or relation is not being imported at the same time, replacing the values of one of its dimensions could result in the loss of its data. |
Produces a list of the definitions. For dimensions, the output lists the number of values in each dimension, as they are imported into the target workspace. For composites, the output lists the number of dimension value combinations. IMPORT also indicates the number of bytes read and the elapsed time every two minutes or, in any case, after the import procedure.
When you define a conjoint or composite that uses an index type other than the default, the IMPORT LIST command displays the index type. When you use the default index type (HASH for conjoints, BTREE for composites), that information is not displayed.
EXPORT (EIF) sends the list to the current outfile. When you specify LIST ONLY, you get only the listing without actually importing anything.
Causes Oracle OLAP to place the correct values in the EIFNAMES and EIFTYPES options without actually importing them. However, Oracle OLAP does not produce a full listing of the object definitions. To produce the list, specify the LIST keyword before the ONLY keyword.
Indicates that, for objects that already exist in the target workspace, IMPORT should update only the data associated with those objects. For formulas that already exist, IMPORT updates their EQ expressions. Objects that IMPORT creates in the target workspace are created with their full definitions and any associated data. You can specify both DATA and DFNS, but when neither is specified, the default is DATA.
Indicates that, for objects that already exist in the target workspace, IMPORT should just update definitions and leave data unchanged. The components of the definition affected by IMPORT DFNS are: LD Command, VNF, and PROPERTY. Objects that IMPORT creates in the target workspace still get their data. You can specify both DATA and DFNS, but when neither is specified, the default is DATA.
Indicates that IMPORT should execute an UPDATE statement after importing each object which can be useful when importing large EIF files that would otherwise cause Oracle OLAP to run out of memory. To control the frequency of updates, use the EIFUPDBYTES option.
Prevents any properties that you have assigned to each object from being read from the EIF file.
Specifies that composite tuples (indexes) that contain only NA data should not be imported into the target workspace. This argument has no effect on tuples that already exist in the workspace.
Specifies the character set that Oracle OLAP uses when importing text data from the file specified by file-id. Normally, an EIF file contains its own specification of its character set, so that this argument is not needed. However, when the EIF file specifies the character set incorrectly or is missing the character set specification, then you must use this argument to specify the character set correctly.
For information about the character sets that you can specify, see Oracle Database Globalization Support Guide.
This argument must be the last one specified. When this argument is omitted, and Oracle OLAP cannot determine the character set from the EIF file itself, then Oracle OLAP imports the data using the database character set, which is recorded in the NLS_LANG option.
(Default) When the EIF file was created using an EXPORT (EIF) command with the API keyword, import any cube metadata defined for the specified items.
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Note: Oracle OLAP automatically executes an UPDATE and a COMMIT after executing this type of import. |
Even if the EIF file was created using an EXPORT (EIF) command with the API keyword, do not import any cube metadata defined for the specified items. When you specify this keyword, Oracle OLAP does not automatically execute an UPDATE and a COMMIT after executing the IMPORT command.
Usage Notes
Separate IMPORT Statements
The MATCH, APPEND, REPLACE, DATA, and DFNS arguments you specify affect all the objects you name to be imported. When you want to treat different objects in different ways, use separate IMPORT statements.
Importing and Exporting Hidden Programs
Importing Relations
When you are importing a relation, IMPORT also brings in the definition and values for the related dimension as well.
Importing Concat Dimensions
When you import a concat dimension into an analytic workspace and the concat dimension and none of its component dimensions already exist in the analytic workspace, then Oracle OLAP imports the concat dimension, its component dimensions, and the definitions of all of the dimensions.
When you import a concat dimension that does not already exist but one or more of its component dimensions already exist in the analytic workspace, then Oracle OLAP imports the concat dimension and any new component dimensions and their definitions. For the component dimensions that already exist in the analytic workspace, Oracle OLAP imports the component dimensions as it does other dimensions, obeying any MATCH, APPEND, REPLACE specifications in the IMPORT statement.
When you import a concat dimension with a name and a definition of a concat dimension that already exists in the analytic workspace, then Oracle OLAP imports the concat dimension as it does other dimension.
When you import a concat dimension with the same name as one that already exists in the analytic workspace but the definition of the imported concat dimension is different than the definition of the existing concat dimension, then the definition of the existing concat dimension does not change and the definitions of the component dimensions of the existing concat dimension do not change. Only the component dimensions of the imported concat dimension that are also component dimensions of the existing concat dimension are imported. When the imported concat dimension does not share any component dimensions with the existing concat dimension, an error condition occurs. When you are importing any objects that are dimensioned by the concat dimension, then Oracle OLAP imports only the values of the object that correspond to the values of the imported dimensions.
Importing and Exporting Dimension Surrogates
You can import or export a dimension surrogate to or from an Express Interchange File (EIF). In those operations, a dimension surrogate behaves like a variable that is dimensioned by the dimension of the surrogate. In an EXPORT operation, the dimension for which the surrogate is defined is also exported. In an IMPORT operation, the dimension for which the surrogate is defined is imported but you can use the MATCH, STATUS, DATA, DFNS, APPEND, and REPLACE keywords to affect which values are imported.
Importing a dimension surrogates also imports the definition and values for the dimension for which it is a surrogate. When a dimension with the same definition already exists in the current analytic workspace, then the effects of the IMPORT keywords such as MATCH, APPEND, REPLACE, DATA, and DFNS are the same for the surrogate as they would be for a variable dimensioned by the dimension. When the name and definition of the imported surrogate is the same as a dimension surrogate that already exists in the current analytic workspace and when the imported surrogate has a value that is identical to a value in the existing surrogate, an error condition occurs.
You can import an INTEGER dimension surrogate when no object of the same name exists in the current analytic workspace or when you use the DFNS keyword. Importing an INTEGER dimension surrogate affects existing INTEGER dimension surrogates when the implicit importing of the dimension of the imported surrogate changes the values of the existing dimension.
APPEND Versus REPLACE
When you are importing an INTEGER dimension that already exists in your target workspace, the following considerations apply.
When the imported INTEGER dimension is larger than the existing one, APPEND and REPLACE have the same effect. The dimension ends up with the number of values in the larger, imported dimension.
When the imported INTEGER dimension is smaller, REPLACE drops the appropriate dimension values from the end of the dimension, along with any associated data, while APPEND leaves the existing dimension values alone.
INTEGER and SHORTINTEGER Data Types
The IMPORT command translates between the INTEGER and SHORTINTEGER data types. When you are importing a variable with one of these data types from an EIF file and it already exists in your workspace as the other type, Oracle OLAP converts the data automatically. The maximum SHORTINTEGER value is 32,767 and the minimum is -32,767. When you import an INTEGER value that exceeds these limits into a SHORTINTEGER variable, the result is NA.
TEXT and ID Data Types
When the EIF file you are importing contains ID data that you want to import into TEXT dimensions, variables, relations, or valuesets, Oracle OLAP automatically converts the ID data to text during the import process.
Existing Programs and Models
When you are importing a program or model that already exists in your workspace, you must specify DFNS. A program or a model is a definition only; it does not have any data. The default option DATA does not import the source code when it already exists.
When you define a program, you may specify a data type or a dimension name, which is used when the program is called as a function. When you specify a data type, it determines the data type of the return value. When you specify a dimension name, the return value is a single value of that dimension. When you import an existing program, the data type or the dimension in the imported program definition and the existing program definition must match. Otherwise, Oracle OLAP produces an error message.
PERMIT Statements
The PERMIT statements associated with an object are imported with the object definition. You can see them when you describe the object. However, permission conditions are not evaluated when the object is imported.
When an object with the same name already exists in the target workspace and you specify the DFNS keyword, the PERMIT statements for the object are updated. However, you must execute a PERMITRESET to put the new permission into effect. When an object with the same name already exists in the target workspace and you do not specify the DFNS keyword, the PERMIT statements for the object are not updated. When there is no pre-existing object in the target workspace, and you import with or without the DFNS keyword, the PERMIT statements for the object are updated, but you must execute a PERMITRESET to put the new permission into effect. (See the PERMIT command.)
When you export and import an entire workspace, then update, detach, and reattach the workspace, Oracle OLAP ensures that all the permissions that were in effect before exporting are in place in the target workspace.
Reducing Workspace Size
You can use IMPORT with an EXPORT statement to compact an entire workspace at once. To do this, first export the workspace and then import it under a different name. You can then delete the old workspace and rename the new one with the original name.
Preserving Conjoint Type
When you export a HASH, BTREE, or NOHASH conjoint dimension to an EIF file, the conjoint type is exported along with the definition in the EIF file. When you then import the conjoint dimension into an analytic workspace, Oracle OLAP preserves the conjoint type when you import into a new dimension or a dimension already using that conjoint type. When you import the dimension into an existing dimension that does not use the same conjoint type, Oracle OLAP does not preserve the original conjoint type that was saved in the EIF file.
EIFBYTES, EIFNAMES, and EIFTYPES
You can use the EIFBYTES option to learn the number of bytes read or written by the most recent IMPORT (EIF File) statement. You can use the EIFNAMES option to get a list of the names of all the objects imported by the most recent IMPORT statement and use the EIFTYPES option to learn the types of objects in that list.
The following format causes IMPORT to store information about the specified objects into the EIFNAMES and EIFTYPES options without actually importing the objects. IMPORT places a list of the object names specified by the IMPORT command in the EIFNAMES option. IMPORT also places a list of the type of each object listed in EIFNAMES into the EIFTYPES option. You may use the LIST keyword to send to the current outfile a full listing of the object definitions.
IMPORT name FROM EIF FILE file-id [LIST] ONLY
For more information, see the entries for EIFBYTES, EIFNAMES, and EIFTYPES options.
Importing Unnamed Composites
When you define variables or other objects with the SPARSE keyword in the dimension list, Oracle OLAP creates an unnamed composite that corresponds to the SPARSE dimension list. When you export or import an object with the unnamed composite in its definition, the composite is automatically exported or imported with the object. Since the unnamed composite is not a regular workspace object, you cannot import or export it independently.
Variable Segments Specified with SEGWIDTH
When you use a CHGDFN statement with the SEGWIDTH keyword to specify the length of variable segments, segment information cannot be exported and imported automatically. You can save your SEGWIDTH settings by exporting the entire workspace, creating a new workspace, importing only the workspace objects into the new workspace, specifying segmentation, and then importing the variable data into the new workspace.
Importing TEXT and NTEXT Values
You can export and import TEXT and NTEXT values. Both data types can be exported to a single EIF file.
Exported TEXT values are stored in the EIF file using the character set specified for the file in the EXPORT (EIF).
Exported NTEXT values are stored in the EIF file as NTEXT (UTF8 Unicode).
NTEXT values imported into TEXT objects are converted into the database character set which can result in data loss when the NTEXT values cannot be represented in the database character set.
TEXT values imported into NTEXT objects are converted into the NTEXT (UTF8 Unicode) character set.
Examples
Example 10-7 Importing Dimensions from an EIF File
This example shows how to import the contents and dimensions of two variables into the current Oracle OLAP workspace from a disk file called finance.eif in the current directory object.
IMPORT actual budget FROM EIF FILE 'finance.eif'
Example 10-8 IIMPORTING a Concat Dimension
This example shows the result of importing a concat dimension that has a definition that is different than a concat dimension that already exists in the current analytic workspace. Suppose that a DESCRIBE statement returns the following definitions for dimensions and variables in the current analytic workspace.
DEFINE city TEXT DIMENSION DEFINE state TEXT DIMENSION DEFINE country TEXT DIMENSION DEFINE locality DIMENSION CONCAT (city, state) DEFINE geog DIMENSION CONCAT (locality, country) DEFINE sales INTEGER VARIABLE <geog>
The following statement reports the sales data.
REPORT sales
The preceding statement produces the following results.
GEOG SALES ------------------- ----- <city: Boston> 1000 <city: Springfield> 2000 <state: Ma> 3000 <country: Usa> 4000
A DESCRIBE statement returns the following definitions for dimensions and variables in the diffconcat.eif file.
DEFINE CITY TEXT DIMENSION DEFINE REGION TEXT DIMENSION DEFINE COUNTRY TEXT DIMENSION DEFINE GEOG DIMENSION CONCAT (CITY, REGION, COUNTRY) DEFINE SALES INTEGER VARIABLE <GEOG>
The following statement reports the sales data for the dimension values in the analytic workspace from which you exported the concat dimension that is in the diffconcat.eif file.
REPORT sales
The preceding statement produces the following results.
GEOG SALES ------------------ ----- <city: Boston> 1111 <city: Worcester> 2222 <region: East> 3333 <country: Usa> 4444
The following statement imports the sales variable from the diffconcat.eif file and implicitly imports the concat dimension geog. The APPEND keyword causes Oracle OLAP to add the value Worcester to the city dimension. After that, it imports new values for sales that correspond to <city: Boston>, <city: Worcester>, and <country: Usa>.
IMPORT sales FROM EIF FILE diffconcat.eif APPEND
After the import operation, reporting the SALES values produces the following results.
GEOG SALES ------------------- ----- <city: Boston> 1111 <city: Springfield> 2000 <city: Worcester> 2222 <state: Ma> 3000 <country: Usa> 4444
You can use the IMPORT (from text) command to copy data from a text file into an Oracle OLAP worksheet object. A worksheet's rows are similar to the lines of a text file.
IMPORT is commonly used to copy text files into an analytic workspace from other software products.
Typically, you use a FILEREAD statement for text files instead of IMPORT. FILEREAD is more efficient and does not require a worksheet object or separate handling of each column of data.
Syntax
IMPORT worksheetname FROM [TEXT|STRUCTURED|RULED [RULER ruler-exp] -
PRN FILE file-id [STOPAFTER n] [TEXTSTART schar] [TEXTEND echar] -
[DELIMITER dchar] [NLS_CHARSET charset-exp]
Parameters
A text expression that specifies the name of an Oracle OLAP worksheet object. When you have not previously defined worksheetname in your workspace, IMPORT defines it for you automatically, using the default dimensions WKSCOL and WKSROW. Any previous contents of worksheetname are overwritten. In any one IMPORT statement, you can import only one worksheetname from one text file.
Indicates that you want to import your Oracle OLAP worksheet from a text file.
Imports a whole source file as-is into an Oracle OLAP worksheet on a line-by-line basis. The source file is copied into a single wide worksheet column with a data type of TEXT. The column is always column 1 of the worksheet. Each line in the source file is imported into a separate cell on a separate row in the first column, using as many rows as there are lines in the source file. A blank line in the source file produces a TEXT value with zero characters (a null) in the corresponding row of the worksheet's first column. (TEXT is the default.)
Imports a source file into a target worksheet on a cell-by-cell basis, automatically performing three functions:
Each line of characters in the source file is copied into a single row of the target worksheet.
Each group of characters on a line in the source file is copied into a separate TEXT cell on the target worksheet row. A group of characters is defined by two conditions: an uninterrupted (exce^pt by a decimal point) sequence of numbers, or enclosure in double quotes. Consequently, numbers containing commas to mark off thousands are split up into different cells unless the commas are first removed.
Any non-numeric characters not enclosed in double quotes are ignored, except minus signs that immediately precede numbers and so are copied into the same TEXT cell along with the numbers. (Be sure there are no spaces between a minus sign and its number in the source file.)
A blank line in the source file results in an NA in the first cell of the corresponding worksheet row.
When your file format does not conform to the pattern described here, you can use the TEXTSTART, TEXTEND, and DELIMITER keywords. These arguments let you customize the delimiters IMPORT uses to identify the start and end of each field.
Indicates import of a file on a column-by-column basis into worksheet cells of various data types. Every line in the source file must follow the same pattern of data along its length as every other line in the file. You describe this data pattern to Oracle OLAP in the one-line ruler-exp using the RULER keyword. IMPORT loops over each line in the source file and copies its contents into a corresponding pattern of cells on a row of the target worksheet, one row for each line. As ruler-exp loops over successive lines in the source file, it adds row after row to the target worksheet, building vertical columns of similar cells as it goes along. Status messages are sent to the current outfile every 20 rows, starting with the message 20 rows processed.
When the source file contains records that follow several different patterns of character groups, use the less exacting options, STRUCTURED or TEXT, to import the data.
Used only with the RULED keyword to specify the data type, length, and repeat count of each character group in the record pattern of the source file. Ruler-exp consists of a list of character-group specifications. Each character-group specification must be separated by a comma (,), by backslash N (\n), or by a space( ). You do not have to include enough specifications to account for all the characters in the basic record pattern (or line pattern) of the source file; RULER steps to the next record as soon as it runs out of specifications on each line, regardless of how far it is from the end of the current record. Remember to enclose literal text in single quotes.
The specifications for groups of characters are of three types: T for TEXT, A for numeric (INTEGER or DECIMAL), and S for skip or ignore. The formats for these types are shown in Table 10-1, "Character-Group Specifications for IMPORT from Text".
Table 10-1 Character-Group Specifications for IMPORT from Text
| Format | Description |
|---|---|
|
[mm] |
Specifies that Oracle OLAP should copy mm groups (default = 1) of nn characters (bytes) apiece as TEXT. Specifying a group (or groups) of 0 characters leaves an empty cell(s) in the corresponding position in the worksheet. Each group may consist of up to 400098 characters. Trailing blanks are stripped. |
|
[mm] |
Specifies that Oracle OLAP should copy mm groups (default = Commas embedded in a number before a period (decimal point) are ignored. Consequently, multiple numbers separated only by commas or two numbers separated only by a single period are treated as parts of a single number (when you want the numbers treated separately, insert spaces between them in the source file). Leading dollar signs ( Numbers preceded by a hyphen, or a hyphen and spaces, and numbers enclosed in parentheses, are treated as negative. Specifying a group (or groups) of |
|
[ |
Specifies that Oracle OLAP should skip or ignore mm groups of nn characters (bytes). The limit for nn is 32,767. (You would probably only use mm to expand this limit to handle a very long record.) |
Identifies the file you want to import. File-id is a text expression that represents the name of the file. The name must be in a standard format for a file identifier.
Specifies that no more than n records should be read from the file. When STOPAFTER is omitted, Oracle OLAP reads the whole file.
The schar argument is a text expression that specifies a single character that you want Oracle OLAP to interpret as the start of a text field in a structured file. The default character is a double quote (").
The echar argument is a text expression that specifies a single character that you want Oracle OLAP to interpret as the end of a text field in a structured file. The default character is a double quote (").
The dchar argument is a text expression that specifies a single character that you want Oracle OLAP to interpret as the general field delimiter in a structured file. Oracle OLAP uses the general field delimiter to identify both numeric and text fields. The default character is a comma (,).
Specifies the character set that Oracle OLAP uses when importing text data from the file specified by file-id which allows Oracle OLAP to convert the data accurately from that character set. This argument must be the last one specified. When this argument is omitted, and Oracle OLAP cannot determine the character set from the file itself, then Oracle OLAP imports the data in the database character set, which is recorded in the NLS_LANG option.
Usage Notes
WKSROW and WKSCOL Dimensions
The WKSROW (the default worksheet row) dimension of an Oracle OLAP worksheet object corresponds to the lines of a text file. The WKSCOL (the default worksheet column) dimension of a worksheet divides each row into cells that can be used to separate data types when there are potentially several types on each line of the source file. WKSROW and WKSCOL are INTEGER dimensions with values of 1, 2, 3, and so on.
Minimum Worksheet Size
Oracle OLAP sets up a minimum-size worksheet that is 63 cells square, regardless of whether or not all the cells are used. When the source text file requires an Oracle OLAP worksheet larger than the minimum, IMPORT automatically increases the dimension values of WKSCOL and WKSROW as needed.
Importing Numbers
When importing a number from a text file, IMPORT gives it an INTEGER data type.
File Transfer to Another Computer
When the file you are importing originated on another computer, ensure that its character set is appropriate. When you transfer a text file to another computer, the communications program handling the transfer makes any necessary character translations; for example, from ASCII to EBCDIC. Set the parameters of the transfer program so that the resulting file is in the correct character set for the receiving computer.
Examples
Example 10-9 Importing Columns Without the RULER Keyword
Suppose you have a file named abctxt in your current directory. It has 10 five-digit groups of INTEGER values, followed by a group of 20 characters of text. To import this file into an Oracle OLAP worksheet called sheet1, use the following statement.
IMPORT sheet1 FROM RULED PRN FILE 'abctxt' ruler '10a5, t20'
The actual format for the file name must follow the conventions for your operating system.
Example 10-10 Importing Columns with the RULER Keyword
Suppose a file called mix has no line delimiters, with records containing 100 characters apiece. Each record has the character distribution illustrated in the following table.
| Character | Content |
|---|---|
| 1 - 10 | To be ignored |
| 11 - 17 | Decimal number |
| 18 - 28 | To be ignored |
| 29 - 30 | Two single-character code |
| 31 - 35 | Integer |
| 36 - 100 | To be ignored |
To import this file into an Oracle OLAP worksheet called sheet2, use the following statement.
DEFINE sheet2 WORKSHEET temp IMPORT sheet2 FROM RULED PRN FILE 'mix' RULER - 's10, a7, s11, 2t1, a5'
You can use the IMPORT (from spreadsheet) command to copy data (not formulas) from a spreadsheet file into an Oracle OLAP worksheet object. A worksheet's dimensions are similar to the columns and rows of a spreadsheet. IMPORT always copies an entire spreadsheet file at a time.
IMPORT is commonly used to copy data from other software products (for example, a Lotus spreadsheet) into an Oracle OLAP workspace.
Syntax
IMPORT worksheetname FROM source [INTO workspace]
where source is one of the following:
Parameters
An Oracle OLAP worksheet object. In any one IMPORT statement, you can import only one worksheetname from one spreadsheet file. You can specify a qualified object name for the worksheet; however, when you specify the INTO worksheet argument, the target workspace specified must be identical. See the INTO workspace argument for information about where the worksheet object is imported.
Indicates that you want to import your Oracle OLAP worksheet from a 1-2-3 file, Version 1 (WKS) or Version 2 (WK1); a Symphony file, Version 1.0 (WRK) or Version 1.1 (WR1); or a data interchange format file (DIF).
Oracle OLAP does not recognize numbers in E format (exponential notation) in DIF files.
An analytic workspace name that identifies the attached workspace into which data is imported. When worksheetname exists in the specified workspace, then its data is overwritten by the imported data. When worksheetname does not already exist, IMPORT creates it in the specified workspace. IMPORT ignores an identically named worksheet when it exists in another attached workspace.
When you do not specify this argument, then Oracle OLAP does the following:
When you have not previously defined worksheetname in an attached workspace, IMPORT defines it automatically in the current workspace using the default dimensions WKSCOL and WKSROW.
When worksheetname already exists in any attached workspace, IMPORT overwrites the data it contains with the imported data.
Identifies the file you want to import. The file-id argument is a text expression that represents the name of the file. The name must be in a standard format for a file identifier.
Specifies the character set that Oracle OLAP uses when importing text data from the file specified by file-id which allows Oracle OLAP to convert the data accurately from that character set. This argument must be the last one specified. When this argument is omitted, and Oracle OLAP cannot determine the character set from the worksheet itself, then Oracle OLAP imports the data in the database character set, which is recorded in the NLS_LANG option.
|
Note: The NTEXT data type is not supported in worksheets. |
Indicates that you want to import from a source file on a cell-by-cell basis. See "CSV Import".
STOPAFTER n specifies that no more than n records should be read from the file. When STOPAFTER is omitted, Oracle OLAP reads the whole file.
DELIMITER dchar identifies the single character (dchar) that you want Oracle OLAP to interpret as the general field delimiter. The default value is comma.
Usage Notes
Default Dimensions of an Oracle OLAP worksheet object
The default dimensions of an Oracle OLAP worksheet are WKSCOL and WKSROW, which correspond to the columns and rows of a spreadsheet. WKSCOL and WKSROW are INTEGER dimensions with values of 1, 2, 3, and so on. When these dimensions already exist in an attached workspace but not in the current workspace, the IMPORT statement fails when it tries to create these dimensions. You can prevent this problem by first defining the worksheet with different dimensions. (See "Worksheet Dimensions" for more information.)
Addition of Cells when Needed
When the source spreadsheet contains more cells than are defined by the dimensions of the worksheet, IMPORT automatically adds dimension values to provide the required number of cells.
Empty and NA Cells
IMPORT merges the source file with the worksheet on a cell-by-cell basis. Cells from the source file that are not empty, even when they just contain NA, overwrite the contents of the corresponding cells in the worksheet; empty cells in the source file do not overwrite the worksheet; source-file cells beyond the end of the current worksheet are appended to it so that no data is discarded.
Numbers in DIF Files
When importing any number from DIF files, IMPORT gives it a DECIMAL data type.
CSV Import
The CSV import option automatically performs the following functions when importing from a source file into the cells of a worksheet:
Each line of characters in the source file is copied into a single row in the target worksheet.
Each group of characters on a line in the source file is copied into a separate TEXT cell in the target worksheet row, and groups are separated by the delimiter character.
When a group of characters is inside double quotation marks:
A delimiter character found in this group is treated as a literal.
When a double quotation mark occurs within this group, it must be followed by another double quotation mark.
A linefeed (\n) found within the group is ignored.
Spaces or tabs found before a starting quotation mark and after an end quotation mark are ignored.
Examples
Example 10-11 Importing a DIF File
This example shows how to import a spreadsheet in DIF format in a file called mortgage.dif. We define the worksheet first as a temporary object, which saves memory and storage space. IMPORT would define the worksheet sheet1 automatically when it did not already exist. When it had already been used in a previous IMPORT statement, any data in it would be overwritten with new data.
DEFINE sheet1 WORKSHEET TEMP IMPORT sheet1 FROM DIF FILE 'mortgage.dif'
The POP command restores the status of a dimension (including the NAME dimension), the status of a valueset, or the value of an option or single-cell variable that was saved with a previous PUSH statement.
PUSH and POP are commonly used within a program to make changes to options and dimension status that apply only during the program's execution. Afterward, the options and status are the same as they were before the execution of the program.
Syntax
POP name1 [nameN]
Parameters
The name of a dimension, valueset, variable, or option that was specified in a previous PUSH statement, whose saved value you want to restore.
Examples
For an example of using POP, see Example 10-84, "Saving and Restoring Values".
The KEY function returns the value of the specified base dimension for a value of a conjoint dimension or a composite.
Return Value
The return value depends on the data type of the specified base dimension.
Syntax
KEY(dimension-exp, base-dimension-exp)
Parameters
An expression that specifies a value of a conjoint dimension or a composite. When you specify the conjoint dimension itself, KEY uses the first value in status. When you specify the composite itself, KEY uses the first value in status for every base dimension in the composite.
An expression that specifies the name of a base dimension of the previously specified conjoint dimension or composite for which you want to know the dimension value.
Examples
Example 7-139 Reporting with a Conjoint
Suppose you want to produce a report of data dimensioned by a conjoint dimension. You can label each row with the base values of each conjoint dimension value with the KEY function. Each base value occupies its own column and you have more control over the layout.
The following program excerpt loops over the conjoint dimension proddist, whose values are a combination of product and district. Assume also that there is a variable named dsales which is dimensioned by proddist.
DEFINE proddist DIMENSION <product district> LD Conjoint dimension made up of combinations of product and district values DEFINE dsales VARIABLE DECIMAL <month proddist> LD Sparse sales data made dense by dimensioning by conjoint dimension proddist
The program excerpt shows dsales for three months. The base values of the conjoint dimension value each occupy their own column. For contrast, the second loop uses the conjoint dimension directly, without the KEY function. The conjoint dimension values are displayed in one column, with angle brackets.
LIMIT month TO FIRST 3 FOR proddist ROW KEY(proddist district) KEY( proddist product) ACROSS month: dsales BLANK 2 FOR proddist ROW W 25 proddist ACROSS month: dsales
The program produces the following report.
Boston Tents 32,153.52 32,536.30 43,062.75 Denver Canoes 45,467.80 51,737.01 58,437.11 Atlanta Sportswear 114,446.26 123,164.92 138,601.64 <Tents, Boston> 32,153.52 32,536.30 43,062.75 <Canoes, Denver> 45,467.80 51,737.01 58,437.11 <Sportswear, Atlanta> 114,446.26 123,164.92 138,601.64
The FILEVIEW command works with the FILENEXT function to read one record at a time of an input file, process the data, and store the data in Oracle OLAP dimensions and variables according to the descriptions of the fields. Use FILENEXT to read the record, then use one or more FILEVIEW statements to process the fields as needed. FILEVIEW has the same attributes as FILEREAD for specifying the format of the input and the processing of the output.
Syntax
FILEVIEW fileunit [field-desc...]
Parameters
A fileunit number that is assigned to a file opened for reading (READ mode) in a previous call to the FILEOPEN function.
A field description describes how to process one or more fields in each input record. Attributes in the field description specify how to format the input data. FILEVIEW reads each field according to the format specification and assigns the input data to the specified object. You can assign the data to the object directly or you can specify an expression to manipulate the data before you assign it. One field description can assign data from one input field to one Oracle OLAP object. Alternately you can use the ACROSS keyword to assign several values in the input record to a variable that is dimensioned by the fastest varying dimension. Because field attributes include the column number in the input record, you can process input fields in any order.
The format for the field description is as follows.
[[pos] ACROSS dim [limit-clause]:] [attribs] object [= exp]
One or more attributes that specify the position in the record where Oracle OLAP begins reading the fields specified by the ACROSS description. To specify the position, use the attributes FIELD, SPACE, and COLUMN (see the FILEREAD command). The pos argument is optional when the series of fields specified in the ACROSS phrase begins in the next field for structured records, or the next byte for ruled records.
Specifies the dimension of one or more data fields in the input record. FILEVIEW assigns the data in the fields to a variable according to the values in the current status of dim. Typically, each field description processes one value. However, using the ACROSS keyword, you can process one input value for each dimension value currently in the status. When you want the looping to apply to multiple action statements, enclose the action statements in angle brackets.
An ACROSS statement has the following syntax.
ACROSS dimension [limit-clause]:
action-statement
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
The following example limits month to the last six values, no matter what the current status of month is.
ACROSS month last 6: units
One or more attributes that tell Oracle OLAP the position in the record and the format of the input data. (See the FILEREAD command for an explanation of the available attributes.)
An Oracle OLAP variable, dimension, or relation to which the input data is assigned. When = exp is missing, the data is assigned implicitly to the object. When = exp is present, the data is processed according to the expression and then assigned to object.
You can use the keyword VALUE to represent the value in a particular field of a record. VALUE represents the data from the file, formatted according to the FILEREAD attributes you use. When the field in the record is blank, FILEREAD considers its value to be NA. By default, the data type of VALUE is the data type of the target object. However, you can specify a different data type with an attribute keyword. VALUE can be used more than once to represent different values from the same record. For each instance, specify the column from which to read each value, as shown in the following example code.
sales = if col 1 w 1 text value eq 'A' then col 2 w 8 value - else col 10 w 8 value
In this example, the default data type of VALUE is decimal, which is the data type of the target object sales. However, the first instance of VALUE is compared to a text expression, so you must use the attribute TEXT to specify its data type.
The SELECT field-description keyword processes varying record types (such as records with different structures or different target objects) with one FILEVIEW statement. Within a field description, you can use the following syntax:
SELECT exp -
[WHEN exp action [WHEN exp action ...]] -
[ELSE action]
IF bool-exp THEN action [ELSE action]
DO
field-desc
[field-desc]
...
DOEND
The action argument is one of the following:
NULL (no action occurs)
field-description, including nested IF and SELECT statements.
SELECT evaluates the first expression, which may contain invocations of the VALUE keyword, and which has a default data type of TEXT. SELECT then sequentially compares the result with the WHEN expressions. When the first match is found, the associated action occurs. When no match is found, the ELSE action (if specified) occurs.
The IF field-description keyword processes varying record types (such as records with different structures or different target objects) with one FILEVIEW statement. Within a field description, you can use the following syntax.
IF bool-exp THEN action [ELSE action]
action is the same as described for SELECT.
IF evaluates the Boolean expression, which may contain invocations of the VALUE keyword. IF performs the THEN action when the expression is TRUE or the ELSE action, if specified, when the expression is FALSE. No action occurs when the expression is NA.
Usage Notes
Record Order
FILEVIEW can process the fields in a record in any order. List the field descriptions in the order you want to process them, identifying the fields with explicit column numbers. You can also use several FILEVIEW statements on the same record to do different processing depending on the data you find in the record.
Alternative OLAP DML Statement
When you want to process all the records in a file in the same way, without complicated optional processing, a FILEREAD statement is easier to use.
Dimension Values
When the target object of a field description is a dimension, you can specify whether the data in the file is used to add values to the dimension or not. The dimension attributes are MATCH and APPEND:
MATCH -- Any value encountered in a field must already be a value of the dimension. FILEVIEW temporarily limits status to that value. When it is not already a dimension value, FILEVIEW generates an error. After executing a FILEVIEW statement, the dimension status is the same as before the execution of the statement.
APPEND -- The values in the field can already exist or they can be new. When the value exists, FILEVIEW limits status to that value; when it does not, FILEVIEW adds the value and then limits status. The dimension is limited to ALL when FILEVIEW is finished.
For more information about handling dimensions, see the FILEREAD command.
Handling Errors When FILEVIEW Encounters an Error
When FILEVIEW encounters an error, you can control what happens with an error trap and appropriate processing. Errors can be caused by attempts to convert data to an incompatible data type or by encountering invalid dimension values. You can use the FILEERROR function to find out what type of error occurred. After processing the error, you can use GOTO to branch back to the FILEVIEW statement.
Attribute List
For a complete list of the attributes for FILEVIEW and FILEREAD and for more information about processing NA values, reading date values, reading multidimensional data, storing NTEXT values, and specifying attributes, see the FILEREAD command.
FILEVIEW with Composites
The discussions of composites and variables dimensioned by composites in FILEREAD also apply to FILEVIEW.
Examples
Example 9-133 Varying Months
The following program processes an input file that contains sales data for a variable number of months. The file has the following records:
Record 1 -- Title (to be ignored).
Record 2 -- Column labels. Month names are used to set the status of month. The number of months is unknown before processing the file.
Record 3 -- Dashes underlining column labels (to be ignored).
Record 4 -- Blank.
Record 5 to end -- There are three record types for Record 5—one for each type of line to be read.
One record type for Record 5 represents a detail line with the contents shown in the following table.
| Column | Width | Format | Data |
|---|---|---|---|
| 1 | 8 | Symbolic | District name or blank (When the district name is blank on a detail line, the most recent line containing a district determines the current district.) |
| 10 | 10 | Symbolic | Product name |
| 21 | 10 | Symbolic | Sales for first month |
| 33 | 10 | Symbolic | Sales for second month |
| 45 | To end of record | Symbolic | Sales for additional months |
Another record type in Record 5 represents a totals line with the contents shown in the following table.
| Column | Width | Data |
|---|---|---|
| 1 | 18 | Blank |
| 21 | To end of record | Totals |
A third record type of Record 5 contains dashes or equal signs as row separators as illustrated in the following table.
| Column | Width | Data |
|---|---|---|
| 1 | 18 | Blank |
| 21 | To end of record | Dashes (--) or equal signs (==) |
This is a report of the sample file.
This is the Title
Jan95 Feb95 Mar95 Apr95
---------- ---------- ---------- ----------
Boston Tents 32,153.52 32,536.30 43,062.75 57,608.39
Canoes 66,013.92 76,083.84 91,748.16 125,594.28
Racquets 52,420.86 56,837.88 58,838.04 69,338.88
Sportswear 53,194.70 58,913.40 62,797.80 67,869.10
Footwear 91,406.82 86,827.32 100,199.46 107,526.66
---------- ---------- ---------- ----------
295,189.82 311,198.74 356,646.21 427,937.31
---------- ---------- ---------- ----------
Atlanta Tents 40,674.20 44,236.55 51,227.06 78,469.37
.
.
.
Footwear 53,284.54 57,331.30 59,144.76 70,516.98
---------- ---------- ---------- ----------
231,780.46 245,812.33 275,622.68 355,784.92
---------- ---------- ---------- ----------
1,813,326 1,985,731 2,185,174 2,638,409
========== ========== ========== ==========
The program figures out which months are covered in the file, then reads the detail lines and assigns the sales data to the appropriate district and month. The program ignores total lines and underlines when FILEVIEW finds columns 1 through 19 blank. The program takes the name of the data file as an argument.
DEFINE salesdata PROGRAM
LD Store Several Months of Sales Data in an Analytic Workspace
PROGRAM
VARIABLE fil.unit INTEGER
VARIABLE flag BOOLEAN
VARIABLE mname TEXT
VARIABLE label TEXT
VARIABLE savedist TEXT
TRAP ON error NOPRINT
PUSH month district
fil.unit = FILEOPEN(ARG(1) READ)
IF FILENEXT(fil.unit) NE YES "Skip Record 1
THEN SIGNAL noread
IF FILENEXT(fil.unit) NE YES "Process Record 2
THEN SIGNAL noread
FILEVIEW fil.unit COLUMN 21 ACROSS month: -
WIDTH 10 mname = JOINLINES( mname VALUE)
LIMIT month TO mname
IF FILENEXT(fil.unit) NE YES "Skip Record 3
THEN SIGNAL noread
IF FILENEXT(fil.unit) NE YES "Skip Record 4
THEN SIGNAL noread
WHILE FILENEXT(fil.unit) "Process Record 5 To End Of File
DO
"Store Value In Local Label Variable
FILEVIEW fil.unit COLUMN 1 WIDTH 18 label
IF label NE NA "Check For NA (Blank Field)
THEN DO "Get District Value If Present
IF EXTCHARS(label, 1, 8) NE ' '
"Set District Status
THEN savedist = BLANKSTRIP(EXTCHARS(label, 1, 8))
FILEVIEW fil.unit -
COLUMN 1 WIDTH 8 district = IF VALUE NE NA THEN -
VALUE ELSE savedist -
COLUMN 10 WIDTH 10 product -
COLUMN 19 ACROSS month: WIDTH 10 SPACE 2 -
SCALE 2 newsales
DOEND
NEXT:
DOEND
FILECLOSE fil.unit
POP month district
RETURN
error:
IF fil.unit EQ NA
THEN SHOW JOINCHARS('Can\'t Open Data File ' ARG(1) '.')
ELSE IF ERRORNAME NE 'attn' AND ERRORNAME NE 'QUIT'
THEN DO
SHOW JOINCHARS('RECORD ' RECNO(fil.unit) ' is invalid.')
GOTO NEXT
DOEND
ELSE IF ERRORNAME EQ 'noread'
THEN DO
SHOW 'File Too Short.'
FILECLOSE fil.unit
DOEND
ELSE DO
SHOW 'Data Import Interrupted.'
FILECLOSE fil.unit
DOEND
POP month district
RETURN
Example 9-134 Additional Processing
When you want to save the dimension value that FILEVIEW read for display or further processing, you can read the field again and save the value in a variable. These lines in a program display the name of the month that FILEVIEW read. The FILEVIEW command saves the month value in column 1 in a variable called mname.
WHILE FILENEXT(fil.unit)
DO
FILEVIEW fil.unit WIDTH 8 month WIDTH 5 INTEGER units -
COLUMN 1 WIDTH 8 mname
SHOW mname PROMPT
DOEND
Example 9-135 Using the VALUE Keyword as a Function
Suppose you want to read and report data from a disk file similar to the following, named numbers.dat, which has columns 15 characters wide.
1.0 2.0 3.0 4.0 5.0
-1.0 -2.0 -3.0 -4.0 -5.0
0.0 0.0 1.43900000E+03 1.39900000E+03
You can read this data using the VALUE keyword as a function with FILEVIEW in a program similar to the following one (named try). However, this first example does not work. The FILEVIEW command skips fields. The reason for the data skipping is that each time FILEREAD fetches a field from the current record, it updates the column pointer to point past the field. When the next fetch does not specify a position (using the COLUMN, SPACE, or FIELD attribute), data is read from the default position established by the previous fetch. This behavior is typically desirable; however it does not work when multiple fetches are needed to perform a single assignment (for example, when the VALUE function is coded twice in the same IF...THEN...ELSE command block, as shown here). The NAMELIST and DIRLIST attributes return one value for multiple versions of a particular file name in the directory. The NAMELIST attribute also returns only one value for multiple files in the directory with the same root file name but different file types.
DEFINE try PROGRAM
PROGRAM
VARIABLE funit INTEGER
DEFINE dvar VARIABLE DECIMAL <year>
PUSH year
LIMIT year TO LAST 5
TRAP ON ERROR
funit=FILEOPEN('numbers.dat' R)
WHILE FILENEXT(funit)
DO
FILEVIEW funit ACROSS year: W 15 TEXT dvar = -
IF FINDCHARS(VALUE, 'e') EQ 0 - "Incorrect Use of Value
THEN CONVERT(VALUE, dec) - "Results in Skipped
ELSE -9999.99 "Fields
REPORT DOWN year dvar
DOEND
error:
FILECLOSE funit
DELETE dvar
POP year
END
When you execute the try program,
try
the output skips numbers, as in the following.
YEAR DVAR ------------- ---------- Yr93 2.00 Yr94 4.00 Yr95 NA Yr96 -9,999.99 Yr97 -9,999.99 YEAR DVAR ------------- ---------- Yr93 -2.00 Yr94 -4.00 Yr95 NA Yr96 -9,999.99 Yr97 -9,999.99 YEAR DVAR ------------- ---------- Yr93 0.00 Yr94 -9,999.99 Yr95 -9,999.99 Yr96 -9,999.99 Yr97 -9,999.99
However, when the SPACE attribute is used to make the second VALUE back up some distance so it reads the same field that the first VALUE read, everything works fine. SPACE can be used in the preceding sample program by changing the THEN clause to the following clause.
THEN CONVERT(SPACE -15 VALUE, dec) -
Now when you execute the program,
try
the output looks like this.
YEAR DVAR ------------- ---------- Yr93 1.00 Yr94 2.00 Yr95 3.00 Yr96 4.00 Yr97 5.00 YEAR DVAR ------------- ---------- Yr93 -1.00 Yr94 -2.00 Yr95 -3.00 Yr96 -4.00 Yr97 -5.00 YEAR DVAR ------------- ---------- Yr93 0.00 Yr94 0.00 Yr95 -9,999.99 Yr96 -9,999.99 Yr97 -9,999.99
Within an OLAP DML program, the ARGCOUNT function returns the number of arguments that were specified when the current program was invoked.
Return Value
INTEGER
Syntax
ARGCOUNT
Examples
Example 7-21 Checking the Number of Arguments
In the following example, the program, a user-defined function, verifies that three arguments are passed. When the number of arguments passed is not equal to 3, the program terminates with -1 as a return value.
DEFINE threearg PROGRAM INTEGER
LD User-defined function expecting three arguments
PROGRAM
ARGUMENT division TEXT
ARGUMENT product TEXT
ARGUMENT month MONTH
IF ARGCOUNT NE 3
THEN RETURN -1
ELSE
DO
...
The SYS_CONTEXT function returns the value of parameter associated with the context namespace.
|
See also: For more information, see the SYS_CONTEXT function in Oracle Database SQL Language Reference. |
Return Values
VARCHAR2.
Syntax
SYS_CONTEXT(namespace, parameter [, length ])
Parameters
A text expression that specifies a namespace which is a valid SQL identifier. The context namespace must have been created, and the associated parameter and its value must also have been set using the DBMS_SESSION.set_context procedure.
A text expression that specifies an attribute associated with a namespace. This parameter and its value must have previously been set using the DBMS_SESSION.set_context procedure. The parameter is not case sensitive, but it cannot exceed 30 bytes in length.
A numeric expression that specifies the maximum size of the return value. The value that you specify must be a NUMBER (or a value that can be implicitly converted to NUMBER) and in the range of 1 to 4000 bytes,. If you specify an invalid value, then Oracle OLAP ignores it and uses the default value of 256 bytes.
Usage Notes
USERENV Built-In Namespace
Oracle provides a built-in namespace called USERENV, which describes the current session.
For more information on the predefined parameters of namespace USERENV, see the SYS_CONTEXT function in Oracle Database SQL Language Reference.
Examples
The TO_TIMESTAMP_TZ function converts text data to a value with the TIMESTAMP_TZ data type.
Return Value
TIMESTAMP_TZ
Syntax
TO_TIMESTAMP_TZ (char-exp [, fmt [ 'nlsparam' ] ])
Parameters
A text expression that you wan to convert.
Specifies the datetime format template to be used to convert the text expression. See Table 9-4, "Datetime Format Elements" for more information about the datetime format template.
When you omit this argument, the function uses the default format of TIMESTAMP_TZ for the object.
Specifies the language in which month and day names and abbreviations are returned. This argument can have this form:
'NLS_DATE_LANGUAGE = language'
If you omit this argument, then this function uses the default date language for your session.
Examples
The OLAP_API_SESSION_INIT package provides procedures for maintaining a table of initialization parameters for the OLAP API.
This chapter contains the following topics:
The OLAP_API_SESSION_INIT package contains procedures for maintaining a configuration table of initialization parameters. When the OLAP API opens a session, it executes the ALTER SESSION commands listed in the table for any user who has the specified roles. Only the OLAP API uses this table; no other type of application executes the commands stored in it.
This functionality provides an alternative to setting these parameters in the database initialization file or the init.ora file, which would alter the environment for all users.
During installation, the table is populated with ALTER SESSION commands that have been shown to enhance the performance of the OLAP API. Unless new settings prove to be more beneficial, you do not have to make changes to the table.
The information in the table can be queried through the ALL_OLAP_ALTER_SESSION view alias, which is also described in this chapter.
|
Note: This package is owned by theSYS user. You must explicitly be granted execution rights before you can use it. |
ALL_OLAP_ALTER_SESSION is the public synonym for V$OLAP_ALTER_SESSION, which is a view for the OLAP$ALTER_SESSION table. The view and table are owned by the SYS user.
The STARTUP procedure starts an OLAP session without attaching any user-defined workspaces.
STARTUP initializes the OLAP processing environment and attaches the read-only EXPRESS workspace, which contains the program code for the OLAP engine.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
STARTUP ( );
Example
The following example starts an OLAP session.
EXECUTE dbms_aw.startup();
Within an OLAP DML program, the ARGUMENT statement declares an argument that is expected by the program. Within the program, the argument is stored in a structure similar to a variable or valueset. The argument is initialized with the value that was passed when the program was invoked. An argument exists only while the program is running.
The ARGUMENT statement is used only in programs, and it must precede the first executable line in the program. Be careful to distinguish the ARG abbreviation of the ARGUMENT statement from the ARG function.
Syntax
ARGUMENT name {datatype|dimension|VALUESET dim}
Parameters
The name by which the argument is referenced in the program. An argument cannot have the same name as a local variable or valueset. You name an argument according to the rules for naming analytic workspace objects (see the DEFINE command).
The data type of the argument, which indicates the kind of data to be stored. You can specify any of the data types that are listed and described in the DEFINE VARIABLE entry. Also, when you want to the program to be able to receive an argument without converting it to a specific data type, you can also specify WORKSHEET for the data type.
|
Important: When you declare an argument to be of type NTEXT, and a TEXT value is passed into the program, Oracle OLAP converts the TEXT value to NTEXT. Similarly, when you declare an argument to be of type TEXT, and an NTEXT value is passed into the program, Oracle OLAP converts the NTEXT value to TEXT. Data can be lost when NTEXT is converted to TEXT. |
The name of a dimension, whose value is contained in the argument. The argument holds a single value of the dimension. Assigning a value that does not currently exist in the dimension causes an error.
Indicates that name is a valueset. The keyword dim specifies the dimension for which the valueset holds values. Argument valuesets can be used within the program in the same way you would use a valueset in the analytic workspace.
Usage Notes
The Life Span of an Argument
An argument exists only while the program in which it is declared is running. When the program terminates, the argument ceases to exist and its value is lost. Therefore, an argument is not an analytic workspace object.
A program can terminate when a RETURN or SIGNAL statement, or at the last line of the program executes. When the program calls a subprogram, the original program is temporarily suspended and the argument still exists when the subprogram ends and control returns to the original program. A program that calls itself recursively has separate arguments for each running copy of the program.
Declaring Arguments that Are Passed Into a Program
When declaring arguments that are passed into a program special considerations apply.
Arguments Passed by Value Arguments are passed into a program by value. Consequently, the called program is given only the value of an argument, without access to any analytic workspace object to which it might be related. Therefore, you can change an argument value within the called program without affecting any value outside the program. You can think of an argument variable or valueset as a conveniently initialized local variable or local valueset.
Argument Processing for a Function When a program is invoked either with a CALL statement or as a function, the following two-step process occurs:
The specified data types are established. Argument expressions specified by the calling program are evaluated left to right, and their data types are identified. An expression representing a dimension value can be a text (TEXT or ID), numeric (INTEGER, DECIMAL, and so on), or RELATION value. An error in one argument expression stops the process.
Each specified data type is matched with the declared data type. Argument expressions are matched positionally with the declared arguments. The first argument expression is matched with the first declared argument, the second argument expression with the second argument, and so on. Each expression is converted in turn to the declared data type of the declared argument.
When an argument is declared as a dimension value, the matching value passed from the calling program can be TEXT or ID (representing a value of the specified dimension), numeric (representing a logical dimension position), or RELATION (representing a physical dimension position). The RELATION method is the way Oracle OLAP passes along dimension values that are the result of evaluating a dimension name or relation name used as the matching value. When the matching value is a noninteger numeric value (for example, DECIMAL), it is rounded to the nearest INTEGER value to represent a logical dimension position.
When an argument is declared as something other than a dimension value, and the matching value from the calling program is a RELATION value, an error occurs. When you want to pass a RELATION value and receive it as a TEXT argument, use CONVERT to convert the value in the program's argument list.
When an argument is declared as a valueset of a dimension, only the name of a valueset of that dimension is accepted as an argument.
When an error occurs in either the first or second step, the program is not executed.
Argument Processing for a Command When a program is invoked as a standalone command with its arguments not enclosed by parentheses, the arguments are matched positionally with the declared arguments. The called program can reference the specified arguments either as declared arguments or through the ARG (n), ARGS, and ARGFR (n) functions. In this situation, the arguments are passed as text strings, not by value.
Extra Arguments When the calling program specifies more arguments than there are declarations in the called program, the extra arguments are ignored. When the calling program specifies fewer arguments than there are declarations in the called program, the extra arguments are given NA values.
Argument Name that Duplicate the Names of Analytic Workspace Objects
Ordinarily, when you give an argument the same name as an analytic workspace object, the argument (not the analytic workspace object) is referenced within the program. Exceptions to this rule occur only when the statement in which the reference is made requires an analytic workspace object as an argument.
Examples
Example 9-44 Passing an Argument to a User-Defined Function
Sometimes verifying user input to the GET function can become complicated. The usual method involves a line of code such as the following one.
SHOW GET(INT VERIFY VALUE GT 0 AND VALUE LT 100 - IFNOT 'The value must be between 1 and 100')
You can create a user-defined function to make the GET expression simpler. For example, the following program can be used as a function to check for values between 0 and 100.
DEFINE verit PROGRAM BOOLEAN
PROGRAM
ARGUMENT uservalue INT
TRAP ON haderror NOPRINT
IF uservalue GT 100
THEN SIGNAL toobig 'The value must be 100 or smaller.'
ELSE IF uservalue LT 0
THEN SIGNAL toosmall 'The value must be 0 or greater.'
RETURN TRUE
haderror:
RETURN FALSE
END
The following GET expression uses the verit function.
SHOW GET(INT VERIFY VERIT(VALUE) IFNOT ERRORTEXT)
Example 9-45 Passing Multiple Arguments
Suppose, in the product.rpt program, that you want to supply a second argument that specifies the column width for the data columns in the report. In the product.rpt program, you would add a second ARGUMENT statement to declare the INTEGER argument to be used in setting the value of the COLWIDTH option.
ARGUMENT natext TEXT ARGUMENT widthamt INTEGER NASPELL = natext COLWIDTH = widthamt
To specify eight-character columns, you could run the product.rpt program with the following statement.
CALL product.rpt ('Missing' 8)
When the product.rpt program also requires the name of a product as a third argument, then in the product.rpt program you would add a third ARGUMENT statement to handle the product argument, and you would set the status of the product dimension using this argument.
ARGUMENT natext TEXT ARGUMENT widthamt INTEGER ARGUMENT rptprod PRODUCT NASPELL = natext COLWIDTH = widthamt LIMIT product TO rptprod
You can run the product.rpt program with the following statement.
CALL product.rpt ('Missing' 8 'TENTS')
In this example, the third argument is specified in uppercase letters with the assumption that all the dimension values in the analytic workspace are in uppercase letters.
Example 9-46 Using the ARGUMENT Statement
Suppose you are writing a program, called product.rpt. The product.rpt program produces a report, and you want to supply an argument to the report program that specifies the text that should appear for an NA value in the report. In the product.rpt program, you can use the declared argument natext in an ARGUMENT statement to set the NASPELL option to the value provided as an argument.
ARGUMENT natext TEXT NASPELL = natext
To specify Missing as the text for NA values, you can execute the following statement.
CALL product.rpt ('Missing')
In this example, literal text enclosed in single quotes provides the value of the text argument. However, any other type of text expression works equally well, as shown in the next example.
DEFINE natemp VARIABLE TEXT TEMP natemp = 'Missing' CALL product.rpt (natemp)
Example 9-47 Passing the Text of an Expression
Suppose you have a program named custom.rpt that includes a REPORT statement, but you want to be able to use the program to present the values of an expression, such as sales - expense, and individual variables.
custom.rpt 'sales - expense'
Note that you must enclose the expression in single quotation marks. Because the expression contains punctuation (the minus sign), the quotation marks are necessary to indicate that the entire expression is a single argument.
In the custom.rpt program, you could use the following statements to produce a report of this expression.
ARGUMENT rptexp TEXT REPORT &rptexp
For an example of using ampersand substitution to pass multiple dimension values, see Example 10-18, "Using Ampersand Substitution with LIMIT".
Example 9-48 Passing Workspace Object Names and Keywords
Suppose you design a program called sales.rpt that produces a report on a variable that is specified as an argument and sorts the product dimension in the order that is specified in another argument. You would run the sales.rpt program by executing a statement like the following one.
sales.rpt units d
In the sales.rpt program, you can use the following statements.
ARGUMENT varname TEXT ARGUMENT sortkey TEXT SORT product &sortkey &varname REPORT &varname
After substituting the arguments, these statements are executed in the sales.rpt program.
SORT product D units REPORT units
The MODINPUTORDER option controls whether the equations in a simultaneous block of a model are executed in the order in which you place them or in an order determined by the model compiler. MODINPUTORDER has no effect on the order of equations in simple blocks and step blocks.
|
See: "Model Options" for descriptions of all of the options that control the solution of simultaneous blocks. |
Data Type
BOOLEAN
Syntax
MODINPUTORDER = {YES|NO}
Parameters
The equations in a simultaneous block of a model are executed in the order in which they appear in the model.
(Default) The equations in a simultaneous block are executed in an order determined by the model compiler.
Examples
Example 5-55 Using the Default Order
The following statements define the income.calc model.
DEFINE income.calc MODEL MODEL DIMENSION line month Net.Income = Opr.Income - Taxes Opr.Income = Gross.Margin - TOTAL(Marketing + Selling + R.D) Marketing = LAG(Opr.Income, 1, month) Gross.Margin = Revenue - Cogs END
The following statements compile the model and produce a compilation report using the MODEL.COMPRPT program.
COMPILE income.calc MODEL.COMPRPT income.calc
These statements produce the following output.
MODEL INCOME.CALC <LINE MONTH>
BLOCK 1 (SIMPLE)
INCOME.CALC 5: gross.margin = revenue - cogs
BLOCK 2 (SIMULTANEOUS <MONTH>)
INCOME.CALC 4: marketing = lag(opr.income, 1, month)
INCOME.CALC 3: opr.income = gross.margin - total(marketing + selling + r.d)
END BLOCK 2
INCOME.CALC 2: net.income = opr.income - taxes
END BLOCK 1
When you compile income.calc with MODINPUTORDER set to its default value of NO, you can see that the compiler reverses the order of the equations in the simultaneous block.
Example 5-56 Changing the MODINPUT Value
The following statements set the value of MODINPUTORDER to YES, compile the model, and produce a compilation report.
MODINPUTORDER = YES COMPILE income.calc MODEL.COMPRPT income.calc
These statements produce the following output.
MODEL INCOME.CALC <LINE MONTH>
BLOCK 1 (SIMPLE)
INCOME.CALC 5: gross.margin = revenue - cogs
BLOCK 2 (SIMULTANEOUS <MONTH>)
INCOME.CALC 3: opr.income = gross.margin - total(marketing + selling + r.d)
INCOME.CALC 4: marketing = lag(opr.income, 1, month)
END BLOCK 2
INCOME.CALC 2: net.income = opr.income - taxes
END BLOCK 1
You can see that the compiler leaves the simultaneous equations in the order in which you placed them.
The MODSIMULTYPE option specifies the method to use for solving simultaneous blocks in a model.
|
See: "Model Options" for a list of all of the options that control the solution of simultaneous blocks. |
Data Type
ID
Syntax
MODSIMULTYPE = {'AITKENS'|'GAUSS'}
Parameters
(Default) Oracle OLAP uses the Aitkens delta-squared solution method. In the first two of every three iterations over a block of simultaneous equations, the equations are solved using the values from the previous iteration, and the results are tested for convergence and divergence. In every third iteration, the results are obtained not by solving the equations, but by making a next-guess calculation. This calculation uses the results of the previous three iterations. The results of the guesses are not tested for convergence and divergence, and the solution always continues to the next iteration.
Oracle OLAP uses the Gauss-Seidel solution method. Equations in a simultaneous block are solved in each iteration over the block. The results are tested for convergence and divergence in each iteration.
Usage Notes
Solving Simultaneous Blocks
Oracle OLAP uses an iterative method to solve the equations in a simultaneous block. In each iteration, except the next-guess iterations in an Aitkens solution, a comparison value is calculated from the result of the current iteration and the result of the previous iteration. When the comparison value falls within a specified tolerance (see the MODTOLERANCE option), the equation is considered to have converged. When the comparison value is too great (see the MODOVERFLOW option), the equation is considered to have diverged and solution of the block ends.
When all equations in a block converge, the block is considered solved. When any equation diverges or when any equation fails to converge after a specified number of iterations (see the MODMAXITERS option), solution of the block (and of the model) fails and Oracle OLAP generates an error.
Next-Guess Calculation
The Aitkens method requires three values to perform a next-guess calculation. Therefore, in the first three iterations over a simultaneous block, Oracle OLAP solves the equations. The fourth iteration is a next-guess iteration that uses the results from the first three iterations in its calculation.
Thereafter, every third iteration is a next-guess iteration that calculates results by using the previous guess and the equation results from the intervening two iterations. For example, the seventh iteration makes a next-guess calculation that is based on the guess from the fourth iteration and the equation results from the fifth and sixth iterations.
Memory Required
The Aitkens method usually speeds convergence, and it generally produces more accurate results than the Gauss-Seidel method. However, the Aitkens method requires more memory because the results of three previous iterations are stored.
In general, use the Aitkens method. Use the Gauss-Seidel method only when limited memory is a problem on your system.
Handling NA Values When Solving Simultaneous Blocks in a Model
In calculating equation results and making next-guess calculations, Oracle OLAP observes the setting of the NASKIP2 option. NASKIP2 controls how NA values are handled when + (plus) and - (minus) operations are performed. The setting of NASKIP2 is important when you specify a solution variable that contains NA values. Since the values in the solution variable are used as the initial values in the first iteration over a simultaneous block, the results of the equations might be NA when there are NA values in the solution variable. An NA result in the first iteration might also produce NA results in later iterations. Therefore, to avoid obtaining NA for the results, you can ensure that the solution variable does not contain NA values or you can set NASKIP2 to YES before running the model.
Data Type Problems
A simultaneous equation might fail to converge when it assigns data to a variable with an INTEGER data type or when you specify a solution variable with an INTEGER data type for a dimension-based model. Oracle OLAP converts the data to decimal values when it calculates the equation in each iteration, but the results are stored in the INTEGER variable between iterations which has the effect of rounding the values and thereby interfering with a progression toward convergence.
Function Problems
A simultaneous equation might fail to converge when it contains a function that produces rounded values (such as INSTRB or ROUND) or when it contains a function that introduces discontinuities in the data (such as MAX or MIN).
Starting-Value Problems
The solution of a simultaneous block is sensitive to starting values. For example, when a model has a proportional relationship between two model values, then starting values close to zero inhibits convergence. Consequently, attempt to use starting values that are reasonable for the equations being solved.
Order of Equations
The solution of a simultaneous block is also sensitive to the order of the equations. When you compile a model, the model compiler determines an optimal equation order that is based on the dependencies among the equations.
To force the equations in a simultaneous block to be solved in a particular order, you can write the equations in the desired order and set the MODINPUTORDER option to YES before compiling the model. When MODINPUTORDER is YES, the model compiler leaves the equations in a simultaneous block in the order in which they appear in the model.
By placing simultaneous equations in a particular order and setting MODINPUTORDER to YES before compiling the model, you might be able to encourage convergence in some models. In general, however, it is preferable to rely on the model compiler to order the equations.
Producing an Execution Report
After running a model, you can use the MODEL.XEQRPT program to produce a report about the execution of the model.
Examples
Example 5-60 Economizing on Memory Requirements
When a model named budget98 is a complex model that iterates over a large number of dimension values in a simultaneous block, you can economize on the memory requirements of the model solution by using the Gauss-Seidel method.
The following statements specify the Gauss-Seidel method and run the model.
MODSIMULTYPE = 'GAUSS' budget98 budget
The $AGGREGATE_FROM property specifies the same behavior as that specified by a FROM clause in an AGGREGATE command or an AGGREGATE function. By adding an $AGGREGATE_FROM property to a variable you can ensure this behavior when the variable is aggregated — even when it is aggregated by an AGGREGATE statement does not include the FROM clause.
Both the $AGGREGATE_FROM property and the FROM clause specify an object from which Oracle OLAP obtains the detail data for the aggregation.
Syntax
You add or delete an $AGGREGATE_FROM property to the most recently defined or considered object (see DEFINE and CONSIDER commands) by issuing a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$AGGREGATE_FROM' fromspec
To delete the property, issue the following statement.
PROPERTY DELETE '$AGGREGATE_FROM'
Parameters
An arbitrarily dimensioned variable, formula, or relation from which the detail data for the aggregation is obtained.
Examples
Example 4-3 Using the $AGGREGATE_FROM Property
Example 9-15, "Aggregating into a Different Variable" uses the following AGGREGATE command to populate the total_sales_exclud_north variable with aggregate values computed from the sales variable.
AGGREGATE total_sales_exclud_north USING agg_sales_exclud_north FROM sales
You can place a $AGGREGATE_FROM property on the total_sales_exclud_north variable by issuing the following statements.
CONSIDER total_sales_exclud_north PROPERTY '$AGGREGATE_FROM' 'sales'
Now you can aggregate the data by issuing the following AGGREGATE command that does not include a FROM clause.
AGGREGATE total_sales_exclud_north USING agg_sales_exclud_north
The NEXT_DAY function returns the date of the first instance of a particular day of the week that follows the specified date.
Return Value
DATETIME
Syntax
NEXT_DAY(datetime-expression, weekday)
Parameters
An expression that has the DATETIME data type.
A text expression that identifies a day of the week (for example, Monday). Valid names are controlled by the NLS_DATE_LANGUAGE option.
Examples
The CONTEXT function lets you obtain information about object values that are saved in a context. You must first create the context with the CONTEXT command.
Return Value
The data type of the return value of the CONTEXT function depends on the arguments you provide. When you use the CONTEXT function without supplying any arguments, it returns a multiline text value that contains the names of all the contexts in the current session.
Syntax
CONTEXT ([context-name [UPDATE|name]])
Parameters
A text expression that contains the name of the context. Using the CONTEXT function with only the context-name returns a multiline text value that contains the names of all the objects saved in that context.
When you specify UPDATE with the CONTEXT function, the return value is the number of times values have been saved or dropped from the context.
The name of an object whose value is saved in the context. When you specify name with the CONTEXT function, the return value is the saved status or value of that object.
Examples
Example 7-47 Listing Context Names
In the following statement, the CONTEXT function returns the name of the only context in the current session which is the same context used in Example 9-72, "Saving Dimension Status".
SHOW CONTEXT
The statement produces the following output.
democontext1
Within an OLAP DML program, the TRAP command causes program execution to branch to a label when an error occurs in a program or when the user interrupts the program. When execution branches to the trap label, that label is deactivated.
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See also: For a discussion of how Oracle OLAP handles declarative errors in programs and models, see "Declarative Errors". |
Syntax
TRAP {OFF|ON errorlabel [NOPRINT|PRINT]}
Parameters
Deactivates the trap label. Since only one trap label can be active at a time, you do not supply errorlabel when setting TRAP OFF. When you try to include a label with OFF, an error occurs.
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Note: When an error occurs in a program that contains a trap label, execution branches to the label and the trap is deactivated. You do not have to execute an explicitTRAP OFF statement. Thus, an error occurring after execution has branched to the label does not cause execution to branch to the same label again. |
Activates the trap label (errorlabel). When TRAP is active, any error in the program causes execution to branch to errorlabel.
The name of a label elsewhere in the program constructed following the "Guidelines for Constructing a Label". Execution of the program branches to the line directly following the specified label.
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Note: Note that errorlabel, as specified in ON, must not be followed by a colon. However, the actual label elsewhere in the program must end with a colon.When an actual trap label that corresponds to errorlabel does not exist elsewhere in the same program, execution stops with an error |
Indicates whether to suppress output of the error message. NOPRINT suppresses the message. PRINT (default) means that the error message is sent to the current outfile before execution branches to the trap label. With the OFF keyword, NOPRINT and PRINT are meaningless and produce an error.
Examples
Example 10-156 Trapping a Program Error
The following program fragment uses a TRAP statement to direct control to a label where options and dimension status are set back to the values they had before the program was executed and an error is signaled.
PUSH month DECIMALS LSIZE PAGESIZE TRAP ON haderror NOPRINT LIMIT month TO LAST 1 ... POP month DECIMALS LSIZE PAGESIZE RETURN haderror: POP month DECIMALS LSIZE PAGESIZE SIGNAL ERRORNAME ERRORTEXT
Example 10-157 Producing a Program Error Message Immediately
To produce the error message immediately, use a TRAP statement in each nested program, but do not use the NOPRINT keyword. When an error occurs, an error message is produced immediately, and execution branches to the trap label.
At the trap label, perform whatever error-handling commands you want and restore the environment. Then execute a SIGNAL statement that includes the PRGERR keyword.
SIGNAL PRGERR
When you use the PRGERR keyword in the SIGNAL statement, no error message is produced, and the name PRGERR is not stored in ERRORNAME. The SIGNAL statement signals an error condition that is passed up to the program from which the current program was run. When the calling program contains a trap label, then execution branches to that label.
When each program in a chain of nested programs uses the TRAP and SIGNAL commands in this way, you can pass the error condition up through the entire chain. Each program has commands like these.
TRAP ON error ... "Body of program and normal exit commands RETURN error: ... "Error-handling and exit commands SIGNAL PRGERR
Example 10-158 Producing a Program Error Message at the End of the Chain
To produce the error message at the end of a chain of nested programs, use a TRAP statement that includes the NOPRINT keyword. When an error occurs in a nested program, execution branches to the trap label, but the error message is suppressed.
At the trap label, perform whatever error-handling commands you want and restore the environment. Then execute the following SIGNAL statement.
SIGNAL ERRORNAME ERRORTEXT
The preceding SIGNAL statement contains includes ERRORNAME and ERRORTEXT within it. The ERRORNAME option contains the name of the original error, and the ERRORTEXT option contains the error message for the original error. When the calling program contains a trap label, then execution branches to that label.Consequently, the SIGNAL statement passes the original error name and error text to the calling program.
When each program in a chain of nested programs uses the TRAP and SIGNAL commands in this way, the original error message is produced at the end of the chain. Each program has commands like the following.
TRAP ON error NOPRINT ... "Body of program and normal exit commands RETURN error: ... "Error-handling and exit commands SIGNAL ERRORNAME ERRORTEXT
The VALUES function returns the default status list or the current status list of a dimension or dimension surrogate, or it returns the values in a valueset. VALUES returns a multiline text value that contains one dimension value on a line.
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Note: Because composites do not have status, you cannot use the VALUES function with a composite. When you attempt to do so, Oracle OLAP displays an error message. |
Return Value
TEXT
Syntax
VALUES(dimension [keyword] [INTEGER])
Parameters
A text expression whose value is the name of a dimension, dimension surrogate, or valueset.
One of the following keywords that specify whether you want the current status list or the default status list for a dimension or a surrogate:
NOSTATUS which indicates that VALUES should return the default status list of a dimension or dimension surrogate rather than its current status list.
STATUS which indicates that VALUES should return the current status list of a dimension or dimension surrogate (Default).
These keywords do not affect valuesets. For a valueset, VALUES returns all the values in that valueset whether you specify NOSTATUS, STATUS, or nothing.
When you use the INTEGER keyword, the function returns the position numbers of the dimension or dimension surrogate values rather than the values. When you use INTEGER with a valueset, the function returns the position numbers of the values in the existing dimension, not in the valueset.
Usage Notes
Using a LIMIT Statement With a STATUS Keyword Rather than VALUES
When possible, when you want Oracle OLAP to use the dimension values that are presently in status, use a LIMIT (using values) command with the STATUS keyword (or a LIMIT function with a similar construction) rather than using a VALUES statement. A LIMIT with the STATUS keyword is more efficient than a VALUES (dimname) statement.
Comparing VALUES to CHARLIST
The VALUES function is very similar to the CHARLIST function. VALUES(MONTH) returns the same list as CHARLIST(MONTH).
The main differences are:
For dimensions, the NOSTATUS keyword of VALUES lets you use the default status without first limiting the dimension values to ALL.
The VALUES function lets you use a text expression to specify the dimension or valueset name. See Example 8-162, "VALUES with Text Variables".
Special Considerations for an Ampersand (&)
Under certain circumstances, an ampersand (&) that is intended to be a character in a dimension value name is interpreted as ampersand substitution. When this happens, Oracle OLAP generates an error message.
This happens because Oracle OLAP recognizes special characters in dimension value names with when they are used in tuples in text expressions. For example, you can include spaces, such as naming a dimension value New York instead of NewYork. When you have dimension values that include ampersands in their names, refer to Example 8-163, "Workaround for Dimension Value Names Including an Ampersand".
Examples
Example 8-160 Listing the Values of a Valueset
The easiest way to display the values of a valueset is simply by using the name of the valueset in a SHOW or a REPORT statement. You can also use VALUES to list the values in that valueset.
For example, suppose an analytic workspace contains a valueset called monthset that has the values Jan95, May95, and Dec95. The following statement displays the values.
SHOW VALUES(monthset) Jan95 May95 Dec95
Example 8-161 Listing Position Numbers of a Dimension
You can use VALUES to list the position numbers instead of the actual values in a dimension or valueset. In this example, because you are using the INTEGER keyword with a valueset instead of a dimension, the function returns the position numbers of the values in the month dimension as shown by the output returned by the following statement.
SHOW VALUES(monthset INTEGER) 61 65 72
Therefore, the value Jan95 is shown as the 61st value in the month dimension, May95 as the 65th value, and Dec95 as the 72nd value, although they are the first, second, and third values in monthset.
Example 8-162 VALUES with Text Variables
This example shows how to assign a dimension name to a text variable and use the text variable in the VALUES function instead of the variable name itself. As the following statements illustrate, when the variable textvar has the value district, VALUES(textvar) returns a list of district values.
textvar = 'district' SHOW VALUES(textvar) Boston Atlanta Chicago Dallas Denver Seattle
To list the values of district using the CHARLIST function rather than VALUES, you must use an ampersand.
SHOW CHARLIST(&textvar)
Because ampersands in a program can degrade performance, use VALUES rather than CHARLIST in such cases.
Example 8-163 Workaround for Dimension Value Names Including an Ampersand
When a dimension value name contains an ampersand (&) as one of its characters, and when that dimension is a base dimension of a conjoint dimension, then a text expression that contains the names of dimension values in a tuple can generate an error in certain circumstances. This example shows how to avoid this error.
Suppose you use the following statements to define two dimensions.
DEFINE prod DIMENSION TEXT DEFINE geog DIMENSION TEXT
Next, you use the following statements to define two conjoint dimensions.
DEFINE conj1 DIMENSION <prod geog> DEFINE conj2 DIMENSION <prod geog>
The following statements add dimension values to the prod and geog dimensions.
MAINTAIN prod ADD 'prod1' 'prod&val2' MAINTAIN geog ADD 'geog1' 'geog&val2'
The following statements add tuples (combinations of dimension values) to the CONJ1 conjoint dimension.
MAINTAIN conj1 ADD <'prod1' 'geog1'> MAINTAIN conj1 ADD <'prod&val2' 'geog1'>
Now, suppose you want to use the VALUE function with a MAINTAIN statement to add those same tuples to the conj2 conjoint dimension. When you attempt to use the following statement, it generates an error message.
MAINTAIN conj2 ADD VALUES(conj1) ERROR: (MXMSERR) val2 does not exist in any attached workspace.
This error occurs because the ampersand in the dimension value name prod&val2 is interpreted as an attempt at ampersand substitution.
Instead of using the preceding MAINTAIN statement, you can use the following statement to add the tuples to the CONJ2 conjoint dimension.
MAINTAIN conj2 MERGE < KEY(conj1 prod) KEY(conj1 geog) >
The LIKEESCAPE option lets you specify an escape character for the LIKE operator.
Data Type
ID
Syntax
LIKEESCAPE = char
Parameters
A text expression that specifies the character to use as an escape character in a LIKE text comparison. The default is no escape character.
The LIKE escape character affects the LISTNAMES program, which accepts a LIKE argument that it uses in a LIKE text comparison.
Usage Notes
Using the Escape Character
The LIKE escape character lets you find text expressions that contain the LIKE operator wildcard characters, which are an underscore (_), which matches any single character, and a percent character (%), which matches any string of zero or more characters.
To include an underscore or percent character in a text comparison, first specify an escape character with the LIKEESCAPE option. Then, in your LIKE expression, precede the underscore or percent character with the LIKEESCAPE character you specified.
You might want to avoid using a backslash (\) as the LIKE escape character, because the backslash is the standard OLAP DML escape character. You would therefore need two backslashes to indicate that LIKEESCAPE should treat the second backslash as a literal character.
Examples
Example 5-40 Using an Escape Character with the LIKE Operator
This example demonstrates how to specify an escape character and how to use it with the LIKE operator.
Suppose you have a variable named prodstat that contains the following text values.
DEFINE prodstat TEXT <product> prodstat(product 'Tents') = - 'What are the results of the fabric testing?' prodstat(product 'Canoes') = - 'How has the flooding affected distribution?' prodstat(product 'Racquets') = - 'The best-selling model is Whack_it!' prodstat(product 'Sportswear') = - '90% of the stock is ready to ship.' prodstat(product 'Footwear') = - 'When are the new styles going to be ready?'
Suppose you have the following program, named findeschar, to find certain characters in the text contained in the cells of the prodstat variable. The program uses the LIKE operator.
ARGUMENT findstring TEXT FOR product IF prodstat LIKE findstring THEN SHOW JOINCHARS(product ' - ' prodstat)
Before the program can find a text value that contains a percent character (%) or an underscore (_), you must specify an escape character by using the LIKEESCAPE option. Suppose you want to use a question mark (?) as the escape character. Before you set the escape character to a question mark, the following statement finds text that contains a question mark.
CALL findeschar('%?%') "Find any text that contains a question mark.
The preceding statement produces the following output.
Tents - What are the results of the fabric testing? Canoes - How has the flooding affected distribution? Footwear - When are the new styles going to be ready?
The following statements specify the question mark (?) as the escape character and then call the FINDESCHAR program.
LIKEESCAPE = '?'
CALL findeschar('%?%') "Find any text that ends with a percent character.
The preceding statement does not find any text because none of the text values in prodstat ends in a percent character. To find any text that contains a percent character, the following statement adds another wildcard character. LIKEESCAPE interprets the first percent character as the wildcard that matches zero or more characters, the second percent character as the literal percent character (%) because it is preceded by the question mark escape character, and the third percent character as another wildcard character. The result is that LIKEESCAPE looks for a percent character preceded by and followed by zero or more characters.
CALL findeschar('%?%%') "Find any text that contains a percent character.
The preceding statement produces the following output.
Sportswear - 90% of the stock is ready to ship.
The following statement finds text that contains an underscore.
CALL findeschar('%?%') "Find any text that contains an underscore.
The preceding statement produces the following output.
Racquets - The best-selling model is Whack_it!
The following statement doubles the escape character to find text that contains the escape character.
CALL findeschar('%??%') "Find any text that contains a question mark.
The preceding statement produces the following output.
Tents - What are the results of the fabric testing? Canoes - How has the flooding affected distribution? Footwear - When are the new styles going to be ready?
Example 5-41 Using an Escape Character with the LISTNAMES Program
This example demonstrates how to find the name of an object that contains a LIKE argument wildcard character. These following statements use the LIKEESCAPE option to specify an escape character, define a couple of object names that contain an underscore, and then list the dimensions whose names include an underscore.
LIKEESCAPE = '?' DEFINE my_textdim DIMENSION TEXT DEFINE my_intdim DIMENSION INTEGER LISTNAMES DIMENSION LIKE '%?%'
The preceding statement produces the following output.
3 DIMENSIONs ---------------- MY_INTDIM MY_TEXTDIM _DE_LANGDIM
The DEPRDECLSW function calculates the depreciation expenses for a series of assets. DEPRDECLSW uses a variation on the declining balance method, as described in "Calculation Method Used by DEPRDECLSW", to depreciate assets over the specified lifetime of the assets. DEPRDECLSW begins by using the declining balance method, then switches over to the straight-line method at one of the following points in the time series:
The first period for which straight-line depreciation over the remaining periods exceeds the declining balance depreciation for those periods (the default)
The period specified by the switch-period argument
This variation on the declining-balance method is the most commonly used form of declining-balance depreciation methods.
Return Value
DECIMAL, dimensioned by all the dimensions of start-exp.
Syntax
DEPRDECLSW(start-exp end-exp n [STATUS]
[decline-factor [{FULL|HALF| portion-exp} [switch-period [time-dimension]]]])
Parameters
A numeric expression that contains the starting values of the assets. The start-exp expression must be dimensioned by a time dimension. For each value of the time dimension, start-exp contains the initial value of the assets acquired during that time period. In addition to a time dimension, start-exp can also have non-time dimensions.
A numeric expression that contains the ending value of the assets. The end-exp expression must be dimensioned by the same dimensions as start-exp. For each value of the time dimension, end-exp contains the final (or salvage) value for the assets acquired during that time period. Each value of start-exp must have a corresponding end-exp value. For example, when the assets acquired in 1990 have a salvage value of $200, then the value of end-exp for 1990 is $200.
An INTEGER expression that contains the number of periods for the depreciation life of the assets. The n expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
Specifies that DEPRDECLSW should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the depreciation expenses. By default DEPRDECLSW uses the default status list.
A numeric expression that gives the declining balance rate to use for calculating the depreciation expenses. The decline-factor expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
A factor of 2 indicates a double declining balance. The default is 2.
(Default) Specifies that the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges the full amount to all of the assets in the series. This argument is optional; however, when you include it, you must also include the preceding optional arguments.
Specifies that half of the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges half the full amount to all of the assets in the series. You might want to use HALF when assets are acquired during the second half of the time period. When you specify HALF as the portion of depreciation expenses to charge to the period of acquisition, the HALF factor is applied to each period. Half of each period's full depreciation is rolled to the next period, and the final half period of depreciation takes place in the time period n + 1. This argument is optional; however, when you include it, you must also include the preceding optional arguments.
When you want to charge the full amount for some assets and half the amount for other assets, you can supply a portion-exp expression that is dimensioned by any of the non-time dimensions of start-exp. The portion-exp expression must be a text expression with values of FULL or HALF. This argument is optional; however, when you include it, you must also include the preceding optional arguments.
An INTEGER expression that indicates the time period in which the calculation should switch to the straight-line method. This argument is optional; however, when you include it, you must also include the preceding optional arguments.
A common accounting practice is to switch to a straight-line method in the first period for which straight-line depreciation over the remaining periods exceeds the declining-balance depreciation. You can specify this behavior by not specifying the switch-period argument.
When the switch-period argument is not specified or has a value of NA or 0, the calculation switches from the declining method to the straight-line method in the first period for which straight-line depreciation over the remaining periods exceeds the declining-balance depreciation. In this case, the DEPRDECLSW function behaves just like the DEPRDECL function.
When you want to specify different switch periods for different assets, you can supply an expression that is dimensioned by any of the non-time dimensions of start-exp.
The name of the time dimension by which start-exp and end-exp are dimensioned. When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional. When you include this argument, you must also include the preceding optional arguments
Usage Notes
Calculation Method Used by DEPRDECLSW
DEPRDECLSW calculates the depreciation expense for a given time period as the sum of that period's depreciation expenses for all assets in the series that are not yet fully depreciated. The first period of depreciation for an asset is the period in which it was acquired.
For each time period in which DEPRDECLSW is calculating depreciation according to the declining balance method, it calculates the depreciation expense by multiplying the current value of an asset by the decline-factor and dividing the result by the number of periods in the lifetime of the asset. When DEPRDECLSW switches to the straight-line method, it subtracts the depreciation expense (from previous periods) from the value of an asset and divides the resulting amount by the number of periods left in the lifetime of the asset. However, when the depreciation expense calculated for a specific time period would result in an asset's current value going below its ending value, then the depreciation expense is adjusted. In this instance, the depreciation expense is calculated as the current value minus the ending value.
The straight-line method as used by DEPRDECLSW differs from the traditional straight-line method as used by DEPRSL. Unlike other methods of depreciation, the declining-balance methods of depreciation ignore the salvage value for an asset until the period in which the calculated depreciation would exceed the remaining depreciable value. Even DEPRDECLSW ignores the salvage value in this manner after it switches from the declining-balance method to the straight-line method. For example, suppose the beginning value for an asset is 16,000 and the salvage value is 1,000 over 5 periods. The total depreciation through the periods using declining balance method (here the first three) is 11,544. The straight-line calculations for the remaining periods would be based on the overall remaining value of 16,000 minus 11,544 (3,456), rather than the overall value minus the salvage value (2,456). Thus the depreciation for the last two periods would be 1,728; but for the very last period the salvage value is subtracted out and thus is 728.
Unexpected-Balance Method
When the ending value specified for an asset is relatively high, then an asset might be totally depreciated in fewer periods than were specified for the lifetime of the depreciation. In this instance, when you want the depreciation expense applied across the specified lifetime of the depreciation, you can lower the decline-factor.
DEPRDECLSW and NA Values
When a value of start-exp is NA and the corresponding value of end-exp is not NA, an error occurs. Similarly, when a value of end-exp is NA and the corresponding value of start-exp is not NA, an error occurs.
DEPRDECLSW is affected by the NASKIP option when a value of start-exp and the corresponding value of end-exp are both NA. When NASKIP is YES (the default), DEPRDECLSW treats the values as zeros when calculating the depreciation expenses. When NASKIP is NO, DEPRDECLSW returns NA for all affected time periods.
Examples
Example 7-68 Calculating Depreciation Expenses for Assets Acquired in a Single Period
This example shows how to use DEPRDECLSW to calculate depreciation expenses for assets acquired in a single time period. It also shows the behavior of DEPRDECLSW when you do not specify a switch period.
The following statements create two variables called assets and salvage.
DEFINE assets DECIMAL <year> DEFINE salvage DECIMAL <year>
Suppose you assign the following values to the variables assets and salvage.
YEAR ASSETS SALVAGE ------- ---------- ----------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 0.00 0.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00
The variable assets contains the starting value of the assets acquired in 1995. salvage contains the ending value of the assets acquired in 1995.
The following statement reports the values of assets and salvage, and uses DEPRDECLSW to calculate depreciation expenses for each year, specifying an asset lifetime of 5 years, and a decline factor of 2 (double declining balance). The statement does not specify a switch-period argument. Because of this, DEPRDECLSW uses the default for switch-period, which is to switch from the declining balance method of depreciation in the first period for which straight-line depreciation over the remaining periods exceeds the declining-balance depreciation.
REPORT assets salvage W 12 HEADING 'Depreciation' -
DEPRDECLSW (assets salvage 5 2 FULL)
This statement produces the following report.
YEAR ASSETS SALVAGE Depreciation ------- ---------- ----------- -------------- Yr95 1,000.00 100.00 400.00 Yr96 0.00 0.00 240.00 Yr97 0.00 0.00 144.00 Yr98 0.00 0.00 108.00 Yr99 0.00 0.00 8.00 Yr00 0.00 0.00 0.00
Example 7-69 Specifying the Switch Period
Alternatively, you can specify the period in which the switch occurs.
To switch from the declining balance method to the straight-line method of depreciation in the third year (Yr97), specify 3 as the switch period, as shown in the following statement.
REPORT assets salvage W 12 HEADING 'DEPRECIATION' -
DEPRDECLSW (assets salvage 5 2 FULL 3 year)
This statement produces the following report.
YEAR ASSETS SALVAGE Depreciation -------- ---------- ----------- -------------- Yr95 1,000.00 100.00 400.00 Yr96 0.00 0.00 240.00 Yr97 0.00 0.00 120.00 Yr98 0.00 0.00 120.00 Yr99 0.00 0.00 20.00 Yr00 0.00 0.00 0.00
Example 7-70 Calculating the Depreciation Expenses for Assets Acquired in Multiple Periods
You can use DEPRDECLSW to calculate the depreciation expenses for a series of assets. Suppose you change the values for the year 1997 in the variables assets and salvage to the values shown in the following report.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 500.00 50.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00 Yr01 0.00 0.00 Yr02 0.00 0.00
Now assets and salvage contain nonzero values for 1995 and for 1997.
The following statement reports asset and salvage values along with depreciation expenses for the assets. Note that the call to DEPRDECLSW to calculate the depreciation expenses specifies an asset lifetime of 5 periods (in this case, years) and a decline factor of 2 (double-declining balance). The statement does not specify a switch-period argument. Because of this, DEPRDECLSW uses the default for switch-period, which is to switch from the declining balance method of depreciation in the first period for which straight-line depreciation over the remaining periods exceeds the declining-balance depreciation.
REPORT assets salvage W 12 HEADING 'Depreciation' -
DEPRDECLSW(assets salvage 5 2 FULL)
This statement produces the following output.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100. 00 400.00 Yr96 0.00 0.00 240.00 Yr97 500.00 50.00 344.00 Yr98 0.00 0.00 228.00 Yr99 0.00 0.00 80.00 Yr00 0.00 0.00 54.00 Yr01 0.00 0.00 4.00 Yr02 0.00 0.00 0.00
Notice that the depreciation expense increases in 1997 due to the assets acquired in that year.
The RANK function computes the rank of values in a numeric expression.
Return Value
DECIMAL
Syntax
RANK(expression method [attributes] [BASEDON dimension-list])
where attributes is one or more of the following:
Parameters
The numeric expression for which rankings are to be computed.
The method to use in computing the rank of the values in expression. The method argument can be one of the following keywords. See also "Results of Method Values".
Table 8-11 Methods for Computing RANK
| Method | Description |
|---|---|
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MIN |
Identical values get the same minimum rank. |
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MAX |
Identical values get the same maximum rank. |
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AVERAGE |
Identical values get the same average rank. |
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PACKED |
Identical values get the same rank but the results are packed into consecutive |
|
UNIQUE |
All values get a unique rank; for identical values the rank is arbitrary. |
|
PERCENTILE |
Values are ranked from 1 to 100, based on the relative frequency of their occurrence in the expression. |
|
DECILE |
Values are ranked from 1 to 10, based on the relative frequency of their occurrence in the expression. |
|
QUARTILE |
Values are ranked from 1 to 4, based on the relative frequency of their occurrence in the expression. |
Changes how Oracle OLAP computes RANK within a looping statement (for example, an assignment statement):
When you do not specify RESET, Oracle OLAP ranks the members of each group only once and, then caches those ranked values. As the looping statement continues to execute and RANK executes against same set of values, Oracle OLAP uses those cached values to return values for RANK.
When you include RESET, Oracle OLAP recomputes RANK each and every time it executes within the looping statement. This behavior significantly increases the time it takes for Oracle OLAP to execute the looping statement that contains RANK.
Within a looping statement, the only time you use RANK with RESET is when you know that within any group the rankings of members within that group will change during the execution of the looping statement.
Specifies that Oracle OLAP converts all NA values to the largest positive decimal number or (10**308) before ranking the values.
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Note: An NA expression value produces an NA rank unless you specify either NAFIRST or NALIST. |
Specifies that Oracle OLAP converts all NA values to the largest negative decimal number or -(10**308) before ranking the values.
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Note: An NA expression value produces an NA rank unless you specify either NAFIRST or NALIST. |
Specifies the status of the dimensions that Oracle OLAP uses when calculating RANK. By specifying LIMITSAVE within the RANK function, rather than specify CHGDIMS with LIMITSAVE, you insure that Oracle OLAP evaluates the status only once when RANK needs to calculate a new result.
The dimension values that Oracle OLAP uses to determine dimension status while executing RANK. For the limit-expression argument, you can specify any expression including a valueset, a LIMIT function, or a SORT function.
Specifies how Oracle OLAP sequences values of equal rank.
Any expression including a valueset, a LIMIT function, or a SORT function. Oracle OLAP executes the tiebreaker-expressions in the order in which they are specified. The status of the dimensions of each tiebreaker-expression is the current status of the dimensions or the status specified in the LIMITSAVE clause, if any.
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Note: When you specify a valueset for tiebreaker-expression, Oracle OLAP returns the ranked items in -(STATRANK) order. |
An optional list of one or more of the dimensions of expression to include in the ranking. When you do not specify the dimensions, then RANK bases the ranking on all of the dimensions of expression.
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Note: When the current value of a BASEDON dimension is not in ranking status, Oracle OLAP returns a rank ofNA. |
Usage Notes
Monitoring the Behavior of RANK
The OLAP DML provides the RANK_CALLS, RANK_CELLS, and RANK_SORTS options that you can use to monitor the behavior of the RANK function.
RANK_CALLS The RANK_CALLS option is an INTEGER, read-only option that holds the number of calls that Oracle OLAP has made to the RANK function.
RANK_CELLS The RANK_CELLS option is an INTEGER, read-only option that holds the number of values that Oracle OLAP has computed when executing the RANK function.
RANK_SORTS The RANK_SORTS option is a read-only option that holds the number of sorts that have been triggered by the execution of the RANK function
Results of Method Values
This note describes the results of the different methods of ranking values. The results are based on the sales2 variable, which is described in "Ranking Values", with the geography dimension limited to G2 as the following statements demonstrate.
LIMIT geography TO 'G2' SORT items D sales2 REPORT DOWN geography sales2
The preceding statements produce the following output.
------------------------SALES2------------------------
------------------------ITEMS-------------------------
GEOGRAPHY ITEM4 ITEM2 ITEM3 ITEM1 ITEM5
-------------- ---------- ---------- ---------- ---------- ----------
G2 25.00 20.00 20.00 15.00 7.00
Table 8-12, "Results of Different Methods of Ranking" shows the results of the different methods of ranking that are produced by a statement of the form
REPORT DOWN geography RANK(sales2 MIN BASEDON items)
with the different method keywords substituted for MIN.
Table 8-12 Results of Different Methods of Ranking
| Methods | (ITEM4, G2) = 25 | (ITEM2, G2) = 20 | (ITEM3, G2) = 20 | (ITEM1,G2) = 15 | (ITEM5,G2) = 7 |
|---|---|---|---|---|---|
|
MIN |
1 |
2 |
2 |
4 |
5 |
|
MAX |
1 |
3 |
3 |
4 |
5 |
|
AVERAGE |
1 |
2.5 |
2.5 |
4 |
5 |
|
PACKED |
1 |
2 |
2 |
3 |
4 |
|
UNIQUE |
1 |
2 |
3 |
4 |
5 |
|
PERCENTILE |
100 |
62 |
62 |
25 |
1 |
|
DECILE |
10 |
7 |
7 |
3 |
1 |
|
QUARTILE |
4 |
3 |
3 |
1 |
1 |
Note that the value that is returned by the UNIQUE method for Item2 and Item3 can be either 2 or 3, since the RANK function randomly assigns a unique rank for identical values in the expression.
Examples
Example 8-65 Ranking Values
Assume that your analytic workspace contains geography and items dimensions and sales2 variable.
DEFINE geography DIMENSION TEXT MAINTAIN geography ADD 'g1' 'g2' 'g3' DEFINE items DIMENSION TEXT MAINTAIN items ADD 'Item1' 'Item2' 'Item3' 'Item4' 'Item5' DEFINE sales2 DECIMAL <geography items>
Assume the sales2 variable has the following data values.
-------------SALES2-------------
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 30.00 15.00 12.00
Item2 10.00 20.00 18.00
Item3 15.00 20.00 24.00
Item4 30.00 25.00 25.00
Item5 NA 7.00 21.00
This statement reports the results of using the MIN method to rank the sales2 values based on the items dimension.
report rank(sales2 min basedon items)
The preceding statement produces the following output.
-RANK(SALES2 MIN BASEDON ITEMS)-
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 1.00 4.00 5.00
Item2 4.00 2.00 4.00
Item3 3.00 2.00 2.00
Item4 1.00 1.00 1.00
Item5 NA 5.00 3.00
This statement reports the results of using the MIN method to rank the sales2 values based on the geography dimension.
REPORT RANK(sales2 MIN BASEDON geography)
The preceding statement produces the following output.
----RANK(SALES2 MIN BASEDON-----
-----------GEOGRAPHY)-----------
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 1.00 2.00 3.00
Item2 3.00 1.00 2.00
Item3 3.00 2.00 1.00
Item4 1.00 2.00 2.00
Item5 NA 2.00 1.00
This statement reports the results of using the MIN method to rank the sales2 values based on all of its dimensions.
REPORT RANK(sales2, MIN)
The preceding statement produces the following output.
-------RANK(SALES2, MIN)--------
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 1.00 10.00 12.00
Item2 13.00 7.00 9.00
Item3 10.00 7.00 5.00
Item4 1.00 3.00 3.00
Item5 NA 14.00 6.00
Calculation objects are OLAP DML objects that contain OLAP DML statements that specify analysis to be performed. Calculation objects include: formulas, models, aggregation specifications, allocation specifications, and programs.
This chapter contains information on the following
For information on creating OLAP DML programs, see Chapter 6, "OLAP DML Programs".
The general process of creating a calculation specification object is the following two step process:
Define the calculation object using the appropriate DEFINE statement.
Add the calculation specification to the object definition. You can add the calculation specification to the definition of a calculation object in the following ways:
At the command line level of the OLAP Worksheet, in an input file, or as an argument to a PL/SQL function. In this case, ensure that the object is the current object (issue a CONSIDER statement, if necessary), and, then, issue the appropriate statement that includes the specification as a multiline text argument. To code the specification as a multiline text, you can use a JOINLINES function where each of the text arguments of JOINLINES is a statement that specifies the desired processing, and where the final statement is END.
In an Edit Window of the OLAP Worksheet. In this case, at the command line level of the OLAP Worksheet, issue an EDIT statement with the appropriate keyword. An EDIT statement opens an Edit Window for the specified object. You can then type each statement as an individual line in the Edit Window. Saving the specification and closing the Edit Window when you are finished.
Table 3-1 outlines the OLAP DML statements that you use to create each type of calculation specification.
Table 3-1 Commands for Defining calculation objects
| Calculations | Definition Statement | Specification Statement | For More Information |
|---|---|---|---|
|
Formula |
DEFINE FORMULA |
EQ |
|
|
Model |
DEFINE MODEL |
MODEL |
|
|
Aggregation |
DEFINE AGGMAP |
AGGMAP |
"OLAP DML Aggregation Objects" |
|
Allocation |
DEFINE AGGMAP |
ALLOCMAP |
|
|
Program |
DEFINE PROGRAM |
PROGRAM |
Chapter 6, "OLAP DML Programs" |
You can save an expression in a formula. Frequently, you define a formula for ease of use and to save storage space. Once you have defined a formula for an expression, you can use the name of the formula takes the place of the text of the expression. Oracle OLAP does not store the data for a formula in a variable; instead it is calculated at run time each time it is requested.
Before you create a formula, decide whether you want to specify the expression when you first define the formula object or whether you want to specify the expression for the formula after you define the formula object:
When you decide to specify the expression when you first define the formula object, then:
Issue a DEFINE FORMULA statement to define the formula object. Include the expression in the definition. Do not specify values for the datatype or dimensions arguments.
(Optional) Issue a COMPILE statement to compile the formula.
When you want the formula to be a permanent part of the analytic workspace, save the formula using an UPDATE statement followed by COMMIT.
When you decide to specify the expression for the formula after you define the formula object, then:
Issue a DEFINE FORMULA statement to define the formula object. Specify values for the datatype or dimensions arguments, but do not specify a value for the expression, itself.
Issue a CONSIDER statement to make the formula the current definition and, then, issue an EQ statement to specify the expression for the formula.
(Optional) Issue a COMPILE statement to compile the formula.
When you want the formula to be a permanent part of the analytic workspace, save the formula using an UPDATE statement followed by COMMIT.
For example, you can define a formula to calculate dollar sales, as follows.
DEFINE dollar.sales FORMULA units * price
You can use TRACE to help you debug a forumula.
This topic provides information about creating and executing OLAP DML models. It includes the following subtopics:
An OLAP DML model is a set of interrelated equations that can assign results either to a variable or to a dimension value. For example, in a financial model, you can assign values to specific line items, such as gross.margin or net.income.
gross.margin = revenue - cogs
When an assignment statement assigns data to a dimension value or refers to a dimension value in its calculations, then it is called a dimension-based equation. A dimension-based equation does not refer to the dimension itself, but only to the values of the dimension. Therefore, when the model contains any dimension-based equations, then you must specify the name of each of these dimensions in a DIMENSION statement at the beginning of the model.
When a model contains any dimension-based equations, then you must supply the name of a solution variable when you run the model. The solution variable is both a source of data and the assignment target of model equations. It holds the input data used in dimension-based equations, and the calculated results are stored in designated values of the solution variable. For example, when you run a financial model based on the line dimension, you might specify actual as the solution variable.
Dimension-based equations provide flexibility in financial modeling. Since you do not need to specify the modeling variable until you solve a model, you can run the same model with the actual variable, the budget variable, or any other variable that is dimensioned by line.
Models can be quite complex. You can:
Include one model within another model as discussed in "Nesting Models"
Use data from different time periods as discussed in "Using Data from Past and Future Time Periods"
Solve simultaneous equations as discussed in "Solving Simultaneous Equations"
Create models for different scenarios as described in "Modeling for Multiple Scenarios"
To create an OLAP DML model, take the following steps:
Issue a DEFINE MODEL command to define the program object.
Issue a MODEL command which adds a specification to the model to specify the processing that you want performed.
Compile the model as described in "Compiling Models".
(Optional) If necessary, change the settings of model options listed in "Model Options".
Execute the model as described in "Running a Model".
Debug the model as described in "Debugging a Model".
When you want the model to be a permanent part of the analytic workspace, save the model using an UPDATE command followed by COMMIT.
For an example of creating a model, see Example 10-57, "Creating a Model".
You can include one model within another model by using an INCLUDE statement within a MODEL command. The MODEL command that contains the INCLUDE statement is referred to as the parent model. The included model is referred to as the base model. You can nest models by placing an INCLUDE statement in a base model. For example, model myModel1 can include model myModel2, and model myModel2 can include model myModel3. The nested models form a hierarchy. In this example, myModel1 is at the top of the hierarchy, and myModel3 is at the root.
When a model contains an INCLUDE statement, then it cannot contain any DIMENSION statements. A parent model inherits its dimensions, if any, from the DIMENSION statements in the root model of the included hierarchy. In the example just given, models myModel1 and myModel2 both inherit their dimensions from the DIMENSION statements in model myModel3.
The INCLUDE statement enables you to create modular models. When certain equations are common to several models, then you can place these equations in a separate model and include that model in other models as needed.
The INCLUDE statement also facilitates what-if analyses. An experimental model can draw equations from a base model and selectively replace them with new equations. To support what-if analysis, you can use equations in a model to mask previous equations. The previous equations can come from the same model or from included models. A masked equation is not executed or shown in the MODEL.COMPRPT report for a model
When a model contains an assignment statement to assign data to a dimension value, then the dimension is limited temporarily to that value, performs the calculation, and restores the initial status of the dimension.
For example, a model might have the following statements.
DIMENSION line gross.margin = revenue - cogs
If you specify actual as the solution variable when you run the model, then the following code is constructed and executed.
PUSH line LIMIT line TO gross.margin actual = actual(line revenue) - actual(line cogs) POP line
The fact that using a solution variable in a model causes this behind-the-scenes code construction allows you perform complex calculations with simple model equations. For example, line item data might be stored in the actual variable, which is dimensioned by line. However, detail line item data might be stored in a variable named detail.data, with a dimension named detail.line.
When your analytic workspace contains a relation between line and detail.line, which specifies the line item to which each detail item pertains, then you might write model equations such as the following ones.
revenue = total(detail.data line) expenses = total(detail.data line)
The relation between detail.line and line is used automatically to aggregate the detail data into the appropriate line items. The code that is constructed when the model is run ensures that the appropriate total is assigned to each value of the line dimension. For example, while the equation for the revenue item is calculated, line is temporarily limited to revenue, and the TOTAL function returns the total of detail items for the revenue value of line.
Several OLAP DML functions make it easy for you to use data from past or future time periods. For example, the LAG function returns data from a specified previous time period, and the LEAD function returns data from a specified future period.
When you run a model that uses past or future data in its calculations, you must ensure that your solution variable contains the necessary past or future data. For example, a model might contain an assignment statement that bases an estimate of the revenue line item for the current month on the revenue line item for the previous month.
DIMENSION line month ... revenue = LAG(revenue, 1, month) * 1.05
When the month dimension is limited to Apr2004 to Jun2004 when you run the model, then you must ensure that the solution variable contains revenue data for Mar96.
When your model contains a LEAD function, then your solution variable must contain the necessary future data. For example, when you want to calculate data for the months of April through June of 2004, and when the model retrieves data from one month in the future, then the solution variable must contain data for July 2004 when you run the model.
Oracle OLAP observes the NASKIP2 option when it evaluates equations in a model. NASKIP2 controls how NA values are handled when + (plus) and - (minus) operations are performed. The setting of NASKIP2 is important when the solution variable contains NA values.
The results of a calculation may be NA not only when the solution variable contains an NA value that is used as input, but also when the target of a simultaneous equation is NA. Values in the solution variable are used as the initial values of the targets in the first iteration over a simultaneous block. Therefore, when the solution variable contains NA as the initial value of a target, an NA result may be produced in the first iteration, and the NA result may be perpetuated through subsequent iterations.
To avoid obtaining NA for the results, you can ensure that the solution variable does not contain NA values or you can set NASKIP2 to YES before running the model.
An iterative method is used to solve the equations in a simultaneous block. In each iteration, a value is calculated for each equation, and compares the new value to the value from the previous iteration. When the comparison falls within a specified tolerance, then the equation is considered to have converged to a solution. When the comparison exceeds a specified limit, then the equation is considered to have diverged.
When all the equations in the block converge, then the block is considered solved. When any equation diverges or fails to converge within a specified number of iterations, then the solution of the block (and the model) fails and an error occurs.
You can exercise control over the solution of simultaneous equations, use the OLAP DML options described in "Model Options". For example, using these options, you can specify the solution method to use, the factors to use in testing for convergence and divergence, the maximum number of iterations to perform, and the action to take when the assignment statement diverges or fails to converge.
Instead of calculating a single set of figures for a month and division, you might want to calculate several sets of figures, each based on different assumptions.
You can define a scenario model that calculates and stores forecast or budget figures based on different sets of input figures. For example, you might want to calculate profit based on optimistic, pessimistic, and best-guess figures.
To build a scenario model, follow these steps.
Define a scenario dimension.
Define a solution variable dimensioned by the scenario dimension.
Enter input data into the solution variable.
Write a model to calculate results based on the input data.
For an example of building a scenario model see, Example 10-58, "Building a Scenario Model".
When you finish writing the statements in a model, you can use the COMPILE command to compile the model. During compilation, COMPILE checks for format errors, so you can use COMPILE to help debug your code before running a model. When you do not use COMPILE before you run the model, then the model is compiled automatically before it is solved.You can use the OBJ function with the ISCOMPILED choice to test whether a model is compiled.
SHOW OBJ(ISCOMPILED 'myModel')
When you compile a model, either by using a COMPILE statement or by running the model, the model compiler checks for problems that are unique to models. You receive an error message when any of the following occurs:
The model contains any statements other than DIMENSION, INCLUDE, and assignment (SET) statements.
The model contains both a DIMENSION statement and an INCLUDE statement.
A DIMENSION or INCLUDE statement is placed after the first equation in the model.
The dimension values in a single dimension-based equation refer to two or more different dimensions.
An equation refers to a name that the compiler cannot identify as an object in any attached analytic workspace. When this error occurs, it may be because an equation refers to the value of a dimension, but you have neglected to include the dimension in a DIMENSION statement. In addition, a DIMENSION statement may appear to be missing when you are compiling a model that includes another model and the other model fails to compile. When a root model (the innermost model in a hierarchy of included models) fails to compile, the parent model cannot inherit any DIMENSION commands from the root model. In this case the compiler may report an error in the parent model when the source of the error is actually in the root model. See INCLUDE for additional information.
The model compiler examines each name in an equation to determine the analytic workspace object to which the name refers. Since you can use a variable and a dimension value in the same way in a model equation (basing calculations on it or assigning results to it), a name might be the name of a variable or it might be a value of any dimension listed in a DIMENSION statement.
To resolve each name reference, the compiler searches through the dimensions listed in explicit or inherited DIMENSION statements, in the order they are listed, to determine whether the name matches a dimension value of a listed dimension. The search concludes as soon as a match is found.
Therefore, when two or more listed dimensions have a dimension value with the same name, the compiler assumes that the value belongs to the dimension named earliest in a DIMENSION statement.
Similarly, the model compiler might misinterpret the dimension to which a literal INTEGER value belongs. For example, the model compiler assumes that the literal value '200' belongs to the first dimension that contains either a value at position 200 or the literal dimension value 200.
To avoid an incorrect identification, you can specify the desired dimension and enclose the value in parentheses and single quotes. See "Formatting Ambiguous Dimension Values".
When the compiler finds that a name is not a value of any dimension specified in a DIMENSION statement, it assumes that the name is the name of an analytic workspace variable. When a variable with that name is not defined in any attached analytic workspace, an error occurs.
The model compiler determines the dimensions over which the statements loop. When an equation assigns results to a variable, the compiler constructs code that loops over the dimensions (or bases of a composite) of the variable.
When you run a model that contains dimension-based equations, the solution variable that you specify can be dimensioned by more dimensions than are listed in DIMENSION statements.
When you specify the value of a model dimension as an argument to a user-defined program, the compiler recognizes a dependence introduced by this argument.
For example, an equation might use a program named weight that tests for certain conditions and then weights and returns the Taxes line item based on those conditions. In this example, a model equation might look like the following one.
Net.Income = Opr.Income - weight(Taxes)
The compiler correctly recognizes that Net.Income depends on Opr.Income and Taxes. However, when the weight program refers to any dimension values or variables that are not specified as program arguments, the compiler does not detect any hidden dependencies introduced by these calculations.
The model compiler analyzes dependencies between the equations in the model. A dependence exists when the expression on the right-hand side of the equal sign in one equation refers to the assignment target of another equation. When an equation indirectly depends on itself as the result of the dependencies among equations, a cyclic dependence exists between the equations.
The model compiler structures the model into blocks and orders the equations within blocks and the blocks themselves to reflect dependencies. When you run the model, it is solved one block at a time. The model compiler can produce three types of solution blocks:
Simple Solution Blocks—Simple blocks include equations that are independent of each other and equations that have dependencies on each other that are non-cyclic.
For example, when a block contains equations that solve for values A, B, and C, a non-cyclic dependence can be illustrated as A>B>C. The arrows indicate that A depends on B, and B depends on C.
Step Solution Blocks—Step blocks include equations that have a cyclic dependence that is a one-way dimensional dependence. A dimensional dependence occurs when the data for the current dimension value depends on data from previous or later dimension values. The dimensional dependence is one-way when the data depends on previous values only or later values only, but not both. For more information on one-way dimensional dependence, see "Ensuring One-Way Dimensional Dependence".
Dimensional dependence typically occurs over a time dimension. For example, it is common for a line item value to depend on the value of the same line item or a different line item in a previous time period. When a block contains equations that solve for values A and B, a one-way dimensional dependence can be illustrated as A>B>LAG(A). The arrows indicate that A depends on B, and B depends on the value of A from a previous time period.
Simultaneous Solution Blocks—Simultaneous blocks include equations that have a cyclic dependence that is other than one-way dimensional. The cyclic dependence may involve no dimensional qualifiers at all, or it may be a two-way dimensional dependence. For more information on two-way dimensional dependence, see "Structures for Which the Model Compiler Assumes Two-Way Dimensional Dependence".
When a model contains a block of simultaneous equations, COMPILE gives you a warning message. In this case, you may want to check the settings of the options that control simultaneous solutions before you run the model. "Model Options" lists these options.
An example of a cyclic dependence that does not depend on any dimensional qualifiers can be illustrated as A>B>C>A. The arrows indicate that A depends on B, B depends on C, and C depends on A.
An example of a cyclic dependence that is a two-way dimensional dependence can be illustrated as A>LEAD(B)>LAG(A). The arrows indicate that A depends on the value o~,f B from a future period, while B depends on the value of A from a previous period.
Order of Simultaneous Equations The solution of a simultaneous block of equations is sensitive to the order of the equations. In general, rely on the model compiler to determine the optimal order for the equations. In some cases, however, you may be able to encourage convergence by placing the equations in a particular order.
To force the compiler to leave the simultaneous equations in each block in the order in which you place them, set the MODINPUTORDER option to YES before compiling the model. (MODINPUTORDER has no effect on the order of equations in simple blocks or step blocks.)
Structures for Which the Model Compiler Assumes Two-Way Dimensional Dependence
When dependence is introduced through any of the following structures, the model compiler assumes that two-way dimensional dependence occurs:
A two-way dimensional dependence can occur when you use an aggregation function, such as AVERAGE, TOTAL, ANY, or COUNT.
Opr.Income = Gross.Margin - (TOTAL(Marketing + Selling + R.D)) Marketing = LAG(Opr.Income, 1, month)
A two-way dimensional dependence can occur when you use a time-series function that requires a time-period argument, such as CUMSUM, LAG, or LEAD (except for the specific functions and conditions described in "Ensuring One-Way Dimensional Dependence").
A two-way dimensional dependence also can occur when you use a financial function, such as DEPRSL or NPV.
A cyclic dependence across a time dimension that you introduce through a loan or depreciation function may cause unexpected results. The loan functions include FINTSCHED, FPMTSCHED, VINTSCHED, and VPMTSCHED. The depreciation functions include DEPRDECL, DEPRDECLSW, DEPRSL, and DEPRSOYD.
Ensuring One-Way Dimensional Dependence
When dependence between equations is introduced through any of the following structures, a one-way dimensional dependence occurs:
A one-way dimensional dependence occurs when you use a LAG or LEAD function and when the argument for the number of time periods is coded as an explicit number (either as a value or a constant) or as the result of ABS. (Otherwise, there may be a two-way dependence, involving both previous and future dimension values, and the compiler assumes that a simultaneous solution is required.) The following example illustrates this use of LAG.
Opr.Income = Gross.Margin - (Marketing + Selling + R.D) Marketing = LAG(Opr.Income, 1, month)
A one-way dimensional dependence occurs when you use a MOVINGAVERAGE, MOVINGMAX, MOVINGMIN, or MOVINGTOTAL function, when that the start and stop arguments are nonzero numbers, and when both the start and top arguments are positive or both are negative. (Otherwise, two-way dimensional dependence is assumed.)
Opr.Income = Gross.Margin - (Marketing + Selling + R.D) Marketing = MOVINGAVERAGE(Opr.Income, -4, -1, 1, month)
After compiling a model, you can use the following tools to obtain information about the results of the analysis performed by the compiler:
The MODEL.COMPRPT program produces a report that shows how model equations are grouped into blocks. For step blocks and for simultaneous blocks with a cross-dimensional dependence, the report lists the dimensions involved in the dependence.
The MODEL.DEPRT program produces a report that lists the variables and dimension values on which each model equation depends. When a dependence is dimensional, the report gives the name of the dimension.
The INFO function lets you obtain specific items of information about the structure of the model.
The compiler does not analyze the contents of any programs or formulas that are used in model equations. Therefore, you must check the programs and formulas yourself to make sure they do not do any of the following:
Refer to the value of any variable used in the model.
Refer to the solution variable.
Limit any of the dimensions used in the model.
Invoke other models.
When a model or program violates any of these restrictions, the results of the model may be incorrect.
When you run a model, keep these points in mind:
Before you run a model, the input data must be available in the solution variable.
Before running a model that contains a block of simultaneous equations, you might want to check or modify the values of some OLAP DML options that control the solution of simultaneous blocks. These options are described briefly in "Model Options".
When your model contains any dimension-based equations, then you must provide a numeric solution variable that serves both as a source of data and as the assignment target for equation results. The solution variable is usually dimensioned by all of the dimensions on which model equations are based and also by the other dimensions of the solution variable on which you are not basing equations.
When you run a model, a loop is performed automatically over the values in the current status list of each of the dimensions of the solution variable on which you have not based equations.
When a model equation bases its calculations on data from previous time periods, then the solution variable must contain data for these previous periods. When it does not, or when the first value of the dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR is in status, then the results of the calculation are NA.
To run or solve a model, use the following syntax.
model-name [solution-variable] [NOWARN]
where:
model-name is the name of the model.
solution-variable is the name of a numeric variable that serves as both the source and the target of data in a model that contains dimension-based equations. The solution variable is usually dimensioned by all the dimensions on which model equations are based (as specified in explicit or included DIMENSION commands). The solution-variable argument is required when the model contains any dimension-based equations. When all the model equations are based only on variables, a solution variable is not needed and an error occurs when you supply this argument. See "Dimensions of Solution Variables" for more information on dimensions of solution variables.
NOWARN is an optional argument that specifies that you do not want to be warned when the model contains a block of simultaneous equations.
In a model with dimension-based equations, the solution variable is usually dimensioned by the dimensions on which model equations are based. Or, when a solution variable is dimensioned by a composite, the model equations can be based on base dimensions of the composite. The dimensions on which model equations are based are listed in explicit or inherited DIMENSION statements.
Special Cases of Solution Variables
The following special cases regarding the dimensions of the solution variable can occur:
The solution variable can have dimensions that are not listed in DIMENSION commands. Oracle OLAP automatically loops over the values in the status of the extra dimensions. For example, the model might contain a DIMENSION statement that lists the line and month dimensions, but you might specify a solution variable dimensioned by line, month, and division. Oracle OLAP automatically loops over the division dimension when you run the model. The solution variable can also be dimensioned by a composite that has one or more base dimensions that are not listed in DIMENSION commands. See "Solution Variables Dimensioned by a Composite"
When the solution variable has dimensions that are not listed in DIMENSION commands and when any of these other dimensions are the dimension of a step or simultaneous block, an error occurs.
Oracle OLAP loops over the values in the status of all the dimensions listed in DIMENSION commands, regardless of whether the solution variable is dimensioned by them. Therefore, Oracle OLAP does extra, unnecessary work when the solution variable is not dimensioned by all the listed dimensions. Oracle OLAP warns you of this situation before it starts solving the model.
The inclusion of an unneeded dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR in a DIMENSION statement causes incorrect results when you use a loan, depreciation, or aggregation function in a model equation. The incorrect results occur because any component of a model equation that refers to the values of a model dimension behaves as if that component has all the dimensions of the model.
Solution Variables Dimensioned by a Composite
When a solution variable contains a composite in its dimension list, Oracle OLAP observes the sparsity of the composite whenever possible. As it solves the model, Oracle OLAP confines its loop over the composite to the values that exist in the composite. It observes the current status of the composite's base dimensions as it loops.
However, for proper solution of the model, Oracle OLAP must treat the following base dimensions of the composite as regular dimensions:
A base dimension that is listed in a DIMENSION statement.
A base dimension that is implicated in a model equation created using SET (for example, an equation that assigns data to a variable dimensioned by the base dimension).
A base dimension that is also a base dimension of a different composite that is specified in the ACROSS phrase of an equation. (See SET for more information on assignment statements and the use of ACROSS phrase.)
When a base dimension of a solution variable's composite falls in any of the preceding three categories, Oracle OLAP treats that dimension as a regular dimension and loops over all the values that are in the current status.
When the solution variable's composite has other base dimensions that do not fall in the special three categories, Oracle OLAP creates a temporary composite of these extra base dimensions. The values of the temporary composite are the combinations that existed in the original composite. Oracle OLAP loops over the temporary composite as it solves the model.
The following tools are available for debugging models:
To see the order in which the equations in a model are solved, you can set the MODTRACE option to YES before you run the model.When you set MODTRACE to YES, you can use a DBGOUTFILE statement to send debugging information to a file. The file produced by DBGOUTFILE interweaves each line of your model with its corresponding output.
You can use the MODEL.COMPRPT, MODEL.DEPRT, and MODEL.XEQRPT programs and the INFO function to obtain information about the structure of a compiled model and the solution status of a model you have run.
This topic provides information about aggregating data using the OLAP DML.It includes the following subtopics:
Historically, aggregating data was summing detail data to provide subtotals and totals. However, using OLAP DML aggmap objects you can specify more complex aggregation calculation:
The summary data dimensioned by hierarchical dimension can be calculated using many different types of methods (for example, first, last, average, or weighted average). For an example of this type of aggregation, see Example 9-18, "Aggregating Up a Hierarchy".
The summary data dimensioned by a nonhierarchical dimension can be calculated using a model. Using a model t calculate summary data is useful for calculating values for dimensions, such as line items, that do not have a hierarchical structure. Instead, you create a model to calculate the values of individual line items from one or more other line items or workspace objects. For an example of this type of aggregation, see Example 9-17, "Solving a Model in an Aggregation".
The detail data used to calculate the summary data can be in the variable that contains the summary data or in one or more other variables. The variable that contains the summary data does not have to have the same dimensions as the variables that contain the detail data. For an examples of this type of aggregation, see Example 9-15, "Aggregating into a Different Variable" and Example 9-32, "Capstone Aggregation".
The data can be aggregated as a database maintenance procedure, in response to user requests for summarized data, or you can combine these approaches. See "Executing the Aggregation" for more information.
Data that is aggregated in response to user requests can be calculated each time it is requested or stored or cached in the analytic workspace for future queries.
The specification for the aggregation can be permanent or temporary as described in "Creating Custom Aggregates".
To aggregate data using the OLAP DML, take the following steps:
Decide if you want to aggregate all of the data as a Database maintenance procedure using the AGGREGATE command or on-the-fly at run time using the AGGREGATE function or the $AGGMAP property, or if you want to combine these approaches and precalculate some values and calculate others at run time. For a discussion of the various approaches, see "Executing the Aggregation".
Issue a DEFINE AGGMAP statement to define the aggmap object as type AGGMAP.
Write the aggregation specification as described in AGGMAP.
When aggregating a partitioned variable, run PARTITIONCHECK to check that the aggregation specification created in the previous step is compatible with the variable's partitioning. If it is not, either rewrite the aggregation specification or repartition the variable using CHGDFN.
When some or all of the data is to be aggregated using the AGGREGATE function:
Compile the aggmap object as described in "Compiling Aggregation Specifications".
Add the triggering property, object, or event. For example, add a formula that has the AGGREGATE function as its expression and add $NATRIGGER property to the variable to trigger the execution of that formula in response to a run-time request for data.
When you want the aggmap object to be a permanent part of the analytic workspace, save the aggmap object using an UPDATE statement followed by COMMIT.
For data that is to be calculated using the AGGREGATE command:
(Optional) Set the POUTFILEUNIT option so that you can monitor the progress of the aggregation.
Use the AGGREGATE command, followed by UPDATE and COMMIT to precalculate the data and store it in the analytic workspace.
Compiling the aggmap object is important for aggregation performed at run-time using the AGGREGATE function. Unless the compiled version of the aggmap has been saved, the aggmap is recompiled by each session that uses it.
There are two ways you can compile an aggmap objects:
A COMPILE statement is the only way to compile an aggmap object that is used by an AGGREGATE function. Explicitly compiling an aggmap is also useful for finding syntax errors in the aggmap before attempting to use it to generate data. The following statement compiles the sales.agg aggmap.
COMPILE gpct.aggmap
When you aggregate the data using an AGGREGATE command, include the FUNCDATA phrase in the statement.
When you use the FUNCDATA phrase in an AGGREGATE command, Oracle OLAP compiles the aggmap before it aggregates the data. For example, this statement compiles and precalculates the aggregate data.
AGGREGATE sales USING gpct.aggmap FUNCDATA
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Important: When some data is calculated on the fly, then you must compile and save the aggmap after executing the AGGREGATE command. |
The OLAP DML provides two ways to aggregate data:
As a data maintenance procedure using the AGGREGATE command. To use this method of aggregating data within an aggregation specification, identify data that you want to aggregate in this manner using the PRECOMPUTE statement or PRECOMPUTE clause of the RELATION statement.
At run-time when needed using the AGGREGATE function or adding an $AGGMAP property to the variable.
You can choose whatever method seems appropriate: by level, individual member, member attribute, time range, data value, or other criteria. You can also combine these approaches and precalculate some values and calculate others at run time. In this case, frequently, you use the same aggmap with the AGGREGATE command and the AGGREGATE function. However, in some cases you might use different aggmaps.
One step that you can take to achieve overall good performance is to balance the amount of the data that you aggregate and store in an analytic workspace with the amount of data that you specify for calculation on the fly. You can use a PRECOMPUTE statement or clause within your aggregation specification to ask Oracle OLAP to use special functionality called the Aggregate Advisor to automatically determine what values to aggregate as a data maintenance procedure using the AGGREGATE command, or to explicitly identify the values yourself.
The definitions for most aggregations persist from one session to another. However, you might need to create session-only aggregates at run time for forecasting or what-if analysis, or just because you want to view the data in an unforeseen way. Adding session-only aggregates is sometimes called creating custom aggregates. You can create non-persistent aggregated data without permanently changing the specification for the aggregation in the following ways:
Using a MAINTAIN ADD SESSION statement, define temporary dimension members and include an aggregation specification as part of the definition of these members. The aggregation specification can either be a model or an aggmap. For an example of using this method to create a temporary aggregation, see Example 10-42, "Creating Calculated Dimension Members with Aggregated Values" .
Create a model that specifies the aggregation. Use an AGGMAP ADD statement to add the model to an aggmap at run time. After a session, Oracle OLAP automatically removes any models that you have added to an aggmap in this manner. See AGGMAP ADD or REMOVE model for more information.
Allocating data involves creating lower-level data from summary data. This topic provides an overview of how to allocate data using OLAP DML statements. It includes the following subtopics:
Allocating data using the OLAP DML involves creating an ALLOCMAP type aggmap object that specifies how the data is allocated, and executing that object using the ALLOCATE command that actually distribute the data from a source object to the cells of a target. The target is a variable that is dimensioned by one or more hierarchical dimensions. The source data is specified by dimension values at a higher level in a hierarchical dimension than the values that specify the target cells.
ALLOCATE uses an aggmap to specify the dimensions and the values of the hierarchies to use in the allocation, the method of operation to use for a dimension, and other aspects of the allocation.
Some allocation operations are based on existing data. The object containing that data is the basis object for the allocation. In those operations, ALLOCATE distributes the data from the source based on the values of the basis object.
ALLOCATE has operations that are the inverse of the operations of the AGGREGATE command. The allocation operation methods range from simple allocations, such as copying the source data to the cells of the target variable, to very complex allocations, such as a proportional distribution of data from a source that is a formula, with the amount distributed being based on another formula, with multiple variables as targets, and with an aggmap that specifies different methods of allocation for different dimensions.
The Oracle OLAP allocation system is very flexible and has many features, including the following:
The source, basis, and target objects can be the same variable or they can be different objects.
The source and basis objects can be formulas, so you can perform computations on existing data and use the result as the source or basis of the allocation.
You can specify the method of operation of the allocation for a dimension. The operations range from simple to very complex.
You can specify whether the allocated value is added to or replaces the existing value of the target cell.
You can specify an amount to add to or multiply by the allocated value before the result is assigned to the target cell.
You can lock individual values in a dimension hierarchy so that the data of the target cells for those dimension values is not changed by the allocation. When you lock a dimension value, then the allocation system normalizes the source data, which subtracts the locked data from the source before the allocation. You can choose to not normalize the source data.
You can specify minimum, maximum, floor, or ceiling values for certain operations.
You can copy the allocated data to a second variable so that you can have a record of individual allocations to a cell that is the target of multiple allocations.
You can specify ways of handling allocations when the basis has a null value.
You can use the same aggmap in different ALLOCATE commands to use the same set of dimension hierarchy values, operations, and arguments with different source, basis, or target objects.
To allocate data using an aggmap object, use the following OLAP DML statements in the order indicated:
Issue a DEFINE AGGMAP statement to define the aggmap object.
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Note: When using the OLAP Worksheet, at the command line level, immediately after the DEFINE AGGMAP statement, enter an "empty" allocation specification by coding an ALLOCMAP statement. For example:DEFINE myaggmap AGGMAP ALLOCMAP 'END' |
Add a specification to the aggmap object that specifies the allocation that you want performed. See ALLOCMAP for more information.
When you want the aggmap object to be a permanent part of the analytic workspace, save the aggmap object using an UPDATE statement followed by COMMIT.
(Optional) Set the POUTFILEUNIT option so that you can monitor the progress of the allocation.
(Optional) Redesign the allocation error log by setting the ALLOCERRLOGFORMAT and ALLOCERRLOGHEADER options to nondefault values.
(Optional) Set the $ALLOCMAP property on one or more variables to specify that the aggmap is the default allocation specification for the variables.
(Recommended, but optional) Limit the variable to the target cells (that is, the cells into which you want to allocate data).
Issue an ALLOCATE statement to allocate the data.
Sometimes you want to overwrite existing data when allocating values to a target variable and at other times you want to write allocated values to target cells that have an NA basis before the allocation. For example, when you create a product in your product dimension, then no basis exists for the new product in your budget variable. You want to allocate advertising costs for the entire product line, including the new product.
You can handle NA values using formulas and hierarchical operators in a RELATION statement in the following ways:
Handling NA data with formulas—The preferred method for handling the NA values is to construct a basis that only describes the desired target cells. You can refine your choice of basis values by deriving the basis from a formula. The following statements define a formula that equates the values of the new product to twice the value of an existing product. You could use such a formula as the basis for allocating advertising costs to the new product.
DEFINE formula_basis FORMULA DECIMAL <product> EQ IF product EQ 'NEWPRODUCT' - THEN 2 * product.budget(product 'EXISTINGPRODUCT') - ELSE product.budget
Handling NA data with hierarchical operators—To allocate data to target cells that currently have NA values, use a hierarchical operator in a RELATION statement in the allocation specification. The hierarchical operators use the hierarchy of the dimension rather than existing data as the allocation basis. A danger in using hierarchical operators is the possibility of densely populating your detail level data, which can result in a much larger analytic workspace and require much more time to aggregate the data.
To continue the example of allocating the advertising cost for the new product, you could use the hierarchical last operator HLAST to specify allocating the cost to the new (and presumably the last) product in the product dimension hierarchy.
The ROW command produces a single line of data in cells, one after another in a single row. A series of ROW commands that produce corresponding cells are often used to build up columns of data. For this reason, we normally speak of the ROW command as producing a line of columns. Output from the ROW command is sent to the current outfile.
The ROW command is typically used with other commands, functions, and options that you can think of collectively as report-writing statements
The ROW command itself consists of a series of column descriptions that specify the data to be produced and, optionally, the output format of the data.
In addition, ROW has a versatile capability for doing row and column arithmetic. It can perform calculations and include the calculation results in the output. It can use any kind of calculated expression in the column descriptions; and it can take advantage of row and column totaling functions (see Table 10-6, "Row and Column Arithmetic").
ROW is primarily used in report programs to produce the lines of the report. The maximum width of any row in a report is 4,000 characters.
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Tip: When you know ahead of time that you do not need the subtotaling capability of the ROW command, using a HEADING statement instead of ROW to produce the lines of your report can provide a time savings, since, in this case, Oracle OLAP does not keep track of subtotals. |
Syntax
ROW [attributes] [ACROSS dimension [limit-clause]:] {exp1|SKIP } -
[[attributes] [ACROSS dimension [limit-clause]:] {expn|SKIP }]
Parameters
ROW with no arguments produces a blank line.
One or more attributes for a column. Attributes are format specifications that determine how the data value is formatted within the column. There is no limit to the number of attributes that you can use to describe a column format. (See Table 10-5, "Column Attributes for ROW" for an explanation of each of the available attributes.) The default for some format attributes is determined by the current setting of Oracle OLAP options (see Table 10-7, "Report-Related Options" for a list of these options).
An ACROSS phrase lets you include multiple values of a dimensioned expression in a single row by looping over one dimension (or composite) of the expression. Typically, ROW shows only the value that corresponds to the first dimension value within the current limits. With an ACROSS phrase, ROW produces one data column for each dimension value currently in the status.
You can apply a single ACROSS phrase to multiple data expressions, or you can use separate ACROSS phrases for different data expressions. See "Multiple Expressions" and "Separate ACROSS Phrases".
The name of a dimension or composite over which the statement loops.
When you show data for a variable dimensioned by a composite and you do not include an ACROSS phrase, ROW shows output for all data cells that correspond to the base dimension values of the composite. When a particular combination of base dimension values does not exist in the composite, ROW shows NA for the corresponding data cell. Likewise, when you specify one composite's base dimension in an ACROSS phrase, ROW shows NA for a data cell for which the composite contains no value. However, when you specify a composite in the ACROSS phrase, ROW shows output only for data cells for which combinations of base dimension values exist in the composite which provides a more concise report that better reflects your data.
When the dimension specified in an ACROSS phrase has null status, ROW does not produce any data columns for that ACROSS phrase.
When you specify a dimension in the ACROSS phrase, a clause that enables you to temporarily change the status of that dimension during the execution of the ROW statement.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
The following example temporarily limits month to the last six values, no matter what the current status of month is.
ACROSS month LAST 6: units
When the limits you specify result in empty status for the dimension, an error occurs. However, when you include the phrase IFNONE label, the error is suppressed and execution of your program branches to the specified label where you can handle the error.
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Note: When you specify a composite in the ACROSS phrase, you cannot include a limit-clause argument. You must limit the base dimensions of a composite to the desired values using a LIMIT command before you execute a ROW statement |
Used instead of an expression to indicate that the column is to be left blank.
Table 10-5 Column Attributes for ROW
| Attribute | Meaning |
|---|---|
|
WIDTH n (W n) |
Makes the column n spaces wide. The default width for the first column is the value of the LCOLWIDTH option. For other columns, it is the value of the COLWIDTH option. The maximum width is 4,000 characters. Columns with a width of |
|
SPACE n (SP n) |
Precedes the column with n spaces. The default for the first column is |
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INDENT n |
Indents the value n spaces within its column. The default is 0. |
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LEFT (L) |
Left-justifies the value within its column. (The default for TEXT data.) |
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RIGHT (R) |
Right-justifies the value within its column. (The default for numeric and Boolean data.) |
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CENTER (C) |
Centers the value within its column. |
|
LSET 'text' |
Adds text to the left of the value. When used with an expression that contains |
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NOLSET |
Does not add anything to the left of the value. |
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RSET 'text' |
Adds text to the right of the value. When used with an expression that contains |
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NORSET |
Does not add anything to the right of the value. |
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FILL 'char' |
Puts char into unused positions in the column. The default fill character is a space. |
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DECIMAL n (D n) |
Shows n decimal places. Decimal places are separated by the character currently specified by the DECIMALCHAR option. The default number of decimal places is controlled by the DECIMALS option. |
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NODECIMAL |
Shows the number of decimal places indicated by the DECIMALS option. |
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COMMA |
Marks thousands and millions with commas or the character currently recorded in the THOUSANDSCHAR option. The default is controlled by the COMMAS option. |
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NOCOMMA |
Does not mark thousands and millions. |
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PAREN |
Uses parentheses to indicate negative numbers. The default is controlled by the PARENS option. |
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NOPAREN |
Uses the minus sign to indicate negative numbers. The default is controlled by the PARENS option. |
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LEADINGZERO |
Puts a leading zero before decimal numbers between |
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NOLEADINGZERO |
Suppresses leading zeros before decimal numbers between |
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CNLEADINGZERO |
Puts a leading zero before decimal numbers between |
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MNOTATION |
Always uses M-notation (divides values by one million and appends |
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CMNOTATION |
Conditionally uses M-notation, when needed to make a value fit in a column. |
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NOMNOTATION |
Does not use M-notation (uses asterisks for oversize values). |
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MDECIMAL n |
Shows n decimal places in numbers formatted with M-notation; n can be any number from 0 to 16, or 255. |
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ENOTATION |
Always uses scientific notation, also called exponential notation or E-notation (appends |
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CENOTATION |
Conditionally uses E-notation, when needed to make a value fit in a column. |
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NOENOTATION |
Does not use E-notation (defaults to conditional M-notation). |
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EDECIMAL n |
Shows n decimal places in numbers formatted with E-notation; n can be any number from 0 to 16, or 255. |
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NASPELL 'text' |
Uses text instead of |
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NONASPELL |
Spells |
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ZSPELL 'text' |
Uses text instead of zero numeric values. The default is controlled by the ZSPELL option. |
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NOZSPELL |
Spells zero values as indicated by the ZSPELL option. |
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YESSPELL 'text' |
Text used for |
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NOSPELL 'text' |
Text used for |
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TRUNCATE (TRUNC) |
Truncates a character value to the column width when it does not fit in the column. |
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NOTRUNCATE (NOTRUNC) |
Creates additional lines when the character value does not fit in the column. |
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FOLDUP |
For a multiline character value, places all but the last line above the rest of the row, and the last line on the row with the other values; also strips any leading or trailing spaces. |
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FOLDDOWN |
For a multiline character value, places the first line on the row with the other values, and places additional lines below the rest of the row; also strips any leading or trailing spaces. |
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VALONLY |
Underlines or overlines the value only. (Used with UNDER and OVER.) |
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NOVALONLY |
Underlines or overlines the entire width of the column. (Used with UNDER and OVER.) |
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UNDER textexp |
Underlines the value or column with the value of a character expression (textexp). When textexp is a literal value, it must be enclosed in single quotes. Useful literal values include: To underline only when a condition is met, for textexp use
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OVER textexp |
Overlines the value or column with the value of a character expression (textexp). When textexp is a literal value, it must be enclosed in single quotes. Useful literal values include: To overline only when a condition is met, for textexp use
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Use the functions that are listed in Table 10-6, "Row and Column Arithmetic" to perform calculations on the values generated so far in a report.
Table 10-6 Row and Column Arithmetic
| Function | Data Type | Value Returned |
|---|---|---|
|
COLVAL(n) |
DECIMAL |
Value in the nth column of the current row. When n >
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RUNTOTAL(n) where: n = 1,2, ...32 |
DECIMAL |
Total of all numbers generated in the current column since the last SUBTOTAL or ZEROTOTAL for n. Does not reset total for n to |
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SUBTOTAL(n) where: n = 1,2, ...32 |
DECIMAL |
Total of all numbers generated in the current column since the last SUBTOTAL or ZEROTOTAL for n. Resets total for n to
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The options that are listed in Table 10-7, "Report-Related Options" affect the default format for a ROW command.
Table 10-7 Report-Related Options
| Option | Meaning |
|---|---|
|
COLWIDTH |
Column width for all but the first column when the WIDTH attribute is not used. The default is |
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COMMAS |
Specifies whether a thousands group separator is used when neither the COMMA attribute nor the NOCOMMA attribute is used. The default is |
|
DECIMALS |
Number of decimal places when the DECIMAL attribute is not used. The default is |
|
LCOLWIDTH |
Column width for the first column when the WIDTH attribute is not used. The default is |
|
LSIZE |
Defines the line size within which the STDHDR program centers the standard header. The default is |
|
NASPELL |
Text used for |
|
NLS_LANGUAGE |
Specifies the text used for |
|
NLS_TERRITORY |
Specifies the character used for the decimal marker and the thousands group separator. These values are reflected in the DECIMALCHAR and THOUSANDSCHAR options. |
|
PARENS |
Parentheses usage for negative numbers when neither the PAREN attribute nor the NOPAREN attribute is used. The default is |
|
ZEROROW |
Controls generation or suppression of rows in which all numeric values are zero. The default is |
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ZSPELL |
Text used for zero values when the ZSPELL attribute is not used. The default text is |
Use the statements that are listed in Table 10-8, "OLAP DML Statements That Are Compatible with the ROW Command" with the ROW command.
Table 10-8 OLAP DML Statements That Are Compatible with the ROW Command
| Command | Action |
|---|---|
|
BLANK n |
Produces n blank lines. The default is one line. |
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HEADING column- description(s) |
Produces titles and column headings for a report. Numeric values in headings are not added to column totals. |
|
PAGE |
Forces a page break in output when PAGING is set to |
|
ZEROTOTAL |
Resets all 32 totals to |
|
ZEROTOTAL ALL col(s) |
Resets all 32 totals to |
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ZEROTOTAL n col(s) |
Resets the indicated total (n) to |
Usage Notes
Report-Writing Commands
The ROW command and its associated options and commands are referred to collectively as report-writing statements. Table 10-6, "Row and Column Arithmetic" lists functions you can use for performing row and column arithmetic in reports. Table 10-7, "Report-Related Options" lists report-related options that determine the default format for ROW output. Table 10-8, "OLAP DML Statements That Are Compatible with the ROW Command" lists additional statements that are used in combination with ROW to create reports.You can use the PAGING option and associated paging-related options to produce your report program in a page-oriented format.
Labels for Composites and Conjoint Dimensions
When you produce a report of data that has a composite or a conjoint dimension in its dimension list, you can produce a label column for each base dimension by using the KEY function. You can also provide a separate WIDTH attribute for each label column. For example, when proddist is a composite with the base dimensions product and district, you can use statements similar to the following ones.
FOR proddist ROW W 12 KEY(proddist district) W 8 KEY(proddist product) ...
Multiple Expressions
When you want the same format attribute or ACROSS phrase to apply to multiple data expressions, you can enclose the expressions in angle brackets (< >) and place the common attributes or ACROSS phrase immediately before the bracketed expressions.
attributes <expression1, expression2, ...>
or
ACROSS dimension: <expression1, expression2, ...>
When you have attributes that apply to only one expression within the brackets, place the specific attributes immediately before the expression.
attributes1 <expression1, attributes2 expression2>
When an attribute inside angle brackets (specific to a column) conflicts with an attribute outside the brackets (common to several columns), the specific attribute overrides the common attribute.
You can nest brackets to any depth, if you have an equal number of right and left brackets.
Separate ACROSS Phrases
For data generated with an ACROSS phrase, you can produce all the columns for one expression and then all the columns for additional expressions by using separate ACROSS phrases.
ACROSS dim: expression1, ACROSS dim: expression2
You also can nest ACROSS phrases to show data columns for two or more dimensions of an expression across a row.
ACROSS dim1: ACROSS dim2: expression
Row and Column Arithmetic
See Table 10-6, "Row and Column Arithmetic" for a list of the functions available for row and column arithmetic. You can use these functions to perform calculations on the values already generated in a report. Oracle OLAP maintains 32 running totals for each column, so you can include up to 32 levels of subtotals in a report. Note that when a numeric value is too large to fit into a data cell, ROW rounds it off to the nearest million with the symbol M at the right side of the cell. When a value is still too large, ROW replaces the value with asterisks.
Examples
Example 10-109 Labeling Data Values
In this example, ROW produces a line of output that contains a value of sales, along with the corresponding dimension values for district, month, and product that identify it.
ROW W 8 district month product sales
The preceding statement produces the following row of output.
Boston Jan95 Tents 32,153.52
Example 10-110 Reporting Two Variables
The line of output produced by this ROW statement contains the current dimension value of district, followed by the values of sales and sales.plan for Sportswear for each of the first two months of 1996.
LIMIT month TO 'Jan96' 'Feb96' LIMIT product TO 'Sportswear' ROW W 8 district ACROSS month: <sales sales.plan>
These statements produce the following row of output.
Boston 57,079.10 61,434.20 63,121.50 64,006.91
Example 10-111 Formatting and Labeling the Output
In this ROW statement, you want to see the actual and planned sales of tents for June 1996. You want to limit the status of month only for this one ROW statement, so you include the value Jun96 in the ACROSS phrase. You format the values as whole dollar amounts, and you also add a dollar sign to the values, along with individual labels that identify the actual and planned figures.
LIMIT product TO 'Tents' ROW WIDTH 15 name.product ACROSS month 'Jun96': - DECIMAL 0 LSET '$' W 18 - <RSET ' (actual)' sales - RSET ' (plan)' sales.plan>
These statements produce the following row of output.
3-Person Tents $95,121 (actual) $80,138 (plan)
Example 10-112 Reporting on a Variable Dimensioned by a Composite
In this example, D.SALES is a variable whose dimension list includes the dimension month and the unnamed composite SPARSE <product district>. By specifying the composite in an ACROSS phrase of a ROW statement, you can produce a report that includes only the data cells for which the composite contains values.
LIMIT product TO ALL LIMIT district TO 'Atlanta' LIMIT month TO 'Jan96' ROW ACROSS SPARSE <product district>: d.sales
The $LOOP_AGGMAP property is used to determine how to loop the formula on which it is assigned when a SQL OLAP_TABLE function with the LOOP OPTIMIZED clause is executed. It specifies the name of an aggmap object to use when Oracle OLAP generates a UNION subclause that includes the formula. The value that you specify for this property overrides all other aggmaps associated with a variable (for example, aggmaps for which the variable has an $AGGMAP property) and can be used to clarify which aggmap Oracle OLAP should use when the underlying variables of a formula are associated with different aggmaps.
Syntax
You add or delete a $LOOP_AGGMAP property to the most recently defined or considered formula (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$LOOP_AGGMAP' agggmap-name
To delete the property, issue the following statement.
PROPERTY DELETE '$LOOP_AGGMAP'
Parameters
The name of an aggmap object.
The SORT command arranges the order of values in the current status list of a dimension or a dimension surrogate, or in a valueset.
Syntax
SORT dimension [byhierarchy] [bycriterion...]
where:
byhierarchy is an optional phrase that uses a parent relation to arrange the order of values in the current status list of a hierarchical dimension or its dimension surrogate, or to assign values to a valueset, based on family relationships within the hierarchy. You can include only one byhierarchy phrase in a SORT statement. It must be the first phrase in a SORT statement.
HIERARCHY parent-relation [INVERT] [DEPTH n] [SORTORPHANS]
bycriterion uses an explicit criterion to arrange the order of values in the current status list of a dimension or its dimension surrogate, or to assign values to a valueset. You can include as many bycriterion phrases as you want in a SORT statement.
{A|D} [NAFIRST] criterion
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
Specifies that Oracle OLAP is to sort dimension values based on the values position in parentrel.
Specifies the name of a child-parent self-relation for dimension. For each dimension value, the relation holds another value of the dimension which is its parent dimension value (the one immediately above it in a given hierarchy). This parent relation can have multiple dimensions.
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Tip: You can specify a QDR of parent-relation to specify a single value. |
Indicates that Oracle OLAP places the children in the hierarchy before their parents. (By default, children are placed after their parents.)
Specifies the number of generations down from the top of the hierarchy that Oracle OLAP should place into status and. there, for the values that are included in the result. The default value of n is 99. When you do not want any values in the result (that is, when you want a NULL status), specify -1 for n. When you only want the top of the hierarchy in status (that is, those dimension values that do not have parents), specify 0 (zero).
Specifies that all first cousins whose parents are not in status are sorted together. By default, Oracle OLAP preserves the hierarchical structure when sorting children even when their parents are not in status.
The order in which the values are to be sorted. A means ascending order (alphabetical when the sorting criterion is TEXT, ID, or a relation), and D means descending order (reverse alphabetical when the sorting criterion is TEXT, ID or a relation).
Specifies that NA values are to placed first in the sort rather than last.
The expression to be used as a sorting criterion. Each criterion must be dimensioned by dimension. The first expression is the major sorting criterion. When the expression is multidimensional, SORT uses the first value in status for all dimensions other than the dimension being sorted. You cannot use a valueset as the sorting criterion.
Usage Notes
Sorting a Dimension and a Valueset
When Oracle OLAP sorts a dimension, it sorts the temporary status list of a dimension, not the data dimensioned by it. Since many OLAP DML statements operate on data according to the current status of its dimensions, sorting a dimension appears to have the effect of sorting data. A dimension and any dimension surrogates for it share the same status. Therefore, a SORT statement on a dimension or any of its surrogates sorts them all.
When Oracle OLAP sorts a valueset, it sorts the actual values within the valueset. When you execute UPDATE and COMMIT commands after sorting a valueset, the values in the valueset are stored in that sorted order.
Sorting Alphabetically
To sort a TEXT or ID dimension or its valueset in alphabetical order, use the dimension itself as the sorting criterion.
SORT district A district
Sort Order for Textual Data
The sort order for textual data in an alphabetical sort is controlled by the NLS_SORT option.
Sorting a Time Dimension
The values of dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR are stored internally as numbers. Therefore, when you sort a dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR dimension or its valueset in ascending order, with the dimension itself as the sorting criterion, then the values in the status list or valueset are placed in chronological order. When you sort a dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR dimension or its valueset in descending order, then the values are placed in reverse chronological order.
Sorting Using a Relation as a Criterion
When you use a relation as your sorting criterion, then the sorting is done alphabetically; that is, the dimension or valueset is sorted according to an alphabetical list of the related dimension values. To use a relation as the sorting criterion and keep the related dimension values in their original order, you must use the following expression as your sorting criterion See Example 10-126, "Sorting Using a Relation as the Criterion".
CONVERT(relation, INTEGER)
Sorting Conjoint Dimensions
You can sort a conjoint dimension or its valueset by criteria dimensioned by either the conjoint dimension itself or by one of its base dimensions.
Sorting Concat Dimensions
You can sort a concat dimension or its valueset by criteria dimensioned by either the concat dimension itself or by one of its component dimensions. See Example 10-127, "Sorting Based on a Concat" and Example 10-128, "Sorting Based on a Component".
Sorting a Worksheet
You cannot use a worksheet as a sort criterion. You must first use CONVERT to specify the data type to which values of the worksheet should be converted.
Examples
Example 10-126 Sorting Using a Relation as the Criterion
This example sorts districts according to their unit sales of tents for July 1996. They are sorted first by the region to which they belong and then in descending order of dollar sales. Notice that in the following SORT statement, a relation is used as the primary sorting criterion. Consequently, the districts are sorted by regions listed alphabetically.
LIMIT month TO 'Jul96' LIMIT product TO 'Tents' SORT district A Region.District D sales
Assume you issue the following REPORT statement.
REPORT DOWN district HEADING 'Region' region.district sales
The preceding statement produces the following report that reflects the work of the SORT statement.
PRODUCT: Tents
--------MONTH--------
--------JUL96--------
DISTRICT Region SALES
-------------- ---------- ----------
Dallas Central 154,914.23
Chicago Central 79,934.42
Atlanta East 140,711.00
Boston East 93,972.49
Seattle West 123,700.17
Denver West 100,413.49
In the following SORT statement, CONVERT is used to keep the regions in their original order.
SORT district A CONVERT(region.district INTEGER) D sales
Assume that you issue the following REPORT statement.
REPORT DOWN district HEADING 'Region' region.district sales
The preceding statement produces the following report that reflects the work of the last SORT statement.
PRODUCT: Tents
--------MONTH--------
--------JUL96--------
DISTRICT Region SALES
-------------- ---------- ----------
Atlanta East 140,711.00
Boston East 93,972.49
Dallas Central 154,914.23
Chicago Central 79,934.42
Seattle West 123,700.17
Denver West 100,413.49
When you want the dimension to keep the sorted order of its values permanently, use a MAINTAIN statement after you sort the dimension.
SORT district A district MAINTAIN district MOVE STATUS FIRST
Example 10-127 Sorting Based on a Concat
The following statements sort the concat dimension reg.dist.ccdim in ascending order based on all of its values and report the result.
sort reg.dist.ccdim d reg.dist.ccdim report reg.dist.ccdim
The preceding statement produces the following results.
REG.DIST.CCDIM -------------------- <Region: West> <Region: East> <Region: Central> <District: Seattle> <District: Denver> <District: Dallas> <District: Chicago> <District: Boston> <District: Atlanta>
The following statements sort the concat dimension reg.dist.ccdim in ascending order based on all of its values and report the result.
SORT reg.dist.ccdim A reg.dist.ccdim REPORT reg.dist.ccdim
The preceding statement produces the following results.
REG.DIST.CCDIM -------------------- <District: Atlanta> <District: Boston> <District: Chicago> <District: Dallas> <District: Denver> <District: Seattle> <Region: Central> <Region: East> <Region: West>
Example 10-128 Sorting Based on a Component
The following statements sort the concat dimension reg.dist.ccdim in ascending order based on the values of one of its base dimensions and in descending order based on the values of its other base dimension, and report the result.
SORT reg.dist.ccdim A region D district REPORT reg.dist.ccdim
The preceding statement produces the following results.
REG.DIST.CCDIM -------------------- <REGION: CENTRAL> <REGION: EAST> <REGION: WEST> <DISTRICT: SEATTLE> <DISTRICT: DENVER> <DISTRICT: DALLAS> <DISTRICT: CHICAGO> <DISTRICT: BOSTON> <DISTRICT: ATLANTA>
Example 10-129 Sorting by Hierarchy
Assume that your analytic workspace has two dimensions (geog and time), one relation (geogparent) and one variable (sales) with the following definitions.
DEFINE GEOG DIMENSION TEXT DEFINE TIME DIMENSION TEXT DEFINE GEOGPARENT RELATION GEOG <GEOG> DEFINE SALES VARIABLE INTEGER <TIME GEOG>
If you issue a REPORT statement for sales when all of the values of geog are in status, Oracle OLAP produces the following report. This report displays the values for geog in the order in which they were added to the analytic workspace.
REPORT sales
--------SALES--------
--------TIME---------
GEOG 2004 2005
-------------- ---------- ----------
USA 1,300 NA
Massachusetts 3,881 NA
Florida 3,479 NA
Boston 2,644 NA
Orlando 4,398 NA
Miami 3,294 NA
Pembroke 4,268 NA
California 1,899 NA
Texas 2,115 NA
Los Angeles 2,394 NA
San Francisco 1,334 NA
Dallas 839 NA
Houston 997 NA
However, assume that you issue a SORT statement to sort the values of geog by (1) geogparent and (2) descending by sales. After this sort if you issue a REPORT statement for sales, Oracle OLAP produces the following report. This report displays the values for geog with the states in descending order by sales, but with the cities of each state under the appropriate state.
SORT geog HIERARCHY geogparent D sales
REPORT SALES
--------SALES--------
--------TIME---------
GEOG 2004 2005
-------------- ---------- ----------
USA 1,300 NA
Massachusetts 3,881 NA
Pembroke 4,268 NA
Boston 2,644 NA
Florida 3,479 NA
Orlando 4,398 NA
Miami 3,294 NA
Texas 2,115 NA
Houston 997 NA
Dallas 839 NA
California 1,899 NA
Los Angeles 2,394 NA
San Francisco 1,334 NA
Example 10-130 Sorting Orphans of a Hierarchy
Assume that you have the same objects described in Example 10-129, "Sorting by Hierarchy". Assume also that the states of Florida and Massachusetts are not in status.
When you include the SORTORPHANS keyword in your SORT statement, the cities in Massachusetts and Florida are sorted together.
SORT geog HIERARCHY geogparent SORTORPHANS D sales
REPORT sales
------------------SALES------------------
------------------TIME-------------------
GEOG 2004 2005
-------------- -------------------- --------------------
USA 1,300 NA
Orlando 4,398 NA
Pembroke 4,268 NA
Miami 3,294 NA
Boston 2,644 NA
Texas 2,115 NA
Houston 997 NA
Dallas 839 NA
California 1,899 NA
Los Angeles 2,394 NA
San Francisco 1,334 NA
However, if you exclude the SORTORPHANS keyword, Massachusetts cities and Florida cities are sorted separately.
LIMIT geog COMPLEMENT 'Florida' 'Massachusetts'
SORT geog HIERARCHY geogparent D sales
REPORT SALES
--------SALES--------
--------TIME---------
GEOG 2004 2005
-------------- ---------- ----------
USA 1,300 NA
Pembroke 4,268 NA
Boston 2,644 NA
Orlando 4,398 NA
Miami 3,294 NA
Texas 2,115 NA
Houston 997 NA
Dallas 839 NA
California 1,899 NA
Los Angeles 2,394 NA
San Francisco 1,334 NA
The SMOOTH function computes a single or a double exponential smoothing of a numeric expression.
Return Value
DECIMAL
Syntax
SMOOTH(expression {SINGLE alpha|DOUBLE alpha beta m} [BASEDON dimension-list])
Parameters
The numeric expression whose values are to be smoothed.
The method to use in the exponential smoothing of the values in expression. The SINGLE method specifies single exponential smoothing and requires an alpha argument. The DOUBLE method specifies double exponential smoothing (also known as Holt's linear exponential smoothing) and requires an alpha argument, a beta argument, and an m argument.
A number in the range from 0 to 1 that smooths the difference between the observed data forecast and the last forecast. The higher the value, the more weight the most recent forecast has, so smoothing decreases as the smoothing factor increases. A smoothing factor of 0 completely smooths the forecasts and always returns the first forecast, which is the first data observation. A smoothing factor of 1 produces no smoothing at all and returns the previous data observation. (See "Results of alpha Values".)
A number in the range from 0 to 1 that smooths the difference between the previous forecast and the current forecast. As with the alpha argument, smoothing decreases as the smoothing factor increases.
A positive INTEGER between 1 and the total number of periods of data in the data series. The m argument specifies the number of periods on which to base the forecasts.
An optional list of one or more of the dimensions of expression to include in the exponential smoothing. When you do not specify the dimensions, then SMOOTH bases the smoothing on all of the dimensions of expression.
Usage Notes
The Effect of NASKIP on SMOOTH
SMOOTH is affected by the NASKIP option. When NASKIP is set to YES (the default), then SMOOTH ignores NA values. When NASKIP is set to NO, then SMOOTH returns NA for every forecast after the NA value.
Results of alpha Values
This note illustrates the results of using different alpha values for single exponential smoothing. The results are based on the sales variable with the dimensions limited by the following statements.
LIMIT month TO 'Jan96' TO 'Dec96' LIMIT product TO 'Tents' LIMIT district TO 'Boston' REPORT DOWN month SMOOTH(sales, SINGLE, ALPHA, BASEDON month)
The following table shows the data values of the sales variable and also shows the results of the SMOOTH function in the preceding statement when the alpha argument variable has the different values shown in the table.
| MONTH | Sales of tents in Boston | alpha = 0 | alpha = .1 | alpha = .5 | alpha = .9 |
|---|---|---|---|---|---|
| Jan96 | 50,808.96 | NA | NA | NA | NA |
| Feb96 | 34,641.59 | 50,808.96 | 50,808.96 | 50,808.96 | 50,808.96 |
| Mar96 | 45,742.21 | 50,808.96 | 49,192.22 | 42,725.28 | 36,258.33 |
| Apr96 | 61,436.19 | 50,808.96 | 48,847.22 | 44,233.74 | 44,793.82 |
| May96 | 86,699.67 | 50,808.96 | 50,106.12 | 52,834.97 | 59,771.95 |
| Jun96 | 95,120.83 | 50,808.96 | 53,765.47 | 69,767.32 | 84,006.90 |
| Jul96 | 93,972.49 | 50,808.96 | 57,901.01 | 82,444.07 | 94,009.44 |
| Aug96 | 94,738.05 | 50,808.96 | 61,508.16 | 88,208.28 | 93,976.18 |
| Sep96 | 75,407.66 | 50,808.96 | 64,831.15 | 91,473.17 | 94,661.86 |
| Oct96 | 70,622.91 | 50,808.96 | 65,888.80 | 83,440.41 | 77,333.08 |
| Nov96 | 46,124.99 | 50,808.96 | 66,362.21 | 77,031.66 | 71,293.93 |
| Dec96 | 36,938.27 | 50,808.96 | 64,338.49 | 61,578.33 | 48,641.88 |
Examples
Example 8-102 Smoothing Values
These statements limit the dimensions of the sales variable, set the data column width for reports, and report the data values for sales.
LIMIT month TO 'Jan96' TO 'Dec96' LIMIT product TO 'Tents' LIMIT district TO 'Boston' COLWIDTH = 14 REPORT W 6 DOWN month sales
The preceding statements produce the following output.
DISTRICT: Boston
----SALES-----
---PRODUCT----
MONTH Tents
------ --------------
Jan96 50,808.96
Feb96 34,641.59
Mar96 45,742.21
Apr96 61,436.19
...
Nov96 46,124.99
Dec96 36,938.27
This statement reports the results of using the SMOOTH function on the sales variable with the SINGLE method, a data smoothing factor of .5, and based on the month dimension.
REPORT W 6 DOWN month SMOOTH(sales, SINGLE, .5, BASEDON month)
The preceding statement produces the following output.
DISTRICT: Boston
SMOOTH(SALES,-
-SINGLE, .5,--
BASEDON MONTH)
---PRODUCT----
MONTH Tents
------ --------------
Jan96 NA
Feb96 50,808.96
Mar96 42,725.28
Apr96 44,233.74
...
Nov96 77,031.66
Dec96 61,578.33
(Read-only) The NOSPELL option holds the text that is used for FALSE Boolean values in the output of OLAP DML statements.
The value of the NOSPELL option is the word for "no" in the current language, as specified by the NLS_LANGUAGE option. For example, when NLS_LANGUAGE is set to "American," then the default value of NOSPELL is NO.
Data Type
TEXT
Syntax
NOSPELL
Examples
The EXECUTE procedure executes one or more OLAP DML commands and directs the output to a printer buffer. It is typically used to manipulate analytic workspace data within an interactive SQL session. In contrast to the RUN Procedure, EXECUTE continues to process commands after it gets an error.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON
If you are using a different program, refer to its documentation for the equivalent setting.
Input and output is limited to 4K. For larger values, refer to the INTERP and INTERPCLOB functions in this package.
This procedure does not print the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
EXECUTE (
olap_commands IN VARCHAR2
text OUT VARCHAR2);
Parameters
Table B-22 EXECUTE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semicolons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
|
|
Output from the OLAP engine in response to the OLAP commands. |
Example
The following example attaches the GLOBAL analytic workspace and shows the object definition of TIME.
EXECUTE dbms_aw.aw_attach('global'); EXECUTE dbms_aw.execute('DESCRIBE time'); DEFINE TIME DIMENSION TEXT
The next example shows how EXECUTE continues to process commands after encountering an error:
EXECUTE dbms_aw.execute('SHOW DECIMALS'); 2 EXECUTE dbms_aw.execute('CALL nothing; DECIMALS=0'); BEGIN dbms_aw.execute('CALL nothing; DECIMALS=0'); END; * ERROR at line 1: ORA-34492: Analytic workspace object NOTHING does not exist. ORA-06512: at "SYS.DBMS_AW", line 93 ORA-06512: at "SYS.DBMS_AW", line 122 ORA-06512: at line 1 EXECUTE dbms_aw.execute('SHOW DECIMALS'); 0
The next example show how EXECUTE continues to process commands after encountering an error:
SQL> execute dbms_aw.execute('call nothing; colwidth=20');
BEGIN dbms_aw.execute('call nothing; colwidth=20'); END;
*
ERROR at line 1:
ORA-34492: Analytic workspace object NOTHING does not exist.
ORA-06512: at "SYS.DBMS_AW", line 90
ORA-06512: at "SYS.DBMS_AW", line 119
ORA-06512: at line 1
SQL> execute dbms_aw.execute('show colwidth');
20
PL/SQL procedure successfully completed.
The LISTBY program produces a report of the names of all objects in an analytic workspace that are dimensioned by or related to one or more specified dimensions or composites. You can use LISTBY with a dimension or composite in any attached workspace.
Syntax
LISTBY dimensions
Parameters
A list of one or more dimensions or composites, separated by spaces. When you list multiple dimensions, all the dimensions must be in the same workspace. LISTBY returns a list of objects that are dimensioned by all the dimensions you specify. When you specify an unnamed composite, use the following format:
LISTBY SPARSE dim1 dim2 ...
Usage Notes
Composites and Conjoint Dimensions
The report produced by LISTBY includes any named or unnamed composite, or conjoint dimension, whose base dimension list includes the dimensions you specify.
The report also includes any object whose dimension list includes a named or unnamed composite that in turn has the specified dimensions as base dimensions.
Examples
Example 10-30 Using LISTBY
LISTBY is used here to list the name of every object that is dimensioned by or related to product. The statement LISTBY product produces the following output.
15 objects dimensioned by or related to PRODUCT ---------------------------------------------------------------- ADVERTISING DIVISION.PRODUCT EXPENSE INDUSTRY.SALES NAME.PRODUCT NATIONAL.SALES PRICE PRODUCT.MEMO PRODUCTSET SALES SALES.FORECAST SALES.PLAN SHARE UNITS UNITS.M
Example 10-31 Specifying More Than One Dimension
In this example LISTBY is used to list the name of every object that is dimensioned by or related to both product and market.
LISTBY product market
1 objects dimensioned by or related to PRODUCT, MARKET ---------------------------------------------------------- UNITS.M
The SET1 command assigns a single value to a variable, option, relation, or dimension surrogate. When an object has one or more dimensions, the SET1 command assigns the value to the object cell that is in current status.
Since the SET1 command does not loop through a dimensioned object, you can use it in Assign trigger programs to assign a value to an object.
Syntax
SET1 target-name = expression
Parameters
The name of the target object where the data is assigned and stored. For a list of analytic workspace objects that can be a target object, see Table 10-9, "Using Objects in Assignment Statements".
The source of the data values to be assigned to the object, see Table 10-9, "Using Objects in Assignment Statements"
Examples
For an example of using SET1, see Example 10-164, "Setting Values in an ASSIGN Trigger Program".
The ARCSIN function calculates the angle value (in radians) of a specified sine.
Return Value
NUMBER
Syntax
ARCSIN(expression)
Parameters
An expression that contains the decimal value of a sine.
Usage Notes
Invalid Sine Values
When you provide an ineligible value for the sine expression (that is, a value greater than 1 or less than -1), ARCSIN returns a value of NA.
Examples
Oracle OLAP looks for the Oracle OLAP programs with the following names and executes them as explained in the topic for each program.
An AUTOGO program is a program that you can create and that Oracle OLAP checks for by name when an AW ATTACH command executes.
When you attach an analytic workspace that contains a program named AUTOGO, unless the AW ATTACH statement includes an NOAUTOGO clause or an AUTOGO clause that specifies a program with a different name, Oracle OLAP executes the ONATTACH program.
|
Note: Oracle OLAP checks for this program and other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
BOOLEAN
TRUE when Oracle OLAP has successfully set up and attached the analytic workspace; or FALSE when it has not or when the Autogo program has thrown an exception.
|
Note: You are encouraged to use the normal return values rather than relying on exceptions to create a return value ofFALSE. |
Syntax
To define a program with the name AUTOGO use the syntax shown in DEFINE PROGRAM. Code the actual program as a user-defined function with the following argument.
AUTOGO (password)
Parameters
See AW ATTACH for explanation of password.
Examples
For examples of how attachment programs behave, see Example 9-50, "Startup Programs".
An ONATTACH program is a program that you can create and that Oracle OLAP checks for by name when an AW ATTACH command executes.
When you attach an analytic workspace that contains a program named ONATTACH, unless the AW ATTACH statement includes an NOONATTACH clause or an ONATTACH clause that specifies a program with a different name, Oracle OLAP executes the ONATTACH program.
Depending on the statements in the onattach program, the user is granted or denied access to specific objects or sets of object values. For multiwriter attachment, you can use ACQUIRE commands to provide access to individual workspace objects. For read-only and read/write attachment, you can use PERMIT commands that grant or restrict access to individual workspace objects. All of the objects referred to in a given onattach program must exist in the same analytic workspace.
|
Note: Oracle OLAP checks for this program and other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
BOOLEAN
TRUE when Oracle OLAP has successfully set up and attached the analytic workspace; or FALSE when it has not or when the onattach program has thrown an exception.
|
Note: You are encouraged to use the normal return values rather than relying on exceptions to create a return value ofFALSE. |
Syntax
To define a program with the name ONATTACH use the syntax shown in DEFINE PROGRAM. Code the actual program as a user-defined function with the following argument.
ONATTACH ({READ|WRITE|EXCLUSIVE|MULTI} password)
Parameters
See AW ATTACH for explanations of the attachment modes (that is, READ, WRITE, EXCLUSIVE, and MULTI) and password.
Usage Notes
ONATTACH Programs Created by the OLAP API
When an analytic workspace is created as an OLAP cube using the OLAP API, the OLAP API may also create a program named ONATTACH. You can not modify an ONATTACH program that is automatically created in this way. Additionally, overriding the execution of this ONATTACH is not recommended.
Consequently, when this type of ONATTACH program exists in an analytic workspace, create a different type of startup program to specify behavior that you want performed when that analytic workspace is attached.
Examples
For examples of how attachment programs behave, see Example 9-50, "Startup Programs".
An ONDETACH program is a program that you can create and that Oracle OLAP checks for by name when an AW DETACH command executes. Depending on the value returned by the program, Oracle OLAP executes the code within the program immediately after detaching the analytic workspace.
|
Note: Oracle OLAP checks for other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
BOOLEAN
TRUE when Oracle OLAP has successfully detached the analytic workspace; or FALSE when it has not or when the detach program has thrown an exception.
|
Note: You are encouraged to use the normal return values rather than relying on exceptions to create a return value ofFALSE. |
Syntax
To define a program with the name ONDETACH use the syntax shown in DEFINE PROGRAM.
A PERMIT_READ program is a program that you can create and that Oracle OLAP checks for by name when an AW ATTACH read-only command executes. Depending on the value returned by the program, Oracle OLAP executes the code within the program after attaching the analytic workspace. Depending on the statements in the permit_read program the user is granted or denied access to specific objects or sets of object values. Within permit_read program, you can specify PERMIT commands that grant or restrict access to individual workspace objects. All of the objects referred to in a given permit_read must exist in the same analytic workspace.
|
Note: Oracle OLAP checks for this program and other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
BOOLEAN
TRUE when Oracle OLAP has successfully set up and attached the analytic workspace; or FALSE when it has not or when the permit_read program has thrown an exception
|
Note: You are encouraged to use the normal return values rather than relying on exceptions to create a return value ofFALSE. |
Syntax
To define a program with the name PERMIT_READ use the syntax shown in DEFINE PROGRAM. Code the actual program as a user-defined function with the following argument.
PERMIT_READ (password)
Parameters
See AW ATTACH for an explanation of password. When a user specifies a password when attaching the analytic workspace, then the password is passed as an argument to the program for processing.
Examples
To see the order in which permission programs are executed when an analytic workspace is attached, see Example 9-50, "Startup Programs".
A PERMIT_WRITE program is a program that you can create and that Oracle OLAP checks for by name when an AW ATTACH read/write command executes. Depending on the value returned by the program, Oracle OLAP executes the code within the program after attaching the analytic workspace. Depending on the statements in the permit_write program, the user is granted or denied access to specific objects or sets of object values. Within permit_write program, you can specify PERMIT commands that grant or restrict access to individual workspace object. All of the objects referred to in a given permit_write program must exist in the same analytic workspace.
|
Note: Oracle OLAP checks for this program and other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
BOOLEAN
TRUE when Oracle OLAP has successfully set up and attached the analytic workspace; or FALSE when it has not or when the permit_write program has thrown an exception
|
Note: You are encouraged to use the normal return values rather than relying on exceptions to create a return value ofFALSE. |
Syntax
To define a program with the name PERMIT_WRITE use the syntax shown in DEFINE PROGRAM. Code the actual program as a user-defined function with the following argument.
PERMIT_WRITE (password)
Parameters
See AW ATTACH for an explanation of password. When a user specifies a password when attaching the analytic workspace, then the password is passed as an argument to the program for processing.
Examples
To see the order in which permission programs are executed when an analytic workspace is attached, see Example 9-50, "Startup Programs".
A TRIGGER_AFTER_UPDATE program is a program that you can create in an analytic workspace and that Oracle OLAP checks for by name when an UPDATE command for that analytic workspace executes. When the program exists in the same analytic workspace that you are updating, Oracle OLAP executes the program after executing the UPDATE.
|
Note: The USETRIGGERS option must be set to its default value ofTRUE for a TRIGGER_AFTER_UPDATE program to execute |
Syntax
To create a program with the name TRIGGER_AFTER_UPDATE, follow the guidelines presented in "Trigger Programs".
Examples
Example 6-1 TRIGGER_AFTER_UPDATE Program
Assume you have defined the following program in your analytic workspace.
DEFINE TRIGGER_AFTER_UPDATE PROGRAM
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
END
When you issue an UPDATE statement the program executes and displays the following output.
calltype = TRIGGER triggering event = AFTER_UPDATE triggering subevent = AW
A TRIGGER_AW program is a program that you can create in one analytic workspace and that Oracle OLAP checks for by name when that analytic workspace is current and you create, attach, detach, or delete any other analytic workspace.
|
Note: Oracle OLAP checks for this program and other programs when a user attaches an analytic workspace. See "Startup Programs" for more information. |
Return Value
None.
Syntax
To create a program with the name TRIGGER_AW, follow the guidelines presented in"How to Create a TRIGGER_AW Program".
Usage Notes
How to Create a TRIGGER_AW Program
You create a TRIGGER_AW program by following the following procedure:
Define the program as described in DEFINE PROGRAM.
Name the program TRIGGER_AW.
Code the actual program as described in"Specifying Program Contents".
|
Note: There is no support for recursive triggers. You must set the USETRIGGERS option toNO before you issue an AW statement within an TRIGGER_AW program |
Examples
Example 6-2 A TRIGGER_AW Program
Assume that you have defined a program with the following definition in an analytic workspace named my_aw.
DEFINE TRIGGER_AW PROGRAM PROGRAM SHOW CALLTYPE SHOW TRIGGER(EVENT) SHOW TRIGGER(SUBEVENT) SHOW TRIGGER(NAME) END
When attach the my_aw workspace, the specified values are displayed.
AW ATTACH MY_AW TRIGGER AW ATTACH MY_AW
A TRIGGER_BEFORE_UPDATE program is a program that you can create and that Oracle OLAP checks for by name when an UPDATE command executes. When the program exists in the same analytic workspace that you are updating, Oracle OLAP executes the program and then, depending on the value returned by the program (if any), either does nor does not update the workspace.
|
Note: The USETRIGGERS option must be set to its default value ofTRUE for a TRIGGER_BEFORE_UPDATE program to execute |
Return Value
You can write the program as a function that returns a BOOLEAN value. In this case, when the program returns FALSE, Oracle OLAP does not execute the UPDATE statement that triggered the execution of the TRIGGER_BEFORE_UPDATE program; when the program returns TRUE or NA, the UPDATE statement executes.
Syntax
To create a program with the name TRIGGER_UPDATE, follow the guidelines presented in"Trigger Programs".
Examples
Example 6-3 TRIGGER_BEFORE_UPDATE Program
Assume that an analytic workspace named myaw has an TRIGGER_BEFORE_UPDATE program with the following definition.
DEFINE TRIGGER_BEFORE_UPDATE PROGRAM BOOLEAN
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
RETURN TRUE
END
Assume that you define a TEXT variable named myvar and, then, issue an UPDATE statement. The TRIGGER_BEFORE_UPDSATE program executes.
calltype = TRIGGER triggering event = BEFORE_UPDATE triggering subevent = AW
Because the program returned TRUE, the definition for myvar exists after you detach and reattach the workspace.
AW DETACH myaw
AW ATTACH myaw
DESCRIBE
DEFINE TRIGGER_BEFORE_UPDATE PROGRAM BOOLEAN
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
RETURN TRUE
END
DEFINE MYVAR VARIABLE TEXT
However, if you modified the program so that it returned FALSE, then when you detach and reattach the workspace, not only would the myvar definition not in the workspace, the definition for the TRIGGER_BEFORE_UPDATE program would also not be in the workspace.
A TRIGGER_DEFINE program is a program that you create and that Oracle OLAP checks for by name when a DEFINE command executes. When the program exists in the same analytic workspace in which you are defining a new object, Oracle OLAP executes the program.
|
Note: The USETRIGGERS option must be set to its default value ofTRUE for a TRIGGER_DEFINE program to execute |
Syntax
To create a program with the name TRIGGER_DEFINE, follow the guidelines presented in "Trigger Programs".
Examples
Example 6-4 A TRIGGER_DEFINE Program
Assume that you have written a TRIGGER_DEFINE program with the following description in your analytic workspace.
DEFINE TRIGGER_DEFINE PROGRAM
PROGRAM
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('fully qualified object name ='TRIGGER(NAME))
SHOW JOINCHARS ('type of object = 'OBJ(TYPE TRIGGER(NAME))
DESCRIBE &TRIGGER(NAME)
END
Assume, as shown in the following statements, that you issue a DEFINE VARIABLE statement to define a variable named myvar. As shown by the output following the statement, Oracle OLAP defines the variable and executes the TRIGGER_DEFINE program.
DEFINE myvar VARIABLE TEXT calltype = TRIGGER triggering event = DEFINE fully qualified object name =MYAW!MYVAR type of object = VARIABLE DEFINE MYVAR VARIABLE TEXT
The PAGE program forces a page break in output when PAGING is set to YES. An optional argument to PAGE specifies a conditional page break based on how many lines are left on the page.
The PAGE program is commonly used in report programs. It is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and LISTNAMES.
Syntax
PAGE [n]
Parameters
A positive INTEGER expression that indicates that a page break should occur only when there are fewer than n lines left on the current page. When the number of lines left equals or exceeds n, no page break occurs. See Example 10-70, "Keeping Lines Together".
Usage Notes
Top of Page
No page break occurs when you are already at the top of a page when a PAGE statement is executed.
Producing the Header
The PAGE program signals that further output should be produced on a new page, but it does not produce a header on the new page unless there is further output. When there is further output, Oracle OLAP produces the heading that is defined by the current PAGEPRG program and then starts producing the output.
Examples
Example 10-70 Keeping Lines Together
Suppose you have 12 lines of data that would be hard to read when interrupted by a page break, so you want to prevent such an interruption. Use the PAGE 12 statement immediately before the statements that produce the 12 lines of data. A page break occurs before the 12 lines of data only when there are less than 12 lines left on the page. When there are 12 lines or more left at that point, output continues on the same page.
Example 10-71 Forcing a Page Break
The following lines from a report program force a page break at the start of each loop for district which makes the report for each district start at the top of a page. (The report program uses a heading program called report.head to create a customized heading. See the PAGEPRG option for information on customized heading programs.)
PUSH PAGING PAGEPRG
PAGING = YES
PAGEPRG = 'report.head'
FOR district
DO
PAGE
ROW district
BLANK
FOR month
ROW WIDTH 8 month sales sales.plan
DOEND
PAGE
POP PAGING PAGEPRG
The GROUPINGID command populates a previously-defined object with the grouping ids for the values of a hierarchical dimension, and creates and populates the $GID_DEPTH system property.
A grouping id is a numeric value that corresponds to a level of a hierarchical dimension. The grouping id for the lowest-level of the hierarchy is 0 (zero). Grouping ids are especially useful for identifying values of different levels of a hierarchical dimension. Dimension values in the same level of the hierarchy have the same value for their grouping id. Selecting dimension values for a specific level is easier with grouping ids because the desired values can be identified with a single condition of groupingid = n.
Typically, you use a GROUPINGID statement when you are planning on accessing analytic workspace data in SQL using the OLAP_TABLE function.
|
See also: See "Gidrel Relation" for more information and the GROUPING_ID function in Oracle Database SQL Language Reference for more information on grouping ids. |
Syntax
GROUPINGID [parent-relation] INTO destination-object -
{USING level-relation} [INHIERARCHY {inh-variable | inh-valueset}] [LEVELORDER lo-valueset] -
[ROLLUP | GROUPSET]
where destination-object is one of the following:
Parameters
A self-relation for a hierarchical dimension. This self-relation is dimensioned by a hierarchical dimension. The values of the self-relation are the parents of each value in the hierarchical dimension. The parent-relation argument is optional only when you use the GROUPINGID command to populate a surrogate and the GROUPINGID command includes a LEVELORDER clause.
The name of a previously-defined relation. One dimension of grouping-relation must be the hierarchical dimension. The values of grouping-relation are calculated and populated when the GROUPINGID command executes. When you specify a relation as the destination object, Oracle OLAP automatically creates and sets the $GID_DEPTH property on the relation when it populates it.
The name of a previously-defined numeric variable. One dimension of grouping-variable must be the hierarchical dimension. The data type of grouping-variable can be any numeric type including NUMBER. The values of grouping-variable are calculated and populated when the GROUPINGID command executes.See the DEFINE VARIABLE command for information on defining variables.
The name of a previously-defined surrogate for the hierarchical dimension. The values of grouping-surrogate are calculated and populated when the GROUPINGID command executes. See the DEFINE SURROGATE command for information on defining surrogates.
Specifies that the level of the values of the hierarchical dimension are to be considered when creating grouping ids.
A relation that is dimensioned by the hierarchical dimension. For each value of the hierarchical dimension, the relation has its value the name of the level for the dimension's value.
Specifies that only some values of the hierarchical dimension are to be considered when creating grouping ids.
|
Note: You cannot specify an INHIERARCHY clause when you specify ROLLUP or GROUPSET. |
A BOOLEAN variable that is dimensioned by the hierarchical dimension and, when the hierarchical dimension is a multi-hierarchical dimension, by a dimension that is the names of the hierarchies. The values of the variable are TRUE when the dimension value is in a hierarchy and FALSE when it is not.
The name of a valueset object whose values identify the hierarchical dimension values to be considered when creating grouping ids. Values not included in the valueset are ignored.
Specifies the top-down order of the levels when creating grouping ids.
The name of a valueset object whose values are the names of the levels to be used when creating grouping ids. The order of the values in the valueset object determine the grouping id assigned.
Specifies that Oracle OLAP creates the grouping ids in the same manner as SQL does when you specify ROLLUP in a SQL SELECT statement.
The ROLLUP keyword is valid only when the destination object is a relation. When you specify this keyword, $GID_TYPE and $GID_LIST properties.
Specifies that Oracle OLAP creates the grouping ids in the same manner as SQL does when you specify GROUPING SET in a SQL SELECT statement.
The GROUPSET keyword is valid only when the destination object is a relation. When you specify this keyword, Oracle OLAP also creates and populates two properties on the grouping id relation: the $GID_TYPE and $GID_LIST properties.
Examples
Example 9-145 Using GROUPINGID Command to Populate a Relation with Grouping Ids
Assume your analytic workspace contains the following objects.
DEFINE GEOG DIMENSION TEXT LD A dimension with two hierarchies for geography DEFINE geog_hierlist DIMENSION TEXT LD List of Hierarchies for geog dimension DEFINE GEOG_INHIER VALUESET GEOG <GEOG_HIERLIST> LD A valueset of geog that are just the values in each hierarchy DEFINE GEOG_PARENTREL RELATION GEOG <GEOG GEOG_HIERLIST> LD Self-relation for geog showing parents of each value DEFINE GEOG_INHIER VALUESET GEOG <GEOG_HIERLIST> LD A valueset of geog that are just the values in each hierarchy DEFINE GEOG_LEVELREL RELATION GEOG_LEVELLIST <GEOG GEOG_HIERLIST> LD Level of each dimension member for geog
Assume that those objects have the values shown in the following reports.
REPORT geog_hierlist
GEOG_HIERLIST
--------------
Political_Geog
Sales_Geog
REPORT DOWN geog W 20 geog_parentrel
-------------GEOG_PARENTREL--------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston MA MA
Springfield MA MA
Hartford CT CT
Mansfield CT CT
Montreal Quebec Quebec
Walla Walla WA WA
Portland WA WA
Oakland CA CA
San Diego CA CA
MA USA East
CT USA East
WA USA West
CA USA West
Quebec Canada East
East NA All Regions
West NA All Regions
All Regions NA NA
USA All Countries NA
Canada All Countries NA
All Countries NA NA
->REPORT W 20 geog_inhier
GEOG_HIERLIST GEOG_INHIER
-------------- --------------------
Political_Geog Boston
Springfield
Hartford
Mansfield
Montreal
Walla Walla
Portland
Oakland
San Diego
MA
CT
WA
CA
Quebec
USA
Canada
All Countries
Sales_Geog Boston
Springfield
Hartford
Mansfield
Montreal
Walla Walla
Portland
Oakland
San Diego
MA
CT
WA
CA
Quebec
East
West
All Regions
->REPORT DOWN geog W 20 geog_levelrel
--------------GEOG_LEVELREL--------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston City City
Springfield City City
Hartford City City
Mansfield City City
Montreal City City
Walla Walla City City
Portland City City
Oakland City City
San Diego City City
MA State-Prov State-Prov
CT State-Prov State-Prov
WA State-Prov State-Prov
CA State-Prov State-Prov
Quebec State-Prov State-Prov
East NA Region
West NA Region
All Regions NA All Regions
USA Country NA
Canada Country NA
All Countries All Countries NA
To create grouping ids for the values of geog, you first define a GID dimension with the following definition and you populate it with more values than you expect to have for grouping ids.
DEFINE GID_DIMENSION DIMENSION NUMBER (16,0)
Next you define a relation to hold the grouping ids.
DEFINE GEOG_GIDREL RELATION GID_DIMENSION <GEOG GEOG_HIERLIST>
Now you execute the GROUPINGID command to populate the geog_gidrel relation.
GROUPINGID geog_parentrel INTO geog_gidrel USING geog_levelrel -
INHIERARCHY geog_inhier
A report of geog_gidrel shows that the relation is now populated.
REPORT down geog w 20 geog_gidrel
---------------GEOG_GIDREL---------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston 0 0
Springfield 0 0
Hartford 0 0
Mansfield 0 0
Montreal 0 0
Walla Walla 0 0
Portland 0 0
Oakland 0 0
San Diego 0 0
MA 1 1
CT 1 1
WA 1 1
CA 1 1
Quebec 1 1
East NA 3
West NA 3
All Regions NA 7
USA 3 NA
Canada 3 NA
All Countries 7 NA
When you execute a FULLDSC of geog_gidrel, you can see that the $GID_DEPTH property has been created and populated for geog_gidrel.
DEFINE GEOG_GIDREL RELATION GID_DIMENSION <GEOG GEOG_HIERLIST> PROPERTY '$GID_DEPTH' 4
Example 9-146 Using GROUPINGID to Populate a Variable with Grouping Ids
Assume that you have the following objects in your analytic workspace.
DEFINE geography DIMENSION TEXT WIDTH 12 LD Geography Dimension Values DEFINE geography.parent RELATION geography <geography> LD Child-parent relation for geography DEFINE geography.hierarchyid DIMENSION INTEGER LD Dimension whose values are ids for hierarchies in geography
To create a grouping id variable for the Standard hierarchy of geography, define a child-parent relation of only those values that are in the hierarchy whose grouping ids you want to generate, and define a variable to hold the grouping ids. Examples of these definitions follow.
DEFINE geog.gid INTEGER VARIABLE <geography> DEFINE geography.newparent RELATION geography <geography>
Then populate these variables using statements similar to these.
" Populate the child-parent relation for hierarchy 1 geography.newparent = geography.parent(geography.hierarchyid 1) " Populate the grouping id variables GROUPINGID geography.newparent INTO geog.gid
Reports for the new objects created by this code (geography.newparent and geog.gid) follow.
REPORT geography.newparent GEOGRAPHY GEOGRAPHY.NEWPARENT ---------------- ---------------- World NA Americas World Canada Americas Toronto Canada Montreal Canada Ottawa Canada Vancouver Canada Edmonton Canada Calgary Canada Usa Americas Boston Usa Losangeles Usa Dallas Usa Denver Usa Newyork Usa Chicago Usa Seattle Usa Mexico Americas ... ... Japan Asia Tokyo Japan Osaka Japan Kyoto Japan China Asia Beijing China Shanghai China ... ... India Asia Ireland Europe Taiwan Asia Thailand Asia REPORT geog.gid GEOGRAPHY GEOG.GID ---------------- ---------------- World 7 Americas 3 Canada 1 Toronto 0 Montreal 0 Ottawa 0 Vancouver 0 Edmonton 0 Calgary 0 Usa 1 Boston 0 Losangeles 0 Dallas 0 Denver 0 Newyork 0 Chicago 0 Seattle 0 Mexico 1 ... ... Japan 1 Tokyo 0 Osaka 0 Kyoto 0 China 1 Beijing 0 Shanghai 0 ... ... India 1 Ireland 1 Taiwan 1 Thailand 1
The PERMITREADERROR option controls if an error is signaled on attempted read of a variable, valueset, formula, or relation for which read or write permission is denied by a PERMIT statement.
Data Type
BOOLEAN
Syntax
PERMITREADERROR = NO | YES
Parameters
(Default) When the value ofPERMITREADERROR is YES, an error condition is not created on attempted access of a a variable, valueset, formula, or relation for which read or write permission is denied with a PERMIT statement. Values for which you do not have read permission are displayed as NAs. When you try to change a value for which you do not have write permission, the request is ignored.
When PERMITERROR is YES , an error is signaled upon attempted to read a a variable, valueset, formula, or relation for which read or write permission is denied with a PERMIT statement. The error, which can be trapped, terminates the Oracle OLAP operation that initiated the illegal access.
The MODEL.DEPRPT program produces a report that lists the variables and dimension values on which each model equation depends. When a dependence is dimensional, the report gives the name of the dimension.
Syntax
MODEL.DEPRT
Examples
Example 10-64 Producing a Dependency Report
The MODEL.DEPRPT program produces a dependency report that lists the variables and dimension values that are the assignment target and data sources for each model equation. For each equation, the assignment target and each data source is listed on a separate line. When a target or data source is a dimension value, its line is marked by an asterisk enclosed in square brackets ([*]).
When a target or data source depends on a qualifier, the report specifies the dimension of the qualifier and indicates the type of dependence. The type of dependence can be any of the following:
LAG -- One-way dependence on previous dimension values
LEAD -- One-way dependence on later dimension values
BOTH -- Two-way dependence on both previous and later values
VARIABLE -- Dependence on either previous or later values, depending on the value of a variable when the model is run
QDR -- Qualified data reference
Assume that you want to produce a dependency report for the income.budget model. The following statement and report illustrate this process.
MODEL.DEPRPT income.budget
MODEL INCOME.BUDGET <LINE MONTH>
2 [*](LINE OPR.INCOME):
[*](LINE GROSS.MARGIN)
[*](LINE MARKETING)
3 [*](LINE GROSS.MARGIN):
[*](LINE REVENUE)
[*](LINE COGS)
4 [*](LINE REVENUE):
[*](LINE REVENUE)(LAG <MONTH>)
5 [*](LINE COGS):
[*](LINE COGS)(LAG <MONTH>)
6 [*](LINE MARKETING):
[*](LINE OPR.INCOME)(LAG <MONTH>)
The data sources in statements 4, 5, and 6 have a LAG dependence on the month dimension.
The EVAL_TEXT function evaluates a text expression in an analytic workspace and returns the resulting character string.
You can specify the EVAL_TEXT function in a SELECT from DUAL statement to return a character constant defined in an analytic workspace. For more information, see "Selecting from the DUAL Table" in Oracle Database SQL Language Reference.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
EVAL_TEXT (
olap_text_expression IN VARCHAR2)
RETURN VARCHAR2;
Parameters
Table B-21 EVAL_TEXT Function Parameters
| Parameter | Description |
|---|---|
|
|
An OLAP DML expression that evaluates to a character string. Refer to Chapter 2, "OLAP DML Expressions". |
Example
The following example returns the value of the NLS_LANGUAGE option, which specifies the current language of the session.
SET serveroutput ON
SELECT dbms_aw.eval_text('nls_language') "NLS Language" FROM dual;
The value of NLS_LANGUAGE in this example is AMERICAN.
NLS Language --------------- AMERICAN
The HEADING command produces titles and column headings for a report. The heading output is sent to the current outfile. The form of the HEADING command is the same as that of the ROW command. When you use HEADING, however, Oracle OLAP does not add any numeric values from the heading to column subtotals or grand totals.
Frequently, HEADING statements are used in a PAGEPRG program to produce titles or column headings on each page of a report.
|
Tip: When you know ahead of time that you do not need the subtotaling capability of the ROW command, use the HEADING command instead of ROW to produce the lines of your report can provide a time savings, since, in this case, Oracle OLAP does not keep track of subtotals. |
Syntax
HEADING [attribs] {expression1|SKIP}, [attribs] {expressionN|SKIP}
Parameters
The attributes that specify the format for each column. (See the ROW command for a list and detailed explanation of the available attributes.)
The text to be used as a column heading. To use literal text for a column heading, enclose the text in single quotes. (See the ROW command for more information on using expressions, attributes, and ACROSS groups to produce columns.)
Used instead of an expression to indicate that the column is to be left blank.
Usage Notes
The notes for the ROW command also apply to the HEADING command (except for the note on row and column arithmetic in ROW).
Creating Titles Using Heading
To create a title or subtitle in a report, use HEADING to produce a single "column" with a width equal to the setting of the LSIZE option. You can then center your text within this "column" to produce a centered title.
Maximum Heading Width
The maximum width of any line in a report, including a heading line, is 4,000 characters.
Examples
Example 10-1 Producing Column Headings
In a report, you want to have headings for your columns. You can use a HEADING statement such as the following in your program.
HEADING UNDER '-' CENTER <WIDTH 15 'Product' - ACROSS district FIRST 3: district>
This statement produces the following result.
Product Atlanta Boston Chicago
--------------- ---------- ---------- ----------
The NLS_NUMERIC_CHARACTERS option specifies the decimal marker and thousands group marker for the session. NLS_NUMERIC_CHARACTERS affects the display of numeric data and the setting of the OLAP DML THOUSANDSCHAR option, the DECIMALCHAR option, or both.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_NUMERIC_CHARACTERS = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS database parameters.
Examples
The STATVAL function returns the dimension value that corresponds to a specified position in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
The data type returned by STATVAL is either the data type of the dimension or dimension surrogate value or an INTEGER that indicates its position in the default status list of the dimension. The dimension value that STATVAL returns is converted to a number or a text value, as appropriate to the context. To ensure that STATVAL returns an INTEGER value, specify the INTEGER keyword. See Example 8-120, "Ensuring that STATVAL Returns an INTEGER".
Syntax
STATVAL(dimension position [INTEGER])
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
An INTEGER expression that specifies the position in the current status list of a dimension or a valueset. When you specify a position that has no values, STATVAL returns NA.
Specifies that STATVAL must return an INTEGER that represents the position of the dimension value in the default status list.
Usage Notes
STATVAL in a FOR Loop
In a FOR loop over a dimension, the status is limited to a single dimension value for each iteration of the loop. Therefore, STATVAL has a value only for position 1. For other positions, STATVAL returns NA.
Examples
Example 8-119 STAVAL with Qualified Data References
Suppose you want to know the sales figures for the month ranked fifth among the 10 months with the highest total sales. After limiting month to the TOP 10, use STATVAL in a qualified data reference to produce sales figures for the month ranked fifth.
LIMIT month TO TOP 10 BASEDON TOTAL(sales, month) REPORT month
These statements produce the following report.
MONTH -------------- Jul96 Jun96 Jul95 Aug96 Jun95 Sep96 May96 Aug95 Sep95 MAY95
Using STATVAL in the following REPORT statement produces a different report.
REPORT W 8 DOWN district HEADING -
JOINCHARS('Sales: 5th of Top Ten - ' STATVAL(month 5)) -
sales(month STATVAL(month 5))
This is the report produced by the preceding statement.
------------Sales: 5th of Top Ten - Jun95-------------
-----------------------PRODUCT------------------------
DISTRICT Tents Canoes Racquets Sportswear Footwear
-------- ---------- ---------- ---------- ---------- ----------
Boston 88,996.35 147,412.44 90,840.60 75,206.30 144,162.66
Atlanta 110,765.24 106,327.17 109,695.31 155,652.78 146,364.99
Chicago 70,908.96 108,039.05 100,030.29 104,900.66 148,386.81
Dallas 128,692.56 71,899.23 176,452.58 164,823.10 32,421.25
Denver 91,717.46 99,099.20 140,961.37 99,951.60 70,149.77
Seattle 113,806.48 143,037.62 54,926.87 57,739.03 75,457.04
Notice that the qualified data reference in the following statement means "sales for the fifth month in the default status of month."
sales(month 5)
While the qualified data reference in the following statement means "sales for the fifth month in the current status of month."
sales(month STATVAL(month 5))
The following statements show the different values that are returned for a qualified data reference of month and for STATVAL with month as an argument.
SHOW month(month 5) SHOW STATVAL(month 5)
The preceding statements produce the following output.
May95 Jun95
Example 8-120 Ensuring that STATVAL Returns an INTEGER
Depending on the context, STATVAL may return an INTEGER value without your specifying the INTEGER keyword.
The following statements
LIMIT month TO 'Jun95' TO 'Dec95' SHOW STATVAL(month 3)
produce this output.
Aug95
With the INTEGER keyword,
SHOW STATVAL(month 3 INTEGER)
the following output is produced.
8
When an analytic workspace is attached in multiwriter mode, the ACQUIRE command acquires and (optionally) resynchronizes the specified objects so that their changes can be updated and committed.
Syntax
ACQUIRE {acquired_noresync_objects | RESYNC [CASCADE] -
resync_objects [WAIT] } [CONSISTENT WITH [CASCADE] consistency_objects [WAIT]]
where resync_objects has the following syntax:
resynch_objname [FOR DELETE | [WITH [CASCADE]|WITHOUT] RELATIONS]] , ...
Parameters
A list of one or more variables, relations, valuesets, dimension names, separated by commas, that you want to access in read/write mode without resynchronizing.
To specify individual partitions of a partitioned variable, use the following syntax.
variable_name (PARTITION partition_name [, PARTITION partition_name ]...)
Acquiring objects in this manner preserves all read-only changes made to the objects. You can update variables and dimensions acquired in this manner using an UPDATE statement.
The name of the partition in which you want to acquire the objects.
Specifies acquisition in read/write mode of the latest generation of the specified objects with all private changes discarded.
The name of a a variable, relations, valueset, or dimension name that you want to access in read/write mode and resynchronize.
To specify individual partitions of a partitioned variable, use the following syntax.
variable_name (PARTITION partition_name [, PARTITION partition_name ]...)
When you do not specify WAIT, the ACQUIRE statement fails when another user has acquired any of the objects in resync_objects in read/write mode. When you specify WAIT, Oracle OLAP waits until all objects in resync_objects it can be acquired in read/write mode or the wait times out.
Specifies that additional objects are to be accessible in read-only mode.the behavior of the ACQUIRE statement when a specified object is already acquired by another user and resynchronizes the specified objects when the ACQUIRE statement succeeds.
A list of one or more a list of one or more variables, relations, valuesets, or dimension names, separated by commas, that you want to acquire in read-only mode.
To specify individual partitions of a partitioned variable, use the following syntax.
variable_name (PARTITION partition_name [, PARTITION partition_name ]...)
When you do not specify WAIT, the ACQUIRE statement fails when any of the objects in the consistency_objects are acquired in read/write mode by another user. When you specify the WAIT keyword, Oracle OLAP waits to execute the ACQUIRE statement until none of the objects in consistency_objects are acquired in read/write mode by another user or until the wait times out.
Usage Notes
Understanding Consistency
To some extent you can think of an ACQUIRE statement with a CONSISTENT WITH phrase as a combination of ACQUIRE and RELEASE statements.
ACQUIRE [avar...] RESYNC [rvar ...] cvar ... [WAIT] RELEASE cvar ...
The difference is that an ACQUIRE CONSISTENT WITH statement succeeds even when the user does not have sufficient permissions to acquire cvar variables.
Failure and Error-Handling
All of the clauses in the ACQUIRE statement must succeed or the statement fails. Consequently, either all of the requested objects are acquired or none of them are acquired.
Only one user can acquire an object in read/write mode at a time. You can first acquire an object in read-only mode, and then, assuming another user has not also acquired it in read-only mode, you can acquire it in read/write mode without releasing it first. However, once another user has acquired an object in read-only mode, you cannot acquire the same object in read/write mode until the other user releases the object. When a specified object has been acquired by another user or when your read-only generation for a specified object is not the latest generation for the object, the ACQUIRE statement fails.
Also, it can take a long time for the ACQUIRE statement to complete when you specify WAIT for either the RESYNC or CONSISTENT phrase. During the wait, some variables in the acquisition lists may be released while others may have been acquired. It is even possible for a deadlock to occur which causes the ACQUIRE statement to fail with a timeout error.
To avoid problems caused by deadlock, be thoughtful about the order in which you code ACQUIRE and RELEASE statements and include appropriate error handling routines.
Examples
Example 9-1 Acquiring, Updating, and Releasing Objects
A classic use of multiwriter attachment mode is to allow two users to modify two different objects in the same analytic workspace. For example, assume that an analytic workspace has two variables: actuals and budget. Assume also that one user (user A) wants to modify actuals, while another user (user B) wants to modify budget. In this case, after attaching the analytic workspace in the multiwriter mode, each user acquires the desired variable, performs the desired modification, updates, commits the changes, and then, either detaches the workspace or releases the acquired variable.
User A executes the following statements.
AW ATTACH myworkspace MULTI ACQUIRE actuals ... make modifications UPDATE MULTI actuals COMMIT RELEASE actuals AW DETACH myworkspace
While, at the same time, User B executes the following statements.
AW ATTACH myworkspace MULTI ACQUIRE budget ... make modifications UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace
Example 9-2 Acquiring and Resynchronizing Objects
Assume that two users (named B1 and B2) both have to make what-if changes to budget and possibly modify their parts of budget when they like the results of the what-if changes. Neither user knows if anyone else needs to access budget at the same time that they are or if they have to make any permanent changes to budget. Consequently, they do not want to block anyone while they are performing what-if changes.
In this case, both users perform their what-if computation after attaching the analytic workspace in the multiwriter mode but without acquiring budget. When they later decide to make their what-if changes permanent, they try to acquire budget in unresynchronized mode. When the acquire succeeds, they update budget and commit the changes. The following OLAP DML statements show this scenario.
AW ATTACH myworkspace MULTI ...perform what-if computations ACQUIRE budget ...maybe make some additional final changes UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace
However, when the first acquire does not succeed, however, the users try again to acquire budget in resynchronized mode (possibly requesting a wait). When the resynchronized acquisition succeeds, they re-create the changes (since some relevant numbers might have changed) and then proceed to update and commit their analytic workspace. The following OLAP DML statements show this scenario.
AW ATTACH myworkspace MULTI ... perform what-if computations ACQUIRE budget ...maybe make some additional final changes UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace AW ATTACH myworkspace MULTI ...perform what-if computations ACQUIRE budget --> failed ACQUIRE RESYNC budget WAIT ...determine that the changes are still needed ...make changes to make permanent UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace
Example 9-3 Acquiring Objects While Keeping Consistency
Sometimes you must keep some objects consistent with each other, which requires special care in multiwriter mode.
Assume that two users (User B1 and User B2) both have to modify budget, that budget must be kept consistent with investment, and that another user (User I) needs to modify investment. In this scenario, even though none of the users needs to modify both budget and investment, they all must ensure that when they acquire either budget or investment that no one else has either budget or investment already acquired. To achieve this effect, each user must issue an ACQUIRE statement with the CONSISTENT WITH phrase as shown in the following example code. Note that all of the users must be aware that the objects listed in the CONSISTENT phrase may be resynchronized by the ACQUIRE statement, if needed.
For example, User B1 could issue the following OLAP DML statements.
AW ATTACH myworkspace MULTI ... perform what-if computations ACQUIRE budget CONSISTENT WITH investment ... maybe make some additional final changes UPDATE MULTI budget COMMIT RELEASE budget, investment AW DETACH myworkspace
User B2 could issue the following OLAP DML statements.
AW ATTACH myworkspace MULTI ... perform what-if computations ACQUIRE budget CONSISTENT WITH investment --> failed ACQUIRE RESYNC budget CONSISTENT WITH investment WAIT ... determine that the changes are still needed ... make changes to make permanent UPDATE MULTI budget COMMIT RELEASE budget, investment AW DETACH myworkspace
User I could issue the following OLAP DML statements.
AW ATTACH myworkspace MULTI ACQUIRE investment CONSISTENT WITH budget --> failed ACQUIRE RESYNC investment CONSISTENT WITH budget WAIT ... make changes to investment UPDATE MULTI investment COMMIT RELEASE budget, investment AW DETACH myworkspace
The WRAPERRORS option determines if Oracle OLAP displays long error messages as multiple lines with each line being 72 characters in length.
Data Type
BOOLEAN
Syntax
WRAPERRORS = NO | YES
Parameters
Error messages are not wrapped. (Default)
Error message are wrapped. Oracle OLAP inserts a line break after each group of 72 characters.
Usage Notes
Change in Default Behavior as of Oracle OLAP 10.2
In pre 10.2 releases of Oracle OLAP, long error messages are always wrapped.
Within an OLAP DML program, the CALLTYPE function indicates whether a program was invoked as a function, as a command, by using a CALL statement, or triggered by the execution of an OLAP DML statement.
Return Value
TEXT
The return value of CALLTYPE is:
FUNCTION when the program was invoked as a function that returns a value.
COMMAND when the program was invoked as a a command.
CALL when the program was invoked using a CALL statement.
TRIGGER when the program is a trigger program (that is, when a TRIGGER command associated the program with an object event) was invoked in response to a OLAP DML statement.
Syntax
CALLTYPE
Examples
Example 7-35 Determining the Calling Method
This sample program, called myprog, demonstrates how CALLTYPE returns different values depending on how the program is invoked.
DEFINE myprog PROGRAM
PROGRAM
SHOW CALLTYPE
RETURN('This is the return value')
END
The following statements invoke myprog: 1) as command; 2) with a CALL statement; 3) as a function.
myprog CALL myprog SHOW myprog
The three statements send the following output to the current outfile. Note that the return value of myprog appears only when the program is called as a function.
COMMAND CALL FUNCTION This is the return value
The TOTAL function calculates the total of the values of an expression.
Return Value
The data type of the expression. It can be INTEGER, LONGINT, or DECIMAL.
Syntax
TOTAL(expression [CACHE] [dimension...])
Parameters
The expression to be totalled.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of expression and another dimension that you want as a dimension of the result.
By default, TOTAL returns a single value. When you indicate one or more dimensions for the result, TOTAL calculates values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of expression, but, instead, is dimension that is related to a dimension of expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
How TOTAL Handles NA Values
TOTAL is affected by the NASKIP option. When NASKIP is set to YES (the default), TOTAL ignores NA values and returns the sum of the values that are not NA. When NASKIP is set to NO, TOTAL returns NA when any value in the calculation is NA. When all data values for a calculation are NA, TOTAL returns NA for either setting of NASKIP.
Totaling over a DWMQY Dimension
When expression is dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other DAY, WEEK, MONTH, QUARTER, or YEAR dimension as a related dimension. Oracle OLAP uses the implicit relation between the dimensions. To control the mapping of one DAY, WEEK, MONTH, QUARTER, or YEAR dimension to another (for example, from weeks to months), you can define an explicit relation between the two dimensions and specify the name of the relation as the dimension argument to the TOTAL function.
For each time period in the related dimension, Oracle OLAP totals the data for all the source time periods that end in the target time period. This method is used regardless of which dimension has the more aggregate time periods. To control the way in which data is aggregated or allocated between the periods of two time dimensions, you can use the TCONVERT function.
Multiple Relations in a TOTAL Function
When you break out the total by a related dimension, you are changing the dimensionality of the expression, so Oracle OLAP expects values based on this new dimensionality. It chooses the relation that holds values of that dimension.
When there are multiple relations that hold values of the expected dimension, Oracle OLAP uses the one that was defined first. When there is no relation in which the related dimension is the one expected, Oracle OLAP looks for a relation that is dimensioned by the expected dimension.
For example, assume that there are two relations between district and region, as follows.
DEFINE REGION.DISTRICT RELATION REGION <DISTRICT> LD The region each district belongs to DEFINE DISTRICT.REGION RELATION DISTRICT <REGION> LD The primary district in each region
When an analytic workspace had the two relations described earlier and you specified the following TOTAL function, Oracle OLAP would use the relation region.district by default, because it holds values of the specified dimension.
REPORT TOTAL(sales region)
Examples
Example 8-150 Totaling Sales over All Months
Suppose you would like to see the total sportswear sales for all months for each district. Use the TOTAL function to calculate the total sales. To see a total for each district, specify district as the dimension of the results.
LIMIT product TO 'Sportswear' REPORT W 15 HEADING 'Total Sales' TOTAL(sales district)
The preceding statements produce the following output.
DISTRICT Total Sales -------------- --------------- Boston 1,659,609.90 Atlanta 3,628,616.62 Chicago 2,296,631.81 Dallas 3,893,829.30 Denver 2,133,425.29 Seattle 1,298,215.59
Within an OLAP DML program, the ARGS function lets you reference the arguments that are passed to a program. The function returns all the arguments as a single text value. You can use the ARGS function only within a program that is be invoked as a command, not as a user-defined function or with a CALL statement.
|
Note: Typically, programmers use an ARGUMENT statement to define arguments in a program, thereby negating the need for using the ARGS function to reference arguments passed to the program. For more information on how to use ARGUMENT to define arguments that are passed to a program, see "Declaring Arguments that Are Passed Into a Program" . |
Return Value
TEXT
When no arguments have been specified for the program, ARGS returns a null value
Syntax
ARGS
Examples
Example 7-23 Passing Arguments Using ARGS
Assume you have a program that produces a simple sales report. You want to be able to produce this report for any month, so you do not want to limit the month dimension to any fixed month in the program. You can use the ARGS function in your LIMIT command so that the months for the report can be supplied as an argument when the program is run.
When ARGS is included in the LIMIT command preceded by an ampersand (&), Oracle OLAP substitutes the values of &ARGS before the command is executed and, consequently, treats the whole argument as a phrase of the LIMIT command. The salesreport program has a LIMIT command that includes &ARGS.
DEFINE salesrpt PROGRAM PROGRAM PUSH month product district TRAP ON cleanup LIMIT month TO &ARGS LIMIT product TO 'CANOES' LIMIT district TO ALL REPORT grandtotals DOWN district sales cleanup: POP month product district END
When you execute the following statement, the LIMIT command uses the values Jan96 and Feb96 for the month dimension.
salesrpt 'Jan96' 'Feb96'
The statement produces the following output.
PRODUCT: CANOES
--------SALES--------
--------MONTH--------
DISTRICT Jan96 Feb96
----------------------------------
Boston 70,489.44 82,237.68
Atlanta 56,271.40 61,828.33
Chicago 48,661.74 54,424.94
Dallas 35,244.72 40,218.43
Denver 44,456.41 50,623.19
Seattle 67,085.12 74,834.29
---------- ---------- --
322,208.83 364,166.86
========== ========== ==
The LIMITSTRICT option is a BOOLEAN option that determines how Oracle OLAP behaves when a list of values in a LIMIT command, a LIMIT function, or a QDR contains a nonexistent value.
Syntax
LIMITSTRICT = YES | NO
Parameters
(Default) When a list of values in a LIMIT command, a LIMIT function, or a QDR contains a nonexistent value, Oracle OLAP stops executing the limit and issues an error.
When a list of values in a LIMIT command, a LIMIT function, or a QDR contains a nonexistent value, Oracle OLAP processes the limit while treating the specified value as an NA.
Examples
Example 5-44 Limiting with LIMITSTRICT Set to YES
Assume that you have two dimensions (prod and year) and one variable (sales) with the following definitions and values.
DEFINE prod DIMENSION TEXT
DEFINE year DIMENSION TEXT
DEFINE sales VARIABLE INTEGER <prod year>
PROD
--------------
Radios
TVs
YEAR
--------------
2003
2004
--------SALES--------
--------PROD---------
YEAR Radios TVs
-------------- ---------- ----------
2003 2,459 3,534
2004 3,366 3,018
When LIMITSTRICT is set to YES, then Oracle OLAP treats requests to limit by the nonexistent prod value of 'IDontExist', as a request to limit by an invalid value:
Limiting prod to just nonexistent value, results in the error message ORA-34706 and does not change the values in status for prod.
->LIMIT prod to 'Idontexist' ORA-34706: Idontexist is not a valid TESTLIMITSTRICT!PROD. ->REPORT prod PROD -------------- Radios TVs
Limiting prod to a list of values that includes the nonexistent value results in the error message ORA-34706 and does not change the values in status for prod
->LIMIT prod to 'Idontexist' 'Radios' ORA-34706: Idontexist is not a valid TESTLIMITSTRICT!PROD. ->REPORT prod PROD -------------- Radios TVs
Specifying a nonexistent prod value in a QDR for sales also results in the error message ORA-34706.
->REPORT sales (year '2004'prod 'IDontExist') ORA-34706: IDontExist is not a valid TESTLIMITSTRICT!PROD.
Example 5-45 Limiting with LIMITSTRICT Set to NO
Assume that you have the same two dimensions (prod and year) and variable (sales) described in Example 5-44, "Limiting with LIMITSTRICT Set to YES".
When LIMITSTRICT is set to NO, then Oracle OLAP treats requests to limit by the nonexistent prod value of 'IDontExist', as a request to limit by an NA value:
Limiting prod to just nonexistent value, results in the error message ORA-35654 and does not change the values in status for prod.
->LIMIT prod to 'Idontexist' ORA-35654: The status of the TESTLIMITSTRICT!PROD dimension cannot be set to null. ->REPORT prod PROD -------------- Radios TVs
Limiting prod to a list of values that includes a nonexistent value does not result in an error message. Instead, prod is limited to the existing values.
->LIMIT prod to 'Idontexist' 'Radios' ->REPORT prod PROD -------------- Radios
Specifying a nonexistent prod value in a QDR for sales does not result in an error message. Instead, a report of sales displays an NA value.
->REPORT sales (year '2004'prod 'IDontExist') ---------- NA
The EXTCOLS function extracts specified columns from each line of a multiline text value. The function returns a multiline text value that includes only the extracted columns. Columns refer to the character positions in each line of a multiline text value. The first character in each line is in column one, the second is in column two, and so on.
Return Value
TEXT or NTEXT
EXTCOLS always returns a text value that has the same number of lines as text-expression, though some lines may be empty.
Syntax
EXTCOLS(text-expression [start [numcols]])
Parameters
The TEXT or NTEXT expression from which the specified columns should be extracted. When text-expression is a multiline text value, the characters in the specified columns are extracted from each one of its lines.
An INTEGER, between 1 and 4000, that represents the column position at which to begin extracting. The column position of the first character in each line of text-expression is 1. When you specify a starting column that is to the right of the last character in a given line in text expression, the corresponding line in the return value is empty.
An INTEGER that represents the number of columns to be extracted. When you do not specify numcols, EXTCOLS extracts all the characters from the starting column to the end of each line. When you specify a length that exceeds the number of characters that follow the starting position in a given line in text expression, the corresponding line in the return value includes only existing characters. EXTCOLS does not return spaces at the end of the line to fill in the missing columns.
Examples
Example 7-84 Extracting Text Columns
In this example, four columns are extracted from each line of citylist, starting from the second column.
DEFINE citylist VARIABLE TEXT citylist = 'Boston\nHouston\nChicago'
The statement
SHOW citylist
produces the following output.
Boston Houston Chicago
The statement
SHOW EXTCOLS(citylist 2 4)
produces the following output.
osto oust hica
The PERMITERROR option controls if an error is signaled on attempted access of a variable for which read or write permission is denied by a PERMIT statement.
Data Type
BOOLEAN
Syntax
PERMITERROR = NO | YES
Parameters
When you set PERMITERROR to NO, an error condition is not created on attempted access of a variable for which read or write permission is denied with a PERMIT statement. Values for which you do not have read permission are displayed as NAs. When you try to change a value for which you do not have write permission, the request is ignored.
(Default) When PERMITERROR is YES, an error is signaled upon attempted access of a variable for which read or write permission is denied with a PERMIT statement. The error, which can be trapped, terminates the Oracle OLAP operation that initiated the illegal access.
Usage Notes
PERMITERROR With Non-Data Objects
The setting of PERMITERROR is ignored for violations of permission for non-data objects such as programs, models, and valuesets. Attempted access of variables and relations with permission, whether or not they have dimensionality, is always affected by the setting of PERMITERROR.
Maintaining Dimensions
The setting of PERMITERROR is ignored for violations of maintain and permit permission. Attempted violations of permission to maintain dimensions and to change permission are always treated as errors. Attempted violations of read or write permission for dimensions are, similarly, always treated as errors.
Obtaining Data Without Full Permission
When PERMITERROR is YES and you attempt to fetch a dimensioned variable that contains values that do not have read permission, an error condition is created when the first of those values is encountered. You can avoid creating an error condition by limiting the dimensions in advance so that only permissible values are in status, or by setting PERMITERROR to NO, before doing the report.
Examples
Example 5-90 Report Without Full Permission
In the following example, the read permission on the price variable prevents you from seeing price data for any values of product other than Tents. However, when you set PERMITERROR to NO, you can still do a report of the price variable for Dec. 1996 without creating an error condition.
PERMITERROR = no DESCRIBE price
The output of this statement is
DEFINE PRICE VARIABLE DECIMAL <MONTH PRODUCT> LD Wholesale Unit Selling Price PERMIT READ WHEN product eq 'Tents'
The statements
LIMIT month TO 'Dec96' REPORT price
produce the following output.
----PRICE----
----MONTH----
PRODUCT DEC96
---------------- -------------
Tents 165.64
Canoes NA
Racquets NA
Sportswear NA
Footwear NA
The statements
PERMITERROR = yes REPORT price
produce the following error,
ERROR: You do not have permission to read this value of PRICE
and the following output.
---PRICE---
---MONTH---
PRODUCT DEC96
--------------- -----------
Tents 165.64
The FILENEXT function makes a record available for processing by the FILEVIEW command. It returns YES when it was able to read a record and NO when it reached the end of the file.
Return Value
BOOLEAN
Syntax
FILENEXT(fileunit)
Parameters
An INTEGER value that is assigned to a file that is opened for reading in a previous call to the FILEOPEN function or by the OUTFILE command.
Usage Notes
Opening and Closing Files
Before you can get records from a file with FILENEXT, use the FILEOPEN function to open the file for reading (READ mode). When you are finished, close the file with a FILECLOSE statement.
Processing Data
After reading a record with FILENEXT, use a FILEVIEW statement to process the record. FILEVIEW processes input data and assigns the data to analytic workspace objects or local variables according to a description of each field. You can call FILEVIEW more than once for continued processing of the same record. To process another record, call FILENEXT again.
Automatic Looping
When all the records are being processed in essentially the same way, the FILEREAD command is easier to use because it loops over the records in a file automatically.
Writing Records
To write selected records to an output file, see the FILEPUT command.
Record Numbers
Use the RECNO function to get the current record number for any file that is opened for read-only access.
Reading Binary and Text Files
When you did not specify BINARY for the file when you opened it, FILENEXT reads data up to and including the next newline character. When you specified BINARY for the file when you opened it, you must use FILESET to set LSIZE to the appropriate record length before using the FILENEXT function. Then, FILENEXT reads data one record at a time.
Examples
Example 7-90 Program That Uses FILENEXT
Suppose you receive monthly sales data in a file with the following record layout.
Column Width Format Data
1 1 Text Division code
2 10 Text District name
12 10 Text Product name
30 4 Packed binary Sales in dollars
34 4 Packed binary Sales in units
You want to process records only for your division, whose code is A. The following program excerpt opens the file, reads the lines of the file, determines if the data is for division A and, if so, reads the sales data, then closes the file. The file name is given as an argument on the statement line after the program name.
VARIABLE fil.unit INTEGER
. . .
fil.unit = FILEOPEN(arg(1) READ)
LIMIT month TO &arg(2)
WHILE FILENEXT(fil.unit)
DO
FILEVIEW fil.unit WIDTH 1 rectype
IF rectype EQ 'A'
THEN FILEVIEW fil.unit COLUMN 2 WIDTH 10 district -
WIDTH 10 product -
COLUMN 30 WIDTH 4 BINARY sales -
WIDTH 4 BINARY UNITS
DOEND
FILECLOSE fil.unit
The COMMAS option controls the use of the character that separates thousands and millions in numeric output. This character is typically a comma; however, it might be different depending on your NLS_TERRITORY setting. The THOUSANDSCHAR option records the character that is currently being used for separating thousands. The COMMAS option controls whether the character appears in numeric output.
COMMAS affects all commands that produce output, including the ROW command, HEADING, REPORT, and SHOW.
|
Note: You can use the COMMA and NOCOMMA attributes of a HEADING, REPORT, or ROW command to override the COMMAS setting. |
Data Type
BOOLEAN
Syntax
COMMAS = {NO|YES}
Parameters
Numeric output does not contain a character that separates thousands, millions, and so on.
(Default) Numeric output contains a character that separates thousands, millions, and so on.
Examples
Example 5-10 Showing Numerical Data Without Commas
Suppose you want to look at the cost of goods sold, without commas in the data values. You can set COMMAS to NO before producing your report.
COMMAS = NO LIMIT line TO 'Cogs' LIMIT month TO 'Jan96' 'Feb96' REPORT DOWN division ACROSS month: DECIMAL 0 actual
These statements produce the following output.
LINE: COGS
-----ACTUAL------
------MONTH------
DIVISION Jan96 Feb96
-------------- -------- ----------
Camping 368044 385120
Sporting 287558 315299
Clothing 567767 610727
The SQLBLOCKMAX option controls the maximum number of records retrieved from an Oracle Database at one time. This option provides a means of fine-tuning the performance of data fetches.
Data Type
INTEGER
Syntax
SQLBLOCKMAX = records
Parameters
An INTEGER that identifies the number of records you want fetched at one time. While you can set SQLBLOCKMAX to any INTEGER, no appreciable change in performance results in setting it over 100. The default is 10 records.
Usage Notes
Opening Cursors
Only cursors opened after SQLBLOCKMAX is reset use the new block size.
Number of Records
When a program typically opens a cursor, reads one record, and closes the cursor, set SQLBLOCKMAX to 1. Otherwise, the SQL FETCH statement retrieves 10 records and discards 9 of them. The same is true for other routine fetches of less than 10 records.
Block Size
When your program is fetching small records, you can increase SQLBLOCKMAX to reduce the number of blocks required for the fetch. Oracle OLAP fetches the data into a 64K buffer. The block size in bytes is the number of records multiplied by the size of the records. When the block size exceeds the 64K limit imposed by the buffer, Oracle OLAP automatically reduces the number of records fetched. See Example 5-100, "Defining a Cursor with SQLBLOCKMAX".
Examples
Example 5-100 Defining a Cursor with SQLBLOCKMAX
The following program fragment defines a cursor for fetching 50-byte records from a Database. The new block size easily fits into Oracle OLAP's 64K buffer (50 bytes * 100 = 50k block size).
SQLBLOCKMAX = 100 SQL DECLARE CURSOR c1 FOR SELECT * FROM mydata SQL OPEN c1
The AGGMAP command identifies an aggmap object as a specification for aggregation and adds an aggregation specification to the definition of the current aggmap object. To use AGGMAP to assign an aggregation specification to n aggmap object, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
An alternative to the AGGMAP command is the EDIT AGGMAP statement, which is available only in OLAP Worksheet. The EDIT AGGMAP statement opens an Edit window in which you can add, delete, or change the aggregation specification for an aggmap object.
(Note that there are two other OLAP DML statements that are also sometimes referred to as "AGGMAP statements": AGGMAP ADD or REMOVE model statement that you can use to add or remove a model from an aggmap object of type AGGMAP, and AGGMAP SET that you can use to specify the default aggmap for a variable.)
Syntax
AGGMAP [specification]
Parameters
A multiline text expression that is the aggregation specification for the current aggmap object. Each statement is a line of the multiline text expression. When coding an AGGMAP command at the command line level, separate statements with newline delimiters (\n), or use JOINLINES.
An aggregation specification begins with AGGMAP and ends with an END. Between these statements, you code one or more the following statements depending on the calculation that you want to specify. Minimally, you must code one RELATION (for aggregation) statement.
|
Note: You cannot specify a conjoint dimension in the specification for the aggmap; use composites instead. |
Usage Notes
Creating Temporary or Custom Aggregates
Most aggmap objects are defined to calculate variable values that are dimensioned by permanent dimension members (that is, dimension members that persist from one session to another). However, users might want to create their own aggregates at run time for forecasting or what-if analysis, or just because they want to view the data in an unforeseen way. Adding temporary members to dimensions and aggregating data for those members is sometimes called creating temporary or custom aggregates. For example, you can use a MAINTAIN ADD SESSION statement like the one below to temporarily add a model to an aggmap object.
MAINTAIN dimension ADD SESSION member = model APPLY TO AGGMAP aggmap
Aggregating Variables Dimensioned by Compressed Composites
Keep the following points in mind when designing an aggregation specification for a variable dimensioned by a compressed composite:
RELATION statements in the aggregation specification must be coded following the guidelines given in "RELATION Statements for Compressed Composites".
There is no support for parallel aggregation. Instead, use multiple sessions to compute variables or partitions that have their own compressed composites.
If possible, Oracle OLAP automatically performs incremental aggregation when you reaggregate a variable dimensioned by the compressed composite. In other words, Oracle OLAP determines what changes have occurred since the last aggregation, determines the smallest region of the variable that needs to be recomputed, and recomputes only that region.
Consequently, there is no support for explicit incremental aggregation. You cannot aggregate a variable dimensioned by a compressed composite if the dimension status of the variable is limited. The status of the variable's dimensions must be ALLSTAT for the aggregation to succeed. You can, however, partition using a dense dimension with local compressed composites. In this way you can aggregate only those partitions that contain new data.
Aggregation Options and System Properties
Several options can impact aggregation as outlined in "Aggregation Options".
See "System Properties by Category" for a list of system properties that relate to aggregation or allocation.
Checking for Circularity
AGGREGATE automatically checks relations for circularity in and among multiple hierarchies. When you first define hierarchies, check for circularity by setting PRECOMPUTE statements to NA and AGGINDEX to NO. A XSHIERCK01 error during aggregation indicates that a circular hierarchy may have been detected. However, when the message includes a reference to UNDIRECTED, then multiple paths to an ancestor from a detail data cell have been detected. Some calculations require that a detail data cell use multiple paths to the same ancestor cell. When this is the case, then you must set the MULTIPATHHIER option to YES before you execute the AGGREGATE command. Otherwise, you must correct the error in the hierarchy structure. For more details about this error message and how to interpret it, see the MULTIPATHHIER option.
Examples
Example 9-6 Combining Pre-calculation and Calculation on the Fly
This example describes the steps you can take to pre-calculate some data in your analytic workspace and specify that the rest should be calculated when users request it.
Suppose you define an analytic workspace named mydtb that has a units variable with the following definition.
DEFINE units INTEGER <time, SPARSE <product, geography>>
You now must create and add a specification to the aggmap, which specifies the data that should be aggregated. This example shows you how to use an input file, which contains OLAP DML statements that define the aggmap and add a specification to it:
Identify the name of each dimension's hierarchy. When you have defined the hierarchies as self-relations, you use the names of the self-relations.
Decide which data to aggregate.
Suppose you want to calculate data for all levels of the time and product dimensions, but not for geography. The geography dimension's lowest level of data is at the city level. The second level of the hierarchy has three dimension values that represent regions: East, Central, and West. The third level of the hierarchy has one dimension value: Total.
Suppose that you want to pre-calculate the data for East and store it in the analytic workspace. You want the data for Central, West, and Total to be calculated only when users request that data — that data is not stored in the analytic workspace. Therefore, you must specify this information in the specification that you add to your aggmap object.
Create an ASCII text file named units.txt. Add the following OLAP DML statements to your text file.
DEFINE units.agg AGGMAP <time, SPARSE <product, geography>>
AGGMAP
RELATION myti.parent
RELATION mypr.parent
RELATION myge.parent PRECOMPUTE ('East')
END
The preceding statements define an aggmap named units.agg, then add the three RELATION statements to the aggregation specification when you read the units.txt file into your analytic workspace.
To read the units.txt file into your analytic workspace, execute the following statement.
INFILE 'inf/units.txt'
The units.agg aggmap should now exist in your analytic workspace. You can aggregate the units variable with the following statement.
AGGREGATE units USING units.agg
Now the data for East for all times and products has been calculated and stored in the analytic workspace.
Set up the analytic workspace so that when a user requests data for Central, West, or Total, that data is calculated and displayed. It is generally a good idea to compile the aggmap object before using it with the AGGREGATE function, as shown by the following statement.
COMPILE units.agg
This is not an issue when you are just using the AGGREGATE command, because this statement compiles the aggmap object before it uses it. However, when you do not use the FUNCDATA keyword with the AGGREGATE command, the metadata that is needed to perform calculation on the fly has not been compiled yet. If you have performed all other necessary calculations (such as calculating models), then it is a good practice to compile the aggmap when you load data. When you fail to do so, that means that every time a user opens the analytic workspace, that user has to wait for the aggregation to be compiled automatically. In other words, when any data is calculated on the fly, you can improve query performance for all of your users by compiling the aggmap before making the analytic workspace available to your users.
Add a property to the units variable.
CONSIDER units PROPERTY '$NATRIGGER' 'AGGREGATE(units USING units.agg)'
This property indicates that when a data cell contains an NA value, Oracle OLAP calls the AGGREGATE function to aggregate the data for that cell. Therefore, any units data that is requested by a user displayed. However, only the data for the East dimension value of the geography dimension has actually been aggregated and stored in the analytic workspace. All other data (for Central, West, and Total) is calculated only when users request it.
Example 9-7 Performing Non-additive Aggregation
This example shows how to use operators and arguments to combine additive and non-additive aggregation.
Suppose that you have defined four variables: sales, debt, interest_rate, and inventory. The variables have been defined with the same dimensionality where cp is a composite that has been defined with the product and geography dimensions.
<time cp<product geography>>
Suppose you want to use one AGGREGATE command to aggregate all four variables. The debt variable requires additive aggregation. The sales variable requires a weighted sum aggregation, and interest_rate requires a hierarchical weighted average. Therefore, both sales and interest_rate require a weight object, which you must define and populate with weight values. inventory requires a result that represents the total inventory, which is the last value in the hierarchy.
You specify the aggregation operation for debt and inventory with the OPERATOR keyword. However, because sales and interest_rate have aggregation operations that require weight objects, you must use the ARGS keyword to specify their operations. You define an operator variable to use the OPERATOR keyword. Typically, the operator variable is dimensioned by a measure dimension or a line item dimension.
Here are the steps to define the aggregation you want to occur:
Because you are also using a measure dimension to define an argument variable to use with the ARGS keyword, define that measure dimension, as illustrated by the following statements.
DEFINE measure DIMENSION TEXT MAINTAIN measure 'sales', 'debt', 'interest_rate', 'inventory'
|
Note: Whenever you use ameasure dimension in a RELATION statement, you must include a MEASUREDIM statement in the same aggregation specification |
Define an operator variable named opvar and populate it.The statements specify that the aggregation for debt should use the SUM operator, and the aggregation for inventory should use the HLAST operator.
DEFINE opvar TEXT <measure> opvar (measure 'sales') = 'WSUM' opvar (measure 'debt') = 'SUM' opvar (measure 'interest_rate') = 'HWAVERAGE' opvar (measure 'inventory') = 'HLAST'
Because sales and interest_rate require weight objects, define and populate those weight objects. The following statement defines a weight object named currency (to be used by sales).
DEFINE currency DECIMAL <time geography>
Notice that the currency variable is dimensioned only by time and geography. The purpose of this variable is to provide weights that act as currency conversion information for foreign countries; therefore, it is unnecessary to include the product dimension.
Populate currency with the weight values that you want to use.
The interest_rate variable's nonaddictive aggregation (hierarchical weighted average) requires the sum of the variable debt. In other words, interest_rate cannot be aggregated without the results of the aggregation of debt.
You can now define an argument variable, which you must specify the aggregation results of debt as a weight object for interest_rate. You use the same argument variable to specify currency as the weight object for the sales variable. The following statement defines an argument variable named argvar.
DEFINE argvar TEXT <measure>
The next few statements populate the argument variable.
argvar (measure 'sales') = 'weightby currency' argvar (measure 'debt') = NA argvar (measure 'interest_rate') = 'weightby debt' argvar (measure 'inventory') = NA
For the aggregation of product and geography, the data for the sales, debt, and interest_rate variables can simply be added. But the inventory variable requires a hierarchical weighted average. Consequently, it is necessary to define a second operator variable and a second argument variable, both of which are used in the RELATION statement for product and geography.
The following statements define the second operator variable and populate it.
DEFINE opvar2 TEXT <measure> opvar (measure 'sales') = 'Sum' opvar (measure 'debt') = 'Sum' opvar (measure 'interest_rate') = 'Sum' opvar (measure 'inventory') = 'HWAverage'
The following statements define the second argument variable and populate it.
DEFINE argvar2 TEXT <measure> argvar (measure 'sales') = NA argvar (measure 'debt') = NA argvar (measure 'interest_rate') = NA argvar (measure 'inventory') = 'weightby debt'
Now create the aggmap, by issuing the following statements.
DEFINE sales.agg AGGMAP <time, CP<product geography>> AGGMAP RELATION time.r OPERATOR opvar ARGS argvar RELATION product.r OPERATOR opvar2 ARGS argvar2 RELATION geography.r OPERATOR opvar2 ARGS argvar2 MEASUREDIM measure END
Finally, use the following statement to aggregate all four variables.
AGGREGATE sales debt interest_rate inventory USING sales.agg
Example 9-8 Programmatically Defining an Aggmap
The following program uses the EXISTS function to test whether an AGGMAP exists, and defines the AGGMAP when it does not. It then uses an AGGMAP statement to define the specification for the aggmap.
DEFINE MAKEAGGMAP PROGRAM
LD Create dynamic aggmap
PROGRAM
IF NOT EXISTS ('test.agg')
THEN DEFINE test.agg AGGMAP <geography product channel time>
ELSE CONSIDER test.agg
AGGMAP JOINLINES(-
'RELATION geography.parentrel PRECOMPUTE (geography.lvldim 2 4)' -
'RELATION product.parentrel' -
'RELATION channel.parentrel' -
'RELATION time.parentrel' -
'END')
END
Example 9-9 Creating an Aggmap Using an Input File
Suppose that you have created a disk file called salesagg.txt, which contains the following aggmap definition and specification.
DEFINE sales.agg AGGMAP <time, product, geography> AGGMAP RELATION time.r PRECOMPUTE (time NE 'Year99') RELATION product.r PRECOMPUTE (product NE 'ALL') RELATION geography.r CACHE STORE END
To include the sales.agg aggmap in your analytic workspace, execute the following statement, where inf is the alias for the directory where the file is stored.
INFILE 'inf/salesagg.txt'
The sales.agg aggmap has now been defined and contains the three RELATION statements and the CACHE statement. In this example, you are specifying that all of the data for the hierarchy for the time dimension, time.r, should be aggregated, except for any data that has a time dimension value of Year99. All of the data for the hierarchy for the product dimension, product.r, should be aggregated, except for any data that has a product dimension value of All. All geography dimension values are aggregated. The CACHE STORE statement specifies that any data that are rolled up on the fly should be calculated just once and stored in the cache for other access requests during the same session.
You can now use the sales.agg aggmap with an AGGREGATE command, such as.
AGGREGATE sales USING sales.agg
In this example, any data value that dimensioned by a Year99 value of the time dimension or an All value of the product dimension is calculated on the fly. All other data is aggregated and stored in the analytic workspace.
Example 9-10 Using Multiple Aggmaps
When you use a forecast, you must ensure that all of the input data that is required by that forecast has been pre-calculated. Otherwise, the forecast uses incorrect or nonexistent data. For example, suppose your forecast requires that all line items are aggregated. Using a budget variable that is dimensioned by time, line, and division, one approach would be to perform a complete aggregation of the line dimension, forecast the dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, and then aggregate the remaining dimension, division.
You can support this processing by defining three aggmap objects:
Define the first aggmap, named forecast.agg1, which aggregates the data needed by the forecast. It contains the following statement.
RELATION line.parentrel
Define the second aggmap, named forecast.agg2, which aggregates the data generated using the first aggmap and the forecast. It contains the following statement.
RELATION division.parentrel PRECOMPUTE ('L3')
Define the third aggmap, named forecast.agg3, which contains the RELATION statements in the specifications of the first two aggmaps.
RELATION line.parentrel
RELATION division.parentrel PRECOMPUTE ('L3')
When your forecast is in a program named fore.prg, then you would use the following statements to aggregate the data.
AGGREGATE budget USING forecast.agg1 "Aggregate over LINE CALL fore.prg "Forecast over TIME AGGREGATE budget USING forecast.agg2 "Aggregate over DIVISION "Compile the limit map for LINE and DIVISION COMPILE forecast.agg3 "Use the combined aggmap for the AGGREGATE function CONSIDER budget PROPERTY 'NATRIGGER' 'AGGREGATE(budget USING forecast.agg3)'
Example 9-11 Using an AGGINDEX Statement in an Aggregation Specification
Suppose you have two variables, sales1 and sales2, with the following definitions.
DEFINE sales1 DECIMAL <time, SPARSE<product, channel, customer>> DEFINE sales2 DECIMAL <time, SPARSE<product, channel, customer>>
You do not want to precompute and commit all of the sales data to the database, because disk space is limited and you must improve performance. Therefore, you must create an aggmap, in which you specify which data should be pre-computed and which data should be calculated on the fly.
You define the aggmap, named sales.agg, with the following statement.
DEFINE sales.agg AGGMAP <time, SPARSE<product, channel, customer>>
Next, you use an AGGMAP statement to enter the following specification for sales.agg.
RELATION time.r PRECOMPUTE (time NE 'Year99') RELATION product.r PRECOMPUTE (product NE 'All') RELATION channel.r RELATION customer.r AGGINDEX NO
This aggregation specification tells Oracle OLAP that all sales data should be rolled up committed to the Database except for any data that has a time dimension value of Year99 or a product dimension value of All—the data for those cells is calculated the first time a user accesses them. The AGGINDEX value of NO tells Oracle OLAP not to create the indexes for data that should be calculated on the fly.
Now you execute the following statement.
sales2 = AGGREGATE(sales1 USING sales.agg) ACROSS SPARSE - <product, channel, customer>
sales2 now contains all of the data in sales1, plus any data that is aggregated for Year99—this is because time is not included in a composite.
On the other hand, the data that is aggregated for the product value of All is not computed and stored in sales2. This data is not computed or stored because the product dimension is included in a composite—the indexes that are required for dimensions that are included in composites were not created because the aggregation specification contains an AGGINDEX NO statement. Since the indexes did not exist, Oracle OLAP never called the AGGREGATE function to compute the data to be calculated on the fly.
Example 9-12 Aggregating By Dimension Attributes
Assume that when your business makes a sales it keeps records of the customer's name, sex, age, and the amount of the sale. To hold this data, your analytic workspace contains a dimension named customer and three variables (named customer_sex, customer_age, and sales) that are dimensioned by customer.
REPORT W 14 <customer_sex customer_age sales> CUSTOMER CUSTOMER_SEX CUSTOMER_AGE SALES -------------- -------------- -------------- -------------- Clarke M 26 26,000.00 Smith M 47 15,000.00 Ilsa F 24 33,000.00 Rick M 33 22,000.00
You want to aggregate the detail sales data over sex and age to calculate the amount of sales you have made to males and females, and the amount of sales for different age ranges. To hold this data you need an INTEGER variable that is dimensioned by hierarchical dimensions for sex and age. You also need an aggmap object that specifies the calculations that Oracle OLAP performs to populate this variable from the data in the sales variable.
To create and populate the necessary objects, you take the following steps:
Create and populate dimensions and self-relations for hierarchical dimensions named sex and age.
DEFINE sex DIMENSION TEXT DEFINE sex.parentrel RELATION sex <sex> DEFINE age DIMENSION TEXT DEFINE age.parentrel RELATION age <age> AGE AGE.PARENTREL -------------- -------------------- 0-20 All 21-30 All 31-50 All 51-100 All No Response All All NA SEX SEX.PARENTREL -------------- -------------------- M All F All No Reponse All All NA
Create and populate relations that map the age and sex dimensions to the customer dimension.
DEFINE customer.age.rel RELATION age <customer> DEFINE customer.sex.rel RELATION sex <customer> CUSTOMER CUSTOMER.AGE.REL CUSTOMER.SEX.REL -------------- -------------------- -------------------- Clarke 21-30 M Smith 31-50 M Ilsa 21-30 F Rick 31-50 M
Create a variable named sales_by_sex_age to hold the aggregated data. Like the sales variable this variable is of type DECIMAL, but it is dimensioned by sex and age rather than by customer.
DEFINE sales_by_sex_age VARIABLE DECIMAL <sex age>
Define an AGGMAP type aggmap object named ssa_aggmap to calculate the values of the sales_by_sex_age variable.
DEFINE SSA_AGGMAP AGGMAP AGGMAP RELATION sex.parentrel OPERATOR SUM RELATION age.parentrel OPERATOR SUM BREAKOUT DIMENSION customer - BY customer.sex.rel, customer.age.rel OPERATOR SUM END
Notice that the specification for the ssa_aggmap includes the following statements:
A BREAKOUT DIMENSION statement that specifies how to map the customer dimension of the sales variable to the lowest-level values of the sales_by_sex_age variable. This statement specifies the name of the dimension of the variable that contains the detail values (that is, customer) and the names of the relations (customer.sex.rel and customer.age.rel) that define the relations between customer dimension and the sex and age dimensions.
Two RELATION statements that specify how to aggregate up the sex and age dimensions of the sales_by_sex_age variable. Each of these statements includes the name of the child-parent relation (sex.parentrel or age.parentrel) that define the self-relation for the hierarchal dimension (sex or age).
Populate the sales_by_sex_age variable by issuing an AGGREGATE command that specifies that the detail data for the aggregation comes from the sales variable.
AGGREGATE sales_by_sex_age USING ssa_aggmap FROM sales
After performing the aggregation, a report of sales_by_sex_age shows the calculated values.
---------------------SALES_BY_SEX_AGE----------------------
----------------------------SEX----------------------------
AGE M F No Reponse All
-------------- -------------- -------------- -------------- --------------
0-20 NA NA NA NA
21-30 26,000.00 33,000.00 NA 59,000.00
31-50 37,000.00 NA NA 37,000.00
51-100 NA NA NA NA
No Response NA NA NA NA
All 63,000.00 33,000.00 NA 96,000.00
Example 9-13 Using a CACHE Statement in an Aggregation Specification
Suppose you have a sales variable with the following definition.
DEFINE sales DECIMAL <time, SPARSE<product, channel, customer>>
You do not want to pre-compute and commit all of the sales data, because space is limited and you must improve performance. Therefore, you must create an aggmap, in which you specify which data should be pre-computed and which data should be calculated on the fly.
You define the aggmap, named sales.agg, with the following statement.
DEFINE sales.agg AGGMAP <time, SPARSE<product, channel, - customer>>
Next, you use the AGGMAP statement to enter the following aggregation specification forsales.agg.
AGGMAP RELATION time.r PRECOMPUTE (time NE 'YEAR99') RELATION product.r PRECOMPUTE (product NE 'ALL') RELATION channel.r RELATION customer.r CACHE SESSION END
This aggregation specification tells Oracle OLAP that all sales data should be rolled up and committed, except for any cells that have a time dimension value of Year99 or a product dimension value of ALL; the data for those cells is calculated the first time a user accesses them. Because the CACHE statement uses the SESSION keyword, that means that when those cells are calculated on the fly, the data is stored in the cache for the remainder of the Oracle OLAP session. That way, the next time a user accesses the same cell, the data does not have to be calculated again. Instead, the data is retrieved from the session cache.
Example 9-14 Populating All Levels of a Hierarchy Except the Detail Level
Assume that your analytic workspace contains the relations and dimensions with the following definitions.
DEFINE geog.d TEXT DIMENSION DEFINE geog.r RELATION geog.d <geog.d> DEFINE sales_by_units INTEGER VARIABLE <geog.d> DEFINE sales_by_revenue DECIMAL VARIABLE <geog.d> DEFINE price_per_unit DECIMAL VARIABLE <geog.d>
Assume that you create two aggmap objects. One aggmap object, named units_aggmap, is the specification to aggregate data in the sales_by_units variable. The other aggmap object, revenue_aggmap, is the specification to calculate all of the data except the detail data in the sales_by_revenue variable.
DEFINE units_aggmap AGGMAP AGGMAP RELATION geog.r OPERATOR SUM END DEFINE revenue_aggmap AGGMAP AGGMAP RELATION geog.r OPERATOR WSUM ARGS WEIGHTBY price_per_unit CACHE NOLEAF END
The following steps outline the aggregation process:
Before either the sales_by_unit or sales_by_revenue variables are aggregated, they have the following values.
GEOG.D SALES_BY_UNIT SALES_BY_REVENUE --------- ------------- ---------------- Boston 1 NA Medford 2 NA San Diego 3 NA Sunnydale 4 NA MA NA NA CA NA NA USA NA NA
After the data for the sales_by_unit variable is aggregated, the sales_by_unit and sales_by_revenue variables have the following values.
AGGREGATE sales_by_unit USING units_aggmap GEOG.D SALES_BY_UNIT SALES_BY_REVENUE --------- ------------- ---------------- Boston 1 NA Medford 2 NA San Diego 3 NA Sunnydale 4 NA MA 3 NA CA 7 NA USA 10 NA
After the data for the sales_by_revue variable is aggregated, the sales_by_unit and sales_by_revenue variables have the following values.
AGGREGATE sales_by_revenue USING revenue_aggmap FROM units_aggmap GEOG.D SALES_BY_UNIT SALES_BY_REVENUE --------- ------------- ---------------- Boston 1 NA Medford 2 NA San Diego 3 NA Sunnydale 4 NA MA 3 13.5 CA 7 31.5 USA 10 45.0
Example 9-15 Aggregating into a Different Variable
Assume that there is a variable named sales that is dimensioned by time, a hierarchical dimension, and district, a non-hierarchical dimension.
DEFINE time DIMENSION TEXT
DEFINE time.parentrel RELATION time <time>
DEFINE district DIMENSION TEXT
DEFINE sales VARIABLE DECIMAL <time district>
-----------------------SALES-----------------------
---------------------DISTRICT----------------------
TIME North South West East
------------ ------------ ------------ ------------ ------------
1976Q1 168,776.81 362,367.87 219,667.47 149,815.65
1976Q2 330,062.49 293,392.29 237,128.26 167,808.03
1976Q3 304,953.04 354,240.51 170,892.80 298,737.70
1976Q4 252,757.33 206,189.01 139,954.56 175,063.51
1976 NA NA NA NA
Assume also that you want to calculate the total sales for each quarter and year for all districts except the North district. To perform this calculation using an aggmap object, you take the following steps:
Create a valueset named not_north that represents the values of district for which you want to aggregate data.
DEFINE not_north VALUESET district LIMIT not_north TO ALL LIMIT not_north REMOVE 'North'
Define a variable named total_sales_exclud_north to hold the results of the calculation.
DEFINE total_sales_exclud_north VARIABLE DECIMAL <time>
Notice that, like sales, the total_sales_exclud_north variable is dimensioned by time. However, unlike sales, the total_sales_exclud_north variable is not dimensioned by district since it holds detail data for each district, but only the total (aggregated) values for the South, West, and East districts (that is, all districts except North).
Define an aggmap object that specifies the calculation that you want performed.
DEFINE agg_sales_exclud_north AGGMAP AGGMAP RELATION time.parentrel OPERATOR SUM DROP DIMENSION district OPERATOR SUM VALUES not_north END
Notice that the aggregation specification consists of two statements that specify how to perform the aggregation:
A RELATION statement that specifies how to aggregate up the hierarchical time dimension
A DROP DIMENSION statement that specifies how to aggregate across the non-hierarchical district dimension. In this case, the DROP DIMENSION also uses the not_north valueset to specify that values for the North district are excluded when performing the aggregation
Aggregate the data.
AGGREGATE total_sales_exclud_north USING agg_sales_exclud_north FROM sales
The report of the total_sales_exclud_north variable shows the aggregated values.
TIME ALL_SALES_EXCEPT_NORTH ------------ ------------------------------ 1976Q1 731,850.99 1976Q2 698,328.58 1976Q3 823,871.02 1976Q4 521,207.09 1976 2,775,257.69
Example 9-16 Using a MEASUREDIM Statement in an Aggregation Specification
Suppose you have defined a measure dimension named measure. You then define an operation variable named myopvar, which is dimensioned by measure. When you use myopvar in an aggregation specification, you must also include a MEASUREDIM statement that identifies measure as the dimension is included in the definition of myopvar.
The MEASUREDIM statement should follow the last RELATION statement in the aggregation specification, as shown in the following example.
DEFINE sales.agg AGGMAP <time, product, geography> AGGMAP RELATION time.r OPERATOR myopvar RELATION product.r RELATION geography.r MEASUREDIM measure END
Example 9-17 Solving a Model in an Aggregation
This example uses the budget variable.
DEFINE budget VARIABLE DECIMAL <line time> LD Budgeted $ Financial
The time dimension has two hierarchies (Standard and YTD) and a parent relation named time.parentrel as follows.
-----TIME.PARENTREL------
----TIME.HIERARCHIES-----
TIME Standard YTD
-------------- ------------ ------------
Last.YTD NA NA
Current.YTD NA NA
Jan01 Q1.01 Last.YTD
...
Dec01 Q4.01 Last.YTD
Jan02 Q1.02 Current.YTD
Feb02 Q1.02 Current.YTD
Mar02 Q1.02 Current.YTD
Apr02 Q2.02 Current.YTD
May02 Q2.02 Current.YTD
Q1.01 2001 NA
...
Q4.01 2001 NA
Q1.02 2002 NA
Q2.02 2002 NA
2001 NA NA
2002 NA NA
The relationships among line items are defined in the following model.
DEFINE income.budget MODEL MODEL DIMENSION line time opr.income = gross.margin - marketing gross.margin = revenue - cogs revenue = LAG(revenue, 12, time) * 1.02 cogs = LAG(cogs, 1, time) * 1.01 marketing = LAG(opr.income, 1, time) * 0.20 END
The following aggregation specification pre-aggregates all of the data. Notice that all of the data must be pre-aggregated because the model includes both LAG functions and a simultaneous equation.
DEFINE budget.aggmap1 AGGMAP AGGMAP MODEL income.budget RELATION time.parentrel END
Example 9-18 Aggregating Up a Hierarchy
Suppose you define a sales variable with the following statement.
DEFINE sales VARIABLE <time, SPARSE <product, geography>>
The aggregation specification for sales might include RELATION statements like the following.
AGGMAP
RELATION time.r PRECOMPUTE ('Yr98', 'Yr99')
RELATION product.r
RELATION geography.r PRECOMPUTE (geography NE 'Atlanta')
END
The AGGREGATE command aggregates values for Yr98 and Yr99, over all of products, and over all geographic areas except for Atlanta. All other aggregates are calculated on the fly.
Example 9-19 Using Valuesets
Suppose you have a hierarchy dimension named time.type, whose dimension values are Fiscal and Calendar, in that order. These hierarchies are in conflict, and you want to precompute some time data but calculate the rest on the fly. Because the Calendar hierarchy is the last dimension value in the hierarchy dimension, consequently, you must define a valueset to get the correct results for the Fiscal hierarchy.
First, use the following statements to define and populate a valueset.
DEFINE time.vs VALUESET time LIMIT time.vs TO 'Calendar' 'Fiscal'
You can then use the valueset in the following RELATION statement. Because the Fiscal hierarchy is the last hierarchy in the valueset, the data that is aggregated is accurate for the Fiscal hierarchy.
RELATION time.r(time.vs) PRECOMPUTE ('Yr99', 'Yr00')
Example 9-20 Aggregating with a RELATION Statement That Uses an ARGS Keyword
You can list the arguments in a RELATION statement directly in the statement or as the value of a text variable. For example, the following statement specifies WEIGHTBY wobj as an argument.
RELATION time.r OPERATOR wsum ARGS WEIGHTBY wobj
Alternatively, you can define an variable for the argument whose value is the text of the WEIGHTBY clause.
DEFINE argvar TEXT argvar = 'WEIGHTBY wobj'
Then the RELATION statement can specify the text variable that contains the WEIGHTBY clause.
RELATION time.r OPERATOR WSUM ARGS argvar
Example 9-21 Aggregating Using a Measure Dimension
Suppose you want to use a single AGGREGATE command to aggregate the sales, units, price, and inventory variables. When you want to use the same operator for each variable, then you do not have to use a measure dimension. However, when you want to specify different aggregation operations, then you must use a measure dimension.
The following statement defines a dimension named measure.
DEFINE measure DIMENSION TEXT
You can then use a MAINTAIN statement to add dimension values to the measure dimension.
MAINTAIN measure ADD 'sales', 'units', 'quota', 'inventory'
Use the measure dimension to dimension a text variable named meas.opvar that you use as the operator variable.
DEFINE meas.opvar TEXT WIDTH 2 <measure>
The following statements add values to OPVAR
meas.opvar (measure 'sales') = 'SU' meas.opvar (measure 'units') = 'SU' meas.opvar (measure 'price') = 'HA' meas.opvar (measure 'inventory') = 'HL'
The aggregation specification might look like the following. Note that when you specify an operator variable in a RELATION statement, you must include a MEASUREDIM statement that specifies the name of the measure dimension (measure in the following example) in the aggregation specification.
DEFINE opvar.aggmap AGGMAP AGGMAP RELATION geography.parentrel PRECOMPUTE (geography.lvldim 2 4) RELATION product.parentrel OPERATOR opvar RELATION channel.parentrel OPERATOR opvar RELATION time.parentrel OPERATOR opvar MEASUREDIM measure END
Example 9-22 Aggregating Using a Line Item Dimension
Suppose you have two variables, actual and budget, that have these dimensions.
<time line division>
You want to use different methods to calculate different line items. You create a text variable that you use as the operator variable.
DEFINE line.opvar TEXT WIDTH 2 <line>
You then populate line.opvar with the appropriate operator for each line item, for example.
line.opvar (line 'Net.Income') = 'SU' line.opvar (line 'Tax.Rate') = 'AV'
The aggregation specification might look like this.
DEFINE LINE.AGGMAP AGGMAP AGGMAP RELATION time.parentrel OPERATOR line.opvar RELATION division.parentrel END
Example 9-23 Skip-Level Aggregation
Suppose you want to aggregate sales data. The sales variable is dimensioned by geography, product, channel, and time.
First, consider the hierarchy for each dimension. How many levels does each hierarchy have? What levels of data do users typically query? When you are designing a new workspace, what levels of data do your users plan to query?
Suppose you learn the information described in the following table about how users tend to query sales data for the time hierarchy.
| Time Level Names | Descriptive Level Name | Examples of Dimension Values | Do users query this level often? |
|---|---|---|---|
| L1 | Year | Year99, Year00 | yes |
| L2 | Quarter | Q3.99, Q3.99, Q1.00 | yes |
| L3 | Month | Jan99, Dec00 | yes |
While the next table shows how your users tend to query sales data for the geography hierarchy.
| Geography Level Names | Descriptive Level Name | Examples of Dimension Values | Do users query this level often? |
|---|---|---|---|
| L1 | World | World | yes |
| L2 | Continent | Europe, Americas | no |
| L3 | Country | Hungary, Spain | yes |
| L4 | City | Budapest, Madrid | yes |
Finally, the next table shows how your users tend to query sales data for the product dimension hierarchy.
| Product Level Names | Descriptive Level Name | Examples of Dimension Values | Do users query this level often? |
|---|---|---|---|
| L1 | All Products | Totalprod | yes |
| L2 | Division | Audiodiv, Videodiv | yes |
| L3 | Category | TV, VCR | yes |
| L4 | Product | Tuner, CDplayer | yes |
Using this information about how users query data, use the following strategy for aggregation:
Fully aggregate time and product because all levels are queried frequently.
For the geography dimension, aggregate data for L1 (World) and L3 (Country) because they are queried frequently. However, L2 is queried less often and so can be calculated on the fly.
The lowest level of data was loaded into the analytic workspace. The aggregate data is calculated from this source data.
Therefore, the aggregation specification might look like the following.
RELATION time.parentrel RELATION geography.parentrel PRECOMPUTE (geog.leveldim 'L3' 'L1') RELATION product.parentrel
Example 9-24 Aggregation Specification with RELATION Statements That Include PRECOMPUTE Clauses
This aggregation specification uses PRECOMPUTE clauses in the RELATION statements to limit the data that is aggregated by the AGGREGATE command.
DEFINE gpct.aggmap AGGMAP LD Aggmap for sales, units, quota, costs AGGMAP RELATION geography.parentrel PRECOMPUTE (geography.levelrel 'L3') RELATION product.parentrel PRECOMPUTE (LIMIT(product complement 'TotalProd')) RELATION channel.parentrel RELATION time.parentrel PRECOMPUTE (time NE '2001') END
Within an aggregation specification, an AGGINDEX statement tells Oracle OLAP whether the compilation of that aggmap should create indexes (meaning, composite tuples) for data cells that are calculated on the fly by the AGGREGATE function. Therefore, the AGGINDEX statement has an effect on a dimension that is included in a composite but it has no effect on a dimension that is not included in a composite.
These indexes are used by the MODEL statement in an AGGMAP and by statements that use the ACROSS phrase to help Oracle OLAP loop over variables that are dimensioned by composites. These statements expect all data to be calculated. When you specify calculating some data on the fly, that data appears to be missing. When you set AGGINDEX to YES, then the statements try to access the missing data whether or not you are using the AGGREGATE function to perform calculation on the fly (meaning, you have added to the variable whose data is being aggregated an NA trigger property that calls the AGGREGATE function).
When the indexes have been created and you use AGGREGATION with the AGGREGATE function, then when MODEL (or a statement that uses the ACROSS phrase) requests the missing data, that data is calculated on the fly. That means that the results of the MODEL (or other statement) are correct, because the statement has all of the data that it needs.
When these indexes have not been created, the missing data cannot be calculated. Consequently, the statements that need the indexes interpret the missing data as NA data, even when you use the AGGREGATE function.
Syntax
AGGINDEX {YES|NO}
Parameters
(Default) Tells the AGGMAP compiler to ensure that all possible indexes are created whenever an aggmap is recompiled. In other words, indexes are created both for the data that is being pre-calculated and the data that is calculated on the fly. Data is recalculates on the fly happens when a COMPILE statement compiles the aggmap and when the AGGREGATE command executes an aggmap whose specification has changed since the last time it was compiled. The creation of all possible indexes results in a longer compilation time but faster execution of the AGGREGATE function. For a discussion of when AGGINDEX should be set to YES, see "When To Use an AGGINDEX Value of YES".
Does not create the indexes for data that is calculated on the fly. Omitting the creation of these index values accelerates the compilation time, but causes Oracle OLAP to treat the uncomputed data as NA data whenever the MODEL statement in an AGGMAP or an ACROSS phrase is executed. For a discussion of when AGGINDEX should be set to NO, see "When To Use an AGGINDEX Value of NO".
Usage Notes
When To Use an AGGINDEX Value of YES
The primary advantage to using an AGGINDEX value of YES is that then Oracle OLAP always try to access data that you have specified to be calculated on the fly. When you have created an $NATRIGGER property for a variable that calls the AGGREGATE function, the variable appears to have been fully precomputed. That means that when any NA value is encountered, the NA trigger is called during the execution of an ACROSS phrase or the MODEL statement in an AGGMAP. When the NA trigger is called, the AGGREGATE function is executed, and the data is calculated on the fly.
When AGGINDEX has a value of NO, then the NA trigger is called only to aggregate data for dimensions that are not included in a composite. Data for dimensions that are included in composites is interpreted as NA values.
For example, suppose you have two variables called sales1 and sales2, which are defined with the following definitions.
DEFINE sales1 DECIMAL <time, SPARSE <product, geography>> DEFINE sales2 DECIMAL <time, SPARSE <product, geography>>
Now suppose you have an aggmap object named sales.agg, which has the following definition.
DEFINE sales.agg AGGMAP <time, SPARSE <product, geography>>
When you add a specification to the sales.agg aggmap, you enter RELATION statements for time, geography with PRECOMPUTE clauses that specify NA which specifies that no data is aggregated—instead, all of the data for any variable that uses this aggmap is calculated on the fly.
RELATION time.r PRECOMPUTE (NA) RELATION product.r PRECOMPUTE (NA) RELATION geography.r PRECOMPUTE (NA)
Now attach the following $NATRIGGER property to the sales1 variable.
CONSIDER sales1 PROPERTY '$NATRIGGER' 'AGGREGATE(sales1 USING sales.agg)'
Consider the effect of AGGINDEX in the following statement. Because you did not enter an AGGINDEX statement in the sales.agg aggregation specification, the default of AGGINDEX YES is assumed.
sales2 = sales1 ACROSS SPARSE <product, geography>
This statement loops over the data in sales1 and copies the values into sales2. This statement causes the NA trigger to call the AGGREGATE function for all of the data that you have specified to be calculated on the fly in sales1. Consequently, after the aggregation that sales2 contains a copy of sales1 plus all the aggregate data cells (the cells that would have been calculated if the sales1 data had been completely precomputed, meaning, fully rolled up).
However, when you put an AGGINDEX NO statement in the sales.agg aggregation specification, then sales2 contains a copy of the data in sales1 and the aggregate data cells for the time dimension.
Note that in both cases, $NATRIGGER is called to aggregate time data, because the time dimension is not included in the composite, so the value of AGGINDEX has no effect on it.
When To Use an AGGINDEX Value of NO
You can use an AGGINDEX value of NO when you know that either of the following is true:
Your application does not contain an ACROSS phrase or a MODEL statement in an AGGMAP command.
The results of your MODEL statements or ACROSS phrases are additive, and data that needs to be aggregated can be calculated safely on the fly.
Each of the preceding cases ensures that the data that you have specified to be calculated on the fly is available at the appropriate time.
By setting AGGINDEX to NO, the size of the indexes is reduced, and overall application performance improves.
When Using an AGGINDEX Value Of NO Causes Problems
When you run a MODEL that assumes all data that should be aggregated has been aggregated, then you may get NA data where real data should occur. For instance, suppose you have a variable that has a composite that includes the time dimension. You perform a calculation that subtracts the fourth quarter from the total for the year. When the value of Year is to be calculated dynamically, and the AGGINDEX statement is set to NO, then the result of the calculation is NA. When the value of Year was precomputed or when AGGINDEX is set to YES, then the MODEL correctly calculates a result equal to the sum of the first three quarters.
Index Creation Is Based on Existing Data
Only the indexes that are needed to aggregate existing data are created when AGGINDEX has a value of YES. For example, suppose one dimension in your composite is a dimension named time. The lowest-level data for the time dimension is at the monthly level. Therefore, the dimension values that are associated with the lowest-level data are Jan99, Feb99, and so on. The monthly data aggregates to quarters and to years. Suppose you have data for the first six months of the year. When AGGINDEX has a value of YES, indexes are created for the Q1, Q2, and Yr99 dimension values, but not for Q3 and Q4.
Reducing Compilation Time When AGGINDEX is YES
One disadvantage of using the default of AGGINDEX YES is that the compilation of the aggmap takes a longer time to complete. You can eliminate the cost of this extra time by using the FUNCDATA keyword with the AGGREGATE command. When you use the FUNCDATA keyword, all possible indexes (regardless of how you have limited your data) are created. However, do not use the FUNCDATA keyword when you use a different aggmap to execute the AGGREGATE command and the AGGREGATE function.
Examples
For an example of using an AGGINDEX statement, see Example 9-11, "Using an AGGINDEX Statement in an Aggregation Specification".
Within an aggregation specification, a BREAKOUT DIMENSION statement specifies how a dimension of the target variable maps to one or more dimensions of the source variable. You use this statement in an aggregation specification when you are aggregating the detail data from one variable (the source variable) into another variable (the target variable) that has a different dimension (that is, a "breakout" dimension) than the variable that contains the detail data.
Syntax
BREAKOUT DIMENSION dimname BY relation [, relation...] -
OPERATOR operation [ARGS argument]
where:
relation has the following syntax:
relationname [IGNORE ignore_dim_value [DEFAULT default_dim_value]]
argument specifies the settings of various options and is one or more of the following phrases:
Parameters
The name of a dimension in the variable that contains the detail data (that is, the source variable).
The name of a relation whose values relate a dimension of the target variable to dimname.
Specifies that if the target dimension is QDRd to the value specified by ignore_dim-value then AGGREGATE does not use the relation specified by relationname to limit the source dimension.
Specifies that if all relations have an IGNORE phrase, then AGGREGATE uses the value specified by default_dim-value value to create a QDR rather than using a relation. If all relations have an IGNORE phrase and you do not include a DEFAULT phrase, the AGGREGATE arbitrarily chooses a relationship to limit by.
when dimname is QDRd to the dimension value specified by ignore_dim-value then AGGREGATE does not use the relation specified by relationname to limit the source dimension
Identifies the calculation method used to aggregate the data.
A keyword that describes the type of aggregation to perform. The keywords are listed in Table 9-1, "Aggregation Methods".
Indicates optional handling of the aggregation.
Specifies whether to allow division by zero.
YES allows division by zero; a statement involving division by zero executes without error but produces NA results.
NO disallows division by zero; a statement involving division by zero stops executing and produces an error message.
The default value is the current value of the DIVIDEBYZERO option.
Specifies whether to allow decimal overflow, which occurs when the result of a calculation is very large and can no longer be represented by the exponent portion of the numeric representation. Specify YES to allow overflow, which means that a calculation that generates overflow executes without error and produces NA results. Specify NO to disallow overflow, which means that; a calculation involving overflow stops executing and generates an error message. The default value is the current value of the DECIMALOVERFLOW option.
Specifies whether NA values are input. Specify YES when you want Oracle OLAP to ignore NA values when aggregating which means that only actual values are used in calculations. Specify NO when you want Oracle OLAP to consider NA values are considered which means that when any of the values being considered are NA, the calculation returns NA.The default value is the current value of the NASKIP option.
The value that you specify for the NASKIP phrase does not effect calculation performed when you specify HAVERAGE, HFIRST, HLAST, HWAVERAGE, HWFIRST, HWLAST for operation.
Indicates that weighted aggregation is to be performed. You must include a WEIGHTBY clause when you specify HWAVERAGE, HWFIRST, HWLAST, SSUM, WAVERAGE, WFIRST, WLAST, or WSUM for operation. The WEIGHTBY phrase always includes a wobj argument and can optionally include the WNAFILL keyword. For more information about the use of the WEIGHTBY phrase, see RELATION (for aggregation) statement of the AGGMAP command.
Indicates handling for NA values. The default values for WNAFILL vary depending on the value of operation.
Substitutes a number for every NA value. That number replaces every NA value in the weight object, weight formula, or weight relation. The default for HWAVERAGE and SSUM is The default for HWFIRST, HWLAST, WAVERAGE, WFIRST, WLAST, and WSUM is 1.0 .
Specifies that NA values are to be specified as NA. NA is the default for OR.
For more information about using the WNAFILL phrase, see RELATION (for aggregation) statement of the AGGMAP command.
A variable, formula, or relation that provides the weighted values. It can be numeric or BOOLEAN. When wobj is BOOLEAN, then TRUE has a weight of 1.0 and FALSE has a weight of 0.0. A formula is queried only when needed, depending on the dimensionality of the formula and the variable being aggregated. When wobj is a relation, it should be a one-dimensional self-relation. For more information about specifying values for wobj, see RELATION (for aggregation) statement of the AGGMAP command.
Examples
For an example of using the BREAKOUT DIMENSION statement, see Example 9-12, "Aggregating By Dimension Attributes".
Within an aggregation specification, a CACHE statement tells Oracle OLAP whether to cache or store the calculated data, whether to populate leaf or detail data when the variable data is aggregated using detail data from another variable, and whether to cache NA values when a summary values calculates to NA.
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Note: The CACHE statement is only one factor that determines whether variable data that has been aggregated on-the-fly using the AGGREGATE function is stored or cached. See "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data". |
Syntax
CACHE {NOSTORE|NONE|STORE|SESSION|DEFAULT} [LEAF|NOLEAF] [NA|NONA]
Parameters
For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP calculates the data each time the AGGREGATE function executes. When you specify either of these keywords, Oracle OLAP does not store or cache the data calculated by the AGGREGATE function.
For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP stores data calculated by the AGGREGATE function in the variable in the Database. When you specify this option, the results of the aggregation are permanently stored in the variable when the analytic workspace is updated and committed.
For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP caches data calculated by the AGGREGATE function in the session cache (see "What is an Oracle OLAP Session Cache?"). When you specify this option, the results of the aggregation are ignored during updates and commits and are discarded after the session.
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Note: When SESSCACHE is set toNO, Oracle OLAP does not cache the data even when you specify SESSION. In this case, specifying SESSION is the same as specifying NONE. |
(Default) For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP uses the value of the VARCACHE option to determine what to do with data that is calculated by the AGGREGATE function. See "How Oracle OLAP Determines Whether to Store or Cache Aggregated Data".
When the variable data is aggregated using detail data from another variable, specifies that Oracle OLAP calculates the leaf data for the variable.
(Default) When the variable data is aggregated using detail data from another variable, specifies that Oracle OLAP does not calculate the leaf data for the variable.
For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP places any NA values that are the results of the execution of the AGGREGATE function in the Oracle OLAP session cache. In this case, when there is a variable has an $NATRIGGER property with an AGGREGATE function as its expression, Oracle OLAP does not recalculate the values for the variable. (For more information on the caching NA values, see "How Oracle OLAP Determines Whether to Store or Cache Results of $NATRIGGER".)
For data that is calculated using the AGGREGATE function, specifies that Oracle OLAP does not cache any NA values that are the results of the execution of the AGGREGATE function. In this case, when a variable has an $NATRIGGER property with an AGGREGATE function as its expression, Oracle OLAP recalculates the values for the variable.
Usage Notes
When to Use NOSTORE
Use NOSTORE when you know that your users are likely to modify pre-computed data, and you want any data that calculated by the AGGREGATE function to consistent with any of those users' changes.
In other words, suppose a user makes a change to detail-level data, such as sales figures for three stores, which are in a geography dimension. The geography dimension rolls up data from stores to cities to states to regions to countries. In other words, there are five levels in the geography dimension's hierarchy. Now suppose that users tend to access data only at the store level (your detail data), the regions level, and the countries level. Those are the levels for which you roll up sales data and commit it to the Database. Because users do not access data at the city and state level, you specify that the data cells in those two levels are calculated on the fly. When users modify the store-level data and then access city data, the city data are calculated every time that a user requests it. Therefore, any changes that a user makes to the store-level details accurately rollup to the city and state level every time that user accesses a data cell in the city or state level. (However, this is not true of the data in the region and country levels, because those cells store pre-computed data.)
When to Use STORE or SESSION
The advantage to using STORE or SESSION is that it improves query performance. For example, suppose your users use a Table tool to look at a variable's data and an individual user requests the same data cells several times in the same session. When you use the default of NOSTORE, then any data that is not aggregated using the AGGREGATE command has to be calculated every time the user requests that data even if you do not use the FORECALC keyword in the AGGREGATE function. On the other hand, when you use STORE or SESSION, then any given cell of data is calculated only once because it is available in either the variable or the cache for the entire session. Therefore, the next time a user requests that data cell, the data is returned from the variable or the cache instead of being calculated on the fly, which results in faster query time for the user.
Frequently you do not want the data that is calculated using the AGGREGATE function to be stored permanently in the Database since that would defeat the purpose of calculating data on the fly.
To ensure that the aggregated values cannot be permanently committed to the Database, use SESSION.
Use STORE when you know either of the following is true which also ensures that the data that is calculated on the fly using the AGGREGATE function is not committed to the Database:
The users of the analytic workspace can only open it as read-only
You know that the users of the analytic workspace will not or cannot issue UPDATE and COMMIT statements.
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Note: Use STORE with caution when it is likely that your users modify pre-computed data, and they access data that you have specified to be calculated on the fly using the AGGREGATE function. The problem is that any data that is calculated using the AGGREGATE function before the user's modification does not reflect the user's change unless the user made the change using an AGGREGATE function with the FORCECALC keyword or unless there is an $AGGREGATE_FORCECALC property on the variable being aggregated |
Examples
For examples of using a CACHE statement in an aggregation specification, see Example 9-13, "Using a CACHE Statement in an Aggregation Specification" and Example 9-14, "Populating All Levels of a Hierarchy Except the Detail Level".
Within an aggregation specification, a DIMENSION statement sets the status to a single value of a dimension. When an aggregation specification does not specify such single values with DIMENSION statements, Oracle OLAP uses the current status values of the dimensions when performing the aggregation.
You use a DIMENSION statement to ensure that the status of a dimension is set to the value that you want it to have for the aggregation. You must use a separate DIMENSION statement for each dimension that is not shared by the source, basis, and target objects.
Syntax
DIMENSION dimension 'dimval '
Parameters
the name of the dimension to limit.
A TEXT expression that is the single value of the dimension to which you want the status of the dimension set for the duration of an aggregation.
Within an aggregation specification, a DROP DIMENSION statement specifies how non-hierarchical aggregation across variables is performed. You use this statement in aggregation specification when you are aggregating the detail data from one variable (the source variable) into another variable (the target variable) and you want to aggregate across a non-hierarchical dimension of the source variable. In this case, the target variable has one less dimension (the "dropped" dimension) than the source variable because the values of the source variable associated with this dimension are aggregated to populate the target variable.
Syntax
DROP DIMENSION dimname [VALUES {valsetname|ALL} OPERATOR operation [ARGS argument]
where argument is one or more of the following phrases:
DIVIDEBYZERO {YES|NO}
DECIMALOVERFLOW {YES|NO}
NASKIP {YES|NO}
WEIGHTBY [WNAFILL {number|NA}] wobj
Parameters
The name of a dimension in the source variable that contains the detail data.
Sets the status of dimname during the aggregation.
The name of a valueset object that determines the status of the dimension specified by dimname.
Specifies that all of the values of dimname are in status.
Identifies the calculation method used to aggregate the data.
A keyword that describes the type of aggregation to perform. The keywords are listed in Table 9-1, "Aggregation Methods".
Indicates optional handling of the aggregation.
Specifies whether to allow division by zero. Specify YES to allow division by zero which means that a statement involving division by zero executes without error but produces NA results. Specify NO to disallow division by zero which means that a statement involving division by zero stops executing and produces an error message. The default value is the current value of the DIVIDEBYZERO option.
Specifies whether to allow decimal overflow, which occurs when the result of a calculation is very large and can no longer be represented by the exponent portion of the numeric representation. Specify YES to allow overflow, which means that a calculation that generates overflow executes without error and produces NA results. Specify NO to disallow overflow which means that a calculation involving overflow stops executing and generates an error message. The default value is the current value of the DECIMALOVERFLOW option.
Specifies whether NA values are input. Specify YES when you want Oracle OLAP to ignore NA values when aggregating which means that only actual values are used in calculations. Specify NO when you want Oracle OLAP to consider NA values when aggregating which means that when any of the values being considered are NA, the calculation returns NA. The default value is the current value of the NASKIP option.
The value that you specify for the NASKIP phrase does not effect calculation performed when you specify HAVERAGE, HFIRST, HLAST, HWAVERAGE, HWFIRST, HWLAST for operation.
Indicates that weighted aggregation is to be performed. You must include a WEIGHTBY clause when you specify HWAVERAGE, HWFIRST, HWLAST, SSUM, WAVERAGE, WFIRST, WLAST, or WSUM for operation. The WEIGHTBY phrase always includes a wobj argument and can optionally include the WNAFILL keyword. For more information about the use of the WEIGHTBY phrase, see the RELATION (for aggregation) statement of the AGGMAP command.
Indicates handling for NA values. The default values for WNAFILL vary depending on the value of operation. For more information about using the WNAFILL phrase, see the RELATION (for aggregation) statement of the AGGMAP command.
Substitutes a number for every NA value. That number replaces every NA value in the weight object, weight formula, or weight relation.
0.0 is the default for HWAVERAGE and SSUM.
1.0 is the default for HWFIRST, HWLAST, WAVERAGE, WFIRST, WLAST, and WSUM.
Specifies that NA values are to be specified as NA. NA is the default for OR.
A variable, formula, or relation that provides the weighted values. It can be numeric or BOOLEAN. When wobj is BOOLEAN, then TRUE has a weight of 1.0 and FALSE has a weight of 0.0. A formula is queried only when needed, depending on the dimensionality of the formula and the variable being aggregated. When wobj is a relation, it should be a one-dimensional self-relation. For more information about specifying values for wobj, see the RELATION (for aggregation) statement of the AGGMAP command.
Examples
For an example of using a DROP DIMENSION statement in an aggregation specification, see Example 9-15, "Aggregating into a Different Variable".
Within an aggregation specification, a MEASUREDIM statement identifies the name of a measure dimension that is specified in the definition of an operator variable or an argument variable.
Syntax
MEASUREDIM name
Parameters
The name of the measure dimension. A measure dimension is a dimension that you define. The dimension values are names of existing variables.
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Note: You cannot specify a measure dimension when it is included in the definition of the aggmap object. |
Usage Notes
Defining a Measure Dimension
The following statement defines a dimension named MEASURE.
DEFINE measure DIMENSION TEXT
Populating a Measure Dimension
Once you have defined a measure dimension, you can then use a MAINTAIN statement to add dimension values to the MEASURE dimension.
The following statement adds the names of the sales, units, price, and inventory variables to measure as its dimension values.
MAINTAIN measure ADD 'sales', 'units', 'price', 'inventory'
Using a Measure Dimension with an Operator Variable
The purpose of using measure dimensions is to take advantage of the flexibility of using non-additive aggregation operators. You can use measure dimensions in the definition of operation variables or argument variables.
The following statements show how to define an operator variable named opvar and populate it.
DEFINE opvar TEXT <measure> opvar (measure 'sales') = 'SUM' opvar (measure 'inventory') = 'HLAST'
Examples
For an example of an aggregation specification that includes a MEASUREDIM statement, see Example 9-16, "Using a MEASUREDIM Statement in an Aggregation Specification".
Within an aggregation specification, a MODEL statement executes a predefined model.
Syntax
MODEL modelname [PRECOMPUTE ALL | PRECOMPUTE NA]
Parameters
A text expression that contains the name of a predefined MODEL object.
Specifies whether the model is a static (precomputed) model or a dynamic model.
PRECOMPUTE ALL is the default and specifies a static model. The following conditions must be met:
Any RELATION or MODEL statements that precede it in the aggregation specification must also be specified as PRECOMPUTE ALL.
Any RELATION or MODEL statements that follow it in the aggregation specification can either be specified as PRECOMPUTE ALL or PRECOMPUTE NA.
PRECOMPUTE NA specifies a dynamic model. The following conditions must be met for run-time execution of the model:
All RELATION statements in the aggregation specification must appear before the MODEL statements specified as PRECOMPUTE NA.
Any additional MODEL statements that follow it in the aggregation specification must also be specified as PRECOMPUTE NA.
Usage Notes
Dynamic Models and Non-Additive Operators
Model statements are executed in the order that they are coded within the aggregation specification. Typically, when the order of execution matters to the result, MODEL statements follow the corresponding RELATION statement.
Since the order of RELATION statements that use non-additive operators (for example, MAX) effects the result of the calculation and since dynamic models (that is, MODEL statements that include a PRECOMPUTE NA phrase) must follow all RELATION statements, the use of dynamic models with non-additive operators is somewhat constrained.
Examples
For an example of using a model in an aggregation specification, see Example 9-17, "Solving a Model in an Aggregation".
Within an aggregation specification, a PRECOMPUTE statement specifies which of the variable's aggregate values are calculated only with the AGGREGATE command.
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Note: An aggregation specification that has a PRECOMPUTE statement cannot have any PRECOMPUTE clauses in its RELATION statements. |
Syntax
PRECOMPUTE precompute-phrase
where precompute-phrase is one of the following:
Parameters
Specifies an explicit percentage of the aggregate variable values that are aggregated as a database maintenance procedure using an AGGREGATE command. Oracle OLAP uses special functionality called the Aggregate Advisor to determine exactly which values are in the percentage.
Specifies that Oracle OLAP uses the Aggregate Advisor to determine how many and which aggregate variable values to aggregate as a database maintenance procedure using an AGGREGATE command.
Specifies that all aggregated data is precomputed using an AGGREGATE command.
Specifies that all values should be calculated on the fly using the AGGREGATE function (that is, that no data should be precalculated with the AGGREGATE command).
Within an aggregation specification, a RELATION statement specifies how data is aggregated across a hierarchical dimension. Frequently, an aggregation specification contains one RELATION statement for each of the hierarchical dimensions of a variable.
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Note: Do not confuse this RELATION statement which can only be used as part of an AGGMAP command with either the RELATION command that defines a default relation for a dimension or the RELATION statement that is used as part of an ALLOCMAP command. |
Syntax
RELATION rel-name [(valueset...)] -
[PRECOMPUTE (precompute-phrase)] -
[OPERATOR {operation|opvar}] -
[PARENTALIAS dimension-alias-name] -
[ARGS {argument|argsvar}] -
[LOAD_STATUS(status-valueset-name)]
where:
precompute-phrase is one or more of the following:
argument is one or more of the following:
argsvar is a text variable that contains argument phrases for some or all dimension values.
Parameters
A relation that defines a hierarchy by identifying the parent of every dimension value in a hierarchy.
Sets the status of one or more dimensions for the duration of the aggregation. It overrides the current status.
Indicates that some dimension values are populated only with the AGGREGATE command. The PRECOMPUTE clause of the RELATION statement limits the data that is aggregated by the AGGREGATE command. In its simplest form, you can think of the PRECOMPUTE clause as working like a LIMIT dimension TO statement. Notice that the default limit is on the dimension, which is not explicitly named in the RELATION statement.
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Note: An aggregation specification has PRECOMPUTE clauses in any of its RELATION statements cannot also have a PRECOMPUTE statement. Additionally, you cannot specify a PRECOMPUTE phrase for a RELATION statement for a compressed composite. |
Specifies an explicit percentage of the aggregate variable values that are aggregated as a database maintenance procedure using an AGGREGATE command. Oracle OLAP uses special functionality called the Aggregate Advisor to determine exactly which values are in the percentage.
Specifies that Oracle OLAP uses the Aggregate Advisor to determine how many and which aggregate variable values to aggregate as a database maintenance procedure using an AGGREGATE command.
A list of one or more values of dimension.
For all dimensions except those with INTEGER or NUMBER values, the positions of the dimension values that you want precomputed. Specify the positions using INTEGER values, separated by commas.
The name of a valueset. When you include this argument, only data that is dimensioned by the dimension values in the valueset should be precalculated with the AGGREGATE command. The rest of the values can be calculated on the fly.
Note that the current status of a dimension can also limit the data that is precalculated. See the AGGREGATE command for details.
Specifies that data should be precalculated for all dimension values.
Specifies that all values should be calculated on the fly using the AGGREGATE function (that is, that no data should be precalculated with the AGGREGATE command).
Specifies the levels of the dimension to be precomputed. For level-relation-name, specify, as a TEXT value, the name of the relation object that relates the values of the dimension to the names of the levels of the dimension. For level-name, specify, as TEXT values, the name of one or more levels using the same level names used in level-relation-name.
Identifies the calculation method used to aggregate the data.
A keyword that describes the type of calculation to perform. The keywords are listed in Table 9-1, "Aggregation Methods" and can be retrieved by issuing a AGGROPS statement. You can specify a fixed-length three-character abbreviation for the keywords by specifying only the first three characters.
Table 9-1 Aggregation Methods
| Keyword | Description |
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AND |
When any child data value is |
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AVERAGE |
Adds data values, then divides the sum by the number of data values that were added. When you use AVERAGE, there are special considerations described in "Average Operators". |
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FIRST |
The first non- |
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HAVERAGE |
(Hierarchical Average) Adds data values, then divides the sum by the number of the children in the dimension hierarchy. Unlike AVERAGE, which counts only non- This keyword is not affected by the setting of the NASKIP option for argument. |
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HFIRST |
(Hierarchical First) The first data value that is specified by the hierarchy, even when that value is This keyword is not affected by the setting of the NASKIP option for argument. |
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HLAST |
(Hierarchical Last) The last data value that is specified by the hierarchy, even when that value is This keyword is not affected by the setting of the NASKIP option for argument. |
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HWAVERAGE |
(Hierarchical Weighted Average) Multiplies non- When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. This keyword is not affected by the setting of the NASKIP option for argument. |
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HWFIRST |
(Hierarchical Weighted First) The first data value that is specified by the hierarchy multiplied by its corresponding weight value, even when that value is When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. This keyword is not affected by the setting of the NASKIP option for argument. |
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HWLAST |
(Hierarchical Weighted Last) The last data value that is specified by the hierarchy multiplied by its corresponding weight value, even when that value is When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. This keyword is not affected by the setting of the NASKIP option for argument. |
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LAST |
The last non- |
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MAX |
The largest data value among the children of any parent data value. |
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MIN |
The smallest data value among the children of any parent data value. |
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NOAGG |
Do not aggregate any data for this dimension. |
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OR |
When any child data value is |
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SSUM |
(Scaled Sum) Adds the value of a weight object to each data value, then adds the data values. When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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SUM |
(Default) Adds data values. |
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WAVERAGE |
(Weighted Average) Multiplies each data value by a weight factor, adds the data values, and then divides that result by the sum of the weight factors. When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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WFIRST |
(Weighted First) The first non- When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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WLAST |
(Weighted Last) The last non- When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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WMAX |
(Weighted Maximum) The largest data value among the children of any parent data value multiplied by its corresponding weight value. When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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WMIN |
(Weighted Minimum) The smallest data value among the children of any parent data value multiplied by its corresponding weight value. When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
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WSUM |
(Weighted Sum) Multiplies each data value by a weight factor, then adds the data values. When you use this keyword, you must include the WEIGHTBY argument keyword with a variable, formula, or relation as the weight object. |
A TEXT variable that you define that specifies a different the operation for each of its dimension values.
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Note: Not valid for variables dimensioned by compressed composites. |
The opvar argument is used in two ways:
Measure dimension -- Changes the aggregation method depending upon the variable being aggregated. Changing the aggregation method based on the variable being aggregated is useful when a single aggmap is used to aggregate several variables that must be aggregated with different methods. Whether you pre-aggregate all of the measures in a single AGGREGATE command or in separate statements, AGGREGATE uses the operation variable to identify the calculation method. The values of the measure dimension are the names of the variables to be aggregated. It dimensions a text variable whose values identify the operation to be used to aggregate each measure. The aggregation specification must include a MEASUREDIM statement that identifies the measure dimension. See Example 9-21, "Aggregating Using a Measure Dimension".
Line item dimension -- Changes the aggregation method depending upon the line item being aggregated. The line item dimension is typically non-hierarchical and identifies financial allocations. The line item dimension is used both to dimension the data variable and to dimension a text variable that identifies the operation to be used to aggregate each item. The operation variable is typically used to aggregate line items over time. You do not use the MEASUREDIM statement in the aggmap. See Example 9-22, "Aggregating Using a Line Item Dimension".
The opvar argument cannot be dimensioned by the dimension it is used to aggregate. For example, when you want to specify different operations for the geography dimension, then opvar cannot be dimensioned by geography.
To minimize the amount of paging for the operator variable, define the operation variable as type of TEXT with a fixed width of 8.
Specifies that an alias dimension for the dimension being aggregated is QDRd to the parent value currently being aggregated.
The name of the alias dimension for the dimension of rel-name.
Indicates optional handling of the aggregation.
Specifies whether to allow division by zero.
YES allows division by zero; a statement involving division by zero executes without error but produces NA results.
NO disallows division by zero; a statement involving division by zero stops executing and produces an error message.
The default value is the current value of the DIVIDEBYZERO option.
Specifies whether to allow decimal overflow, which occurs when the result of a calculation is very large and can no longer be represented by the exponent portion of the numeric representation.
YES allows overflow; a calculation that generates overflow executes without error and produces NA results.
NO disallows overflow; a calculation involving overflow stops executing and generates an error message.
The default value is the current value of the DECIMALOVERFLOW option.
Specifies whether NA values are input.
YES specifies that NA values are ignored when aggregating. Only actual values are used in calculations.
NO specifies that NA values are considered when aggregating. When any of the values being considered are NA, the calculation returns NA.
The default value is the current value of the NASKIP option.
The value that you specify for the NASKIP phrase does not effect calculation performed when you specify HAVERAGE, HFIRST, HLAST, HWAVERAGE, HWFIRST, HWLAST for operation.
Indicates that weighted aggregation is to be performed. You must include a WEIGHTBY clause when you specify HWAVERAGE, HWFIRST, HWLAST, SSUM, WAVERAGE, WFIRST, WLAST, or WSUM for operation. The WEIGHTBY phrase always includes a wobj argument and, optionally, can include the WNAFILL keyword.
Indicates handling for NA values. The default values for WNAFILL vary depending on the value of operation. The default value for HWAVERAGE and SSUM is 0.0. The default value for OR is NA. The default value for the other operators is 1.0. WNAFILL defaults for each operator in an aggregation specification. In other words, when one RELATION statement includes a WSUM OPERATOR, then WNAFILL defaults to 1.0. When the next RELATION statement includes an SSUM OPERATOR, then WNAFILL defaults to 0.0, and so on. See "Using WNAFILL".
A variable, formula, or relation that provides the weighted values. It can be numeric or BOOLEAN. When wobj is BOOLEAN, then TRUE has a weight of 1.0 and FALSE has a weight of 0.0. A formula is queried only when needed, depending on the dimensionality of the formula and the variable being aggregated. When wobj is a relation, it should be a one-dimensional self-relation. See Using Weighted Aggregation Methods for more information about specifying values for wobj.
YES specifies that when Oracle OLAP aggregates a variable using this relation that it also populates the Aggcount variable associated with that variable. For more information on Aggcount variables, see "Aggcount Variables".
NO specifies that when Oracle OLAP aggregates a variable using this relation that it does not populate the Aggcount variable associated with that variable. For more information on Aggcount variables, see "Aggcount Variables".
A TEXT variable that contains the argument options for some or all dimension values.
Specifies that, for the aggregation, Oracle OLAP consider the values specified by status-valueset-name as the detail or lowest level of the hierarchy.
A previously-defined valueset that specifies the lowest-level values to have in status when performing the aggregation. When performing any aggregation using an aggmap with a RELATION statement with this clause, Oracle OLAP temporarily sets the status of the dimension to the values specified by status-valueset-name and their ancestors. The valueset specified by status-valueset-name must be a single dimensional valueset for the relation dimension (not the hierarchy dimension). Additionally, the valueset specified by status-valueset-name cannot contain both a value and an ancestor of that value.
Usage Notes
Ordering RELATION Statements with Non-Additive Operators
The order of RELATION statements that use non-additive operators effects the result of the calculation. For example the max of sum is not generally equal to the sum of max. Consequently, the order of RELATION statements within an aggregation specification must follow the logical requirements of the calculation. This logical necessity limits the use of dynamic models within an aggregation as discussed in "Dynamic Models and Non-Additive Operators".
RELATION Statements for Compressed Composites
When designing the aggregation specification, follow these guidelines when coding RELATION statements for compressed composites:
The HAVERAGE, HWAVERAGE, HWFIRST, HWLAST, SSUM, WAVERAGE, WFIRST, WLAST, WMAX, WMIN, and WSUM operators cause data values to change with each level of aggregation, regardless of sparsity. When possible, to insure the largest amount of overall compression, place RELATION statements with these operatorw?s at the beginning of your aggregation specification before RELATION statements that use an AND, AVERAGE, FIRST, HFIRST, HLAST, LAST, MAX, MIN, NOAGG, OR, or SUM operator.
When an AGGMAP contains a RELATION statement that specifies the AVERAGE operator, any variable using that aggregation specification must be defined using a DEFINE VARIABLE statement with a WITH AGGCOUNT phrase.
You can only specify a single aggregation operation. You cannot specify aggregation operations using an opvar variable.
Two Ways to use Valuesets
You can use valuesets to:
Limit hierarchy dimensions. You can limit which hierarchies are used by the AGGREGATE command and AGGREGATE function and the order in which these hierarchies should be used. The valueset that you use specifies the names of a dimension's hierarchies. To use a valueset in this way, use the following syntax.
RELATION rel-name (valueset)
In this case, using valuesets provides a way to manage hierarchies that are in conflict with each other, meaning, when the same dimension value stores data for different children in different hierarchies (such as, Q1 stores data for Jan, Feb, and Mar in the Calendar hierarchy, but Q1 stores data for May, Jun, and Jul in the Fiscal hierarchy).
Specify which values should be calculated on the fly by the AGGREGATE function and which values should be pre-calculated by the AGGREGATE command. The valueset that you use specifies the names of dimension values. To use a valueset in this way, use the following syntax.
RELATION rel-name PRECOMPUTE (valueset)
In this case, you use the valueset that follows the PRECOMPUTE keyword.
When you use valuesets to limit hierarchy dimensions and when using multiple aggmaps and the hierarchies are inconsistent, you must also use the FORCECALC keyword in the AGGREGATE function or have set an $AGGREGATE_FORCECALC property on the variable to be aggregated.
When You Change a PRECOMPUTE or an OPERATOR Clause
Any time you make changes to a PRECOMPUTE or an OPERATOR clause, aggregate the variable data again and recompile the aggmap to produce accurate data.
Aggregating Data Loaded into Different Hierarchy Levels
When data is loaded into dimension values that are at different levels of a hierarchy, then you must be careful in how you set status in the PRECOMPUTE clause in a RELATION statement in your aggregation specification.
Suppose that a time dimension has a hierarchy with three levels: months aggregate into quarters, and quarters aggregate into years. Some data is loaded into month dimension values, while other data is loaded into quarter dimension values. For example, Q1 is the parent of January, February, and March. Data for March is loaded into the March dimension value. But the sum of data for January and February is loaded directly into the Q1 dimension value. In fact, the January and February dimension values contain NA values instead of data. Your goal is to add the data in March to the data in Q1.
When you attempt to aggregate January, February, and March into Q1, the data in March simply replaces the data in Q1. When this happens, Q1 contains only the March data instead of the sum of January, February, and March.
To aggregate data that is loaded into different levels of a hierarchy, create a valueset for only those dimension values that contain data.
DEFINE all_but_q4 VALUESET time LIMIT all_but_q4 TO ALL LIMIT all_but_q4 REMOVE 'Q4'
Within the aggregation specification, use that valueset to specify that the detail-level data should be added to the data that exists in its parent, Q1, as shown in the following statement.
RELATION time.r PRECOMPUTE (all_but_q4)
Average Operators
There are several issues involved in using the AVERAGE, HAVERAGE, WAVERAGE, and HWAVERAGE operators:
Oracle OLAP needs a separate INTEGER variable in which it stores the non-NA counts of the number of leaf nodes that contributed to aggregate values to calculate average values. When you want to aggregate a variable using one the average operators, include the WITH AGGCOUNT phrase in the DEFINE VARIABLE statement for the variable.
Accuracy when averaging—All decimal data is converted to floating point format, both for storing and for calculations, consequently, in some cases, an average aggregation computed on a DECIMAL or SHORTDECIMAL variable can differ in the least significant digits from a result you compute by hand. For this reason, you might want to use the NUMBER data type when accuracy is more important than computational speed, such as variables that contain currency amounts. See "Numeric Expressions" for more information.
Using Average operators when aggregating using an AGGREGATE command—When you use an average operator with the PRECOMPUTE keyword, the best practice is to use variables that have a decimal or NUMBER data type to ensure the accuracy of the results.
Using Average operators for partial aggregations—When you use an average operator in a partial aggregation, then you must always aggregate using the same INTEGER variable (that is, Aggcount or Countvar variable). Do not change the values that are stored in this INTEGER variable between aggregations. Finally, the number of INTEGER variables must match the number of variables that are being aggregated.
HAVERAGE, HFIRST, HLAST, AND HWAVERAGE Operators
The "hierarchical" operators (HAVERAGE, HFIRST, HLAST, AND HWAVERAGE) are intended to provide an alternative form of NA handling.
FIRST, HFIRST, LAST, AND HLAST Operators
These operators rely on the existing order of the dimension values, which are assumed to be the default logical order of that dimension. For example, in a month dimension, it is assumed that February follows January, March follows February, and so on.
When you must change the default order, use the MAINTAIN statement to do so. For example, suppose Q1 includes January, February, and March, but you must make February the last month in the Q1 instead of March. Use the following statement to do so.
MAINTAIN time MOVE 'Feb01' AFTER 'Mar01'
Now, the LAST operator assumes that FEB01 is the last month in Q1.
Read Permissions and Aggmaps
When you change the read permission to rel-name in a RELATION statement, then you must recompile the aggmap before using it with the AGGREGATE function. Compilation is not an issue when you use the AGGREGATE command, because the aggmap is recompiled automatically. However, when you do not have read access to every rel-name in the aggmap, then attempting to use that aggmap results in an error message.
Using Weighted Aggregation Methods
When you use a weighted method of aggregation, you must define and populate an object that contains the weights. You identify the aggregation method in the OPERATOR clause and the weight object in the ARGS clause.
The weight object can be a variable, a formula, or a relation. Special considerations apply depending on the type of object. the data type of the weight object, and whether or not you are performing a partial aggregation.
Weight Object Considerations Based on Type of Object The following considerations apply depending on the type of object that you use for the weight object:
When the weight object is a variable, you can define it with a numeric or BOOLEAN data type. Use a variable as your weight object when you want to pre-calculate weight values and commit them to the Database. You can use a variable weight object with any weight option.
When the weight object is a relation, define it as a one-dimensional self-relation. You can use the weight object to specify that the weight for a specific cell is contained in the current variable at a different location. Use a relation as your weight object when you use a line item or a measure dimension. In this case, one line item is used as the weight to calculate the aggregate value of another line item. Using a relation enables you to specify another set of cells in the variable being aggregated as the weight values for a weighted operation.
When the weight object is a formula, that formula is queried only as often as needed, depending on the dimensionality of the formula and the dimensionality of the variable whose data is being aggregated. You can define the formula with a numeric or BOOLEAN data type. Use a formula as your weight object when you want to calculate weight values on the fly. A formula weight object is similar to a variable weight object, except that it cannot be aggregated. The value of a formula weight object is executed dynamically. Therefore, you cannot use a formula weight object with many of the weight options.
Considerations Based on Data Type of the Weight Object The following considerations apply when the weight object is numeric or BOOLEAN:
When the weight object has a numeric data type, It is good practice for the weight object variable to have the same dimensionality (or a subset thereof) as the variable to which it corresponds, but it is not required. When you use Oracle numbers or decimals to define your data variable, then always use the same data type to define the corresponding weight object. Otherwise, use the same data type for the weight object and the data variable unless you use WAVERAGE or HWAVERAGE; in this case, use a decimal or NUMBER data type to define the weight object.
When the weight object variable, formula, or relation that you define has a BOOLEAN data type, then TRUE represents a weight of 1.0 and FALSE represents a weight of 0.0. Furthermore, when an NA value is multiplied by any value, the result is NA.
Weight Object Considerations When Performing Partial Aggregations When you use any operators that require the WEIGHTBY phrase, and you are performing a partial aggregation, then do not change the values that are stored in the weight object between AGGREGATE commands.
Using WNAFILL
For example, suppose you use the WSUM operator to perform currency conversion. The currency conversation rates are applied at the detail data level. Only the detail data needs to be converted, because the variable data is aggregated after the conversion. To get the correct results, all of the non-detail level weight values in the weight object would have to be 1. Although this strategy produces correct results, it is inefficient. The best practice is to use the default WNAFILL value of 1 which specifies that all NA values in the weight object should be treated as if they have a weight of 1. In this case, because the operator is WSUM, you do not have to include WNAFILL in the AGGREGATE command, because the default values are correct.
For example, the following statement causes the value 0.7 to be substituted for every NA value in the salesw weight object.
AGGREGATE sales USING sales.agg WEIGHTBY WNAFILL 0.7 salesw
When you do not want to specify a number to replace NA values, then you can use NA instead of a number, as shown in the following statement.
AGGREGATE sales USING sales.agg WEIGHTBY WNAFILL NA salesw
Specifying NA after WNAFILL has the following effect:
When the aggregation specification contains a WAVERAGE or a WSUM OPERATOR, then any child cell in the weight object that has an NA value is treated as an NA cell.
When the aggregation specification contains an SSUM OPERATOR, then the results depend on how the Oracle OLAP option NASKIP is set. When NASKIP is set to YES, then any NA value is treated as 0.0. However, when NASKIP is set to NO, then any NA value is treated as an NA cell.
Effects of Dimension Status on Aggregation
A RELATION statement only aggregates those source data values that are in status—whether you set the status using LIMI T statements or a LOAD STATUS clause on the RELATION statement. The parent values are calculated regardless of whether they are in status or not. For example, when only Jan01, Feb01, and Mar01 are in status for the time dimension, then Q1.01 is calculated (but no other quarters), and 2001 is calculated (but no other years) using only Q1.01 as input since the other quarters are NA. This functionality is useful when you want to aggregate just the new data in your analytic workspace.
Assume that there is a variable named sales that is dimensioned by time, a hierarchical dimension, and district, a non-hierarchical dimension.
DEFINE time DIMENSION TEXT
DEFINE time.parentrel RELATION time <time>
DEFINE district DIMENSION TEXT
DEFINE sales VARIABLE DECIMAL <time district>
REPORT DOWN time sales
-----------------------SALES-----------------------
---------------------DISTRICT----------------------
TIME North South West East
------------ ------------ ------------ ------------ ------------
1976Q1 168,776.81 362,367.87 219,667.47 149,815.65
1976Q2 330,062.49 293,392.29 237,128.26 167,808.03
1976Q3 304,953.04 354,240.51 170,892.80 298,737.70
1976Q4 252,757.33 206,189.01 139,954.56 175,063.51
1976 NA NA NA NA
Examples
For examples of aggregation specifications that include RELATION statements, see the examples in the AGGMAP command.
(Read-only) The THOUSANDSCHAR option is the value specified for the NLS_NUMERIC_CHARACTERS option discussed in NLS Options.
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Note: The value of THOUSANDSCHAR only affects the way Oracle OLAP formats numbers in output. It does not affect the way numbers should be formatted for input. |
Data Type
ID
Syntax
THOUSANDSCHAR
Examples
Example 5-105 Displaying the Decimal and Thousands Markers
The following statements show the DECIMALCHAR and THOUSANDSCHAR values. Assume that you issue the following statements.
SHOW THOUSANDSCHAR SHOW DECIMALCHAR
Assume that a comma is displayed as the marker for THOUSANDSCHAR and that a period is displayed as the marker for DECIMALCHAR. With these values, a SHOW TOTAL(sales) statement would produce the following output.
63,181,743.50
The STDDEV function calculates the standard deviation of the values of an expression.
When STDDEV is affected by the NASKIP option. When NASKIP is set to YES (the default), STDDEV ignores NA values and returns the standard deviation of the values that are not NA. When NASKIP is set to NO, STDDEV returns NA when any value in the calculation is NA. When all data values for a calculation are NA, STDDEV returns NA for either setting of NASKIP.
Return Value
DECIMAL
Syntax
STDDEV(expression [dimensions])
Parameters
The numeric expression whose standard deviation is to be calculated.
The dimensions of the result. By default, STDDEV returns a single value. When you indicate one or more dimensions for the results, STDDEV calculates a standard deviation along the specified dimension(s) and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions. When it is a related dimension, you can specify the name of the relation instead of the dimension name which enables you to choose the relation to use when there are multiple relations between dimensions.
Usage Notes
Using STDDEV With an Expression Dimensioned by a DWMQY Dimension
When expression is dimensioned by a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you can specify any other dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR as a related dimension. Oracle OLAP uses the implicit relation between the dimensions. To control the mapping of one dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR to another (for example, from weeks to months), you can define an explicit relation between the two dimensions and specify the name of the relation as the dimension argument to the STDDEV function.
For each time period in the related dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR, Oracle OLAP calculates the standard deviation of the data values of the source time periods that end in the target time period. This method is used regardless of which dimension has the more aggregate time periods. To control the way in which data is aggregated or allocated between the periods of two dimensions of type DAY, WEEK, MONTH, QUARTER, and YEAR, you can use the TCONVERT function.
Examples
Example 8-121 Calculating the Standard Deviation of Monthly Sales
This example calculates the average number of tents sold during the first three months of 1996, along with the standard deviation from that average.
LIMIT district TO ALL LIMIT month TO 'Jan96' TO 'Mar96' LIMIT product TO 'Tents' REPORT HEADING 'Average' AVERAGE(units month) - HEADING 'Stddev'STDDEV(units months)
These statements produce the following output.
MONTH Average Stddev -------------- ---------- ---------- Jan96 262.33 49.32 Feb96 247.83 57.37 Mar96 320.50 68.17
The $DEFAULT_LANGUAGE property identifies a dimension as the language dimension for the analytic workspace in which it is defined and specifies the default language for that language dimension.
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Note: There can be only one language dimension in an analytic workspace and only that dimension can have a $DEFAULT_LANGUAGE property. |
Syntax
Before you add or delete a $DEFAULT_LANGUAGE property to your language dimension, you must make that dimension the most recently defined or considered object (see DEFINE and CONSIDER commands). You add $DEFAULT_LANGUAGE property using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$DEFAULT_LANGUAGE' language
To delete the property, issue the following statement.
PROPERTY DELETE '$DEFAULT_LANGUAGE'
Parameters
A TEXT expression that is a value in your language dimension, or an empty string.
Usage Notes
Working with Language Dimensions
A language dimension is a dimension that has a $DEFAULT_LANGUAGE property defined for it. There can only be one language dimension in an analytic workspace. Working with language dimensions involves:
Creating a Language Dimension To create a language dimension, take the following steps:
Define a TEXT dimension using DEFINE DIMENSION.
Populate the language dimension with the names of the languages you want to support. As language names, use valid values for NLS_LANGUAGE.
Add the $DEFAULT_LANGUAGE property to the dimension thereby identifying the dimension to Oracle OLAP as the language dimension in the analytic workspace.
Defining Multi-language Variables that are Dimensioned by the Language Dimension To create multi-language variables, you include the language dimension as a dimension of the variable as illustrated in Example 4-8, "Attaching a Language Dimension".
Working with Language Dimension Status When an analytic workspace with a language dimension is attached, Oracle OLAP initializes the status of the language dimension, as follows:
Oracle OLAP limits the language dimension to the value of the SESSION_NLS_LANGUAGE option when the language dimension contains that value.
If the language dimension does not contain value to which the SESSION_NLS_LANGUAGE option is set, then Oracle OLAP limits the language dimension to the language specified in the dimension's $DEFAULT_LANGUAGE property when the $DEFAULT_LANGUAGE property contains a value and when that value is a value of the language dimension.
If the language dimension does not contain value to which the SESSION_NLS_LANGUAGE option is set and if the language dimension's $DEFAULT_LANGUAGE property is empty or names a nonexistent value, Oracle OLAP limits the language dimension to the value of the language dimension to the first value in the dimension's default order.
By default, after initialization, the status of a language dimension cannot be changed. However, you can change this behavior by changing the value of the LOCK_LANGUAGE_DIMS option from TRUE to FALSE which changes the status of the language dimension to ALL and enables issuing LIMIT statements against the dimension.
Exporting Language Dimensions
When exporting an analytic workspace using EXPORT (EIF), Oracle OLAP takes the following steps to determine what values of the language dimension to export:
If the value of the LOCK_LANGUAGE_DIMS option is FALSE when an EXPORT statement executes, Oracle OLAP honors the current status of the language dimension and performs the export accordingly.
If the value of the LOCK_LANGUAGE_DIMS option is TRUE when an EXPORT statement executes, Oracle OLAP:
Changes the value of the LOCK_LANGUAGE_DIMS option to FALSE (thereby setting the status to ALL) before executing the EXPORT statement.
Executes the EXPORT statement. Oracle OLAP exports all of the values of the language dimension.
Changes the value of the LOCK_LANGUAGE_DIMS option to TRUE and resets the status of the language dimension according to the value of the SESSION_NLS_LANGUAGE option.
Examples
Example 4-7 Creating a Language Dimension
This example illustrates creating a language dimension named mylangs that supports the use of both French and American and that specifies that the default language is American.
NLS_LANGUAGE = 'AMERICAN' DEFINE mylangs DIMENSION TEXT MAINTAIN mylangs ADD 'FRENCH' 'AMERICAN' CONSIDER mylangs PROPERTY '$DEFAULT_LANGUAGE' 'AMERICAN' SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs') AMERICAN REPORT mylangs MYLANGS -------------- FRENCH AMERICAN
Example 4-8 Attaching a Language Dimension
Assume that in an analytic workspace named myaw that you have created a language dimension named mylangs as described in Example 4-7, "Creating a Language Dimension". Assume also that you have created a products dimension and a prod-desc variable with the following definitions and values.
DEFINE MYLANGS DIMENSION TEXT
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
AMERICAN
DEFINE PRODUCTS DIMENSION TEXT
DEFINE PROD_DESC VARIABLE TEXT <PRODUCTS MYLANGS>
MYLANGS
--------------
FRENCH
AMERICAN
PRODUCTS
--------------
PROD01
PROD02
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
FRENCH Pantalons JupesAMERICAN Trousers Skirts
Assume that you attach the analytic workspace. By displaying the options for the analytic workspace and requesting a A report of mylangs and prod_desc, shows that Oracle OLAP has limited the mylangs dimension to American which is the value of the SESSION_NLS_LANGUAGE option.
SHOW NLS_LANGUAGE
AMERICAN
AW ATTACH myaw RW
" Get the default language in our language dimension
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
AMERICAN
SHOW SESSION_NLS_LANGUAGE
AMERICAN
SHOW LOCK_LANGUAGE_DIMS
yes
SHOW STATIC_SESSION_LANGUAGE
no
REPORT mylangs
MYLANGS
--------------
AMERICAN
REPORT prod_desc
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
AMERICAN Trousers Skirts
Example 4-9 Changing NLS_LANGUAGE
Assume that you have attached the analytic workspace myaw as described in Example 4-8, "Attaching a Language Dimension". Now you change the value of NLS_LANGUAGE to French. Because the value of STATIC_SESSION_LANGUAGE is set to NO, making this change effectively changes the value of the SESSION_NLS_LANGUAGE option to French. When the value of SESSION_NLS_LANGUAGE option is French, as a report of mylangs and prod_desc illustrates, Oracle OLAP limits the mylangs dimension to French.
SET NLS_LANGUAGE= 'FRENCH'
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
AMERICAN
SHOW NLS_LANGUAGE
FRENCH
SHOW SESSION_NLS_LANGUAGE
FRENCH
SHOW LOCK_LANGUAGE_DIMS
oui
SHOW STATIC_SESSION_LANGUAGE
non
REPORT mylangs
MYLANGS
--------------
FRENCH
REPORT prod_desc
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
FRENCH Pantalons Jupes
Example 4-10 Setting NLS_LANGUAGE to a Value that is Not in a Language Dimension
Assume that in the analytic workspace named myaw (described in Example 4-9, "Changing NLS_LANGUAGE" ) the value of NLS_LANGUAGE is set first to American and then set to Spanish. As illustrated in the following code, since the language dimension, mylangs, does not include Spanish as one of its values, Oracle OLAP limits the mylangs dimension using the value of the $DEFAULT_LANGUAGE property which is American.
"Change the value of NLS_LANGUAGE to AMERICAN
SET NLS_LANGUAGE= 'AMERICAN'
"Change the value of NLS_LANGUAGE to SPANISH
SET NLS_LANGUAGE= 'SPANISH'
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
AMERICAN
SHOW NLS_LANGUAGE
SPANISH
SHOW SESSION_NLS_LANGUAGE
SPANISH
SHOW LOCK_LANGUAGE_DIMS
sí
SHOW STATIC_SESSION_LANGUAGE
no
REPORT mylangs
MYLANGS
--------------
AMERICAN
REPORT prod_desc
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
AMERICAN Trousers Skirts
Assume that you had defined the mylangs language dimension without specifying a default language using the following code.
DEFINE mylangs DIMENSION TEXT MAINTAIN mylangs ADD 'FRENCH' 'AMERICAN' CONSIDER mylangs PROPERTY '$DEFAULT_LANGUAGE' ''
In this case, when you set the value of NLS_LANGUAGE to Spanish, since the language dimension, mylangs does not have a value specified for its $DEFAULT_LANGUAGE property, Oracle OLAP limits the mylangs dimension using the first value in the mylangs dimension which is French.
NLS_LANGUAGE = 'SPANISH'
SHOW OBJ(PROPERTY '$DEFAULT_LANGUAGE' 'mylangs')
SHOW NLS_LANGUAGE
SPANISH
SHOW SESSION_NLS_LANGUAGE
SPANISH
SHOW LOCK_LANGUAGE_DIMS
sí
SHOW STATIC_SESSION_LANGUAGE
no
REPORT mylangs
MYLANGS
--------------
FRENCH
REPORT prod_desc
------PROD_DESC------
------PRODUCTS-------
MYLANGS PROD01 PROD02
-------------- ---------- ----------
FRENCH Pantalons Jupes
The EXPORT command copies workspace objects from your analytic workspace to an external file. You can use EXPORT to copy both data and object definitions from your workspace to an EIF file, or you can use it to copy an OLAP DML worksheet object to a spreadsheet file.
Because the syntax of the EXPORT command is different depending on whether it is being used to produce an EIF file or a spreadsheet file, two separate entries are provided:
The EXPORT (to EIF) command copies data and definitions from your Oracle OLAP analytic workspace to an EIF file. EXPORT also copies all dimensions of the exported data, even when you do not specify them in the command. The status of the data's dimensions in Oracle OLAP determines which values are exported.
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Tip: There are several options that determine how EIF files are imported and exported. These options are listed in "EIF Options". |
EXPORT (to EIF) is commonly used with IMPORT (EIF) to copy one Oracle OLAP workspace to another. You export objects from the source workspace to an EIF file and then import the objects from the EIF file into the target workspace. The source and target workspaces can reside on the same platform or on different platforms.
Syntax
EXPORT export_item TO EIF FILE file-name [LIST] [NOPROP] -
[NOREWRITE|REWRITE] [FILESIZE n [K, M, or G]] -
[NOTEMPDATA] [NLS_CHARSET charset-exp] [AGGREGATE | NOAGGR] -
[API | NOAPI]
where export_item is one of the following:
Parameters
Specifies that Oracle OLAP exports all the objects currently in the status of NAME (and, therefore, not necessarily all objects in the workspace).
|
Note: When you want to export cube metadata (that is, when the default API keyword is in effect), you must export all of the objects in the workspace (that is, you must specify the ALL keyword for export_item). You cannot export cube metadata when you export only some workspace objects. |
The name of an analytic workspace object or option to be exported. You can list multiple names for export.
Specifies a new name for the analytic workspace object or option. When you specify an expression, or a local variable, or a local valueset, then you must use AS name to provide a name for the object that IMPORT (EIF) uses to receive the data
|
Important: You cannot rename dimensions. |
An expression to be computed and exported. You can list multiple names for export.
When you want to export a large multidimensional object that may require multiple passes to write into memory, then you can use SCATTER AS scattername to improve file I/O performance. You must first define one or two new single-dimension text variables (scattername and scattertype) and assign text values and their corresponding data types to scattername. When you use SCATTER AS scattername, this tells Oracle OLAP to export the multidimensional expression as separate variables in the slices you have specified in scattername. When each of the slice variables is to have the same data type, you can simply make exp have that data type, in which case you do not have to use TYPE scattertype.
The EXCLUDING phrase applies only to a concat dimension that you specify with the name argument. The value you specify for concatbasedim, specifies the base dimensions of the concat that Oracle OLAP does not export.
Specifies that Oracle OLAP exports all the objects currently in the status of NAME (and, therefore, not necessarily all objects in the workspace).
Indicates that you want to create an EIF file.
A text expression that is the name of the file to which output should be written. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use the CDA command to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Sends to the current outfile the definition of each object as it begins to export it. For dimensions, EXPORT indicates the number of values being exported, and for composites, it lists the number of dimension value combinations. EXPORT also produces a message that shows the total number of bytes read every two minutes and after the export procedure.
Prevents any properties that you have assigned to each object using a PROPERTY from being written to the EIF file.
Specifies whether EXPORT overwrites the target file when it already exists. NOREWRITE (the default) leaves an existing target file intact and sends an error message to the current outfile. REWRITE causes EXPORT to replace the existing file with the new EIF file.
Sets the maximum size of each component file (main file and extension files) for EIF files. When a file's size grows beyond the value of FILESIZE or the current disk or location becomes full, Oracle OLAP creates an EIF extension file. See"EIF Extension Files".
FILESIZE affects component files created after it is set. Previous component files may have various sizes, determined by the FILESIZE setting at the time each one was created or by the size it reached when its disk was full.
When you do not specify K, M, or G, the value you specify for n is interpreted as bytes. When you specify K, M, or G after the value n, the value is interpreted as kilobytes, megabytes, or gigabytes, respectively.
You can set FILESIZE to any value between 81,920 bytes (80K) and 2,147,479,552 bytes (2G).
Prevents data in TEMP variables from being written to the EIF file.
Specifies the character set that Oracle OLAP uses when exporting text data to the file specified by file-name which allows Oracle OLAP to convert the data accurately into that character set. This argument must be the last one specified. When this argument is omitted, then Oracle OLAP exports the data in the database character set, which is recorded in the NLS_LANG option.
Export aggregated data. (Default behavior.)
Do not export aggregated data.
(Default) Export any cube metadata defined for the specified items.
Do not export any cube metadata defined for the specified items.
Usage Notes
Exporting and Importing Between Different Platforms
When you transfer an EIF file between computers, use a binary transfer to overcome file-format incompatibilities between platforms. The EIF file must have been created with the EIFVERSION set to a version that is less than or equal to the version number of the target workspace. See the EIFVERSION option for information about verifying the target version number.
Exporting Relations
When you export a relation, EXPORT exports the definition and the values in status for the related dimension and the dimensions of the relation.
Exporting Conjoint Dimensions
When you export a conjoint dimension, ensure that the status of the base dimensions and the status of the conjoint dimension match. Since there is an implicit relation between conjoint and base dimensions, Oracle OLAP exports the base dimensions with the conjoint dimension, but it cannot export all the conjoint dimension values in the current status when the related base values are not also in status.
Exporting Dimension Surrogates
When you export a dimension surrogate, Oracle OLAP also exports the dimension of the surrogate. For more information, see "Importing and Exporting Dimension Surrogates".
Reducing Workspace Size
When you have added and then deleted many objects or dimension values, you might want to use EXPORT (from EIF) with the IMPORT (EIF) command to remove extra space from your analytic workspace. You can make your workspace smaller, perhaps substantially so. To do this, use the EXPORT command with the ALL keyword to put all the data in an EIF file, create another workspace with a different name, and then import the EIF file into the new workspace. You can then delete the old workspace and refer to the new one with the same workspace alias that you used for the original one.
Preserving the Type of a Conjoint Dimension
When you export a HASH, BTREE, or NOHASH conjoint dimension to an EIF file, the conjoint type is exported along with its definition in the EIF file. When you then import the conjoint dimension into an analytic workspace, Oracle OLAP preserves the conjoint type when you import into a new dimension or a dimension already using that conjoint type. When you import the dimension into an existing dimension that does not use the same conjoint type, Oracle OLAP does not preserve the original conjoint type that was saved in the EIF file.
Exporting Unnamed Composites
When you export or import an object with an unnamed composite in its definition, the composite is automatically exported or imported with the object. You cannot import or export an unnamed composite independently.
EIF Extension Files
EIF extension file names have the structure filename.ennn, where nnn is a three-digit number beginning with 001. For example, assume you have an EIF file named export.eif, the extension files are named export.e001, export.e002, and so on. You can set the extension to three characters by using the EIFSHORTNAMES option. Extension files are created in the same directory object as the original EIF file, unless you specify a different one with the EIFEXTENSIONPATH option.
Saving SEGWIDTH Setting Information
When you use the SEGWIDTH keyword of the CHGDFN command to specify the length of variable segments, segment information cannot be exported and imported automatically. You can save your SEGWIDTH settings by exporting the entire workspace, creating a new workspace, importing only the workspace objects into the new workspace, specifying segmentation, and then importing the variable data into the new workspace.
Exporting Objects with the Same Name From Two Different Workspaces
When you want to export two objects that have the same name from two different workspaces, you must rename one of them in the EIF file by exporting it with the AS keyword. Objects in an EIF file cannot have duplicate names.
Exporting a PERMIT_READ or PERMIT_WRITE Program
The contents of a PERMIT_READ or a PERMIT_WRITE program is emptied when exported. To successfully copy the contents of these programs to and from analytic workspaces, rename them before using EXPORT (to EIF); and then, after using IMPORT (from EIF) to copy them into an analytic workspace, name them back to PERMIT_READ or PERMIT_WRITE.
Exporting TEXT and NTEXT Values
You can export and import TEXT and NTEXT values. Both data types can be exported to a single EIF file.
Exported TEXT values are stored in the EIF file using the character set specified for the file in the EXPORT command.
Exported NTEXT values are stored in the EIF file as NTEXT (UTF8 Unicode).
NTEXT values imported into TEXT objects are converted into the database character set which can result in data loss when the NTEXT values cannot be represented in the database character set.
TEXT values imported into NTEXT objects are converted into the NTEXT (UTF8 Unicode) character set.
Examples
Example 9-116 Exporting Variables
Suppose you want to export the values in status and the dimensions of two variables called actual and budget from your current Oracle OLAP workspace to a disk file called finance.eif in your current directory object. Use the following statement.
EXPORT actual budget TO EIF FILE 'finance.eif'
Example 9-117 Exporting a Large Object
Suppose you want to export a large, multidimensional object that is likely to require multiple passes to write into memory. To improve file I/O performance, you can create a single-dimension variable to tell Oracle OLAP how to slice the multidimensional variable into smaller pieces. Suppose, also, that the large object is the sales variable, which is dimensioned by month, product, and district. To specify how sales should be sliced, create a single-dimension variable, as shown in the following statement.
DEFINE salescatter VARIABLE TEXT <district>
Because salescatter is dimensioned by district, this tells Oracle OLAP to divide sales into district slices. Because district has six values, sales is divided into six slices. Each slice must be named. To do so, assign values to each district in salescatter. You can then assign the appropriate data type to each slice, for example, by using a QDR (qualified data reference), when desired.
To export SALES, execute the following statement.
EXPORT sales SCATTER AS salescatter TYPE TYPEVAR TO EIF FILE 'slice.eif'
To import the variables, specify which of the named slices you want, as in the following statement.
IMPORT dist1 dist2 dist3 dist4 dist5 dist6 FROM EIF FILE 'slice.eif'
Alternatively, you can import all of the variables.
IMPORT ALL FROM EIF FILE 'slice.eif'
The EXPORT (to spreadsheet) command copies an Oracle OLAP worksheet object that you have created to a spreadsheet file and automatically translate it into the appropriate format. An analytic worksheet's dimensions form the columns and rows of the spreadsheet file. The current status of these dimensions determines which part of a worksheet is exported.
You can also export an analytic worksheet to an EIF file as described in EXPORT (EIF). EXPORT (to spreadsheet) is commonly used to copy part of your Oracle OLAP workspace into a file that can be read by other software, such as Lotus 1-2-3, or Symphony.
Syntax
EXPORT worksheetname TO {WKS|WK1|WRK|WR1|DIF} FILE file-name -
[STATRANK] [NOREWRITE|REWRITE] [NLS_CHARSET charset-exp]
Parameters
An Oracle OLAP worksheet object that you have created. In any one EXPORT (to spreadsheet) command, you can export only one worksheetname to one spreadsheet file.
Indicates that you want to export an Oracle OLAP worksheet to a 1-2-3 file, version 1.
Indicates that you want to export an Oracle OLAP worksheet to a 1-2-3 file, version 2.
Indicates that you want to export an Oracle OLAP worksheet to a Symphony file, version 1.0.
Indicates that you want to export an Oracle OLAP worksheet to a Symphony file, version 1.1.
Indicates that you want to export an Oracle OLAP worksheet to a data interchange format file.
FILE specifies the file that you are creating. For file-name, specify a text expression that is the name of the file. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use the CDA command to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Specifies that the row and column numbers exported with worksheet data should be the current status rankings of the WKSROW and WKSCOL dimensions.
(Default) Specifies that Oracle OLAP does not overwrite the target file when it already exists, but instead displays an error.
Specifies that Oracle OLAP overwrites the target file when it already exists.
Specifies the character set that Oracle OLAP uses when exporting text data to the worksheet file specified by file-name which allows Oracle OLAP to convert the data accurately into that character set.
For information about the character sets that you can specify, see Oracle Database Globalization Support Guide.
This argument must be the last one specified. When this argument is omitted, then Oracle OLAP exports the data in the database character set, which is recorded in the NLS_LANG option.
Examples
The INTERP_SILENT procedure executes one or more OLAP DML commands and suppresses all output from them. It does not suppress error messages from the OLAP command interpreter.
Input to the INTERP_SILENT function is limited to 4K. To display the output of the OLAP DML commands, use the EXECUTE procedure, or the INTERP or INTERPCLOB functions.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
INTERP_SILENT (
olap-commands IN VARCHAR2);
Parameters
Table B-26 INTERP_SILENT Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
Example
The following commands show the difference in message handling between EXECUTE and INTERP_SILENT. Both commands attach the GLOBAL analytic workspace in read-only mode. However, EXECUTE displays a warning message, while INTERP_SILENT does not.
EXECUTE dbms_aw.execute('AW ATTACH global'); IMPORTANT: Analytic workspace GLOBAL is read-only. Therefore, you will not be able to use the UPDATE command to save changes to it. EXECUTE dbms_aw.interp_silent('AW ATTACH global');
The PARTITION function returns the name of the partition in which a value is stored.
Return Value
Text
Syntax
PARTITION (partition_template_values)
Parameters
An expression that represents one or more values of the partition template (for example, the name of a partition template or a QDR).
Examples
Example 8-60 Retrieving the Name of a Partition
Assume that you have defined the following objects.
DEFINE time DIMENSION TEXT
DEFINE product DIMENSION TEXT
DEFINE time_parentrel RELATION time <time>
DEFINE partition_sales_by_year PARTITION TEMPLATE <time product> -
PARTITION BY LIST (time)(PARTITION time_2003 VALUES -
('2003','Dec2003', 'Jan2003','31Dec2003','01Dec2003','31Jan2003','01Jan2003')-
<time product> PARTITION time_2002 VALUES -
('2002', 'Dec2002', 'Jan2002', '31Dec2002', '01Dec2002','31Jan2002','01Jan2002')-
<time product>)
DEFINE sales DECIMAL <partition_sales_by_year<time product>>
Assume that these object have the values shown in the following report.
REPORT DOWN PARTITION(partition_sales_by_year) time product sales
PARTITION(PART
ITION_SALES_BY
_YEAR) TIME PRODUCT SALES
-------------- ---------- ---------- ----------
TIME_2003 2003 00001 NA
TIME_2003 Dec2003 00001 NA
TIME_2003 Jan2003 00001 NA
TIME_2003 31Dec2003 00001 14.78
TIME_2003 01Dec2003 00001 15.52
TIME_2003 31Jan2003 00001 13.61
TIME_2003 01Jan2003 00001 10.39
TIME_2003 2003 00002 NA
TIME_2003 Dec2003 00002 NA
TIME_2003 Jan2003 00002 NA
TIME_2003 31Dec2003 00002 16.05
TIME_2003 01Dec2003 00002 12.27
TIME_2003 31Jan2003 00002 10.83
TIME_2003 01Jan2003 00002 11.07
TIME_2002 2002 00001 NA
TIME_2002 Dec2002 00001 NA
TIME_2002 Jan2002 00001 NA
TIME_2002 31Dec2002 00001 18.80
TIME_2002 01Dec2002 00001 13.64
TIME_2002 31Jan2002 00001 12.41
TIME_2002 01Jan2002 00001 16.97
TIME_2002 2002 00002 NA
TIME_2002 Dec2002 00002 NA
TIME_2002 Jan2002 00002 NA
TIME_2002 31Dec2002 00002 17.47
TIME_2002 01Dec2002 00002 16.58
TIME_2002 31Jan2002 00002 18.94
TIME_2002 01Jan2002 00002 18.36
As shown in the following code, you can use the PARTITION function to retrieve the names of the partition in which a a value is stored.
SHOW partition_sales_by_year
<2003, 00001>
" Use a QDR to identify the partition of a specific time value
SHOW PARTITION(partition_sales_by_year (time '31Jan2002'))
TIME_2002
REPORT DOWN time PARTITION(partition_sales_by_year)
PARTITION(PARTITION_S
----ALES_BY_YEAR)----
-------PRODUCT-------
TIME 00001 00002
-------------- ---------- ----------
2003 TIME_2003 TIME_2003
2002 TIME_2002 TIME_2002
Dec2003 TIME_2003 TIME_2003
Jan2003 TIME_2003 TIME_2003
Dec2002 TIME_2002 TIME_2002
Jan2002 TIME_2002 TIME_2002
31Dec2003 TIME_2003 TIME_2003
01Dec2003 TIME_2003 TIME_2003
31Jan2003 TIME_2003 TIME_2003
01Jan2003 TIME_2003 TIME_2003
31Dec2002 TIME_2002 TIME_2002
01Dec2002 TIME_2002 TIME_2002
31Jan2002 TIME_2002 TIME_2002
01Jan2002 TIME_2002 TIME_2002
The AGGMAP ADD or REMOVE model command adds or removes a previously-defined model from a previously-defined aggregation specification (that is, aggmap object of type AGGMAP). Models are used in aggregation specifications to aggregate data over a non-hierarchical dimension (such as line items), which has no parent relation and therefore cannot be aggregated by a RELATION statement. See MODEL (in an aggregation) for details.
|
Note: Although you can use the AGGMAP ADD MODEL and AGGMAP REMOVE MODEL statements to temporarily add a model to an aggmap object, typically you use a MAINTAIN ADD SESSION statement like the one below to perform this action.MAINTAIN dimension ADD SESSION member = model APPLY TO AGGMAP aggmap When you use a MAINTAIN ADD SESSION statement neither the calculated member or its definition persists from session to session; both are deleted after the session in which they are created |
Syntax
AGGMAP {ADD model TO aggmap|REMOVE model FROM aggmap}
Parameters
Temporarily adds a model to an aggmap object. The model is attached to the aggmap only for the duration of the session. Even when the analytic workspace has been updated and committed, the model is discarded from the aggmap when the session is closed.
Removes a model from an aggmap.
The name of the model object that you want to add to the specified aggmap.
The name of a previously defined aggmap object of type AGGMAP.
Examples
Example 9-25 Temporarily Adding a Model to an Aggmap
Assume for example, that you have an aggmap object named letter.aggmap with the following definition.
DEFINE LETTER.AGGMAP AGGMAP
AGGMAP
RELATION letter.letter PRECOMPUTE ('AA')
END
Assume also that you want to create summarized variable data for the cells that are dimensioned by the dimension values AAB and ABA. However, you do not want this data to be permanently stored in the analytic workspace. You just want to see the data during your session.
To perform this type of aggregation, you can take the following steps:
Create a dimension value for the custom aggregate. This dimension value is the parent of the dimension values AAB and ABA. The following statement adds 'BB' to the letter dimension.
MAINTAIN letter ADD 'BB'
Create a MODEL object that contains an AGGREGATION function, which associates child dimension values with the new dimension value. The following model identifies BB as the parent of AAB and ABA. Note that the parent dimension value (in this case, BB) cannot already be defined as a parent in the parent relation (letter.letter).
DEFINE LETTER.MODEL MODEL
MODEL
DIMENSION letter
BB=AGGREGATION('AAB' 'ABA')
Execute an AGGMAP ADD statement to append the model to the existing AGGMAP object.
AGGMAP ADD letter.model TO letter.aggmap
The aggmap now looks like this.
DEFINE LETTER.AGGMAP AGGMAP
AGGMAP
RELATION letter.letter PRECOMPUTE ('AA')
END
AGGMAP ADD letter.model
The model is executed only by the AGGREGATE function like the one shown here; the AGGREGATE command ignores it.
REPORT AGGREGATE(units USING letter.aggmap)
When you want to remove the model from the aggmap during a session, use the AGGMAP REMOVE statement.
To ensure that your aggmap does not become a permanent object in the analytic workspace, before you close your session issue the following statement to delete the dimension values that you added in Step 1.
MAINTAIN letter DELETE 'BB'
When your session ends, Oracle OLAP automatically removes the model added using the AGGMAP ADD statement. You do not have to issue an explicit AGGMAP REMOVE statement.
The OBSCURE function provides two mechanisms for encoding a single-line text expression. Depending on the mechanism you use, OBSCURE can also restore the encoded value to its original form.
|
Note: This function performs simple encoding. For information on using secure encryption and other security features in Oracle, see Oracle Database Security Guide. |
Return Value
TEXT
|
Note: The return value of the OBSCURE function always has a text data type. However, unless you specify the TEXT keyword, the actual value returned byOBSCURE(HASH) and OBSCURE(HIDE) is binary. When you want to be able to manage these encoded values as text (for example, when you want to be able to store them in a text file), you must specify the TEXT keyword. See Example 8-59, "Generating Text Data". |
Syntax
OBSCURE({HASH|HIDE|UNHIDE} [TEXT] seed-exp input-exp)
Parameters
Specifies that Oracle OLAP encodes the input text expression according to the seed expression that you specify. With the HASH keyword:
Encoded values cannot be restored to their original form.
The same seed expression and input text always produce the same result.
Specifies that Oracle OLAP encodes the input text expression according to the seed expression that you specify. With the HIDE keyword:
Encoded values can be un-encoded to their original form with UNHIDE.
The same seed expression and input text always produce different results.
The HIDE keyword provides a mechanism for storing values in encoded form while actually comparing their un-encoded values.
When specified with the original seed expression, decodes values encoded with the HIDE keyword to their original form. See "Decoding Text".
The TEXT keyword causes OBSCURE to convert binary data to text, such that the return value consists only of text data. When you do not specify the TEXT keyword, the output of OBSCURE is binary data. See "Decoding Text", and "Generating Text Data".
A single-line case-sensitive text expression that is used as a seed value when encoding of the input text expression.
A single-line case-sensitive text expression to be encoded or decoded by OBSCURE.
Usage Notes
Decoding Text
When you have used OBSCURE(HIDE) with the TEXT keyword to encode a text expression, you must also specify the TEXT keyword with OBSCURE(UNHIDE) to decoded expression to its original value.
Examples
Example 8-59 Generating Text Data
The following statements illustrate the use of the TEXT keyword.
DEFINE encoded_text VARIABLE TEXT DEFINE unencoded_text VARIABLE TEXT unencoded_text = 'max' encoded_text = OBSCURE(HIDE TEXT 'XXXX' unencoded_text) SHOW encoded_text
This SHOW statement generates the following output.
c5WF/XfABuY
The same statements without the TEXT keyword would produce binary output from the SHOW statement.
The QUAL function lets you explicitly specify a qualified data reference (QDR). Use QUAL in cases where the syntax of a QDR is ambiguous and could either be misinterpreted by Oracle OLAP or cause a syntax error.
QDRs provide a mechanism for limiting one or more dimensions of an expression to a single value. QDRs are useful when you want to temporarily reference a value that is not in the current status.
Return Value
The value that is returned has the same data type as the expression being qualified.
Syntax
QUAL(expression, dimname1 dimexp1 [, dimnameN dimexpN])
Parameters
The expression being qualified. Use QUAL to qualify complex expressions that contain computation, function calls, or ampersand substitution. You can also use QUAL when the expression is a simple variable name. However, QUAL is not required for simple expressions, and you can use the following standard QDR syntax.
expression(dimname1 dimexp1 [, dimname2 dimexp2 ...])
The dimension to be limited. You can specify one or more of the dimensions of the expression. Each dimension must be paired with a dimexp. You can specify a dimension surrogate instead of the dimension.
An expression that represents the value to which the dimension should be limited. The expression can be a value of the dimension, a text expression whose result is a value of the dimension, a numeric expression whose result is the logical position of a value of the dimension, or a relation of the dimension.
When the dimension being limited is a conjoint dimension, then dimexp must be enclosed in angle brackets and must include a value for each of its base dimensions.
When the dimension being limited is a concat dimension, then dimname and dimexp can be one combination listed in Table 8-10, "Valid dimname and dimexp Combinations for Concat Dimensions".
Table 8-10 Valid dimname and dimexp Combinations for Concat Dimensions
| dimname | dimexp |
|---|---|
|
The name of the concat dimension |
A value of the concat dimension |
|
The name of the concat dimension |
The name of a base dimension |
|
The name of a base dimension of the concat dimension |
A value of the base dimension |
|
The name of a base dimension of the concat dimension |
The name of the concat dimension |
Examples
Example 8-62 Using QUAL with MAX
The following example first shows how you might view your data by limiting its dimensions, and then how you might view it by using QUAL.
Assume that you issue the following OLAP DML statements to limit the view of the Cogs line data in the Sporting division to January 1996 through June 1996, and, then, report by month on the maximum value of actual costs or budgeted costs or MAX(actual,budget), actual costs, and budgeted costs for each month.
LIMIT month TO 'Jan96' TO 'Jun96' LIMIT line TO 'Cogs' LIMIT division TO 'Sporting' REPORT DOWN month W 11 MAX(actual,budget) W 11 actual W 11 budget
The preceding statements produce the following report.
DIVISION: SPORTING
---------------LINE----------------
---------------COGS----------------
MAX(ACTUAL,
MONTH BUDGET) ACTUAL BUDGET
-------------- ----------- ----------- -----------
Jan96 287,557.87 287,557.87 279,773.01
Feb96 323,981.56 315,298.82 323,981.56
Mar96 326,184.87 326,184.87 302,177.88
Apr96 394,544.27 394,544.27 386,100.82
May96 449,862.25 449,862.25 433,997.89
Jun96 457,347.55 457,347.55 448,042.45
Now consider how you might view the same figures for MAX(actual,budget) without changing the status of line or division.
ALLSTAT LIMIT month TO 'Jan96' TO 'Jun96' REPORT HEADING 'For Cogs in Sporting Division' DOWN month - W 11 HEADING 'MAX(actual,budget)'- QUAL(MAX(actual,budget), line 'Cogs', division 'Sporting') For Cogs in Sporting MAX(actual, Division budget) -------------- ----------- Jan96 287,557.87 Feb96 323,981.56 Mar96 326,184.87 Apr96 394,544.27 May96 449,862.25 Jun96 457,347.55
When you attempt to produce the same report with standard QDR syntax, Oracle OLAP signals an error.
REPORT HEADING 'For Cogs in Sporting Division' DOWN month - W 11 HEADING 'MAX(actual,budget)'- MAX(actual,budget) (line cogs, division sporting)
The following error message is produced.
ERROR: A right parenthesis or an operator is expected after LINE.
Example 8-63 Using QUAL with a Concat Dimension
The following example shows two ways of limiting the values of a concat dimension in a QUAL function. The reg.dist.ccdim concat dimension has region and district as its base dimensions. The rdsales variable is dimensioned by month, product, and reg.dist.ccdim.
LIMIT month TO 'Jan96' TO 'Jun96' LIMIT product TO 'Tents' 'Canoes' " Limit the concat by specifying one of its component dimensions REPORT W 30 QUAL(rdsales * 2, month 'Feb96', district 'Boston')
These statements produce the following report.
QUAL(RDSALES * 2, MONTH
PRODUCT 'Feb96', DISTRICT 'Boston')
-------------- ------------------------------
Tents 69,283.18
Canoes 164,475.36
" Limit the concat by specifying one of its values
REPORT W 30 QUAL(rdsales * 2, month 'Mar96', reg.dist.ccdim '<district: Boston>')
QUAL(RDSALES * 2, MONTH
'Mar96', REG.DIST.CCDIM
PRODUCT '<district: Boston>')
-------------- ------------------------------
TENTS 91,484.42
CANOES 195,244.56
The LISTFILES command lists all the open files that can be referenced by the FILEQUERY function which includes all files opened by FILEOPEN, OUTFILE, and LOG command.
Syntax
LISTFILES
Examples
Example 10-32 Listing Open Files
The following example shows how to use LISTFILES to see which open files can be referenced by the FILEQUERY function.
DEFINE fil.unit VARIABLE INTEGER
fil.unit = FILEOPEN('report' WRITE)
LISTFILES
These statements produce the following output.
10 w D:\WINNT35\SYSTEM32\report
The FETCH command specifies how analytic workspace data is retrieved for use in the relational table created by the OLAP_TABLE function which you use to access analytic workspace data using SQL.
You can only use the FETCH command in the OLAP_command parameter of the OLAP_TABLE function; you cannot use it in any other context.
Within the OLAP_TABLE function, the FETCH keyword specifies explicitly how analytic workspace data is mapped to a table object. The FETCH keyword is provided for Express applications that are migrating to the Oracle Database.
|
Note: Use the FETCH keyword in OLAP_TABLE only when you are upgrading an Express application that used the FETCH command for SNAPI. When you are upgrading an Express application, note that the syntax is the same here as in Express 6.3. You can use the same FETCH commands that you used previously. |
When using FETCH as an argument in OLAP_TABLE, you must enter the entire statement on one line, without line breaks or continuation marks of any type.
To fetch or import data from an relational table into analytic workspace objects using SQL commands embedded in the OLAP DML, use the OLAP DML SQL command.
|
See also: For more information on theOLAP_TABLE function, see Appendix A, "OLAP_TABLE SQL Functions" |
Syntax
FETCH expression... [TAG tag-exp] [LABELED] [data-order]
where data-order is one of the following:
Parameters
One expression for each target column, in the same order they appear in the row definition. Separate expressions with spaces or commas.
This keyword is ignored; it is retained in the syntax only for backward compatibility.
This keyword is ignored; it is retained in the syntax only for backward compatibility. All fetches are labeled.
Orders the data block according to the dimension list specified in <order-dim...>. Specify dimensions or composites or a combination of the two within angle brackets. Dimensions are ordered from fastest to slowest varying, with the first dimension being the fastest varying. When you specify a USING clause, then you cannot specify ACROSS or DOWN.
Orders the data block in columns and rows and specifies the column dimensions. For across-dim, specify a list of one or more dimensions, composites, the NONE keyword, or a combination of these. When you specify two or more ACROSS dimensions, then they vary from slowest to fastest, with the first dimension being the slowest.
When you specify ACROSS but not DOWN, then all unspecified dimensions default to DOWN dimensions, which vary from fastest to slowest in the order that the dimensions appear in the object definitions. However, adding the NONE keyword to the ACROSS dimension list fetches only the first value in status for the unspecified DOWN dimensions.
When you specify an ACROSS clause, then you cannot specify a USING clause.
Orders the data block in columns and rows and specifies the row dimensions. For down-dim, specify a list of one or more dimensions, composites, the NONE keyword, or a combination of these. When you specify two or more DOWN dimensions, then they vary from slowest to fastest, with the first dimension being the slowest.
When you specify DOWN but not ACROSS, then all unspecified dimensions default to ACROSS dimensions, which vary from fastest to slowest in the order that the dimensions appear in the object definitions. However, adding the NONE keyword to the DOWN dimension list fetches only the first value in status for the unspecified ACROSS dimensions.
When you specify a DOWN clause, you cannot specify a USING clause.
Usage Notes
Default Data Order
When you do not specify a USING or DOWN/ACROSS clause, the dimensions of the data vary from fastest to slowest in the order they are listed in the workspace object definitions.
Using Expressions with Different Dimensionality
When you specify multiple expressions with different dimensionality in one FETCH command, the ordering of the dimensions from fastest to slowest varying is not predictable.
Maximum Size of Data Block
You can use MAXFETCH to set an upper limit on the size of a data block generated by FETCH.
Variables Defined with Composites
For variables defined with composites, you can specify the composites instead of the base dimensions in the ACROSS, DOWN, and USING clauses of FETCH which minimizes the number of NA fields in the resulting data block. When a variable has been defined with a named composite, you can specify the name of the composite after the USING, DOWN or ACROSS keyword. You specify unnamed composites with the syntax used to define them. For example, a variable d.sales with the following definition
DEFINE d.sales VARIABLE DECIMAL <month SPARSE<product district>>
could be fetched with the expression SPARSE<product district> immediately following a USING, DOWN, or ACROSS keyword.
Examples
For an example of using FETCH in OLAP_TABLE, see Example A-9, "Script Using FETCH with OLAP_TABLE".
The JOINBYTES function joins two or more text values as a single line.
JOINBYTES ignores any arguments that have a value of NA and removes line breaks from the text it joins. (To preserve the breaks in a multiline text expression, use the INSCHARS.) Also, when the length of the joined line exceeds 4,000 (The maximum length of a joined line), JOINBYTES automatically breaks the line and puts the remaining bytes on the next line. The line break could occur between the two bytes of a double-byte character. JOINBYTES would then end one line with the first byte of the double-byte character and start the next line with the second byte of the character.
Return Value
TEXT
Syntax
JOINBYTES(first-expression, next-expression...)
Parameters
An expression to which JOINBYTES joins next-expression. When the first-expression has a data type other than TEXT or NTEXT, JOINBYTES converts it to TEXT. Use the CONVERT or TO_CHAR function to convert a NTEXT expression to TEXT.
One or more expressions to join with first-expression. When an expression you want to concatenate has a data type other than TEXT or NTEXT, JOINBYTES converts it to TEXT. Use the CONVERT or TO_CHAR function to convert a NTEXT expression to TEXT.
Examples
Example 7-135 Using JOINBYTES to Concatenate Values
This example shows how you can use JOINBYTES to combine text with the current values of the two variables name.product and price. The variable price has a data type of DECIMAL; however, JOINBYTES automatically converts its value to TEXT to join it with the other text values.
LIMIT product TO 'Canoes' LIMIT month TO 'Dec96'
The JOINBYTES function
JOINBYTES('Current Price for ' name.product ' is: $' price)
returns the following value.
Current Price for Aluminum Canoes is: $200.03
The ISVALUE function tests whether a dimension or a composite has a specified value.
|
Tip: Use INSTAT to determine whether a value of a dimension is in the current status of the dimension. |
Return Value
BOOLEAN
Syntax
ISVALUE(name, value)
Parameters
The name of the dimension or the composite to be checked.
When the composite is unnamed, use the SPARSE keyword to refer to the composite (for example, SPARSE <market product>).
The value you want to test, either a text literal or text expression for an ID or TEXT dimension, an INTEGER for an INTEGER dimension, or a combination of values enclosed by angle brackets for composites and conjoint dimensions.
Examples
Example 7-133 Testing Valid Values
Suppose you want to find out if Packs is a value of the product dimension. The following statement produces the answer YES or NO.
SHOW ISVALUE(product, 'Packs')
Example 7-134 Testing Logical Position Numbers
You can test for the logical position numbers of base dimension values in a conjoint dimension. For example, suppose market and product are the base dimensions of the conjoint dimension markprod. The following statement tests whether or not there is a value assigned to the combination of the fourth market dimension value and the third product dimension value.
SHOW ISVALUE(markprod, '<4 3>')
Within an OLAP DML program, the ARG function lets you reference arguments passed to a program. The function returns one argument as a text value.
|
Note: Typically users use an ARGUMENT statement to define arguments in a program, thereby negating the need for using the ARG function to reference arguments passed to the program. For more information on how to use ARGUMENT to define arguments that are passed to a program, see "Declaring Arguments that Are Passed Into a Program" . |
Return Value
TEXT
Syntax
ARG(n)
Parameters
The number by position of the argument whose value you want to reference. ARG(1) returns the first argument to the program, ARG(2) returns the second argument, and so forth. When the program is called with fewer than n arguments, ARG returns a null value. ARG also returns a null value when n is zero or negative.
Examples
Example 7-20 Assigning Arguments
Suppose you have a program that produces a sales report. You want to be able to produce this report for any two periods of months, so you do not want to limit the month dimension to any particular month in the program. Instead, you use ARG functions in the LIMIT command so that the starting and ending months for the two periods can be supplied as arguments when the program is run.
Notice the UPCASE function preceding the ARG functions. UPCASE allows the arguments to be specified in upper- or lowercase, even though dimension values in the analytic workspace are in uppercase. A prefixed & (ampersand) would have a similar effect since it tells Oracle OLAP to substitute the values of ARG before the LIMIT command is executed -- in this case, a value of the month dimension. However, an & (ampersand) has the disadvantage of preventing compilation of program lines in which it appears, and slower execution results.
DEFINE salesrpt PROGRAM PROGRAM PUSH month product district TRAP ON cleanup LIMIT month TO UPCASE(ARG(1)) TO UPCASE(ARG(2)) LIMIT product TO 'CANOES' LIMIT district TO all REPORT grandtotals DOWN district sales LIMIT month TO UPCASE(ARG(3)) TO UPCASE(ARG(4)) REPORT grandtotals DOWN district sales cleanup: POP month product district END
To run the program, you specify the program name (salesrpt) followed by two sets of months to mark the beginning and the end of the two periods of sales to be reported. Then, when the LIMIT MONTH statements are executed, Oracle OLAP passes the months specified on the command line as return values for ARG(1), ARG(2), ARG(3), and ARG(4) in the LIMIT commands.
salesrpt 'Jan95' 'Mar95' 'Jan96' 'Mar96'
This statement produces the following output.
PRODUCT: Canoes
------------SALES--------------
------------MONTH--------------
DISTRICT Jan95 Feb95 Mar95
---------------------------------------------
Boston 66,013.92 76,083.84 91,748.16
Atlanta 49,462.88 54,209.74 67,764.20
Chicago 45,277.56 50,595.75 63,576.53
Dallas 33,292.32 37,471.29 43,970.59
Denver 45,467.80 51,737.01 58,437.11
Seattle 64,111.50 71,899.23 83,943.86
---------- --------- ---------
303,625.98 341,996.86 409,440.44
========== ========== ==========
PRODUCT: Canoes
------------SALES---------------
------------MONTH---------------
DISTRICT Jan96 Feb96 Mar96
---------------------------------------------
Boston 70,489.44 82,237.68 97,622.28
Atlanta 56,271.40 61,828.33 77,217.62
Chicago 48,661.74 54,424.94 68,815.71
Dallas 35,244.72 40,218.43 46,810.68
Denver 44,456.41 50,623.19 57,013.01
Seattle 67,085.12 74,834.29 87,820.04
---------- --------- ---------
322,208.83 364,166.86 435,299.35
========== ========== ==========
The DBGOUTFILE command (abbreviated DOTF) sends debugging information to a file. When you set PRGTRACE and MODTRACE to YES, the file produced by DBGOUTFILE interweaves each line of your program, model, or infile with its corresponding output. When you set ECHOPROMPT to YES, the debugging file also includes error messages.
Syntax
DBGOUTFILE {EOF | TRACEFILE | [APPEND] file-name [NOCACHE]}
Parameters
Closes the current debugging file, and debugging output is no longer sent to a file.
Specifies that the debugging output should be directed to the Oracle trace file, which is identified by the TRACEFILEUNIT option.
Specifies that the output should be added to the end of an existing file. When you omit this argument and a file exists with the specified name, the new output replaces the current contents of the file.
A text expression that is the name of the file to which debugging output should be written. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Specifies that Oracle OLAP should write to the debugging file each time a line is executed. Without this keyword, Oracle OLAP reduces file I/O activity by saving text and writing it periodically to the file.
The NOCACHE keyword slows performance significantly, but it ensures that the debugging file records every line as soon as it is executed. When you are debugging a program that aborts after a certain line, NOCACHE ensures that you see every line that was executed.
Examples
Example 9-76 Debugging with a Debugging File
The following statements create a useful debugging file called debug.txt in the current directory object.
PRGTRACE = yes ECHOPROMPT = yes DBGOUTFILE 'debug.txt'
After executing these statements, you can run your program as usual. To close the debugging file, execute this statement.
DBGOUTFILE EOF
In the following sample program, the first LIMIT command has a syntax error.
DEFINE ERROR_TRAP PROGRAM PROGRAM TRAP ON traplabel LIMIT month TO FIRST badarg LIMIT product TO FIRST 3 LIMIT district TO FIRST 3 REPORT sales traplabel: SIGNAL ERRORNAME ERRORTEXT END
With PRGTRACE and ECHOPROMPT both set to YES and with DBGOUTFILE set to send debugging output to a file called debug.txt, the following text is sent to the debug.txt file when you execute the error_trap program.
(PRG= ERROR_TRAP) (PRG= ERROR_TRAP) TRAP ON traplabel (PRG= ERROR_TRAP) (PRG: ERROR_TRAP) LIMIT month TO FIRST badarg ERROR: BADARG does not exist in any attached database. (PRG= ERROR_TRAP) traplabel: (PRG= ERROR_TRAP) SIGNAL ERRORNAME ERRORTEXT ERROR: BADARG does not exist in any attached database.
Example 9-77 Sending Debugging Information to a File
The following is the text of a program whose first LIMIT command has a syntax error.
DEFINE error_trap PROGRAM PROGRAM TRAP ON traplabel LIMIT month TO FIRST BADARG LIMIT product TO FIRST 3 LIMIT district TO FIRST 3 REPORT sales traplabel: SIGNAL ERRORNAME ERRORTEXT END
The following statement sends debugging information to a file named debug.txt.
DBGOUTFILE 'debug.txt'
With PRGTRACE and ECHOPROMPT both set to YES, Oracle OLAP sends the following text to the debug.txt file when you execute the ERROR_TRAP program. The last line in the file is the command to stop recording the debugging information.
error_trap (PRG= ERROR_TRAP) (PRG= ERROR_TRAP) trap on traplabel (PRG= ERROR_TRAP) (PRG: ERROR_TRAP) limit month to first badarg ERROR: BADARG does not exist in any attached workspace. (PRG= ERROR_TRAP) traplabel: (PRG= ERROR_TRAP) signal errorname errortext ERROR: BADARG does not exist in any attached workspace. dbgoutfile eof
The WHILE command repeatedly executes a statement while the value of a Boolean expression remains TRUE. You can only use WHILE within a program.
Syntax
WHILE boolean-expression
statement block
Parameters
Serves as the criterion for statement execution. While the expression remains TRUE, statement is repeatedly executed. When the expression becomes FALSE, the execution of statement ceases, and the program continues with the next line. Ensure that something in the statement (or statements) eventually causes the Boolean expression to become FALSE; otherwise, the code becomes an endless loop.
One or more statements to be executed while the Boolean expression is TRUE. You can execute two or more statements by enclosing them within DO ... DOEND brackets. The DO statement should follow immediately after the WHILE statement.
Usage Notes
WHILE Compared to IF
The WHILE statement's main use is as an alternative to the IF...THEN...ELSE comand.When you want one or more statements in your program to execute repeatedly while a Boolean expression remains TRUE, you use WHILE. When you want them to execute only once when a Boolean expression is TRUE, you use IF.
Boolean Constant
You can specify a constant for the Boolean expression. When your statement is WHILE TRUE, make sure to include a BREAK, RETURN, or EXIT statement between DO ... DOEND so the program can finish the loop.
Branching in a Loop
You can use the BREAK, CONTINUE, and GOTO commands to branch within, or out of, a WHILE loop, thereby altering the sequence of statement execution.
Examples
Example 10-176 Using a WHILE Loop in a Program
In the following program lines, the statements following DO are executed when the Boolean expression count LT 10 is TRUE. Within the loop, the code searches for an instance of some condition and, when it finds one, it adds 1 to count. When count reaches 10, the loop ends. The code in the loop must ensure that count will, at some time, reach 10. Otherwise, the loop never ends
WHILE count LT 10
DO
..." (statements)
IF ....
count = count + 1
DOEND
The UPDATE command moves analytic workspace changes from a temporary area to the database table in which the workspace is stored. Typically, you use an UPDATE statement when you are finished making changes in an analytic workspace; however, you can also specify UPDATE commands periodically as you go along.
Your changes are not saved until you execute a COMMIT statement, either from Oracle OLAP or from SQL. When you do not use the UPDATE and COMMIT commands, changes made to an analytic workspace during your session are discarded when you end your Oracle session.
|
Note: You can detach and reattach an analytic workspace without losing updated changes, even though they are not committed because the detaching and reattaching occur within a single database session |
Syntax
UPDATE [MULTI [acquired_objects]] [analytic_workspaces]
Parameters
When you do not specify any parameters, the command updates all analytic workspaces that are attached in read/write non-exclusive and read/write exclusive modes and all acquired objects (that is, all acquired variables, relations, valuesets, and dimensions) in all analytic workspaces that are attached in multiwriter mode.
A list of the names of acquired objects, separated by commas, in analytic workspaces attached in multiwriter mode. These objects can be any object that you have acquired using an ACQUIRE statement.
To specify individual partitions of a partitioned variable, use the following syntax.
variable_name (PARTITION partition_name [, PARTITION partition_name ]...)
|
Important: you cannot update an object when it is dimensioned by an acquired and maintained dimension unless you update that dimension first. |
A list of names, separated by commas. of one or more workspaces attached in read/write or multiwriter mode.
Usage Notes
Automatic COMMIT
Many users execute DML statements using SQL*Plus or OLAP Worksheet. Both of these tools automatically execute a COMMIT statement when you end your session.
Triggering Program Execution When UPDATE Executes
Using the TRIGGER command, you can make an UPDATE statement an event that automatically executes an OLAP DML program. See "Trigger Programs" for more information
Shared Workspaces
When you have attached a shared workspace and another user has read/write access, that user's UPDATE and COMMIT commands do not affect your view of the workspace. Your view of the data remains the same as when you attached the workspace. When you want access to the changes, you can detach the workspace and reattach it.
Effect of a ROLLBACK Statement
The OLAP DML does not provide a way to issue a SQL ROLLBACK statement; however, you could execute one in your session from outside Oracle OLAP (for example, through PL/SQL). When a ROLLBACK statement is executed in your session, Oracle OLAP checks to see whether there are uncommitted updates in an attached workspace.
When there are uncommitted updates (that is, you have made changes and executed an UPDATE statement, but you have not subsequently executed a COMMIT statement), then Oracle OLAP discards your changes and detaches the workspace.
When you have no uncommitted updates, then Oracle OLAP takes no action in response to a ROLLBACK statement. Consequently, when you have not issued an UPDATE statement since your last COMMIT statement, Oracle OLAP takes no action and all your changes remain in the workspace during your session.
When you rollback to a savepoint and there are uncommitted updates that occurred after the savepoint, Oracle OLAP discards those updates and detaches the workspace. Uncommitted updates that occurred before the savepoint remain in the workspace, and you can see them when you reattach the workspace in the same session.
Examples
The TO_DATE function converts a formatted TEXT or NTEXT expression to a DATETIME value.
Return Value
DATETIME
Syntax
TO_DATE(text-exp, [fmt,] [option setting])
Parameters
The text expression that contains a date to be converted. The expression can have the TEXT or NTEXT data type. A conversion from NTEXT can result in an incorrect result when the NTEXT value cannot be interpreted as a date.
A text expression that identifies a datetime format template. This template specifies how the conversion from text to DATETIME should be performed. For information about datetime format templates, see Table 9-4, "Datetime Format Elements".
An OLAP option (such as NLS_DATE_LANGUAGE) and its new setting, which temporarily overrides the setting currently in effect for the session. Typically, this option identifies the language of text-exp when it is different from the session language. See Example 8-140, "Specifying a Default Language and a Date Format".
Do not specify an option that sets other options. For example, do not set NLS_LANGUAGE or NLS_TERRITORY; set NLS_DATE_LANGUAGE instead. While TO_DATE saves and restores the current setting of the specified option so that it has a new value only for the duration of the statement, TO_DATE cannot save and restore any side effects of changing that option. For example, NLS_TERRITORY controls the value of NLS_DATE_FORMAT, NLS_NUMERIC_CHARACTERS, NLS_CURRENCY, NLS_CALENDAR, and other options. When you change the value of NLS_TERRITORY in a call to TO_DATE, all of these options are reset to their territory-appropriate default values twice: once when NLS_TERRITORY is set to its new value for the duration of the TO_DATE statement, and again when the saved value of NLS_TERRITORY is restored.
Usage Notes
Capitalization
Capital letters in words, abbreviation, or Roman numerals in a format element produce corresponding capitalization in the return value. For example, the format element DAY produces MONDAY, Day produces Monday, and day produces monday.
Unrecognized Dates
When TO_DATE cannot construct a value with a valid DATE value using fmt, it returns an error. For example, when an alphanumeric character appears in text-exp where fmt indicates a punctuation character, then an error results.
Examples
Example 8-139 Converting Text Values to DATE Values
The following statement converts January 15, 2002, 11:00 A.M. to the default date format of 15JAN02, and stores that value in a DATE variable named bonusdate.
bonusdate = TO_DATE('January 15, 2002, 11:00 A.M.', -
'Month dd, YYYY, HH:MI A.M.')
Example 8-140 Specifying a Default Language and a Date Format
The following statements set the default language to Spanish and specify a new date format. The NLS_DATE_LANGUAGE option, when used in the TO_DATE function, allows the American month name to be translated.
NLS_DATE_FORMAT = 'Day: Month dd, yyyy HH:MI:SS am'
NLS_DATE_LANGUAGE = 'spanish'
SHOW TO_DATE('November 15, 2001', 'Month dd, yyyy', -
NLS_DATE_LANGUAGE 'american')
The date is translated from American to Spanish and displayed in the new date format.
Jueves : Noviembre 15, 2001 12:00:00 AM
The SYSTEM function identifies the platform on which Oracle OLAP is running.
Data Type
TEXT
Syntax
SYSTEM
Usage Notes
Relevance of the Platform
Because Oracle OLAP is incorporated in the Oracle Database, the operating system on which it is running should not be an important factor in its behavior.
|
Note: All references to external files are made through directory objects, which are not platform specific |
Examples
The INLIST function determines whether every line of a text value is a line in a second text value. Normally, INLIST is used to determine whether all the lines of a list (in the form of a multiline text value) can be found in a master list (in the form of a second multiline text value).
INLIST accepts TEXT values and NTEXT values as arguments. When only one argument is NTEXT, then INLIST automatically converts the other argument to NTEXT before performing the function operation.
Return Value
BOOLEAN
Syntax
INLIST(masterlist list)
Parameters
A multiline text expression to which the lines of list are compared.
A multiline text expression whose lines are compared with the lines of masterlist. When every line of list can be found as a line of masterlist, INLIST returns the value YES. When one or more lines of list are not found in masterlist, INLIST returns the value NO.
Examples
Example 7-118 Comparing a List to a Master List
This example shows how to use INLIST to determine whether the lines of one list can be found in a master list. The master list in this case is a multiline text value in a variable called depts. The depts variable has the following values.
Marketing Purchasing Accounting Engineering Personnel
The first function call compares a list, which is specified as a text literal, with the master list. The return value is YES.
INLIST(depts, 'Accounting\nPersonnel')
The second function call compares a variable newlist that has the following values,
Development Accounting
with the master list in depts. The return value is NO.
INLIST(depts, newlist)
The MOVINGMIN function (abbreviated MVMIN) returns a series of minimum values for the values of a dimensioned variable or expression over a specified dimension. For each dimension value in status, MOVINGMIN searches the data for the minimum value in the range specified, relative to the current dimension value.
When the variable or expression has only the specified dimension, MOVINGMIN produces a single series of minimum values, one for each dimension value in the status. When the variable or expression has dimensions other than the one specified, MOVINGMIN produces a separate series of minimum values for each combination of values in the status list of the other dimensions.
Return Value
DECIMAL when the data type of expression is DECIMAL or SHORT; otherwise, NUMBER.
Syntax
MOVINGMIN(expression, start, stop, step, [dimension [STATUS|limit-clause]])
Parameters
A numeric variable or calculation from whose values you want to find the minimum values; for example, UNITS or SALES-EXPENSE.
Integer values that specify the range of values over which you want to find minimum values. The value of start specifies the beginning of the range. The value of stop specifies the end of the range. Specify the values of start and stop relative to the current value of dimension. To specify a negative position for start or stop preceed the value with a comma. Thus, you specify zero (0) for the current dimension value, and -1 for the value preceding the current value. (See also "How the Moving Functions Handle Out-of-Range and NA Values".)
|
Note: By default this function uses the default status list when identifying the range of values to average. You can specify either the STATUS or limit-clause phrase to change this behavior. |
|
Tip: When you want to range to the end of status, for convience and to document your intent, specify the value of stop as OBJ function with the DIMMAX keyword |
A positive whole number that specifies whether to search every value in the range, or every other value, or every third value, and so on. A value of 1 for step means search every value. A value of 2 means check the first value, the third value, the fifth value, and so on. For example, when the current month is Jun96 and the start and stop values are -3 and 3, a step value of 2 means search the months Mar96, May96, Jul96 and Sep96 and return the minimum value that occurs in one of those four months.
The dimension over which the moving minimum is calculated. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, Quarter, or YEAR.
When expression has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want MOVINGMIN to use that dimension, you can omit the dimension argument.
Specifies that MOVINGMIN should use the current status list (that is, only the dimension values currently in status in their current status order) when calculating the moving minimum.
Specifies that MOVINGMIN uses the values specified by a LIMIT function or those specified with the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
Examples
For an example of calculating minimum sales, see Example 8-31, "Calculating a Moving Average".
The TRIGGER function retrieves the event, subevent, or name of the object or analytic workspace that caused the execution of a trigger program (that is, a TRIGGER_DEFINE, TRIGGER_AFTER_UPDATE, or TRIGGER_BEFORE_UPDATE program, or any program identified as a trigger program using the TRIGGER command).
When the current program is a trigger program, the TRIGGER function returns the trigger information for that program. When it is not, the TRIGGER function returns trigger information for the most recently executed trigger program.
Return Values
TEXT
Syntax
TRIGGER (NAME | EVENT | SUBEVENT)
Parameters
For a program identified as a trigger program using the TRIGGER command, returns the object for which the trigger program is association. For a TRIGGER_AW, TRIGGER_DEFINE, TRIGGER_AFTER_UPDATE, or TRIGGER_BEFORE_UPDATE program, returns the name of the analytic workspace that caused the program to execute.
Returns the name of the event (DML statement) that triggered the execution of the program.
When the value returned by EVENT is MAINTAIN, AFTER_UPDATE or BEFORE_UPDATE, returns more information on the OLAP DML statement that triggered the execution of the program. Valid subevents for AW are outlined in Table 8-18, "Subevents for the AW Event". Valid subevents for MAINTAIN are outlined in Table 8-19, "Subevents for the MAINTAIN Event". Valid subevents for UPDATE are outlined in Table 8-20, "Subevents for UPDATE Events".
Table 8-18 Subevents for the AW Event
| Subevent | Description |
|---|---|
|
CREATE |
Returned when a AW CREATE statement triggered the execution of the program. |
|
ATTACH |
Returned when a AW ATTACH statement triggered the execution of the program. |
|
DELETE |
Returned when a AW DELETE statement triggered the execution of the program. |
|
DETACH |
Returned when a AW DETACH statement triggered the execution of the program. |
Table 8-19 Subevents for the MAINTAIN Event
| Subevent | Description |
|---|---|
|
ADD |
Returned when a MAINTAIN ADD statement triggered the execution of the program. |
|
DELETE |
Returned when any MAINTAIN DELETE statement except a MAINTAIN DELETE ALL statement triggered the execution of the program. |
|
DELETE ALL |
Returned when a MAINTAIN DELETE ALL statement triggered the execution of the program. |
|
MERGE |
Returned when a MAINTAIN MERGE statement triggered the execution of the program. |
|
MOVE |
Returned when a MAINTAIN MOVE statement triggered the execution of the program. |
|
RENAME |
Returned when a MAINTAIN RENAME statement triggered the execution of the program. |
Table 8-20 Subevents for UPDATE Events
| Subevent | Description |
|---|---|
|
AW |
Returned when an UPDATE command triggered the execution of a TRIGGER_AFTER_UPDATE or TRIGGER_BEFORE_UPDATE program. |
|
MULTI |
Returned when an UPDATE command triggered the execution of a program identified as a trigger program using the TRIGGER command when an object is acquired in multiwriter mode. |
Examples
For examples of using the TRIGGER function, see Example 6-3, "TRIGGER_BEFORE_UPDATE Program" and Example 10-166, "Assigning an Alternative Value using an Assign Trigger".
The ADVISE_REL procedure helps you determine how to preaggregate a dimension in an analytic workspace. When you specify a percentage of the dimension to preaggregate, ADVISE_REL recommends a set of dimension members.
The ADVISE_REL procedure takes a family relation, a valueset, and a precompute percentage as input. The family relation is an object that specifies the hierarchical relationships between the members of a dimension. The valueset must be defined from the dimension to be analyzed. Based on the precompute percentage that you specify, ADVISE_REL returns a set of dimension members in the valueset.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_REL (
family_relation_name IN VARCHAR2,
valueset_name IN VARCHAR2,
precompute_percentage IN INTEGER DEFAULT 20,
compressed IN BOOLEAN DEFAULT FALSE);
Parameters
Table B-8 ADVISE_REL Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of a family relation, which specifies a dimension and the hierarchical relationships between the dimension members. |
|
|
The name of a valueset to contain the results of the procedure. The valueset must be defined from the dimension in the family relation. If the valueset is not empty, |
|
|
A percentage of the dimension to preaggregate. The default is 20%. |
|
|
Controls whether the advice is for a regular composite ( |
The ABS function calculates the absolute value of an expression. Since, the absolute value of a real number is its numeric value without regard to its sign (for example, 3 is the absolute value of both 3 and -3), this function always returns a positive value.
Return Value
DECIMAL.
The dimensionality of the result is the same as the specified expression.
Syntax
ABS(expression)
Parameters
The expression whose absolute value is to be calculated.
Examples
Example 7-1 Finding Values in an Absolute Range
Suppose you are interested in how close your planned 1996 sales figures for sportswear in Boston were to the actual sales. You would like to see those months where budgeted figures are off by more than $5,000 in either direction. You can use ABS to help you find those months.
LIMIT product TO 'Sportswear' LIMIT district TO 'Boston' LIMIT month TO YEAR 'Yr96' LIMIT month KEEP ABS(sales - sales.plan) GT 5000 REPORT DOWN month sales sales.plan sales - sales.plan
These statements produce the following output.
DISTRICT: BOSTON
------------PRODUCT-------------
-----------SPORTSWEAR-----------
SALES -
MONTH SALES SALES.PLAN SALES.PLAN
-------------- ---------- ---------- ----------
Jun96 79,630.20 73,568.52 6,061.68
Jul96 95,707.30 80,744.18 14,963.12
Aug96 82,004.00 71,811.45 10,192.55
Sep96 89,988.60 78,282.07 11,706.53
Dec96 50,281.40 56,720.87 -6,439.47
The PERCENTAGE function computes the percent of total for each value in a numeric expression.
Return Value
DECIMAL
Syntax
PERCENTAGE(expression [CACHE] [BASEDON dimension-list])
Parameters
The numeric expression for which percent figures are to be computed.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
An optional list of one or more of the dimensions of expression on which to base the percentage for each value. When you do not specify the dimensions, then PERCENTAGE bases the percentage on the total of all of the values of all of the dimensions of expression.
Usage Notes
The Effect of NASKIP on PERCENTAGE
PERCENTAGE is affected by the NASKIP option. When NASKIP is set to YES (the default), then PERCENTAGE ignores NA values. When NASKIP is set to NO, then PERCENTAGE returns NA for any cell in expression whose value is NA.
Examples
Example 8-61 Calculating the Percentage
The following statements s limit the month and district dimensions, and report the data values, with subtotals, for the units variable.
LIMIT month TO 'Jul96' TO 'Sep96' LIMIT district TO 'Denver' REPORT SUBTOTALS W 8 units
The preceding statement produces the following output.
DISTRICT: DENVER
----------UNITS-----------
----------MONTH-----------
PRODUCT Jul96 Aug96 Sep96
-------------- -------- -------- --------
Tents 608 517 441
Canoes 467 363 411
Racquets 3,006 2,836 2,838
Sportswear 2,395 2,039 2,138
Footwear 1,581 1,532 1,667
-------------- -------- -------- --------
TOTAL DENVER 8,057 7,287 7,495
This statement reports the percentage that each month value represents of the total month values for each of the product values that are in status. The total of the values that PERCENTAGE returns for each product value is 1.
REPORT SUBTOTALS W 8 DOWN month PERCENTAGE(units BASEDON month)
DISTRICT: DENVER
-----------PERCENTAGE(UNITS BASEDON MONTH)------------
-----------------------PRODUCT------------------------
MONTH Tents Canoes Racquets Sportswear Footwear
-------- ---------- ---------- ---------- ---------- ----------
Jul96 0.39 0.38 0.35 0.36 0.33
Aug96 0.33 0.29 0.33 0.31 0.32
Sep96 0.28 0.33 0.33 0.33 0.35
-------- ---------- ---------- ---------- ---------- ----------
TOTAL 1.00 1.00 1.00 1.00 1.00
DENVER
This statement reports the percentage that each product value represents of the total product values for each of the month values that are in status.
REPORT SUBTOTALS W 8 PERCENTAGE(units BASEDON product)
DISTRICT: DENVER
-PERCENTAGE(UNITS BASEDON-
---------PRODUCT)---------
----------MONTH-----------
PRODUCT Jul96 Aug96 Sep96
-------------- -------- -------- --------
Tents 0.08 0.07 0.06
Canoes 0.06 0.05 0.05
Racquets 0.37 0.39 0.38
Sportswear 0.30 0.28 0.29
Footwear 0.20 0.21 0.22
-------------- -------- -------- --------
TOTAL DENVER 1.00 1.00 1.00
This statement reports the percentage based on all of the dimensions of the units variable. The total of all of the values that PERCENTAGE returns is 1.
REPORT SUBTOTALS W 8 PERCENTAGE(units)
DISTRICT: DENVER
----PERCENTAGE(UNITS)-----
----------MONTH-----------
PRODUCT Jul96 Aug96 Sep96
-------------- -------- -------- --------
Tents 0.03 0.02 0.02
Canoes 0.02 0.02 0.02
Racquets 0.13 0.12 0.12
Sportswear 0.10 0.09 0.09
Footwear 0.07 0.07 0.07
-------------- -------- -------- --------
TOTAL DENVER 0.35 0.32 0.33
The total for all of the values for both the product and month dimensions is 1.00.
The DEPRSL function calculates the depreciation expenses for a series of assets. DEPRSL uses the straight-line method, as described in "DEPRSL Calculation Method", to depreciate the assets over the specified lifetime of the assets. The starting and ending values are specified for the assets acquired in each time period.
Return Value
DECIMAL, dimensioned by all the dimensions of start-exp.
Syntax
DEPRSL(start-exp end-exp n [STATUS] [{FULL|HALF| portion-exp} [time-dimension]])
Parameters
A numeric expression that contains the starting values of the assets. The start-exp expression must be dimensioned by a time dimension. For each value of the time dimension, start-exp contains the initial value of the assets acquired during that time period. In addition to a time dimension, start-exp can also have non-time dimensions.
A numeric expression that contains the ending values of the assets. The end-exp expression must be dimensioned by the same dimensions as start-exp. For each value of the time dimension, end-exp contains the final (or salvage) value for the assets acquired during that time period. Each value of start-exp must have a corresponding end-exp value. For example, when the assets acquired in 1995 have a salvage value of $200, then the value of end-exp for 1995 is $200.
An INTEGER expression that contains the depreciation lifetime of the assets. The n expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
Specifies that DEPRSL should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the depreciation expenses. By default DEPRSL uses the default status list.
(Default) Specifies that the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges the full amount to all of the assets in the series.
Specifies that half of the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges half the full amount to all of the assets in the series. When you specify HALF as the portion of depreciation expenses to charge to the period of acquisition, the HALF factor is applied to each period. Half of each period's full depreciation expense is rolled to the next period, and the final half period of depreciation takes place in the time period n + 1. You might want to use HALF when assets are acquired during the second half of the time period.
When you want to charge the full amount for some assets and half the amount for other assets, you can supply a portion-exp expression that is dimensioned by any of the non-time dimensions of start-exp. The portion-exp expression must be a text expression with values of FULL or HALF.
The name of the time dimension by which start-exp and end-exp are dimensioned. When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional.
Usage Notes
DEPRSL Calculation Method
DEPRSL calculates the depreciation expense for a given time period as the sum of that period's depreciation expenses for all assets in the series that are not yet fully depreciated. The first period of depreciation for an asset is the period in which it was acquired.
DEPRSL and NA Values
When a value of start-exp is NA and the corresponding value of end-exp is not NA, an error occurs. Similarly, when a value of end-exp is NA and the corresponding value of start-exp is not NA, an error occurs.
DEPRSL is affected by the NASKIP option when a value of start-exp and the corresponding value of end-exp are both NA. When NASKIP is YES (the default), DEPRSL treats the values as zeros when calculating the depreciation expenses. When NASKIP is NO, DEPRSL returns NA for all affected time periods.
Examples
Example 7-71 Using DEPRSL to Calculate Depreciation Expenses for Assets Acquired in a Single Period
This example shows how to use DEPRSL to calculate depreciation expenses for assets acquired in a single time period.
The following statements create two variables called assets and salvage.
DEFINE assets DECIMAL <year> DEFINE salvage DECIMAL <year>
Suppose you assign the following values to the variables assets and salvage.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 0.00 0.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00
The variable assets contains the starting value of assets acquired in 1995. The variable salvage contains the ending value of the assets acquired in 1995.
The following statement reports the values of assets and salvage, and uses DEPRSL to calculate depreciation expenses for each year, specifying an asset lifetime of 5 years.
REPORT assets salvage W 12 HEADING 'Depreciation' - DEPRSL(assets salvage 5 FULL year)
This statement produces the following output.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100.00 180.00 Yr96 0.00 0.00 180.00 Yr97 0.00 0.00 180.00 Yr98 0.00 0.00 180.00 Yr99 0.00 0.00 180.00 Yr00 0.00 0.00 0.00
Example 7-72 Using DEPRSL to Calculate the Depreciation Expenses for Assets Acquired in Multiple Periods
You can also use DEPRSL to calculate the depreciation expenses for a series of assets. Suppose you change the values for the year 1997 in the variables assets and salvage to the values shown in the following report.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 500.00 50.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00 Yr01 0.00 0.00 Yr02 0.00 0.00
Now assets and salvage contain nonzero values for 1995 and for 1997.
The following statement reports asset and salvage values along with depreciation expenses for the assets. Note that the call to DEPRSL to calculate the depreciation expenses specifies an asset lifetime of 5 periods (in this case, years).
REPORT assets salvage W 12 HEADING 'Depreciation' -
DEPRSL(assets salvage 5 FULL year)
This statement produces the following report.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ------------- -------------------- Yr95 1,000.00 100.00 180.00 Yr96 0.00 0.00 180.00 Yr97 500.00 50.00 270.00 Yr98 0.00 0.00 270.00 Yr99 0.00 0.00 270.00 Yr00 0.00 0.00 90.00 Yr01 0.00 0.00 90.00 Yr02 0.00 0.00 0.00
The assets acquired in 1995 were fully depreciated in 1999. Therefore, for 2000 and 2001, DEPRSL returns a figure that includes the depreciation expense for the assets acquired in 1997 only.
The BASEVAL function loops over a concat dimension and returns the values of the base dimensions of a concat dimension. When a base dimension is a concat dimension, then the values of its base dimensions are returned, also.
Return Value
The following are the rules that determine the data types of the values returned by BASEVAL:
The data type of the return value is NTEXT when any of the component dimensions of concatdim is of type NTEXT, or when any component dimension is a conjoint that uses a simple dimension of type NTEXT.
The data type of the return value is the data type of the component dimensions when all of the component dimensions have the same data type and when none of the component dimensions is a conjoint.
The data type of the return value is TEXT in all other cases.
Syntax
BASEVAL(concatdim)
Parameters
Specifies the concat dimension for which you want the base values. The data types of the values returned depend on the data types of the base dimensions of the concat dimension.
Examples
Example 7-30 Returning NTEXT Values
The following example creates two simple dimensions and a nonunique concat dimension, then gets the values of the concat dimension.
DEFINE textdim DIMENSION TEXT DEFINE ntextdim DIMENSION NTEXT MAINTAIN textdim ADD 'v1' 'v2' MAINTAIN ntextdim ADD 'n1' 'n2' DEFINE concatdim DIMENSION CONCAT(textdim ntextdim) REPORT w 18 BASEVAL(concatdim)
The preceding statement returns the following.
CONCATDIM BASEVAL(CONCATDIM) -------------------- ------------------ <textdim: v1> v1 <textdim: v2> v2 <ntextdim: n1> n1 <ntextdim: n2> n2
The data type of the returned values is NTEXT. The BASEVAL function converted the v1 and v2 TEXT values into NTEXT values before returning them.
Example 7-31 Returning the Base Values of a Base Concat Dimension
This example defines the simple dimensions state and city and adds values to them. It defines a nonunique concat dimension, statecity, with state and city as the bases and then defines another nonunique concat dimension, geog, with region, district, and statecity as its bases. Finally, the REPORT statement returns the values returned by the BASEVAL function.
DEFINE city DIMENSION TEXT DEFINE state DIMENSION TEXT MAINTAIN city ADD 'Boston' 'Worcester' 'Portsmouth' 'Portland' - 'Burlington' 'Hartford' 'New York' 'Albany' MAINTAIN state ADD 'MA' 'NH' 'ME' 'VT' 'CT' 'NY' DEFINE statecity DIMENSION CONCAT(state city) DEFINE geog DIMENSION CONCAT(region district statecity) LCOLWIDTH = 20 REPORT W 16 BASEVAL(geog)
The preceding statement returns the following.
GEOG BASEVAL(GEOG) -------------------- ---------------- <region: East> East <region: Central> Central <region: West> West <district: Boston> Boston <district: Atlanta> Atlanta <district: Chicago> Chicago <district: Dallas> Dallas <district: Denver> Denver <district: Seattle> Seattle <state: MA> MA <state: NH> NH <state: ME> ME <state: VT> VT <state: CT> CT <state: NY> NY <city: Boston> Boston <city: Worcester> Worcester <city: Portsmouth> Portsmouth <city: Portland> Portland <city: Burlington> Burlington <city: Hartford> Hartford <city: New York> New York <city: Albany> Albany
The CATEGORIZE function groups the values of a numeric expression into categories. You define the categories by specifying a series of increasing numeric values. The result that CATEGORIZE returns is dimensioned by all the dimensions of expression. For each cell in expression, CATEGORIZE returns one of the following: the category in which the number falls, zero (0) for a value below the range of the first category, minus one (-1) for a value above the range of the last category, or NA for an NA value.
Return Value
DECIMAL
Syntax
CATEGORIZE(expression {values|group-expression})
where values has the following syntax:
bottom-value [next-lowest-break-value] top-value
Parameters
The numeric expression whose values are to be categorized.
A number that specifies the lowest number in the series and sets the bottom limit of category 1.
A number that specifies the beginning of the range of the next category.
A number that specifies the highest number in the series and sets the upper limit of the highest category.
A one-dimensional numeric expression that defines the break values for the categories.
Examples
Example 7-36 Specifying Category Range Values
Assume that your analytic workspace contains the following geography and items dimensions and sales2 variable.
DEFINE geography DIMENSION TEXT MAINTAIN geography ADD 'g1' 'g2' 'g3' DEFINE items DIMENSION TEXT MAINTAIN items ADD 'Item1' 'Item2' 'Item3' 'Item4' 'Item5' DEFINE sales2 DECIMAL <geography items>
Assume the sales2 variable has the following data values.
-------------SALES2-------------
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 30.00 15.00 12.00
Item2 10.00 20.00 18.00
Item3 15.00 20.00 24.00
Item4 30.00 25.00 25.00
Item5 NA 7.00 21.00
This statement reports the result of categorizing the sales2 variable.
REPORT CATEGORIZE(sales2 10 15 20 25)
The preceding statement produces the following output.
-CATEGORIZE(SALES2 10 15 20 25)-
-----------GEOGRAPHY------------
ITEMS g1 g2 g3
-------------- ---------- ---------- ----------
Item1 -1.00 2.00 1.00
Item2 1.00 3.00 2.00
Item3 2.00 3.00 3.00
Item4 -1.00 3.00 3.00
Item5 NA 0.00 3.00
Example 7-37 Specifying a Group-Expression
These statements define a groups dimension and a groupval variable.
DEFINE groups DIMENSION TEXT MAINTAIN groups ADD 'Grp1' 'Grp2' 'Grp3' 'Grp4' DEFINE groupvals DECIMAL <groups> groupvals(groups 'Grp1') = 10 groupvals(groups 'Grp2') = 15 groupvals(groups 'Grp3') = 20 groupvals(groups 'Grp4') = 25
This statement reports the result of calling the CATEGORIZE function with the sales variable as the expression argument and the groupvals variable as the group-expression argument of the call.
REPORT CATEGORIZE(sales, groupvals)
The preceding statement produces the same output as the statement in the "Specifying Category Range Values" .
The ARCCOS function calculates the angle value (in radians) of a specified cosine.
Return Value
NUMBER
Syntax
ARCCOS(expression)
Parameters
An expression that contains the decimal value of a cosine.
Usage Notes
Invalid Cosine Values
When you provide an ineligible value for the cosine expression (that is, a value greater than 1 or less than -1), ARCCOS returns a value of NA.
Examples
The FILTERLINES function applies a filter expression that you create to each line of a multiline text expression.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
FILTERLINES(source-expression filter-expression)
Parameters
A multiline text expression whose lines should be modified according to filter-expression.
An expression to be applied as a filter to each line of source-expression. The terms of the filter expression dictate the processing that FILTERLINES performs on each line of the source expression.
The filter expression may produce NA, which means that there is no line in the resulting text expression corresponding to the current line of the source expression.
You can use the keyword VALUE in your filter expression to represent the current line of the source expression.
Usage Notes
The Result of FILTERLINES
FILTERLINES returns a text expression composed of the lines that result from the action of the filter expression on each line of the source expression. The filter expression may return multiline text for any or all of the input source lines. None of these lines are acted on again by the filter expression.
Examples
Example 7-94 Removing Extension From File Names
The following example shows how FILTERLINES could be used on a list of file names to produce a list of those same file names without extensions.
With a multiline text variable named filelist that evaluates to
myfile1.txt file2.txt myfile3 file4.txt
the statement
SHOW FILTERLINES(FILELIST -
IF FINDCHARS(VALUE '.') GT 0 -
THEN EXTCHARS(VALUE 1 FINDCHARS(VALUE '.') -1) -
ELSE VALUE)
produces the following output.
myfile1 file2 myfile3 file4
The $GID_TYPE property, which is automatically created and set when a GROUPINGID command with either the ROLLUP or GROUPSET keyword populates a grouping id relation, specifies whether the grouping type of the grouping ids.
Syntax
You cannot explicitly define a $GID_TYPE property. Oracle OLAP automatically creates a $GID_TYPE property on a grouping id relation when the execution of a GROUPIONGID command with either the ROLLUP or GROUPSET keyword creates the relation.
$GID_TYPE = ROLLUP | GROUPSET
Parameters
Specifies that the grouping ids are of the rollup type.
For more information on this type of grouping type, see the discussion of ROLLUP in the rollup cube clause of a SQL SELECT statement in Oracle Database SQL Language Reference.
Specifies that the grouping ids are of the grouping set type.
For more information on this type of grouping type, see the discussion of grouping sets in the grouping sets clause of a SQL SELECT statement in Oracle Database SQL Language Reference.
The $STORETRIGGERVAL property specifies if, when a $NATRIGGER expression executes, Oracle OLAP replaces the NA values in the variable with the results of the expression.
|
Note: Applications typically use the $VARCACHE property rather than the $STORETRIGGERVAL property since the functionality of the $STORETRIGGERVAL property is subsumed within the $VARCACHE property. |
Syntax
You add or delete a $STORETRIGGERVAL property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$STORETRIGGERVAL' value
To delete the property, issue the following statement.
PROPERTY DELETE '$ASTORETRIGGERVAL'
Parameters
A BOOLEAN expression that contains the value of the property.
Examples
The INITCAP function returns a specified text expression, with the first letter of each word in uppercase and all other letters in lowercase. Words are delimited by white space or characters that are not alphanumeric.
Return Value
The same data type as the expression.
Syntax
INITCAP (text-exp)
Parameters
A text expression.
Examples
The REDO command re-executes a statement that you entered earlier in your session. The statement is retrieved from the command log, which is a list of up to 256 statements that you have entered most recently during the current session. REDO enables you to changes in the statement before it is re-executed.
|
Note: REDO statements themselves are not included in the command log; however, the statements re-executed by REDO are included. |
Syntax
REDO [number|index] 'original' 'replacement' [specifier]
Parameters
A positive INTEGER that indicates the number of the statement to be re-executed. You can display the statements, with their numbers, using a RECAP statement.
A negative INTEGER or 0 (zero) that indicates the position of the statement to be re-executed relative to the end of the command log. The most recent statement is 0, the one before that is -1, and so on. The default is 0.
A text literal that is part of the statement to be re-executed.
A text literal that should replace original when the statement is re-executed.
A specifier listed in Table 10-2, "Valid Values for REDO specifier". Each specifier indicates where text replacement should occur in the re-executed statement.
Table 10-2 Valid Values for REDO specifier
| Specifier | Meaning |
|---|---|
|
|
Indicates that only the first occurrence of original should be changed to replacement. |
|
|
Indicates that only the last occurrence of original should be changed to replacement. |
|
n |
A number indicating which occurrence of original should be changed to replacement. For example, |
|
|
Indicates that all occurrences of original should be changed to replacement |
|
|
Indicates that all occurrences of original should be changed to replacement. |
The default is ALL. When you do not provide a specifier, all occurrences of original are changed to replacement.
Usage Notes
REDO with No Argument
When you type REDO without an argument, the most recent statement are re-executed.
Case-Sensitivity
When matching original with the text of the statement to be re-executed, REDO ignores case differences. For example, assume you specify AT as original, REDO matches it with at, At, aT, or AT in the statement.
When replacing original with replacement, REDO retains the case of all characters in replacement. For example, assume you specify ShOw as replacement, that is exactly how it appears in the re-executed statement.
Examples
The CHANGEBYTES function changes one or more occurrences of a specified string in a text expression to another string.
Return Value
TEXT
Syntax
CHANGEBYTES(text-expression oldtext newtext [number])
Parameters
A TEXT expression in which bytes are to be changed. When text-expression is a multiline TEXT expression, CHANGEBYTES preserves the line breaks in the returned value.
A TEXT expression that contains one or more bytes that to be changed.
A TEXT expression that contains one or more bytes that to replace oldtext.
An INTEGER that represents the number of times oldtext should be replaced with newtext when oldtext appears more than once in text-expression. The default is to change all occurrences of oldtext.
Examples
The SQRT function computes the square root of an expression.
Return Value
DECIMAL
Syntax
SQRT(expression)
Parameters
The numeric expression whose square root is to be computed.
Usage Notes
Negative Expressions
When expression is negative and ROOTOFNEGATIVE is set to NO, an error occurs. When expression is negative and ROOTOFNEGATIVE is set to YES, SQRT returns the value NA.
Examples
The TO_TIMESTAMP function converts text data to a value of TIMESTAMP data type.
Return Values
TIMESTAMP
Syntax
TO_TIMESTAMP(char-exp [, fmt [ 'nlsparam' ] ])
Parameters
A text expression that you wan to convert.
Specifies the datetime format template to be used to convert the text expression. See Table 9-4, "Datetime Format Elements" for more information about the datetime format template.
When you omit this argument, the function uses the default format of TIMESTAMP for the object.
Specifies the language in which month and day names and abbreviations are returned. This argument can have this form:
'NLS_DATE_LANGUAGE = language'
If you omit this argument, then this function uses the default date language for your session.
Examples
Example 8-145 Converting To and Extracting From Timestamp Data
SHOW NLS_DATE_FORMAT
DD-MON-RR
SHOW TO_TIMESTAMP('10-SEP-0614:10:10:10.123000' 'DD MON RR HH24:MI:SS.FF')
10-SEP-14 10.10.10.123 AM
SHOW TO_TIMESTAMP_TZ ('2006-03-26 7:33:00 -4:00', 'YYYY-MM-DD HH:MI:SS TZH:TZM')
26-MAR-06 07.33.00 AM -04:00
DEFINE mytimestamp VARIABLE TIMESTAMP
DEFINE mytimezone VARIABLE TEXT
DEFINE mytimestamptz VARIABLE TIMESTAMP_TZ
mytimestamp = '26-MAR-06'
mytimezone = '-04:00'
mytimestamptz = FROM_TZ (mytimestamp mytimezone)
REPORT mytimestamptz
MYTIMESTAMPTZ
------------------------------
26-MAR-06 12.00.00 AM -04:00
SHOW EXTRACT (TIMEZONE_HOUR FROM mytimestamptz)
-4.00
The $AGGREGATE_FROMVAR property specifies the same behavior as that specified by a FROMVAR clause in an AGGREGATE command or an AGGREGATE function. By adding an $AGGREGATE_FROMVAR property to a variable you can ensure this behavior when the variable is aggregated — even when it is aggregated by an AGGREGATE statement does not include the FROMVAR clause.
Both the $AGGREGATE_FROMVAR property and the FROMVAR clause specify two or more objects from which Oracle OLAP obtains the detail data for the aggregation.
Syntax
You add or delete an $AGGREGATE_FROMVAR property to the most recently defined or considered object (see DEFINE and CONSIDER commands) by issuing a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$AGGREGATE_FROMVAR' textvar ACROSS dimname
To delete the property, issue the following statement.
PROPERTY DELETE '$AGGREGATE_FROMVAR'
Parameters
A TEXT expression that specifies an arbitrarily dimensioned variable or formula that specifies the names of the objects from which to obtain detail data when performing a capstone aggregation. Specify NA to indicate that a node does not need detail data to calculate the value.
Specifies the dimension or a named composite that the aggregation loops over to discover the cells in the objects specified by textvar. Because the objects specified by textvar can be formulas, you can realize a significant performance advantage by supplying a looping dimension that eliminates the sparsity.
Examples
Example 4-4 Capstone Aggregation Using the $AGGREGATE_FROMVAR Property
Example 9-32, "Capstone Aggregation" uses the following AGGREGATE command to perform the final capstone aggregation.
AGGREGATE sales_capstone76 USING capstone_aggmap FROMVAR capstone_source
As the following statements illustrate, you can omit the FROMVAR clause if you create the appropriate FROMVAR property on sales-capstone76.
CONSIDER sales_capstone76 PROPERTY '$AGGREGATE_FROMVAR' 'capstone_source' AGGREGATE sales_capstone76 USING capstone_aggmap
The LIMIT.SORTREL option controls if a sort is done when you limit a dimension to a related dimension.
Data Type
BOOLEAN
Syntax
LIMIT.SORTREL = {YES|NO}
Parameters
(Default) Oracle OLAP performs a sort when you limit a dimension to a related dimension.
Oracle OLAP does not perform a sort when limiting to a related dimension.
Usage Notes
The Sorting Explained
Normally, when you limit a dimension to a related dimension, the values of the dimension being limited are arranged in the order of the related dimension. When there are multiple values of the first dimension related to a value of the related dimension, the values are sorted in the order of the default status of the first dimension. It is this sort that LIMIT.SORTREL suppresses.
Output Lists when LIMIT.SORTREL Is NO
When LIMIT.SORTREL is NO, the output for any given dimension may not list values in logical order.
Examples
Example 5-43 Efficient Processing
You are performing calculations on a variable dimensioned by a large dimension named product. Your product dimension has all levels of the product hierarchy embedded in it: category, vendor, brand, and so on. You are performing the calculations one level at a time, using the relationship between product and productlevel. Because the order of the dimension values is not important for the calculations and because you are limiting product using a related dimension, you use LIMIT.SORTREL to suppress unnecessary sorting which makes the process more efficient.
LIMIT.SORTREL = NO
The syntax of the AW command varies depending on the task that you want to perform.
Usage Notes
Triggering Program Execution When an AW Statement Executes
When a program named TRIGGER_AW exists in an analytic workspace, the execution of an AW statement for that workspace automatically executes that program. See "Trigger Programs" and the TRIGGER_AW program, for more information.
When an AW ATTACH statement executes Oracle OLAP checks for other programs as well. See "Startup Programs" for more information.
Options Related to the AW Statement
"Analytic Workspace Options" lists the options that you might want to reset before you either create or attach an analytic workspace.
EXPRESS Workspace
When your Database is installed with the OLAP option, the EXPRESS workspace is always attached in read-only mode in your session. It never automatically becomes the current workspace, even when it is the first or only workspace in your workspace list, because it is for internal use by Oracle OLAP. You can make the EXPRESS workspace the current workspace by explicitly attaching it, but this is not recommended. You cannot detach the EXPRESS workspace.
The AW ALIASLIST command assigns or deletes one or more workspace alias for the specified attached workspace or, when no workspace is specified, for the current workspace. ALIAS indicates that the alias or aliases should be assigned, and UNALIAS indicates that the alias or aliases should be deleted. All aliases for a given workspace are automatically deleted when you detach an analytic workspace.
Syntax
AW ALIASLIST [workspace] {ALIAS|UNALIAS} alias1, alias2, ...
Parameters
The name of the analytic workspace. You can specify either an analytic workspace name or an analytic workspace alias, depending on the keywords you are using.
Assigns one or more workspace alias for the specified attached workspace or, when no workspace is specified, for the current workspace. ALIAS indicates that the alias or aliases should be assigned, and UNALIAS indicates that the alias or aliases should be deleted.
All aliases for a given workspace are automatically deleted when you detach an analytic workspace. Therefore, each time you attach an unattached workspace, you must reassign its aliases.
Deletes one or more workspace alias for the specified attached workspace or, when no workspace is specified, for the current workspace.
The alias name for the analytic workspace. Alias names:
Can be from 1 - 26 characters in length. All characters must come from the database character set and must be letters, numerals, or underscores.
Cannot begin with a numeral and cannot be reserved words in the DML. (Use RESERVED to identify reserved words.)
Examples
Example 9-49 Assigning an Alias
The following statement assigns sdemo as an alias for the demo workspace, which was created by a user named scott. The full name of the workspace is specified because the current user is not scott.
AW ALIASLIST scott.demo ALIAS sdemo
In the following statement, the user named scott assigns mydemo as an alias for the same workspace.
AW ALIASLIST demo ALIAS mydemo
The AW ATTACH command attaches an analytic workspace to your session. Oracle OLAP makes the specified workspace the current one. Previously attached workspaces move down in the list of attached workspaces to make room for the new current one at the top of the list. When there is a cached version of the requested analytic workspace then the cached version is moved back to the list of attached workspaces unless, of course, the current version of the analytic workspace is more recent than the cached version.
When you attach multiple workspaces, the code and data in all the attached workspaces are available during your session. The current workspace is first on the workspace list, which Oracle OLAP keeps for your session.
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Note: When an AW ATTACH statement executes, it can trigger the execution of several programs. See "Startup Programs" for more information. |
Syntax
AW ATTACH workspace -
[ONATTACH [progname]|NOONATTACH] -
[RO [THAW] ] | RW | RWX | MULTI [THAW]] [WAIT | NOWAIT] ] -
[AUTOGO [progname]|NOAUTOGO] -
[AFTER workspace|BEFORE workspace|LAST|FIRST] -
[PASSWORD password]
Parameters
The name of the analytic workspace. When you use the ATTACH keyword to attach an analytic workspace that is not already attached, you must specify the workspace name. Again this is because no alias has been assigned using AW ALIAS LIST. However, when you use the ATTACH keyword on an already attached workspace (for example, to change its position in the workspace list), you can assign an alias using AW ALIAS LIST and then use that assigned alias.
(Default) When you do not specify progname, the ONATTACH clause automatically runs a program named ONATTACDH if one exists in the attached workspace. You can get the same results by not specifying NOONATTACH.
Specifying NOONATTACH indicates that when a program named ONATTACH exists in the workspace, Oracle OLAP should not execute that program.
(Default) When you do not specify progname, the AUTOGO clause automatically runs a program named AUTOGO if one exists in the attached workspace. You can get the same results by not specifying NOAUTOGO.
When you do specify progname, the AUTOGO clause automatically runs the specified program in the attached program.
Specifying NOAUTOGO indicates that when a program named AUTOGO exists in the workspace, Oracle OLAP should not execute that program.
(Default) Specifies that the workspace is attached in read-only access mode. Users can make private changes to the data in the workspace to perform what-if analysis but cannot commit any of these changes.
an analytic workspace that is attached read-only can be accessed simultaneously by several sessions. The read-only attach mode is compatible with the read/write and multiwriter access mode. A user can attach an analytic workspace in read-only mode when other users have the workspace attached in either read/write and multiwriter access mode. Likewise, a user cannot attach an analytic workspace in read/write exclusive mode when another user has it attached in read-only mode. When you attach an analytic workspace with read-only access, Oracle OLAP executes a program called PERMIT_READ, when it finds one in the workspace.
Specifies that Oracle OLAP attach the current view of an analytic workspace that was frozen using an AW FREEZE command without the NOTHAW keyword.
Specifies that the workspace is attached in read/write access mode. Only one user can have an analytic workspace open in read/write at a time. The user has to commit either all or none of the changes made to the workspace.
an analytic workspace that is attached read/write non-exclusive can be accessed simultaneously by several sessions. The read/write non-exclusive attach mode is only compatible with the read-only access mode. A user can attach an analytic workspace in read/write mode when other users have the workspace attached in read-only mode; however, a user cannot attach an analytic workspace in read/write mode when another user has it attached in any other mode. Likewise, a user cannot attach an analytic workspace in any mode other than read-only when another user has it attached in read/write non-exclusive mode. When you attach an analytic workspace with read/write access, Oracle OLAP executes a program called PERMIT_WRITE, when it finds one in the workspace.
Specifies that the workspace is attached in read/write exclusive access mode. Only one user can have an analytic workspace open in read/write exclusive at a time. The user has to commit either all or none of the changes made to the workspace.
an analytic workspace that is attached read/write exclusive cannot be accessed by any other sessions. The read/write exclusive attach mode is not compatible with any other access modes. A user cannot attach an analytic workspace in read/write exclusive mode when another user has it attached in any mode. Likewise, a user cannot attach an analytic workspace in any other mode when another user has it attached in read/write exclusive mode. When you attach an analytic workspace with read/write access, Oracle OLAP executes a program called PERMIT_WRITE, when it finds one in the workspace.
Specifies that the workspace is attached in multiwriter access mode. An analytic workspace that is attached in multiwriter mode can be accessed simultaneously by several sessions. In multiwriter mode, users can simultaneously modify the same analytic workspace in a controlled manner by specifying the attachment mode (read-only or read/write) for individual variables, relations, valuesets, and dimensions.
The multiwriter attach mode is only compatible with read-only and multiwriter modes. A user cannot attach an analytic workspace in multiwriter mode when another user has it attached in read/write or exclusive modes. Likewise, a user cannot attach an analytic workspace in read/write or exclusive mode when another user has it attached in multiwriter mode.
Specifies whether Oracle OLAP waits for an analytic workspace to become available for access when you request access to an analytic workspace that is being used with read/write exclusive access or when you request read/write access to an analytic workspace that is being used with read/write non-exclusive access. NOWAIT (the default) causes Oracle OLAP to produce an error message indicating that the workspace is unavailable. When you specify WAIT, Oracle OLAP waits for the workspace to become available for access. The number of seconds that Oracle OLAP waits for access depends on the value of the Oracle OLAP AWWAITTIME option.
(Default) Makes the workspace you are attaching the current workspace in the workspace list.
Puts the workspace after the current workspace in the workspace list and before the EXPRESS workspace. When there are other workspaces attached before the EXPRESS workspace, the specified workspace is attached after them. When there are no workspaces before the EXPRESS workspace, LAST makes the specified workspace the current one. LAST ignores any workspaces after the EXPRESS workspace.
Let you specify the position in the workspace list of the newly attached workspace relative to an analytic workspace that is attached. Use AFTER, rather than LAST, to attach an analytic workspace after the EXPRESS workspace. When specifying BEFORE puts the workspace first, the workspace becomes the current one.
The order of the workspace list determines the order in which workspaces are searched when Oracle OLAP looks for programs or objects named in programs.
Specifies a password to be checked in a startup program to give or deny access to the workspace being attached. See "Startup Programs".
Usage Notes
Using ATTACH on an Already-Attached Workspace
Reattaching an attached workspace with a AW ATTACH workspace statement does not cause Oracle OLAP to bring a new copy of the workspace into working memory. Instead, Oracle OLAP takes the following actions:
Makes the workspace the current workspace.
Runs an Autogo program, when you specify the AUTOGO keyword
However, when you have made any changes to data during the session, they are not discarded when you reattach an active workspace. Furthermore, current aliases for the workspace are not changed.
Managing Analytic Workspaces Attached in Multiwriter Mode
You use the following commands to manage objects in multiwriter mode:
ACQUIRE -- Acquires and (optionally) resynchronizes the specified objects so that their changes can be updated and committed.
RELEASE -- Changes the access mode of the specified variables, relations, valuesets, or dimensions from read/write (acquired) access to read-only access.
RESYNC -- Drops private changes for the specified read-only objects and retrieves the data from the latest visible generations.
REVERT-- Drops all changes made to the specified objects since they were last updated, resynchronized (using a RESYNC statement), or acquired using ACQUIRE with the RESYNC phrase, or since the analytic workspace was attached.
The following considerations apply:
Only one user can acquire an object in read/write mode at a time. You can first acquire an object in read-only mode, and then, assuming another user has not also acquired it in read-only mode, you can acquire it in read/write mode without releasing it first. However, once another user has acquired an object in read-only mode, you cannot acquire the same object in read/write mode until the other user releases the object. When a specified object has been acquired by another user or when your read-only generation for a specified object is not the latest generation for the object, an acquire fails.
You must resynchronize all variables, valuesets, and relations that share a composite dimension at the same time.
When resynchronizing objects, keep in mind the logical relationship of different objects to avoid losing the logical consistency of the data by promoting some objects, but not others to a new generation.
Objects that share a composite dimension can be resynchronized separately when all such objects that are not being resynchronized are either unchanged or acquired.
You cannot update a variable if any of its dimensions have been acquired and modified.
You must acquire a dimension before you maintain it.
If you release a dimension, then an automatic revert occurs.
Releasing objects that have been updated does not allow others to acquire the object until you commit or roll back the transaction. It may still be useful to release an object that has been updated before a commit when one wants to make further what-if changes and later update all acquired variables
Reverting a dimension after adding dimension values is not recommended since it can result in suboptimal space allocation for variables dimensioned by that dimension
If an acquired variable is dimension by an acquired dimension that has been maintained then you cannot update that variable until after you update or release the dimension.
You cannot delete dimension values.
Attaching a Frozen Analytic Workspace
Once an analytic workspace is frozen, attaching an analytic workspace in RO and MULTI attaches the frozen view of the workspace unless you specify the THAW keyword to request that the current view be attached. (When you attach in RW or RW, you always get the latest generation.)
When you attach the current view, the state of the analytic workspace may not necessarily be consistent if there is a multi-step build with intermediate commits. For example, assume that there is an analytic workspace that has two variables: actual and budget. Assume also that you have populated actual and then issued UPDATE and COMMIT commands. At this point in time, there is data only in actual.
When you are attaching a frozen analytic workspace in read multi mode, you can use the multi-writer commands (RESYNC and ACQUIRE) to retrieve up-to-date versions of the data whether or not you have specified AW FREEZE with the NOTHAW keyword.
Conflicts between Workspace Names and Aliases
You cannot attach an analytic workspace that is in your schema and whose name is the same as an assigned alias. Similarly, you cannot assign an alias that duplicates the name of an attached workspace that is in your schema. Furthermore, you cannot assign the same alias to two attached workspaces.
In an AW DELETE statement, when you specify an analytic workspace name (for an analytic workspace that is not attached) and the name is the same as an assigned alias, Oracle OLAP interprets the name as an alias and reports an error.
Examples
Example 9-50 Startup Programs
Assume that you have created an analytic workspace named awtest that contains five programs named PERMIT_READ, PERMIT_WRITE, ONATTACH, MYATTACH, and AUTOGO that have the following definitions.
DEFINE PERMIT_READ PROGRAM BOOLEAN PROGRAM SHOW 'permit_read program executing' AW LIST RETURN YES END DEFINE PERMIT_WRITE PROGRAM BOOLEAN PROGRAM SHOW 'permit_write program executing' AW LIST RETURN YES END DEFINE ONATTACH PROGRAM BOOLEAN PROGRAM SHOW 'onattach program executing' AW LIST RETURN YES END DEFINE MYATTACH PROGRAM BOOLEAN PROGRAM SHOW 'myattach program executing' AW LIST RETURN YES END DEFINE AUTOGO PROGRAM PROGRAM SHOW 'autogo program executing' AW LIST END
The programs that execute when you attach awtest vary depending on the attachment mode and keywords in the AW ATTACH statement:
When you attach awtest in read/write mode using the following statements.
AW DETACH awtest AW ATTACH awtest RW
First the PERMIT_WRITE program executes, and then the ONATTACH program executes.
When you attach awtest in read-only mode using the following statements.
AW DETACH axuserwtest AW ATTACH awtest NOONATTACH RO
Only the PERMIT_READ program executes.
When you attach awtest in read-only mode using the following statements.
AW DETACH awtest AW ATTACH awtest RO
First the PERMIT_READ program executes, and then the ONATTACH program executes.
When you attach awtest in read-only mode using the following statements.
AW DETACH awtest AW ATTACH awtest ONATTACH myattach RO
First the PERMIT_READ program executes, and then the MYATTACH program executes.
When you attach awtest in multi mode using the following statements.
AW DETACH awtest AW ATTACH awtest MULTI
First the PERMIT_WRITE program executes, and then the ONATTACH program executes.
When you attach awtest in read-only mode using the following statements.
AW DETACH awtest AW ATTACH awtest AUTOGO
First the PERMIT_WRITE program executes. Secondly, the ONATTACH program executes. Finally, the AUTOGO program executes.
Example 9-51 Attaching an Analytic Workspace Using an ONATTACH Program
Suppose you have two workspaces of sales data, one for expenses and one for revenue. You have a third workspace called analysis contains programs to analyze the data. Your analysis workspace has the following ONATTACH program to attach the other two.
DEFINE onattach PROGRAM PROGRAM AW ATTACH expenses RW AFTER analysis AW ATTACH revenues RW AFTER analysis END
To run the ONATTACH program, attach the analysis workspace with the following statement.
AW ATTACH analysis
When you issue an AW LIST statement, you can see from the following output, that all three of your analytic workspaces are attached.
ANALYSIS R/W CHANGED XUSER.ANALYSIS REVENUE R/W UNCHANGED XUSER.REVENUES EXPENSES R/W UNCHANGED XUSER.EXPENSES EXPRESS R/O UNCHANGED SYS.EXPRESS
The AW CREATE command creates a new workspace and make it the current workspace in your session.
Oracle OLAP automatically executes a COMMIT as part of its procedure for creating an analytic workspace. Previously attached workspaces move down in the list of attached workspaces to make room for the new one at the top of the list.
Also, if the current analytic workspace is creating a different analytic workspace and the current workspace contains a program named TRIGGER_AW, then the TRIGGER_AW program executes.
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Note: Before you can create an analytic workspace you need the appropriate SQL GRANT privileges as outlined in "Privileges Needed to Create and Delete Analytic Workspaces". |
Syntax
AW CREATE workspace [position] [UNPARTITIONED|PARTITIONS n] -
[SEGMENTSIZE n [K, M, or G]] [TABLESPACE tblspname]
where position specifies the workspace's position in the workspace list and is one of the following values. (FIRST is the default.)
Parameters
The name of the analytic workspace. Workspace names:
Can be from 1 - 26 characters in length. All characters must come from the database character set and must be letters, numerals, or underscores.
Cannot begin with a numeral and cannot be reserved words in the DML. (Use RESERVED to identify reserved words.)
(Default) Makes the workspace you are attaching the current workspace.
Puts the workspace after the current workspace and before the EXPRESS workspace. When there are other workspaces attached before the EXPRESS workspace, the specified workspace is attached after them. When there are no workspaces before the EXPRESS workspace, LAST makes the specified workspace the current one. LAST ignores any workspaces after the EXPRESS workspace.
Specify the position of the newly attached workspace relative to an analytic workspace that is already attached. Use AFTER, rather than LAST, to attach an analytic workspace after the EXPRESS workspace. When specifying BEFORE puts the workspace first, the workspace becomes the current one.
The order of the workspace list determines the order in which workspaces are searched when Oracle OLAP looks for programs or objects named in programs.
Specifies that the relational table that is the analytic workspace is not a partitioned table.
Specifies that the relational table that is the analytic workspace is a hash partitioned table with n partitions. Specifying a value of 0 (zero) for n is the same as specifying UNPARTITIONED. The default value of n is 8.
With the CREATE keyword, this argument sets the maximum size of each segment for the workspace being created. When you do not specify K, M, or G, the value you specify for n is interpreted as bytes. When you specify K, M, or G after the value n, the value is interpreted as kilobytes, megabytes, or gigabytes, respectively.
Specifies the name of an Oracle Database tablespace in which the analytic workspace is created.
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Tip: Oracle suggests that you use the TABLESPACE argument to create your workspace in a tablespace that has been prepared for this purpose. Ask your DBA which tablespace use. |
Usage Notes
Analytic Workspace Permissions
You can add security to analytic workspaces at several levels:
At the relational table level using SQL GRANT statements
At the analytic workspace level and workspace object level using different attachment modes and startup programs. See the AW ATTACH command and "Startup Programs".
Examples
Example 9-52 Creating and Starting an analytic workspace
You can use the AW command with the CREATE keyword to create and start a new workspace.
AW CREATE mywork
The AW DELETE command deletes a detached analytic workspace from the Database. It is important to note that Oracle OLAP automatically executes a COMMIT as part of its procedure for deleting an analytic workspace. The DELETE keyword executes successfully only when no user has the workspace attached.
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Note: If the current analytic workspace is deleting a different analytic workspace and the current workspace contains a program named TRIGGER_AW, then the TRIGGER_AW program executes. |
Syntax
AW DELETE workspace
Parameters
The name of the analytic workspace. You must specify the name; you cannot specify an alias.
Usage Notes
Deleting an Unattached Workspace
When you attempt to delete an unattached workspace and the name is the same as an assigned alias, Oracle OLAP interprets the name as an alias and reports an error.
Examples
Example 9-53 Deleting an analytic workspace
You can use the AW command with the DELETE keyword to delete an analytic workspace.
AW DELETE mywork
The AW DETACH command removes an analytic workspace from the workspace list. When you remove the first workspace, the second workspace becomes the current workspace (unless it is the EXPRESS workspace). When you detach an analytic workspace, changes that were made before an UPDATE was issued remain in the Database and become permanent with the next COMMIT. When changes were made after the UPDATE was issued, they are discarded.
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Note: When a program named TRIGGER_AW exists in the analytic workspace, the execution of an AW DETACH statement automatically executes that program. |
Syntax
AW DETACH [CACHE|NOCACHE] workspace
Parameters
Specifies that the analytic workspace is cached if there have been no changes to it since it was attached. (Default)
Specifies that the analytic workspace is not cached even if there have been no changes to it since it was attached.
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Note: You must specify NOCACHE when you detach an analytic workspace if you want Oracle OLAP to execute any Permission, OnAttach, or Autogo programs the next time you attach the workspace in the same session. |
The name of the analytic workspace. You can specify either an analytic workspace name or an analytic workspace alias, depending on the keywords you are using.
Usage Notes
Determining if an Analytic Workspace Has Changed
The following statements indicate if an analytic workspace has been changed while it was attached:
AW function with the CHANGED keyword
AW LIST shows the analytic workspace as unattached.
Cache Size
By default the list of cached analytic workspaces is two. In other words, by default only two analytic workspaces can be on the cached at one time and as new workspaces are added to the cache list, earlier workspaces are removed. For example, assume that you have detached two analytic workspaces in the following order: 1) mywk1, 2) mywk2. Now you issue an AW DETACH CACHE command for mywk3. Oracle OLAP removes mywk1 from the cache and the cache list and caches mywk3 adding it to the cache list after mywk2.
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Note: Under severe memory contention, Oracle OLAP may release memory by emptying the cache. |
You can change the size of the cache by using the event number 37372 where level is the number of analytic workspaces to retain. Specify a level of 1024 to disable the cache entirely. Not determined for beta: Is this information valid to regular developers?
Programs Executed When an Analytic Workspace is Detached
When an analytic workspace is detached, the following programs may execute:
If that analytic workspace being detached contains a program named ONDETACH, the ONDETACH program executes.
If the current analytic workspace is detaching a different analytic workspace and the current workspace contains a program named TRIGGER_AW, then the TRIGGER_AW program executes.
Examples
Example 9-54 Detaching an analytic workspace
You can use the AW command with the DETACH keyword to detach an analytic workspace.
AW DETACH expense
The AW FREEZE command commits the current transaction (if any) and sets a flag that specifies that the analytic workspace is the default attach version of the workspace. Later, when a request is made to attach the workspace in read only or read multi mode, Oracle OLAP attaches this flagged generation of the analytic workspace.
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Note: You must be attached to the analytic workspace in a write mode to execute this command. |
Syntax
AW FREEZE [NOTHAW]
Parameters
Specifies that you cannot specify the THAW keyword with AW ATTACH when you attach the workspace at a later time.
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Note: Once an analytic workspace is frozen, attaching an analytic workspace in read only or read multi mode attaches the analytic workspace as of the frozen view unless you specify the THAW keyword with the AW ATTACH command. |
Usage Notes
Freezing an Analytic Workspace
Keep the following points in mind when freezing an analytic workspace:
Only one generation of an analytic workspace can be frozen at a time
You cannot refreeze a currently frozen analytic workspace without first thawing it using the AW THAW command.
The AW LIST command sends to the current outfile a list of the active workspaces, along with their update status.
Syntax
AW LIST
Usage Notes
Output Produced by AW LIST
The first workspace in the list is the current workspace, unless you do not have a current workspace. The meaning of the update status, CHANGED or UNCHANGED, depends on whether the workspace is attached with read/write or read-only access and whether or not the workspace is being shared with other users. The update status displayed by AW LIST is as follows:
An unshared workspace in read/write mode -- The update status is CHANGED when you have made changes since attaching the workspace or since your last update.
An unshared workspace in read-only mode -- The status is always UNCHANGED because you cannot update it.
A shared or unshared workspace in read/write mode -- The status is CHANGED when you have made changes since attaching the workspace or since your last update.
A shared workspace in read-only mode -- The status is CHANGED when another user has updated it since you accessed it. To access the new objects or data, you must detach and reattach the workspace after the other user commits his or her changes. If you keep the workspace attached, then your view of the workspace remains unchanged.
Current Workspace
The name of the current workspace is first on the workspace list and is the name returned by the AW(NAME) function. (See the AW function for details.) The NAME dimension includes only the objects in the current workspace. Programs such as AWDESCRIBE and LISTBY list only objects in the current workspace. When an analytic workspace is active but not current, you can change and update its data, edit and run its programs, and modify its objects.
Examples
Assume that you have just connected to Oracle OLAP using the OLAP Worksheet. You issue an AW LIST statement that returns a value showing that the only attached analytic workspace is EXPRESS.
AW LIST EXPRESS R/O UNCHANGED SYS.EXPRESS
Now you create an analytic workspace and issue another AW LIST statement. You can see that both the EXPRESS analytic workspace and the newly created analytic workspace are attached.
AW CREATE myaw AW LIST MYAW R/W UNCHANGED MYNAME.MYAW EXPRESS R/O UNCHANGED SYS.EXPRESS
The AW PURGE CACHE command detaches any analytic workspaces that are currently in the cache.
Syntax
AW PURGE CACHE
The AW ROLLBACK TO FREEZE makes current the version of the analytic workspace that was created by the last AW FREEZE command.
Syntax
AW ROLLBACK TO FREEZE
The AW SEGMENTSIZE command sets up an analytic workspace for multiple segments.
Syntax
AW SEGMENTSIZE n [K, M, or G] [workspace]
Parameters
The name of the analytic workspace. You can specify either an analytic workspace name or an analytic workspace alias, depending on the keywords you are using.
Sets the maximum size of each segment for a specified workspace or, when no workspace is specified, for the current workspace.
When the current workspace already has several segments, setting SEGMENTSIZE affects only the most recent one and has no effect on previous ones. Previous segments may have various sizes, determined by the SEGMENTSIZE setting at the time each one was created. When you do not specify K, M, or G, the value you specify for n is interpreted as bytes. When you specify K, M, or G after the value n, the value is interpreted as kilobytes, megabytes, or gigabytes, respectively.
The AW THAW command commits the current transaction (if any) and undoes a previous AW FREEZE command.
Syntax
AW THAW
Deletes all of the objects and data from an existing analytic workspace. Oracle also deallocates all of the table space used by the analytic workspace.Removing data using AW TRUNCATE can be more efficient and less "destructive" than deleting an analytic workspace using AW DELETE. For example, when you remove data using AW TRUNCATE, all of the object privileges that were previously granted remain.
For more information on truncating a table, see TRUNCATE TABLE in Oracle Database SQL Language Reference.
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Note: Before you can truncate an analytic workspace in a schema that you do not own, you need the appropriate SQL GRANT privilege as outlined in "Privileges Needed to Create and Delete Analytic Workspaces". |
Syntax
AW TRUNCATE workspace
Parameters
The name of the analytic workspace. You must specify the name; you cannot specify an alias.
Examples
The ISEMPTY function identifies if a variable or one or more of its partitions has values.
Return Value
BOOLEAN
FALSE when the specified variable or partitions have values; TRUE when they are empty.
Syntax
ISEMPTY( variable [(PARTITION partition [,PARTITION partition]...)])
Parameters
The name of the variable to check for values.
The name of one or more partitions of variable, separated by commas, to check for values.
The ADD_MODEL_DIMENSION program adds a DIMENSION (in models) statement to a cube dimension's model. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
Syntax
CALL ADD_MODEL_DIMENSION(logical_dim, model_name, explicit_dim)
Parameters
Since ADD_MODEL_DIMENSION is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name of the logical model that is associated with logical_dim.
A text expression that is the name of the dimension that you want to add to the cube dimension's model.
Within an OLAP DML program, the FOR command specifies one or more dimensions whose status controls the repetition of one or more statements. These statements, along with the FOR statement itself, are often called a FOR loop.
Syntax
FOR dimension...
statement
Parameters
One or more dimensions whose current status controls the repetition of one or more statements. The statements are repeated for each combination of the values of the specified dimensions in the current status. When two or more dimensions are specified, the first one varies the slowest. You can specify a composite instead of a dimension.
The statement to be repeated. To repeat two or more statements, enclose them between DO and DOEND.
DO
statement1
...
statementN
DOEND
When you are repeating only one statement after FOR, you can omit DO and DOEND.
Usage Notes
FOR Dimension
A FOR statement loops over the values in status of the specified dimension. After the last dimension value, dimension status is restored to what it was before the loop, and execution of the program resumes with the next statement.
Status Inside a Loop
The TEMPSTAT command limits the dimension you are looping over inside a FOR loop or inside a loop that is automatically generated by a REPORT statement.
No Sorting
Because current status defines and controls a FOR loop, you cannot sort the FOR dimension within the loop.
Assignment Statements and Other Looping Statements
An OLAP DML assignment statement (SET), and some other OLAP DML statements automatically loop over dimension status and do so more efficiently than a FOR loop. Be careful not to cause extra looping by putting an assignment statement or one of these statements in a FOR loop.
Branching
You can use BREAK, CONTINUE, and GOTO statements to branch within, or out of, a FOR loop, thereby altering the sequence of statement execution.
Nested FOR Statements
FOR statements can be nested within a FOR loop to any depth when matching DO and DOEND statements are supplied where appropriate.
Examples
Example 9-136 Using FOR in a DO Loop to Repeat ROW Commands
In a report program, you want to show the unit sales of tents for each of three months. Use the following FOR statement with a DO/DOEND sequence to repeat ROW commands and BLANK commands for each value of the month dimension.
LIMIT product TO tents
LIMIT month TO 'Jan96' TO 'Mar96'
ROW district
ROW UNDER '-' VALONLY name.product
BLANK
FOR month
DO
ROW INDENT 5 month WIDTH 6 UNITS
BLANK
DOEND
The program lines produce the following report.
BOSTON
3-Person Tents
--------------
Jan96 307
Feb96 209
Mar96 277
Example 9-137 Using a FOR Statement for Looping Over Values
The FOR command executes the commands in the loop for each value in the current status of the dimension. You must limit the dimension to the desired values before executing a FOR statement. For example, you can produce a series of output lines that show the price for each product.
LIMIT month TO FIRST 1
LIMIT product TO ALL
FOR product
SHOW JOINCHARS('Price for ' product ': $' price)
Each output line has the following format.
Price for TENTS: $165.50
When your data is multidimensional, you can specify multiple dimensions in a FOR statement to control the order of processing. For example, you can use the following statement to control the order in which dimension values of the units data are processed.
FOR month district product units = ...
When this assignment statement is executed, the month dimension varies the slowest, the district dimension varies the next slowest, and the product dimension varies the fastest. Thus, a loop is performed over all products for the first district before doing the next district, and over all districts for the first month before doing the next month.
Within the FOR loop, each specified dimension is temporarily limited to a single value while it executes the statements in the loop. You can therefore work with specific combinations of dimension values within the loop.
Example 9-138 Using DO/DOEND in a FOR Loop
When actual figures for unit sales are stored in a variable called units and projected figures for unit sales are stored in a variable called units.plan, then the code in your loop can compare these figures for the same combination of dimension values.
LIMIT month TO FIRST 1
LIMIT product TO ALL
LIMIT district TO ALL
FOR district product
DO
IF (units.plan - units)/units.plan GT .1
THEN SHOW JOINCHARS(-
'Unit sales for ' product ' in ' -
district ' are not within 10% of plan.')
DOEND
These lines of code are processed in the following manner.
The data is limited to a specific month.
All the districts and products are placed in status, and the FOR loop is entered.
In the FOR loop, the actual figure is tested against the planned figure. When the unit sales figure for Tents in Boston is more than 10 percent below the planned figure, then the following message is sent to the current outfile.
Unit sales for TENTS in BOSTON are not within 10% of plan.
After processing all the products, the FOR loop is complete for the first district.
The loop is executed for the second district, and so on.
Note that while the FOR loop executes, each dimension that is specified in a FOR statement is limited temporarily to a single value. When you specify district in the FOR loop, but not product, then all the values of product are in status while the FOR loop executes. The IF...THEN...ELSE command then tests data for only the first value of the product dimension.
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The LAGPCT function returns the percentage difference between the value of a dimensioned variable or expression at a specified offset of a dimension before the current value of that dimension and the current value of the dimensioned variable or expression.
Return Value
DECIMAL or NA when you try to lag before the first period of a dimension of a time dimension.
Syntax
LAGPCT(variable, n, [dimension], [STATUS|NOSTATUS|limit-clause] )
Parameters
A variable or expression that is dimensioned by dimension.
The offset (that is, the number of dimension values) to lag. LAGPCT uses this value to determine the number of values that LAGPCT should go back in dimension to retrieve the value of variable. Typically, n is a positive INTEGER that indicates the number of time periods (or dimension values) before the current one. When you specify a negative value for n, it indicates the number of time periods after the current one. In this case, LAGPCT compares the current value of the time series with a subsequent value.
The dimension along which the lag occurs. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, QUARTER or YEAR.
When variable has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want LAGPCT to use that dimension, you can omit the dimension argument.
Specifies that LAGPCT should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the lag.
(Default) Specifies that LAGPCT should use the default status (that is, a list all the dimension values in their original order) when computing the lag.
Specifies that LAGPCT should use the default status limited by limit-clause when computing the lag.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
To specify that LAG should use the current status limited by limit-clause when computing the lag, specify a LIMIT function for limit-clause.
Usage Notes
Formula Used by LAGPCT
To obtain its results, LAGPCT uses the following formula.
(currentvalue - previousvalue) / previousvalue
When the Previous Value of the Time Series Used by LAGPCT is Zero
When the previous value of the time series used by LAGPCT is zero, the result LAGPCT returns is determined by the DIVIDEBYZERO option. When DIVIDEBYZERO is set to NO, an error occurs. When DIVIDEBYZERO is set to YES, LAGPCT returns NA.
Examples
Example 8-3 Using LAGPCT
Suppose you have a variable called sales that is dimensioned by a hierarchical dimension named time, and dimensions called district and products. Assume also that there is a dimension named timelevels that contains the names of the levels of the time dimension (that is, Month and Year) and a relation named timelevelrel that is dimensioned by time and that has values from timelevels (that is, the related dimension of timelevelrel is timelevels).
You can compare racquet sales in Dallas for 2000 with sales for 1999 by using the LAG function to show 199 values. You can use the LAGPCT function to calculate the percentage difference between the two. You can multiply the value LAGPCT returns by 100 and include a percent sign to display the difference as percentage points.
ALLSTAT LIMIT product TO 'Racquets' LIMIT district TO 'Dallas' LIMIT TIME TO '2000' REPORT DOWN time sales HEADING 'Last Year' - LAG(sales, 1, time, time LEVELREL timelevelrel)- HEADING 'LAGPCT (Decimal Format)' - LAGPCT(sales, 1, time LEVELREL timelevelrel) - HEADING 'LAGPCT (Percent Format)' rset '%' - LAGPCT(sales, 1, time LEVELREL timelevelrel) * 100
produce this report.
DISTRICT: Dallas
------------------PRODUCT------------------
-----------------racquets------------------
LAGPCT LAGPCT
(Decimal (Percent
TIME SALES Last Year Format) Format)
-------------- ---------- ---------- ---------- ----------
2000 93,000,003 89,000,891 0.04 4.49%
With the CDA command, you can identify or change the current directory object for your session.
With an established current directory object, you can specify a file identifier in a DML file access statement without including the name of the directory object. Some examples of file access statements are FILECOPY, FILEMOVE, FILEDELETE, EXPORT, and IMPORT.
Syntax
CDA [directory-alias]
Parameters
A text expression that specifies the directory object that you want to be the current one for your session.
When you do not specify this argument, CDA sends the name of the current directory object to the current outfile. When there is no current directory object, the statement reports that fact.
Usage Notes
Specifying a File Identifier with an Established Current Directory Object
The following statement moves the file log.txt from your session's current directory object to file oldlog.txt in a directory object called backup.
FILECOPY 'log.txt' 'backup/oldlog.txt'
Setting Up a Directory Object
A database administrator must set up a directory object and give you access to it.
Examples
Within SWITCH command, FOR, or WHILE statements in an OLAP DML program, the BREAK command transfers program control from within a SWITCH, FOR, or WHILE statement to the statement immediately following the DOEND associated with SWITCH, FOR, or WHILE.
Syntax
BREAK
Usage Notes
TEMPSTAT Statement and BREAK Statement
Within a FOR loop of a program, when a DO ... DOEND phrase follows TEMPSTAT, status is restored when the DOEND, BREAK, or GOTO is encountered.
Examples
Example 9-58 Using BREAK with SWITCH
The following lines from a program include a SWITCH command with two case labels. The last statement under each case label is BREAK, which ensures that execution does not continue from one set of case statements to the next. Each BREAK statement transfers control to the statement that follows DOEND.
SWITCH userchoice
DESCRIPTION 'MARKET REPORT\NFINANCE REPORT\NNO REPORT')
DO
CASE 'market':
...
BREAK
CASE 'finance':
...
BREAK
DEFAULT:
...
BREAK
DOEND
cleanup:
...
The EXTCHARS function extracts a portion of a text expression.
|
Tip: When you are using a multibyte character set, you can use the EXTBYTES function instead of the EXTCHARS function. |
Return Value
TEXT or NTEXT
Syntax
EXTCHARS(text-expression [start [length]])
Parameters
A TEXT or NTEXT expression from which a portion is to be extracted. When text-expression is a multiline text value, EXTCHARS preserves the line breaks in the returned value.
An INTEGER that represents the character position at which to begin extracting. The position of the first character in text-expression is 1. When you omit this argument, EXTCHARS starts with the first character.
An INTEGER that represents the number of characters to be extracted. When length is not specified, or exceeds the number of characters from start to the end of text-expression, the part from start to the end of text-expression is extracted.
Examples
The RENAME command changes the name of an object in an analytical workspace.
Syntax
RENAME oldname newname [AW workspace]
Parameters
The name of an existing object in an analytic workspace. You can specify a qualified object name to indicate the attached workspace in which the object resides. As an alternative, you can use the AW keyword to specify the workspace. Do not use both.
When you do not use a qualified object name or the AW keyword to specify an analytic workspace, the object is renamed in the current workspace.
For an unnamed composite, use the same syntax that was used to create it. See "Naming an Unnamed Composite".
The new name. The new name of an analytic workspace object cannot duplicate any other name in the workspace in which the object exists. Choose a name according to the rules for naming analytic workspace objects (see the main entry for the DEFINE command. To change a named composite to an unnamed composite, use the SPARSE keyword as the newname argument. See "Unnaming a Named Composite".
The name of an attached workspace in which you want to rename the object. When you do not use a qualified object name or the AW keyword to specify an analytic workspace, the object is renamed in the current workspace.
Usage Notes
Updating Associated Objects
When you change the name of a variable, objects that use that variable, such as formulas, are not automatically updated.
When you change the name of a dimension, the definitions of any objects that are dimensioned by that dimension are automatically updated. Additionally, any valuesets for the renamed dimension are automatically updated for the new name.
RENAME and PERMIT
You may not rename an object when a PERMIT statement denies you the right to change its permission. Renaming an object does not affect permission associated with it.
Naming an Unnamed Composite
You can name an unnamed composite with a RENAME statement. The following example assigns the name m.prod to an unnamed composite that is dimensioned by market and product.
RENAME SPARSE <market product> m.prod
Unnaming a Named Composite
You can change a named composite to an unnamed composite when the composite has no properties or permission restrictions and when there is at least one object dimensioned by it. In addition, there cannot be an unnamed composite with the same dimensions in the same order as the named composite, and the named composite cannot be used in the dimension list of any unnamed composite. To change a named composite to an unnamed composite, use the SPARSE keyword as the newname argument. The following example changes the named composite m.prod to an unnamed composite.
RENAME m.prod SPARSE
Restrictions on Renaming Composites
You cannot rename a composite when it is a base dimension of an unnamed composite, or when one of its base dimensions is an unnamed composite.
Examples
Adds a MODEL (in an aggregation) statement for a specified model into the aggregation map of a cube dimension. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL ADD_CUBE_MODEL(logical_cube, logical_dim, model_name, is_static_model, [position ])
Parameters
Since ADD_CUBE_MODEL is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the name of the cube as defined in the Oracle data dictionary.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name of the logical model that is associated with logical_dim.
A Boolean expression that specifies whether model_name is added before or after the RELATION (for aggregation) statements in the aggmap for logical_cube.
The default value is TRUE which means that the MODEL statement added before the RELATION statements (that is that model_name is a static model).
Specify FALSE if you want the MODEL statement added after the RELATION statements (that is, that model_name is a dynamic model).
An integer that specifies where in the list of either static or dynamic models, the new model is added. For example, if you specify a value of 0 (zero) for position and FALSE for is_static_model, then the model is added as the first dynamic model. The default value of position, is at the end of the list.
When you specify a negative value for position, then the model is added that many positions from the end of the list.
Examples
For an example of using ADD_CUBE_MODEL in conjunction with SET_INCLUDED_MODEL, see the Example provided for SET_INCLUDED_MODEL.
The LOCK_LANGUAGE_DIMS option specifies if the status of language dimension can be changed.
|
See also: "Working with Language Dimension Status", $DEFAULT_LANGUAGE property, SESSION_NLS_LANGUAGE option, and STATIC_SESSION_LANGUAGE option. |
Data Type
BOOLEAN
Syntax
LOCK_LANGUAGE_DIMS= TRUE | FALSE
Parameters
Specifies that Oracle OLAP returns an error if a LIMIT statement tries to limit the status of a language dimension.
When a program changes the value the LOCK_LANGUAGE_DIMS option from FALSE to TRUE, Oracle OLAP resets the status of the language dimension in any attached analytic workspace according to the value of the SESSION_NLS_LANGUAGE option.
Sets the status of the language dimension to ALL, and specifies that programs can modify the status of the language dimension using LIMIT.
When a program changes the value the LOCK_LANGUAGE_DIMS option from TRUE to FALSE, Oracle OLAP resets the status of the language dimension in any attached analytic workspace to ALL.
Examples
Example 5-48 Explicitly Limiting a Language Dimension
Assume that your analytic workspace contains a language dimension named mylangs that has the following definition and values.
DEFINE MYLANGS DIMENSION TEXT PROPERTY '$DEFAULT_LANGUAGE' - 'AMERICAN' MYLANGS -------------- FRENCH AMERICAN
Assume also, as shown by the following report, that when you attach the analytic workspace that the status of mylangs is American.
REPORT mylangs MYLANGS -------------- AMERICAN
As the following code illustrates, you can explicitly change the status of mylangs to French using LIMIT if you first set the value of LOCK_LANGUAGE_DIMS to FALSE. You cannot use LIMIT against a language dimension when the value of LOCK_LANGUAGE_DIMS has its default value of TRUE.
" Try to LIMIT mylangs LIMIT mylangs to 'FRENCH' ORA-33558: The status or contents of the MYAW3!MYLANGS dimension cannot be changed while the LOCK_LANGUAGE_DIMS option is set to yes. " Got an error SHOW LOCK_LANGUAGE_DIMS TRUE " Got the error because LOCK_LANGUAGE_DIMS was TRUE "Change LOCK_LANGUAGE_DIMS to FALSE LOCK_LANGUAGE_DIMS = FALSE " Try to LIMIT mylangs again LIMIT mylangs TO 'FRENCH' " Verify if the LIMIT worked. It did REPORT mylangs MYLANGS -------------- FRENCH " Then relock the language LOCK_LANGUAGE_DIMS = TRUE
This chapter contains the following topics:
One topic for each of the OLAP DML commands that begins with the letters A - G, beginning with ACQUIRE.
Reference topics for the remaining OLAP DML commands appear in alphabetical order in Chapter 10, "OLAP DML Commands: H-Z".
For other OLAP DML reference topics, see Chapter 4, "OLAP DML Properties", Chapter 5, "OLAP DML Options", Chapter 7, "OLAP DML Functions: A - K", and Chapter 8, "OLAP DML Functions: L - Z".
OLAP DML commands work in much the same way as commands in other programming languages—the one exception is the looping nature of OLAP DML commands as discussed in "OLAP DML Statements Apply to All of the Values of a Data Object".
Many OLAP DML commands perform complex actions. Some of these commands are data definition commands like the AW command which you use to create an analytic workspace and the DEFINE command which you use to define objects within an analytic workspace. Other OLAP DML commands are data manipulation commands. For example, you can use the OLAP DML SQL command to embed SQL statements in an OLAP DML program to copy data from relational tables into analytic workspace data objects, or you can use the AGGREGATE command to calculate summary data. Additionally, the DEFINE, MAINTAIN, PROPERTY, SET (=) UPDATE, and AW commands are recognized by Oracle OLAP as events that can trigger the execution of OLAP DML programs. (See "Trigger Programs" for more information.)
|
Tip: Many OLAP DML statements can be coded as a 3-character abbreviation that consists of the first letter of the statement plus the next two consonants. |
Additionally, you can augment the functionality of the OLAP DML by writing an OLAP DML program for use as a command.
A B C D E F G H I L M O P R S T U V W Z
A
B
C
D
E
F
G
H
I
I
L
M
O
P
R
S
T
U
V
W
Z
OLAP Cube and Cube Dimension Modification Commands
Aggregation Commands
Allocation Commands
Assigment Commands
Debugging Commands
Analytic Workspace Object Definition Commands
Dimension Status Commands
Forecast and Regression Commands
Date Formatting Commands
Formula Commands
Analytic Workspace Management Commands
Analytic Workspace Multiwriter Management Commands
File Management Commands
Data Model Commands
Programming Commands
Reporting Commands
Save and Restore Value Commands
Sorting Commands
Spreadsheet Commands
SQL Execution Commands
OLAP DML Statement Edit Commands
For a given variable and aggmap object, the CHANGEDRELATIONS function determines if there are any changes in the aggmap and the relations in the aggmap since the last time the variable was aggregated.
Return Value
BOOLEAN.
TRUE when changes have occurred, FALSE when they have not, or NA when the function cannot determine if changes have occurred.
Syntax
CHANGEDRELATIONS( variable [ [(PARTITION partition [,PARTITION partition]...) ] aggmap] )
Parameters
The name of the variable whose aggmap object you want to check for changes.
The name of one or more partitions of variable, separated by commas, whose aggmap you want to check for changes.
The name of the aggmap object you want to check for changes. When you do not specify a value for aggmap, the function uses the aggmap specified in the $AGGMAP property for variable, if any.
The REGEXP_COUNT function returns the number of times a pattern occurs in a source string. The function evaluates strings using characters as defined by the input character set.
Return value
When a match is found, an INTEGER that indicates the number of occurrences of the pattern; otherwise 0.
Syntax
REGEXP_COUNT (source_char, pattern [, position [, match_param]])
Parameters
The text expression for which the function searches.
The text expression for which the function searches. It is usually a text literal and can contain up to 512 bytes. If the data type of pattern is different from the data type of source_char, then the function converts pattern to the data type of source_char.
Note that the function ignores subexpression parentheses in pattern. For example, the pattern '(123(45))' is equivalent to '12345'. Also, the function interprets a period as a wildcard character that matches any character.
|
See: For a listing of the operators you can specify in pattern, see "Oracle Regular Expression Support" in Oracle Database SQL Language Reference. |
A positive INTEGER indicating the character of source_char where the function should begin the search. The default is 1, meaning that the function begins the search at the first character of source_char. After finding the first occurrence of pattern, the function searches for a second occurrence beginning with the first character following the first occurrence.
A text expression that lets you change the default matching behavior of the function. You can specify one or more of the values shown in the following table.
| Value | Specifies |
|---|---|
c | Case-sensitive matching. |
i | Case-insensitive matching. |
m | Treat the source string as multiple lines. The function interprets ^ (caret) and $ (dollar sign) as the start and end, respectively, of any line anywhere in the source string, rather than only at the start or end of the entire source string. By default, the function treats the source string as a single line. |
n | A newline character is among the characters matched by a period (the wildcard character). By default, it is not. |
x | Ignores whitespace characters. |
If you specify multiple contradictory values for this argument, then the function uses the last value. For example, if you specify 'ic', then the function uses case-sensitive matching. If you specify a character other than those shown above, then the function returns an error.
If you omit this optional argument, then the default case sensitivity is determined by the value of the NLS_SORT parameter; a period (.) does not match the newline character; and the source string is treated as a single line.
The FILEERROR function returns information about the first error that occurred when you are processing a record from an input file with the data reading statements FILEREAD and FILEVIEW. It can tell you what type of error occurred and where Oracle OLAP was in the record. The keyword you specify as an argument determines the kind of information that is returned.
Call FILEERROR once to find out the type of error. Then, you can call FILEERROR again to get more details about what caused the error. The return values for the type of error are also FILEERROR keywords. When FILEERROR returns a value other than NA, then you would probably call FILEERROR a second time using the return value itself as an argument.
The abbreviation for FILEERROR is FILEERR
Return Value
Varies depending on the specified keyword.
Syntax
FILEERROR (TYPE|POSITION|WIDTH|VALUE|DIMENSION)
Parameters
Returns a text expression that specifies the type of error that has occurred. The types of errors and their meanings are listed in Table 7-9, "Types of Errors Returned by FILEERROR".
Table 7-9 Types of Errors Returned by FILEERROR
| Return Value | Meaning |
|---|---|
|
DIMENSION |
The data reading statements tried to set the status of a dimension (through an implicit or explicit MATCH attribute), but the specified position or value did not exist. |
|
NA |
No error occurred in the processing of the current record. |
|
POSITION |
The data reading program tried to read from an invalid location in the record. A POSITION error can occur when the field or column is before the beginning of the record or when the field extends past the end of the record. An error beyond the end of the record occurs only for binary or packed data; for symbolic (textual) data, the data reading statements pad short records with blanks. |
|
VALUE |
The value could not be converted to the requested data type. For packed data, the record had an invalid hexadecimal digit. |
|
WIDTH |
The data reading statements specified an invalid field width. Invalid widths depend on the format of the data, which can be symbolic, packed, or binary:
For binary format, the width requirement depends on whether the data is |
Returns an INTEGER that is the column number (for RULED records) or field number (for STRUCTURED records) when the error occurred.
Returns an INTEGER that is the current field width. It returns NA when NA was specified as the width or the error was a POSITION error. A POSITION error stops processing before the width can be evaluated.
When the error type is VALUE, it returns a text expression that is the value that could not be converted. When the data is packed, the invalid value is shown as hexadecimal escapes. When the error type is DIMENSION, it returns the value that did not match any existing dimension value. For other error types, it returns NA.
When the error type was DIMENSION, it returns a text expression that is the name of the dimension that had no matching dimension values. For other error types, it returns NA.
Usage Notes
Flow of Control
When an error occurs in FILEREAD or FILEVIEW, processing of the current record stops and Oracle OLAP displays an appropriate error message. Then, when your program has a trap label, control branches to the label where you might call FILEERROR to investigate the problem. When you branch back to a FILEREAD or FILENEXT function, processing continues with the next record. When there are more errors in the record, those errors are not evaluated.
Displaying Error Messages in the Current Outfile
Set ECHOPROMPT to YES in your data reading program when you want error messages to be displayed in the current outfile. When the error occurred during FILEREAD or FILEVIEW, any evaluation by FILEERROR occurs after the error message.
Examples
Example 7-88 Error-Handling with TRAP
This example shows a sample trap label (ERROR:) and the error-handling code that follows it. (For information on error trapping and trap labels, see the TRAP command.) The code checks whether the file has been opened. If so, it checks whether the error that caused the branch is a data reading error. When it is, the program calls FILEERROR in a SHOW command to display information about the error. The body of the program (not shown) contains code that opens the file and assigns a file unit number to the variable fil.unit. ERRTYPE is a local variable that is declared at the beginning of the program.
error:
IF fil.unit EQ NA
THEN DO
POPLEVEL 'save'
RETURN
DOEND
IF ERRORNAME NE 'attn'
THEN DO
ERRTYPE = FILEERROR(TYPE)
IF ERRTYPE NE NA
THEN SHOW JOINCHARS('Error in record ' RECNO(fil.unit) -
' in column ' FILEERROR(POSITION) ': ' -
ERRTYPE ' ' FILEERROR(&ERRTYPE))
TRAP ON ERROR
GOTO NEXT
DOEND
FILECLOSE fil.unit
POPLEVEL 'save'
RETURN
For a dimension of type WEEK, the WEEKDAYSNEWYEAR option determines how many days of the new year there must be for a week to be identified as week 1 of the new year.
By default, week 1 in a given year is the first week that contains at least one day in the new year. For example, January 1, 2000, is a Saturday. Using the default, the first week in that year (W1.00) is the period from Sunday, December 26, 1999, through Saturday, January 1, 2000.
Using WEEKDAYSNEWYEAR, you can specify how many days of the year must be present in week 1 in that year. When you use WEEKDAYSNEWYEAR to specify that the first week in a year must contain two or more days, then the week of December 26, 1999, through January 1, 2000, is the last week in 1999 (W53.99), and the week of January 2 through January 8 is the first week in the year 2000 (W1.00).
Data Type
INTEGER
Syntax
WEEKDAYSNEWYEAR = days
Parameters
An INTEGER expression in the range 1 through 7 that indicates how many days in the year must be present in week 1 of that year. The default value for days is 1.
Examples
The Effect of WEEKDAYSNEWYEAR
The following statements send a list of weeks with the associated ending dates for each of those weeks to the current outfile.
DEFINE week DIMENSION WEEK MAINTAIN week ADD '12 18 99' '1 15 00' weekdaysnewyear = 2 REPORT W 22 CONVERT(week date)
These statements produce the following output.
WEEK CONVERT(WEEK DATE) -------------- -------------------- W51.99 18DEC99 W52.99 25DEC99 W53.99 01JAN00 W1.00 08JAN00 W2.00 15JAN00
January 1, 2000, is a Saturday, so setting WEEKDAYSNEWYEAR to 2 causes the week from January 2 through January 8 to appear as W1.00.
The PARENS option controls whether negative numbers are represented in output with parentheses or a minus sign.
Data Type
BOOLEAN
Syntax
PARENS = {YES|NO}
Parameters
Encloses negative values in parentheses, instead of using a minus sign.
(Default) Uses a minus sign to represent negative values.
Usage Notes
Overriding PARENS
The setting of the PARENS option is overridden by a PAREN or NOPAREN attribute in a HEADING, REPORT, or ROW command. The PAREN attribute specifies the use of parentheses; the NOPAREN attribute specifies the use of a minus sign.
Allowing Space for Parentheses
When you use parentheses to represent negative values in a report, Oracle OLAP lines up the positive and negative values in the column. To do this, it reserves the right-most character in each numeric column for the closing parenthesis. The column is always reserved, even when there are no negative values in the output. Consequently, each value requires more space than when you use the minus sign, and you might have to increase your column width to accommodate your data.
Examples
Example 5-89 Showing Negative Values in Parentheses
In a report, you would like to show negative values in parentheses, so you first set PARENS to YES.
LIMIT line TO 'Cogs' LIMIT division TO 'Sporting' LIMIT month TO 'Jan96' TO 'Jun96' PARENS = YES DECIMALS = 0 REPORT DOWN month budget actual budget-actual
These statements produce the following output.
DIVISION: SPORTING
--------------LINE--------------
--------------COGS--------------
BUDGET-ACT
MONTH BUDGET ACTUAL UAL
-------------- ---------- ---------- ----------
Jan96 279,773 287,558 (7,785)
Feb96 323,982 315,299 8,683
Mar96 302,178 326,185 (24,007)
Apr96 386,101 394,544 (8,443)
May96 433,998 449,862 (15,864)
Jun96 448,042 457,348 (9,305)
The following table describes the subprograms provided in OLAP_API_SESSION_INIT.
Table C-2 OLAP_API_SESSION_INIT Subprograms
| Subprogram | Description |
|---|---|
|
|
Specifies an |
|
|
Removes orphaned data, that is, any |
|
DELETE_ALTER_SESSION Procedure |
Removes a previously defined |
This procedure specifies an ALTER SESSION parameter for OLAP API users with a particular database role. It adds a row to the OLAP$ALTER_SESSION table.
Syntax
ADD_ALTER_SESSION (
role_name IN VARCHAR2,
session_parameter IN VARCHAR2);
Parameters
The role_name and session_parameter are added as a row in OLAP$ALTER_SESSION.
Table C-3 ADD_ALTER_SESSION Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of a valid role in the database. Required. |
|
|
A parameter that can be set with a SQL |
Example
The following example inserts a row in OLAP$ALTER_SESSION that turns on query rewrite for users with the OLAP_DBA role.
EXECUTE olap_api_session_init.add_alter_session('OLAP_DBA', 'SET QUERY_REWRITE_ENABLED=TRUE'); Row inserted SELECT * FROM all_olap_alter_session WHERE role='OLAP_DBA'; ROLE CLAUSE_TEXT ------------ ------------------------------------------------------------ OLAP_DBA ALTER SESSION SET QUERY_REWRITE_ENABLED=TRUE
This procedure removes all ALTER SESSION parameters for any role that is not currently defined in the database. It removes all orphaned rows in the OLAP$ALTER_SESSION table for those roles.
Syntax
CLEAN_ALTER_SESSION ();
Example
The following example deletes all orphaned rows.
EXECUTE olap_api_session_init.clean_alter_session();
This procedure removes a previously defined ALTER SESSION parameter for OLAP API users with a particular database role. It deletes a row from the OLAP$ALTER_SESSION table.
Syntax
DELETE_ALTER_SESSION (
role_name IN VARCHAR2,
session_parameter IN VARCHAR2);
Parameters
The role_name and session_parameter together uniquely identify a row in OLAP$ALTER_SESSION.
Table C-4 DELETE_ALTER_SESSION Procedure Parameters
| Parameter | Description |
|---|---|
|
role_name |
The name of a valid role in the database. Required. |
|
session_parameter |
A parameter that can be set with a SQL |
Examples
The following call deletes a row in OLAP$ALTER_SESSION that contains a value of OLAP_DBA in the first column and QUERY_REWRITE_ENABLED=TRUE in the second column.
EXECUTE olap_api_session_init.delete_alter_session('OLAP_DBA', 'SET QUERY_REWRITE_ENABLED=TRUE'); SELECT * FROM all_olap_alter_session WHERE role='OLAP_DBA'; no rows selected
The REVERT command drops all changes made to the specified objects since they were last updated, resynchronized (using a RESYNC statement), acquired using ACQUIRE with the RESYNC phrase, or since the analytic workspace was attached.
Syntax
REVERT objects
Parameters
A list of the names, separated by commas, of acquired variables, valuesets, relations, or dimensions in an analytic workspace attached in multiwriter mode or a list of variables, valuesets, relations, or dimensions in an analytic workspace attached in read-only mode.
Usage Notes
Reverting a Dimension After Adding Dimension Values
Reverting a dimension after adding dimension values is not recommended since it can result in suboptimal space allocation for variables dimensioned by that dimension.
Examples
Example 10-108 Using REVERT to Undo Modifications
Assume that you have a variable named budget in an analytic workspace named myworkspace. Assume, also, that you must modify budget in several steps but do not want to update the analytic workspace data until all steps are completed. For each step, you want to run several models to find the one that produces desired results. To perform this task, take the following steps:
Attach the analytic workspace in multiwriter mode.
Acquire budget.
For each step:
Run the appropriate models, performing revert operations between them until you finds the desired model
Update budget.
Commit and release budget.
The following code accomplishes these tasks.
AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget ...try model 1a --> not acceptable REVERT budget ...try model 1b --> ok. Done with Step 1 UPDATE MULTI budget ...try model 2a --> not acceptable REVERT budget ...try model 2b --> not acceptable REVERT budget ...try model 2c --> ok. Done with Step 2 UPDATE MULTI budget ...try model 3a --> ok. Done with Step 3. Done with all steps. UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace
The CONTEXT command lets you create and use a context during your Oracle OLAP session. A context is a means of preserving object values. After you create a context, you can save the current status of dimensions and the values of options, single-cell variables, valuesets, and single-cell relations in the context. You can then restore some or all of the object values from the context. A context exists only for the duration of an Oracle OLAP session. It is not an analytic workspace object and therefore cannot be saved as part of any analytic workspace. When a context contains saved values for objects in a particular analytic workspace, and you detach that analytic workspace, Oracle OLAP removes those objects from the context. That context retains any saved values for Oracle OLAP options and objects from other analytic workspaces that are still attached.
You can use the CONTEXT function to obtain information about a context.
The CONTEXT command and function provide an alternative to the PUSH and POP statements. With contexts, you can access and update the saved object values, whereas PUSH and POP simply allow you to save and restore values.
Syntax
CONTEXT context-name [ CREATE | APPLY | DISCARD | {SAVE |DROP|RESTORE} objects]
Parameters
A text expression that contains the name of the context.
Creates a context with the name specified by context-name, which must be unique.
Stores the values of the objects specified in objects in the context. You may save the values of single-cell variables and relations in a context. You cannot use the CONTEXT command to save the values of dimensioned variables, dimensioned relations, or the NAME dimension. If you try to save values from these objects, Oracle OLAP produces an error message.
Sets the appropriate objects to the values of all corresponding objects saved in the context.
Deletes the context.
Stores the values of the objects specified in objects in the context.
Drops the values of the objects specified in objects from the context.
|
Note: When you delete an Oracle OLAP object during the session, it is also removed from the context. |
Sets whatever objects you specify in objects to the values of the corresponding objects saved in the context.
One or more object names. Each object name must be separated by a space. When you are listing several name(s) that do not fit on a single line, you may use the continuation character to continue the CONTEXT command on additional lines.
Usage Notes
Naming Convention
A suggested programming practice is to name the context after the analytic workspace with which it is associated.
Examples
Example 9-72 Saving Dimension Status
This example shows how you can use the CONTEXT command to save and restore the status of a dimension. The following statements create a context that includes a subset of the values in the product dimension.
LIMIT product TO 'Tents' 'Canoes' CONTEXT 'democontext1' CREATE CONTEXT 'democontext1' SAVE product
The following statements limit product to all its values and produce a report that lists them all.
LIMIT product TO ALL REPORT product
This is the report.
PRODUCT ----------- Tents Canoes Racquets Sportswear Footwear
The following statements apply the saved context and produce a report that lists only the values included in the context.
CONTEXT 'democontext1' APPLY REPORT product
This is the new report.
PRODUCT ----------- Tents Canoes
The AGGROPS function returns the keywords for all of the aggregation operators that you can specify in a RELATION (for aggregation) statement, listed one name on each line in a multiline text value.
Return Value
TEXT
Syntax
AGGROPS
Example
Example 7-10 Displaying a List of the Aggregation Operators
When you issue a a AGGROPS statement, Oracle OLAP returns a list of all of the aggregation operators.
SHOW AGGROPS SUM WSUM SSUM AND OR FIRST LAST HFIRST HLAST AVERAGE WAVERAGE HAVERAGE HWAVERAGE MIN MAX WFIRST WLAST HWFIRST HWLAST WMIN WMAX NOAGG
When a program, model, or input file is executing, the BADLINE option controls whether Oracle OLAP records, in the current outfile, the line that caused an error.
Data Type
BOOLEAN
Syntax
BADLINE = {YES|NO}
Parameters
When an error occurs during the execution of a program, model, or input file, Oracle OLAP records in the current outfile the name of the program, model, or file in which the error occurred and the line that caused the error. When an error message is included in the output, the BADLINE information appears immediately after the error message.
(Default) When an error occurs in a program, model, or input file, Oracle OLAP does not record the error in the current outfile.
Examples
Example 5-4 Using the BADLINE Option
In a simple program called test, the variable myint1 is divided by zero.
DEFINE test PROGRAM PROGRAM VARIABLE myint1 INTEGER VARIABLE myint2 INTEGER myint1 = 0 myint2 = 250/myint1 END
When you run the program when the DIVIDEBYZERO option is set to NO, then an error occurs because division by zero is not allowed. When BADLINE is set to YES, the following messages are recorded in the current outfile.
ERROR: (MXXEQ01) A division by zero was attempted. Set DIVIDEBYZERO to YES if you want NA to be returned as the result of division by zero. In DEMO!TEST PROGRAM: myint2 = 250/myint1
Example 5-5 Finding Errors in Program Lines
In a simple program called test, the variable myint1 is divided by 0 (zero).
DEFINE test PROGRAM PROGRAM VARIABLE myint1 INTEGER VARIABLE myint2 INTEGER myint1 = 0 myint2 = 250/myint1 END
When you run the program, an error occurs because division by zero is not allowed (that is, when DIVIDEBYZERO is set to NO).
When BADLINE is set to NO only the error is recorded in the current outfile.
ERROR: (MXXEQ01) A division by zero was attempted. (If you want NA to be returned as the result of a division by zero, set the DIVIDEBYZERO option to YES.)
When BADLINE is set to YES, the line that causes the error and the name of the program in which the error occurred are recorded in the current outfile.
ERROR: (MXXEQ01) A division by zero was attempted. (If you want NA to be returned as the result of a division by zero, set the DIVIDEBYZERO option to YES.) In TESTBAD PROGRAM: myint2 = 250/myint1 In EDDE.RUNCMD PROGRAM:
The SESSIONTIMEZONE function returns the time zone of the current session.
Return Values
A time zone offset (a character type in the format '[+|]TZH:TZM') or a time zone region name, depending on how the user specified the session time zone value in the most recent ALTER SESSION statement
Syntax
SESSIONTIMEZONE
Examples
The MEDIAN function calculates the median of the values of an expression. The median is the middle number in a given sequence of numbers.
Return Value
DECIMAL
Syntax
MEDIAN(expression [CACHE] [dimension...])
Parameters
The expression whose median value is to be calculated.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of expression and another dimension that you want as a dimension of the result.
By default, MEDIAN returns a single value. When you indicate one or more dimensions for the result, MEDIAN calculates values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of expression, but, instead, is dimension that is related to a dimension of expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
NA Values and MEDIAN
MEDIAN is affected by the NASKIP option in the same manner as other aggregate functions. When NASKIP is set to YES (the default), MEDIAN ignores NA values and returns the median of the values that are not NA. When NASKIP is set to NO, MEDIAN returns NA when any value of the expression is NA. When all the values of the expression are NA, MEDIAN returns NA for either setting of NASKIP.
Examples
Example 8-24 Calculating Median Monthly Sales
This example shows how to calculate the median monthly sales of sportswear for each sales district.
LIMIT product TO 'Sportswear' REPORT W 12 HEADING 'Median Sales' MEDIAN(sales district)
The preceding statements produce the following output.
DISTRICT Median Sales ----------------- ------------ Boston 67,923.05 Atlanta 152,186.52 Chicago 94,372.06 Dallas 160,854.60 Denver 86,745.40 Seattle 53,950.28
The CALENDARWEEK option determines whether weeks should be aligned with the actual calendar year.
|
Note: You can only use this function with dimensions of type WEEK. |
Data Type
BOOLEAN
Syntax
CALENDARWEEK = {YES|NO}
Parameters
(Default) Specifies that weeks are aligned with the calendar year. For example, if you have defined a dimension of type WEEK, Oracle OLAP numbers its values so that the first week in the calendar year is week 1, the second week in the calendar year is week 2, and so on. Weeks are aligned with the calendar year regardless of any beginning or ending date specified in the WEEK dimension definition.
Specifies that weeks are not aligned with the calendar year. Instead, weeks are numbered so that they are aligned with the date specified in the dimension definition. For example, if you have defined a dimension of type WEEK with a beginning or ending date, its values are numbered so that the week corresponding to the date in the dimension definition is week 1, the following week is week 2, and so on.
Usage Notes
Fiscal Years
Setting CALENDARWEEK to NO causes weeks to be numbered so that the number 1 is assigned to the week beginning or ending on the date specified in the DEFINE DIMENSION statement. This week is then assigned to a fiscal year, which is the calendar year of the first January 1 on or after the week's starting date. For example, if you define a dimension of type WEEK with a starting date of 02Jan1996 (or, equivalently, an ending date of 08Jan1996), the week starting 02Jan1996 is considered week 1 of fiscal year 1997. If, by contrast, you had given the dimension a starting date between 02Jan1995 and 01Jan1996, then the week starting on that date is week 1 of fiscal year 1996.
Examples
Example 5-7 Aligning Weeks with the Calendar Year
The following statements define a dimension of type WEEK, define its ending date, add values to the dimension, and produce a report.
DEFINE week dimension WEEK ENDING '18Jan97' MAINTAIN week ADD '21Dec96' '25Jan97' REPORT W 22 CONVERT(week DATE)
These statements produce the following output.
WEEK CONVERT(WEEK DATE) -------------- -------------------- w51.96 21Dec96 w52.96 28Dec96 w1.97 04Jan97 w2.97 11Jan97 w3.97 18Jan97 w4.97 25Jan97
Example 5-8 Aligning Weeks with a Specified Ending Date
The following statements set the CALENDARWEEK option to NO, which aligns the weeks with the ending date that is specified in the definition of the week dimension in "Aligning Weeks with the Calendar Year".
CALENDARWEEK = NO REPORT W 22 CONVERT(week date)
These statements produce the following output.
WEEK CONVERT(WEEK DATE) -------------- -------------------- w50.97 21Dec96 w51.97 28Dec96 w52.97 04Jan97 w53.97 11Jan97 w1.98 18Jan97 w2.98 25Jan97
The FCOPEN function creates a forecasting context and returns a handle to this context.
You must use the FCOPEN function in combination with other OLAP DML statements as outlined in "Forecasting Programs".
Return Value
INTEGER
Syntax
FCOPEN(text-expression [prototype-handle])
Parameters
The name of the forecasting context.
An INTEGER expression that is the handle to a different forecasting context that was previously-created using the FCOPEN function. Oracle OLAP initializes the new forecasting context with the same options as the forecasting context specified by this parameter. (See the FCSET command for descriptions of the options that specify the characteristics of a forecasting context.)
Examples
For an example of a forecasting program, see Example 9-119, "A Forecasting Program".
The CONVERT function converts values from one type of data to another.
Return Value
The return value depends on the value of the type argument.
Syntax
CONVERT(expression, type [argument...])
Parameters
The expression or variable to be converted.
The type of data to which you want to convert expression. The keywords that represent the types are described in Table 7-3, "Keywords for the type Parameter of the CONVERT Function".
Table 7-3 Keywords for the type Parameter of the CONVERT Function
| Keyword | Description |
|---|---|
|
BINARY |
Does not indicate conversion to a standard Oracle data type but allows additional conversion capabilities. BINARY does no conversion. The internal representation of every value, regardless of data type, is returned as a text value.
|
|
BOOLEAN |
Conversion to Oracle OLAP |
|
BYTE |
Converts a single character into an ASCII |
|
DATE |
Conversion to Oracle OLAP |
|
DATETIME |
Conversion to Oracle OLAP |
|
DECIMAL |
Conversion to Oracle OLAP |
|
DSINTERVAL |
Conversion to Oracle OLAP DML |
|
ID |
Conversion to Oracle OLAP |
|
INFILE |
Encloses an |
|
INTEGER |
Conversion to Oracle OLAP |
|
LONGINTEGER |
Conversion to Oracle OLAP |
|
NTEXT |
Conversion to standard Oracle OLAP data types. Corresponds to the |
|
NUMBER [( |
Conversion to Oracle OLAP |
|
PACKED |
Converts a number to a decimal value and then to packed format -- a text value 8 bytes long containing 15 digits and a plus or minus sign. Fractions cannot be represented in packed numbers; therefore the conversion process rounds decimal numbers to the nearest INTEGER. See "PACKED and BINARY Conversion". |
|
ROWID |
Converts a text value to a |
|
SHORTDECIMAL |
Conversion to Oracle OLAP |
|
SHORTINTEGER |
Conversion to Oracle OLAP |
|
TEXT |
Conversion to standard Oracle OLAP data types. Corresponds to |
|
TIMESTAMP |
Conversion to Oracle OLAP DML |
|
TIMESTAMP_LTZ |
Conversion to Oracle OLAP DML TIMESTAMP_LTZ data type. |
|
TIMESTAMP_TZ |
Conversion to Oracle OLAP DML |
|
UROWID |
Converts a text value to a |
|
YMINTERVAL |
Conversion to Oracle OLAP DML |
When you specify TEXT, NTEXT, ID, DATE, or INFILE for the type, you can specify additional arguments to determine how the conversion should be done as outlined in Table 7-4, "Syntax for Specifying Conversion to TEXT, NTEXT, ID, DATE, and INFILE".
Table 7-4 Syntax for Specifying Conversion to TEXT, NTEXT, ID, DATE, and INFILE
| Keyword for type argument | When Converting From | Syntax for All Parameters |
|---|---|---|
|
TEXT |
Any numeric |
TEXT [decimal-int|DECIMALS [comma-bool|COMMAS [paren-bool|PARENS]]] |
|
NTEXT |
Any numeric |
NTEXT [decimal-int|DECIMALS [comma-bool|COMMAS [paren-bool|PARENS]]] |
|
ID |
Any numeric |
ID [decimal-int|DECIMALS] |
|
TEXT, NTEXT, or ID |
Any datetime |
ID|TEXT|NTEXT ['date_format'] |
|
TEXT, NTEXT, or ID |
DATE |
ID|TEXT|NTEXT ['dateformat'] |
|
ID or TEXT for a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR with VNF |
DATE |
ID [dwmqy-dimension]|TEXT [dwmqy-dimension|'vnf '] |
|
DATE |
TEXT, NTEXT, or ID |
DATE [date-order|dwmqy-dimname] |
|
NTEXT |
TEXT |
NOXLATE |
|
TEXT |
NTEXT |
NOXLATE |
|
INFILE |
INFILE [width-exp|LSIZE [escape-int|0]] | |
|
IBINARY with |
BINARY [width-exp] |
An INTEGER expression that controls the number of decimal places to be used when converting numeric data to TEXT or ID values. When this argument is omitted, CONVERT uses the current value of the DECIMALS option (the default is 2).
A Boolean expression that determines whether commas are used to mark thousands and millions in the text representation of the numeric data. When the value of the expression is YES, commas are used. When this argument is omitted, CONVERT uses the current value of the COMMAS option (the default is YES).
A Boolean expression that determines whether negative values are enclosed in parentheses in the text representation of the numeric data. When the value of the expression is YES, parentheses are used; when the value is NO, a minus sign precedes negative values. When this argument is omitted, CONVERT uses the current value of the PARENS option (the default is NO).
A text expression that specifies the template to use when converting a datetime expression to text. The valid formats for each date field are the same as the formats that you can specify using the DATE_FORMAT command.
When you do not include the date_format argument, the format of the result is determined by the default date format for the session as described in "Default Datetime Format Template".
A text expression that specifies the template to use when converting a DATE-only expression to text. The template can include format specifications for any of the four components of a date (day, month, year, and day of the week). Each component in the template must be preceded by a left angle bracket (<)and followed by a right angle bracket (>). You can include additional text before, after, or between the components.
The valid formats for each date component are the same as the formats allowed in the DATEFORMAT option.
In the following statement, CONVERT returns today's date as a text value that is formatted by a dateformat argument.
SHOW CONVERT(TODAY TEXT '<MM>-<DD>-<YY>')
In this example, today's date is March 31, 1998, and the SHOW statement presents it in the following format.
03-31-98
When you do not include the dateformat argument, the format of the result is determined by the current setting of the DATEFORMAT option.
The name of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. Oracle OLAP uses the VNF of dwmqy-dimension when converting a DATE-only value to a TEXT or an ID value. When you have not specified the VNF of dwmqy-dimension, Oracle OLAP uses its default VNF.
In the following statement, CONVERT returns today's date as a text value that is formatted by the VNF of the YEAR dimension.
show convert(today text year)
In this example, today's date is March 31, 1998, and the SHOW statement presents it in the following format.
YR98
A text template that specifies the value name format to use when converting values of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR to text. The template can include format specifications for any of the components of a time period. Time period components include all the components of a date (day, month, year, and day of the week), plus the fiscal year and period components. The template can also include the name of the DAY, WEEK, MONTH, QUARTER, or YEAR dimension as a component. Each component in the template must be preceded by a left angle bracket and followed by a right angle bracket. You can include additional text before, after, or between the components.
The vnf argument to the CONVERT function is similar to the template in a VNF command. However, a VNF command template must be designed for precise and unambiguous interpretation of input, while the vnf argument is not so constrained. Therefore, the format styles allowed in the vnf argument are more extensive than those allowed in a VNF command template.
Valid format styles for a vnf argument include all the format styles allowed in the template of a VNF command, plus all the format styles allowed in a DATEFORMAT template. DATEFORMAT provides the following format styles that are not allowed in VNF command templates but that are valid in the vnf argument to the CONVERT function:
Ordinal styles for the day of the month (DT and DTL)
First-letter style for the month (MT)
Styles for the day of the week (W, WT, WTXT, WTXTL, WTEXT, and WTEXTL)
Append a B code to any of these formats to indicate that you want to display the beginning day or month of the period, rather than the final day or month.
You can use any combination of VNF and DATEFORMAT format styles with for any dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. This syntax contrasts with the template in a VNF command, in which only certain format combinations are valid for each type of dimension.
In the following statement, CONVERT returns the current value of the MONTH dimension as a text value that is formatted by a vnf argument.
SHOW CONVERT(month TEXT '<MTEXTL>, <YYYY>')
In this example, the first MONTH value in status is DEC97, and the SHOW statement presents it in the following format.
December, 1997
When you do not include the vnf argument, the format of the result is determined by the VNF of the dimension whose values you are converting. When the dimension has no VNF, the result is formatted according to the default VNF for the type of dimension being converted.
A text expression that specifies how to interpret the specified text value as a DATE-only value when the order of the text value's components (month, day, and year) is ambiguous. The expression can be one of the following: 'MDY', 'DMY', 'YMD', 'YDM', 'MYD', or 'DYM'. Each letter represents a component of the date: M stands for month, D stands for day, and Y stands for year.
When you do not include the date-order or dwmqy-dimname argument, any ambiguity in the interpretation of a text expression is resolved by the current setting of the DATEORDER option. Refer to the DATEORDER option for a complete description of DATE-only values and how they are interpreted.
The name of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR whose VNF or default date-order determines how to interpret the specified text value as a DATE-only value when the order of the text value's components is ambiguous.
When you do not include the date-order or dwmqy-dimname argument, any ambiguity in the interpretation of a text expression is resolved by the current setting of the DATEORDER option. Refer to the DATEORDER option for a complete description of DATE-only values and how they are interpreted.
An INTEGER expression that indicates the width of the output from CONVERT. The minimum width is 7. The default width is the current value of the LSIZE option. This argument is required when you specify the escape-int argument.
Indicates whether escape sequences are to be used in the output. For this argument you can specify a value listed in Table 7-5, "Values for escape-int Parameter of the CONVERT".
Table 7-5 Values for escape-int Parameter of the CONVERT
| Value | Description |
|---|---|
|
-1 |
Do not use escapes. Precede -1 with a comma ( |
|
0 |
(Default) Use escapes for unprintable characters. |
|
1 |
Use escapes for all characters. |
For more information on escape sequences in the OLAP DML, see "Escape Sequences".
An INTEGER expression that controls the width of the converted result. It can evaluate to 1, 2, or 4 bytes. The default width is 2 for BOOLEAN, or 4 for INTEGER. When an INTEGER value is too large to fit in the specified width, the result is NA. When the width is invalid or specified for some other data type, an error occurs.
A keyword indicating that no character set conversion should be performed. Instead, Oracle OLAP only tags the converted value with the target data type, leaving the data as it was before the CONVERT function was called. Use this keyword only when it is necessary to store binary data in a TEXT or NTEXT variable.
Usage Notes
INFILE Conversion
The maximum number of characters in a line is 4,000. An error occurs when you try an INFILE conversion that produces a line with more than 4,000 characters. This type of error can occur when the source line exceeds 99 characters and enough of them need escape sequences.
Converting DATE-only Values to Numeric Values
The result of converting a value that has the DATE-only data type to a value with any numeric data type is the sequence number that represents the date (the sequence number 1 represents January 1, 1900).
Oracle OLAP first converts the DATE-only value to an INTEGER value that is the sequence number that represents the DATE-only value. When the target data type is a numeric data type other than INTEGER, Oracle OLAP then converts that INTEGER value to the specified numeric data type.
The value 32,767 is the largest possible value for a SHORTINTEGER, and (as an INTEGER value) represents the date September 17, 1992. Therefore, CONVERT returns NA when you attempt to convert any DATE-only later than September 17, 1992 to a SHORTINTEGER value.
Converting Numeric Values to DATE-only Values
The result is the DATE-only whose sequence number matches the specified number (January 1, 1900 is represented by the sequence number 1); or NA, when the result is outside the range of valid dates. Valid dates range from January 1, 1900 (sequence number 1) to December 31, 9999 (sequence number 2,958,464).
When the numeric data type is an INTEGER data type, Oracle OLAP converts the INTEGER value directly to the DATE-only value whose sequence number matches the specified number. When the numeric data type is not INTEGER, Oracle OLAP first converts the numeric value to an INTEGER value and then converts that INTEGER value to a DATE-only value.
Converting DATE-only Dimension Values to ID Values
When the result is more than eight characters long, the result is truncated.
Converting Relation Values to INTEGER Values
The result is an INTEGER value that represents the position of the value in the relation's dimension. This behavior reflects the fact that the values of a relation are dimension values, not TEXT values.
Converting Values From One Numeric Data Type to Another
The result is the value in the specified data type; or NA when the value is outside the range of valid values for the target data type.
Thus, when you try to convert a an INTEGER value that is larger than 32,767 or smaller than -32,767 to a SHORTINTEGER value, CONVERT returns NA.
String-to-Datetime Conversion Rules
The following formatting rules apply when converting string valu2es to datetime values:
You can omit punctuation included in the format string from the datetime string if all the digits of the numeric format elements, including leading zeros, are specified. In other words, specify 02 and not 2 for two-digit format elements such as MM, DD, and YY.
You can omit time fields found at the end of a format string from the datetime string.
When a match fails between a datetime format element and the corresponding characters in the date string, then Oracle attempts alternative format elements, as shown in Table 7-6, "Oracle Format Matching".
Table 7-6 Oracle Format Matching
| Original Format Element | Additional Format Elements to Try instead Of the Original |
|---|---|
'MM' |
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Converting Null and Blank Text Values to BYTE Values
CONVERT returns the same value for a null string ('') as it does for a blank string (' '). In both cases, you get a result of 32.
PACKED and BINARY Conversion
The PACKED and BINARY types are useful for creating binary files that contain PACKED and BINARY data. To create such a file, use FILEOPEN statement with the BINARY keyword to open the file and FILEPUT to write values to it. You can use the ROW function as an argument to the FILEPUT statement to help format the file.
Examples
Example 7-49 Converting Decimal Values to Text
This example shows how to use the JOINCHARS and CONVERT functions to combine some text with the value of the variable price for a product and month, and show the price without decimal places.
LIMIT month TO 'Jul96'
LIMIT product to 'Canoes'
SHOW JOINCHARS('Price of Canoes = $' CONVERT(price TEXT 0))
Price of Canoes = $200
Example 7-50 Converting Text Values to Escape Sequences
This example shows how to use the CONVERT function with the ESCAPEBASE option to convert a TEXT value from its default decimal escape sequences to hexadecimal escape sequences.
DEFINE textvar VARIABLE TEXT textvar = 'testvalue' SHOW CONVERT(textvar INFILE 9 1) '\d116\d101\d115\d116\d118\d097\d108\d117\d101' ESCAPEBASE = 'x' SHOW CONVERT(textvar INFILE 9 1) '\x74\x65\x73\x74\x76\x61\x6C\x75\x65'
The $LOOP_VAR property specifies that when a OLAP_TABLE SQL function with the LOOP OPTIMIZED clause is executed, the formula on which it is assigned is looped in the same manner as the variable or QDR specified in the property.
Syntax
You add or delete a $LOOP_VAR property to the most recently defined or considered formula (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$LOOP_VAR' qdr | variable
To delete the property, issue the following statement.
PROPERTY DELETE '$LOOP_VAR'
Parameters
A QDR for a dimension of the formula.
A variable with the same dimensions as the formula.
The WKSDATA function returns the data type of each individual cell in a worksheet or the data type of a program argument with the WORKSHEET data type. You can use WKSDATA to help in the process of transferring labels and data between text files and Oracle OLAP.
Return Value
The data type of individual worksheet cells.
Syntax
WKSDATA(worksheetname)
Parameters
Specifies the name of an Oracle OLAP worksheet object, such as workunits.
Usage Notes
Checking One or More Cells
You can use WKSDATA to return the data type of a single worksheet cell by using a qualified data reference for the cell, as in the following format.
SHOW WKSDATA(worksheetname(WKSROW n, WKSCOL n))
Or you can use a REPORT statement in this format with WKSDATA to provide the contents of all the cells in a worksheet side-by-side with their data types.
REPORT worksheetname WKSDATA(worksheetname)
Multiple Data Types
Always use care when using worksheet objects in expressions. Because a worksheet object can contain multiple data types, the actual data type of individual worksheet cells is not considered when an OLAP DML statement is compiled. Instead, code is generated to convert each worksheet cell to the data type it expects at that position in the expression which may lead to unexpected results in some cases.
Text Data
All textual data (as opposed to numeric, Boolean, date, and so on) in a worksheet has the TEXT data type. The ID and NTEXT data types are not supported in worksheets.
Examples
Example 8-169 Checking Data Imported from a Worksheet
Suppose you have imported a flat data file into a worksheet called workunits. You can use WKSDATA to provide a quick way to determine which areas to treat as dimension values and which as data values in bringing the worksheet into standard OLAP workspace format.
This statement produces this output following the statement that shows the data in workunits
REPORT workunits
-----------------WORKUNITS-----------------
------------------WKSCOL-------------------
WKSROW 1 2 3 4
-------------- ---------- ---------- ---------- ----------
1 NA Jan96 Feb96 Mar96
2 Tents 307 209 277
3 Canoes 352 411 488
4 Racquets 1,024 1,098 1,144
5 Sportswear 1,141 1,262 1,340
6 Footwear 2,525 2,660 2,728
This statement uses the WKSDATA function to produce the report following the statement, which shows the data type of each cell in the worksheet.
REPORT WKSDATA(workunits)
------------WKSDATA(WORKUNITS)-------------
------------------WKSCOL-------------------
WKSROW 1 2 3 4
-------------- ---------- ---------- ---------- ----------
1 NA TEXT TEXT TEXT
2 TEXT INTEGER INTEGER INTEGER
3 TEXT INTEGER INTEGER INTEGER
4 TEXT INTEGER INTEGER INTEGER
5 TEXT INTEGER INTEGER INTEGER
6 TEXT INTEGER INTEGER INTEGER
The SQL command passes instructions written in Structured Query Language (SQL) to the relational manager from Oracle OLAP. Using the SQL command, you can insert and update data in relational tables, retrieve data from relational tables into analytic workspace objects, and execute stored procedures.
To use the SQL command, you must be familiar with SQL syntax and with the data structures in your relational database, and have the appropriate access rights to the relational tables that you want to use.
This entry describes the OLAP DML SQL command in general, and subsequent entries discuss the use of the OLAP DML SQL command for specific SQL statements:
Syntax
SQL sql-statement
Parameters
For sql-statement you can specify most SQL statements that can be executed dynamically and also several associated non-dynamic statements. You can also specify PROCEDURE for a stored procedure as described in SQL PROCEDURE. A SQL statement cannot exceed 128K bytes including the values of all non-textual OLAP DML input expressions.
You cannot specify the following SQL statements for sql-statement:
COMMIT -- To commit your changes, issue the OLAP DML COMMIT statement.
ROLLBACK -- You cannot rollback using the OLAP DML. When you specify SQL ROLLBACK, you receive an error message stating that ROLLBACK is not supported as an argument to an OLAP DML SQL statement.
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Important: When you use an OLAP DML SQL statement to request a rollback in some other fashion (for example, using SQL EXECUTE), Oracle OLAP issues a system error message, abnormally terminates the OLAP DML program that issued the statement. Oracle OLAP also detaches, in an indeterminate state, the analytic workspace that contains the OLAP DML program that made the rollback request and any other attached analytic workspaces with uncommitted updates. |
Oracle OLAP evaluates some SQL statements before sending them to the relational manager. For example, Oracle OLAP evaluates SQL PREPARE and SQL EXECUTE, and SQL statements that copy data from relational tables into analytic workspace objects (See "Copying Relational Data into Analytic Workspace Objects" for a list of these statements).
Usage Notes
Copying Relational Data into Analytic Workspace Objects
You can copy relational data into analytic workspace objects using either an implicit cursor or an explicit cursor:
To copy data from relational tables into analytic workspace objects using an implicit cursor, use a SQL SELECT statement. You can use this OLAP DML statement interactively in the OLAP Worksheet or within an OLAP DML program.
To copy data from relational tables into analytic workspace objects using an explicit cursor, use the following commands within an OLAP DML program in the order indicated:
SQL DECLARE CURSOR to define a SQL cursor by associating it with a SELECT statement or procedure.
SQL OPEN to activate a SQL cursor.
SQL FETCH or SQL IMPORT to retrieve and process data specified by a cursor.
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Tip: SQL FETCH offers the most functionality; while SQL IMPORT offers improved performance when copying large amounts of data from relational tables into analytic workspace object. |
SQL CLOSE to close a SQL cursor.
SQL CLEANUP to cancel all SQL cursor declarations and free the memory resources of an SQL cursor.
Oracle OLAP evaluates all of these statements before sending them to the relational manager.
For the syntax of these statements, see the individual topics. For the syntax of other SQL statements, refer to Oracle Database SQL Language Reference.
Inserting Data into a Relational Table
You can insert analytic workspace data into a relational table using SQL PREPARE statement for a SQL INSERT statement (typically with DIRECT= YES), and then executing the statement using SQL EXECUTE.
Options Related to the OLAP DML SQL Statements
Several options are available to you when embedding SQL into the OLAP DML. These options are listed in "SQL Embed Options".
Using OLAP DML Expressions in OLAP DML SQL Statements
You can use OLAP DML expressions (for example, OLAP DML variables) as arguments in many OLAP DML SQL statements. OLAP DML input expressions are values supplied by Oracle OLAP as parameters to a SQL statement. They specify the data to be selected or provide values for data that is being modified. You can use OLAP DML input expressions in SQL WHERE clauses, parameter list for procedures, UPDATE statements, and the value clause of INSERT.
Keep the following points in mind when using an OLAP DML expression in an OLAP DML SQL statement:
OLAP DML expressions must be preceded by a colon (for example, :myvar).
When you specify a dimension or a dimensioned variable as an OLAP DML input expression, the first value in status is used; no implicit looping occurs, although you can use a FOR or an ACROSS statement to loop through all of the values. An OLAP DML input expression can be any expression with an appropriate data type. The value of an OLAP DML input expression is taken when a cursor is opened, not when it is declared. See Example 10-131, "Inserting Data in a Table".
To update or insert data in a relational table that has either the CLOB and NCLOB data type, you use WIDE in the OLAP DML input expression as described in "Inserting Large Text Values into a CLOB or NCLOB Column" .
Error Checking
Oracle OLAP can detect some syntax errors in the arguments to the SQL statement, but most errors are detected by the Oracle RDBMS. Error codes and messages are returned to Oracle OLAP. Check the value of SQLCODE after each SQL statement to determine when it resulted in an error. When it does cause an error (that is when SQLCODE EQ -1), check the value of SQLERRM for information about the cause of the error.
Converting Oracle RDBMS Data Types into Oracle OLAP DML Data Types
Table 10-10, "RDBMS Data Type Conversion to OLAP DML Data Types" shows which Oracle RDBMS data types can be automatically converted into Oracle OLAP DML data types. You must explicitly convert or cast other data types in the SELECT statement within a SQL DECLARE CURSOR statement.
Table 10-10 RDBMS Data Type Conversion to OLAP DML Data Types
| Oracle RDBMS Data Type | OLAP DML Dimension Type | OLAP DML Variable Data Type |
|---|---|---|
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- |
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SQL UPDATE Statements
SQL UPDATE statements can contain a WHERE clause, which specifies a particular search condition. In addition to the search conditions typically used in SQL, the phrase WHERE CURRENT OF cursor is supported for single tables and views that include columns from only one table. The cursor must have been defined with the FOR UPDATE clause as described in SQL DECLARE CURSOR.
Examples
Example 10-131 Inserting Data in a Table
You can use SQL statements such as the following to create a table and add rows to that table. The SQL INSERT statement adds a row to the sales table using values from the dimension salesperson and the variable dollars. It adds one row using the first value of salesperson that is in status.
SQL CREATE TABLE sales (name CHAR(12), dollars INTEGER) SQL INSERT INTO sales VALUES (:salesperson, :dollars)
The SQL CLEANUP command cancels all SQL cursor declarations and frees the memory resources for all SQL cursors. You use the SQL CLEANUP command in combination with other SQL commands to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects"
Syntax
SQL CLEANUP
Examples
For an example of the use of SQL CLEANUP, see Example 10-141, "Fetching Data into a Concat Dimension".
The SQL CLOSE command closes a SQL cursor. You use the SQL OPEN command in combination with other SQL commands to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects".
Syntax
SQL CLOSE cursor
Parameters
The name of a cursor previously opened with a SQL OPEN statement.
Usage Notes
Redefining the Result Set
You can change the result set associated with a cursor by closing the cursor, setting the value of an OLAP DML input expression, and issuing a new SQL OPEN statement. You do not have to free the cursor and redeclare it.
The SQL DECLARE CURSOR command defines an explicit SQL cursor by associating it with a SELECT statement or procedure. The SELECT statement specifies the scope of the data (the rows and columns) selected by the cursor. You use the SQL DECLARE CURSOR command in combination with other SQL commands to use an explicit cursor to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects".
Two pseudo procedures, SQLTABLES and SQLCOLUMNS, allow you to obtain information about tables and columns.
Syntax
SQL DECLARE cursor CURSOR FOR {select-statement [FOR UPDATE]|table-info}
where table-info is one of the following:
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Note: You specify table-info only to declare a cursor when select-statement is a SQL FETCH statement. |
Parameters
The name of the cursor you are defining. Cursor names can consist of 1 to 18 alphanumeric characters or the symbols @, _, $, or #. A name that contains symbols @, $, or # must be enclosed in single quotes. The first character cannot be a number or an underscore. Cursor names are internal to Oracle OLAP. Unless you have issued a SQL CLEANUP statement, when you try to declare a cursor with the same name as a previously declared cursor, but with a different SQL SELECT statement, an error is signaled.
A SQL SELECT statement that identifies the data you want to associate with the cursor. For the syntax of an SQL SELECT statement, refer to Oracle Database SQL Language Reference.
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Tip: Since both OLAP DML syntax and SQL syntax allow you to use AND and OR, construct the clause clearly so that Oracle OLAP can identify the end of an OLAP DML input expression. Use parenthesis to clarify the syntax in these situations and when using a SQL operator that is unknown in Oracle OLAP. |
Indicates that SQL FETCH is used to write data to the table. This clause is required when the cursor is used in an UPDATE statement with a WHERE CURRENT OF cursor clause. The names of the columns to be updated can be listed in an OF clause (for example, FOR UPDATE OF COL1, COL2, COL3).
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Note: The FOR UPDATE clause is ignored by SQL IMPORT and SQL SELECT. |
When declaring a cursor for use by SQL FETCH, calls the pseudo procedure SQLTABLES, which returns the following values for each table that matches the search criterion as illustrated in Example 10-133, "Discovering Information About Relational Tables":
tableowner -- A text value identifying the owner of the table.
tablename -- A text value identifying the name of the table.
tabletype -- A text value identifying the type of table using one of the following: TABLE, VIEW, SYSTEM TABLE, ALIAS, SYNONYM, LOCAL TEMPORARY, GLOBAL TEMPORARY, or NA (indicating an unrecognized type).
When declaring a cursor for use by SQL IMPORT, you cannot use this clause.
When declaring a cursor for use by SQL FETCH, calls the pseudo procedure SQLCOLUMNS, which returns the following values for each column that matches the search criterion as illustrated in Example 10-134, "Discovering Information About the Columns of a Relational Table":
tableowner -- A text value identifying the owner of the table.
tablename -- A text value identifying the name of the table.
colname -- A text value identifying the name of the column.
coltype -- A text value identifying the data type of the column.
olaptype -- A text value identifying the data type that most closely matches coltype.
length -- An INTEGER value identifying the length of column values.
precision -- An INTEGER value identifying the precision of numeric column values.
scale -- An INTEGER value identifying the scale of column values.
nullable -- A text value of Y or N indicating whether the column can contain null values.
When declaring a cursor for use by SQL IMPORT, you cannot use the PROCEDURE SQLCOLUMNS clause.
Literal text or the name of an OLAP DML variable whose value specifies one or more owners. This expression acts as a filter to limit the results to only tables belonging to the specified owners. The keyword NULL or an OLAP DML variable with an NA value causes all table owners to be included in the results.
The expression can be specific, such as 'SCOTT', or it can contain wildcard characters such as 'S%T' (all owners whose name begins with S and ends with T). The value retains its case when it is passed to the database, so be sure to enter the value with the appropriate use of upper- and lowercase letters. For example, Oracle relational databases by default store all values in uppercase and do not match 'scott' or 'Scott' with 'SCOTT'.
Literal text or the name of an OLAP DML variable whose value specifies one or more tables. This expression acts as a filter to limit the results to only tables with the specified names. The keyword NULL or an OLAP DML variable with an NA value causes all tables to be included in the results.
The expression can be specific, such as 'PAYROLL', or it can contain wildcard characters such as '%ROLL' (all tables whose name ends with ROLL). The value retains its case when it is passed to the database, so be sure to enter the value with the appropriate use of upper- and lowercase letters. For example, Oracle relational databases by default store all values in uppercase and do not match 'payroll' or 'Payroll' with 'PAYROLL'.
Literal text or the name of an OLAP DML variable whose value specifies one or more columns. This expression acts as a filter to limit the results to only columns with the specified names. The keyword NULL or an OLAP DML variable with an NA value causes all tables to be included in the results.
The expression can be specific, such as 'SALARY', or it can contain wildcard characters such as 'SAL%' (all columns whose name begins with SAL). The value retains its case when it is passed to the database, so be sure to enter the value with the appropriate use of upper- and lowercase letters. For example, Oracle relational databases by default store all values in uppercase and do not match 'salary' or 'Salary' with 'SALARY'.
Usage Notes
General Restrictions that Apply to SQL DECLARE CURSOR
The following restrictions apply to the SQL DECLARE CURSOR command:
You can use it only in a program.
It cannot contain ampersand substitution.
Restrictions when Declaring a Cursor for Use by SQL IMPORT
When declaring a cursor to be used by a SQL IMPORT statement, you can only use the following simplified syntax.
SQL DECLARE cursor CURSOR FOR select-statement
where select-statement is a SQL SELECT statement that identifies the data you want to associate with the cursor. You cannot use the FOR UPDATE clause or the table-info clause.
Cursor's Result Set
A cursor's result set is determined at the time it is opened, and it is not updated later. Therefore, when you change the value of an OLAP DML input expression after you open its cursor, the change does not affect the cursor's result set. A cursor remains open until a SQL CLOSE statement is executed for that cursor or until a SQL CLEANUP statement closes all cursors. A cursor is not automatically closed at the termination of the program in which it was opened.
Optimizing Fetches
When fetching values into a multidimensional input variable, list the columns that correspond to the dimensions in an ORDER BY clause in the select-statement argument of a SQL DECLARE CURSOR statement, with the slowest-varying dimension first which optimizes performance.
Examples
Example 10-132 Testing for the Value of SQLCODE
Cursor c1 is declared for three columns in the table mkt, which is owned by user sqldba. Values from the three columns are fetched into three analytic workspace objects. The first OLAP DML object is the market dimension, which is temporarily limited to the retrieved value. Because of the temporary status of market, the other column values are assigned to the appropriate cells of the other OLAP DML objects.
This example tests the value of SQLCODE in two places. A more complete program would do more error checking.
DEFINE market DIMENSION TEXT DEFINE mkt.desc TEXT <market> DEFINE mkt.abbrev ID <market> DEFINE sql.market PROGRAM PROGRAM TRAP ON ERROR SQL DECLARE c1 cursor FOR - SELECT mktcode, mktabbrev, mktdesc FROM sqldba.mkt SQL OPEN c1 IF SQLCODE NE 0 THEN SIGNAL SQLERR 'open cursor failed.' WHILE SQLCODE EQ 0 SQL FETCH c1 INTO :APPEND market, :mkt.abbrev, :mkt.desc SQL CLOSE c1 ... RETURN error: ... END
Example 10-133 Discovering Information About Relational Tables
The following program fetches information about all tables owned by Scott. Notice that the value of the ownername variable is set after the SQL DECLARE cursor statement; it can be set any time before the SQL OPEN statement. The tablename variable is not set, but is initialized automatically to NA, which is passed as a null value.
DEFINE ownername TEXT "Search criteria
DEFINE tablename TEXT "Search criteria
DEFINE tblowner TEXT "Search results
DEFINE tblname TEXT "Search results
DEFINE tbltype TEXT "Search results
SQL DECLARE c1 CURSOR FOR PROCEDURE sqltables(:ownername, :tablename)
ownername = 'Scott'
SQL OPEN c1
WHILE SQLCODE EQ 0
DO
SQL FETCH c1 INTO :tblowner, :tblname, :tbltype
... "Process fetched values
DOEND
Example 10-134 Discovering Information About the Columns of a Relational Table
The following program fetches information about all columns in the employee table owned by Scott. Notice that NULL (and not NA) is used for the value of the third argument to SQLCOLUMNS since it is processed by the relational manager, not Oracle OLAP.
DEFINE tblname TEXT "Search results
DEFINE tblowner TEXT "Search results
DEFINE colname TEXT "Search results
DEFINE coltype TEXT "Search results
DEFINE olaptype TEXT "Search results
DEFINE length INTEGER "Search results
DEFINE precision INTEGER "Search results
DEFINE scale INTEGER "Search results
DEFINE nullable TEXT "Search results
SQL DECLARE c1 CURSOR FOR PROCEDURE sqlcolumns('Scott', -
'Employee', NULL)
SQL OPEN c1
WHILE SQLCODE EQ 0
DO
SQL FETCH c1 INTO :tblowner, :tblname, :colname, :coltype, -
:olaptype, :length, :precision, :scale, :nullable
... "Process fetched values
DOEND
The SQL EXECUTE command executes SQL statements that have been compiled using SQL PREPARE. Typically, the SQL statements that you precompile are statements that are executed repeatedly, particularly those involving OLAP DML input expressions, such as INSERT, UPDATE, and DELETE.
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Note: The SQL PREPARE and SQL EXECUTE commands can only be used within the same DML program. |
Syntax
SQL EXECUTE statement-name
Parameters
The name that you assigned to the executable code when you prepared it using SQL PREPARE.
Examples
Example 10-135 Updating a Relational Table Using Analytic Workspace Data
The next example shows a simple update of a table using data stored in Oracle OLAP. The market dimension is limited to one value at a time in the FOR loop. The SQL phrase WHERE s.market=:market specifies that the sales value in the row for that market is the value that is changed.
FOR market SQL UPDATE mkt SET sales=:mkt.sales WHERE s.market=:market
An UPDATE statement should be used in a SQL PREPARE statement and executed in a FOR loop.
SQL PREPARE s2 FROM UPDATE mkt -
SET sales=:mkt.sales WHERE s.market=:market
FOR market
DO
SQL EXECUTE s2
IF SQLCODE NE 0
THEN BREAK
DOEND
The SQL FETCH command retrieves and processes data specified by a named SQL cursor. SQL FETCH assigns the retrieved data to OLAP objects. You use the SQL FETCH command in combination with other SQL commands to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects".
Syntax
SQL FETCH cursor [LOOP [loopcount]] -
INTO :targets... [THEN action-statements...]
where:
targets is one or more of the following:
position is one of the following:
Parameters
The name of a declared and opened cursor.
Specifies that Oracle OLAP should implicitly loop over the rows obtained from a relational table. For each row, Oracle OLAP copies the data in individual fields to objects specified as target analytic workspace objects. When you include a LOOP clause, SQL FETCH continues processing rows until it reaches the end of the active set specified by the cursor, or an error occurs, or loopcount is satisfied. In most cases, use the LOOP clause to improve the performance of SQL FETCH.
When you do not specify a LOOP clause and the cursor contains multiple rows in its active set, you must code the SQL FETCH statement within a WHILE loop. This loop must be based on the value of the SQLCODE option, which returns a nonzero value to indicate the end of the data or an error.
Optional INTEGER argument to the LOOP keyword. Loopcount controls how SQL FETCH loops over the rows from a relational table. Loopcount can be a literal value, an OLAP DML variable, or NA. When loopcount is less than or equal to zero, no looping occurs and no data is fetched.
When you specify a LOOP clause without a value for loopcount, SQL FETCH continues reading rows and copying their contents to target analytic workspace objects until there are no more rows or an error occurs. Internally, each row is processed until SQLCODE is nonzero.
When you specify a literal value for loopcount, SQL FETCH processes the number of rows specified by loopcount or until SQLCODE is nonzero.
When you specify a variable for loopcount, it must be in the form of an OLAP DML variable (preceded by a colon). This variable acts as both an input and an output variable. The initial value of loopcount specifies the number of rows that SQL FETCH attempts to process. Upon completion of the SQL FETCH, loopcount contains the number of rows actually processed.
When you specify NA for loopcount, SQL FETCH processes rows until SQLCODE is nonzero. However, upon completion of the SQL FETCH, loopcount contains the number of rows actually processed.
Identifies the analytic workspace objects in which you want to store data that is retrieved from a relational table. This list of target analytic workspace objects must correspond in number and data type with the list of table columns specified in the select-statement argument of the SQL DECLARE CURSOR command that declared cursor. A target can be a variable, a qualified data reference, a relation, a dimension, a composite, or a conjoint.
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Important: The order in which you specify the target analytic workspace objects affects dimension status. For each dimension value, Oracle OLAP temporarily limits the status of the dimension to the fetched value. Values are assigned to subsequent analytic workspace objects according to this temporary status. See "Conjoints as Target Analytic Workspace Objects" and "Composites as Target Analytic Workspace Objects". |
A target must be preceded by a colon. When the target is a dimension, it can include the MATCH and APPEND keywords to specify dimension handling; in this case, the colon precedes the keywords.
(Default) Oracle OLAP does not perform dimension maintenance on the target dimension or surrogate. It uses the incoming values to align data that is being fetched into dimensioned objects. When a value from the relational database does not match any value in the dimension or surrogate, an error is signaled.
Oracle OLAP performs dimension maintenance on the target dimension, adding new values to the dimension. It uses both old and new dimension values to align data being fetched into dimensioned objects. By default, new values are added to the end of a dimension or surrogate.
position is one of the following:
AFTER dimension-value
Any new values are added after dimension-value in the status list.
BEFORE dimension-value
Any new values are added immediately before dimension-value in the status list.
FIRST
Any new values are added to the beginning of the status list.
LAST
Any new values are added to the end of the status list.
The position can also be used to control how dimension values are processed in action statements.
Assigns the values to the specified surrogate.
Specifies any number of action-statements to be performed each time a row of data is fetched and assigned to target analytic workspace objects. An action-statement can be one of the following:
assignment-statement
IF statement
SELECT-statement
ACROSS statement: action-statement
<action-statement-group>
Refer to the SQL IMPORT command for a complete description of the syntax of action-statements.
Usage Notes
Effect of Order SQL FETCH Targets on Dimension Status
For each dimension value, Oracle OLAP temporarily limits the status of the dimension to the fetched value. Values are assigned to subsequent analytic workspace objects according to this temporary status.
Conjoints as Target Analytic Workspace Objects
You can use a conjoint dimension as a target analytic workspace object, but you must ensure that you select the same number of columns from the relational table as there are simple base dimensions. When Oracle OLAP executes a SQL FETCH statement for a target that is a conjoint dimension, it uses the dimension order that was specified when the conjoint was defined.
Composites as Target Analytic Workspace Objects
You can specify analytic workspace objects for composites just as you would for dimensioned variables. For example, to fetch data into a variable var1 dimensioned by dim1 and dim2, you would specify the following list of target analytic workspace objects.
:dim1 :dim2 :var1
To fetch data into a variable var2 dimensioned by a composite whose dimensions are dim1 and dim2, you would specify the following list of target analytic workspace objects.
:dim1 :dim2 :var2
Null Values
A null value in SQL is equivalent to an NA value in Oracle OLAP, so null values fetched into target analytic workspace objects are given NA values. Since Oracle OLAP handles null values in this way, the SQL command does not support INDICATOR variables in the INTO clause of a SQL FETCH statement. When fetching null values into a dimension, however, Oracle OLAP discards the values for the entire row.
Working with Boolean Variables as Input and Target Objects
You can use Boolean variables as input and target analytic workspace objects for OLAP SQL commands. In OLAP DML input expressions, Oracle OLAP treats Boolean values as INTEGER values with a value of 1 (TRUE) or 0 (FALSE).
As target analytic workspace objects, Boolean variables can receive values from any numeric (or bit) column in a relational table.
Fetching Text Data into DATE Variables
When fetching text data into a DATE variable, the current setting of the DATEORDER option is used to interpret the value. For example, a text value of 12-08-96 could be interpreted as December 8, 1996, or August 12, 1996, depending on the setting of DATEORDER.
Untransferable Data Types
You cannot transfer data with the following data types: LONG RAW, ROWID, UROWID, BLOB, and BFILE.
Examples
Example 10-136 Fetching Data From Relational Tables -- A Simple SQL FETCH
he following program fragment shows the basic steps of declaring and opening a cursor, and fetching the data. Relational data from the Prod_ID and Prod_Name columns of the Products table are fetched into the prod dimension and prod_label variable. The variable prod_label is dimensioned by prod. Notice that the SQL FETCH statement in this example does not include a LOOP clause; it therefore retrieves a single row of data each time it is called.
VARIABLE set_price SHORT
set_price = 20
...
SQL DECLARE highprice CURSOR FOR SELECT Prod_ID, Prod_Name -
FROM Products WHERE suggested_price > :set_price
SQL OPEN highprice
WHILE SQLCODE EQ 0
SQL FETCH highprice INTO :prod, :prod_label
Example 10-137 Fetching Data From Relational Tables with a THEN Clause
The following program fragment shows the SQL FETCH statement from the previous example with the addition of the LOOP keyword and a THEN clause. Because of the LOOP keyword, this SQL FETCH statement does not have to run within a WHILE loop. The action statement following the THEN keyword copies any product names stored in prod_label that start with the letter A into a multiline text variable called a_product.
SQL FETCH highprice LOOP INTO :prod, :prod_label -
THEN IF UPCASE(EXTCHARS(prod_label, 1, 1)) EQ 'a' -
THEN a_product = JOINLINES(a_product prod_label)
Example 10-138 Populating with Relational Data While Maintaining a Conjoint Dimension
In this example, a conjoint dimension (named mpt) is used as a target analytic workspace object. To populate a conjoint dimension, you must select values from the relational database for each of its base dimensions. Here, the three base dimensions are market, product, and time. Therefore, the SELECT statement specifies the three corresponding columns (Mktcode, Prdcode, and Percode). The program assumes that the market, product, and time dimensions are already populated with up-to-date values; Oracle OLAP does not update the base dimensions unless you explicitly specify them as target analytic workspace objects.
DEFINE mpt DIMENSION <market product time> DEFINE sql.mpt PROGRAM PROGRAM ... SQL DECLARE c1 CURSOR FOR - SELECT Mktcode, Prdcode, Percode FROM Sqldba.Data IF SQLCODE NE 0 THEN SIGNAL sqlerrm SQL OPEN c1 SQL FETCH c1 LOOP INTO :append mpt SQL CLOSE c1 ... END
Example 10-139 Populating Data While Maintaining Base and Conjoint Dimensions
To retrieve current values for the base and conjoint dimensions, or to retrieve the values for the first time, you can fetch the values for the base dimensions immediately before you fetch the values for the conjoint dimension. In the following example, the SQL DECLARE CURSOR and SQL FETCH commands have been edited to fetch both base and conjoint dimension values. Notice that the number of columns selected from the relational table must match the number of base dimensions fetched. There are six column specifications in the SELECT statement. The first three match the three base dimensions, and the last three match the conjoint dimension itself.
SQL DECLARE c1 CURSOR FOR -
SELECT Mktcode, Prdcode, Percode, Mktcode, -
Prdcode, Percode FROM Sqldba.Data
...
SQL FETCH c1 LOOP INTO :APPEND market, :APPEND product, -
:APPEND time, :APPEND mpt
Example 10-140 Populating Variables with Relational Table Data while Maintaining Dimensions
In the next example, variable dollars.mpt is dimensioned by the conjoint mpt, and its values are populated in the same SQL FETCH statement with the dimension values. The SQL DECLARE CURSOR and SQL FETCH commands have been edited again with the new column and target analytic workspace object added.
DEFINE dollars.mpt DECIMAL <mpt>
SQL DECLARE c1 CURSOR FOR -
SELECT Mktcode, Prdcode, Percode, Mktcode, Prdcode, -
Percode, Dollars FROM Sqldba.Data
...
SQL FETCH c1 LOOP INTO :APPEND market, :APPEND product, -
:APPEND time, :APPEND mpt, :DOLLARS.mpt
Example 10-141 Fetching Data into a Concat Dimension
Assume that a relational table has four columns of product data and that you decide to create a Product hierarchy with four levels in your analytic workspace to hold this data. The levels in the hierarchy (prod_id, prod_subcategory, prod_category, and products_all) map to columns in the products tables. The lowest level of the hierarchy is prod_id and the highest level is products_all. There is also a column with supplier information in the table.
To hold the data in the analytic workspace you define a dimension was defined for each level of the Product hierarchy, a concat dimension for the hierarchy itself, and a child-parent relation between the values in the hierarchy. You also define a dimension for the supplier data and a relation that holds the relationship between suppliers and products with the following definitions.
DEFINE aw_prod_id DIMENSION NUMBER (6)
DEFINE aw_prod_subcategory DIMENSION TEXT
DEFINE aw_prod_category DIMENSION TEXT
DEFINE aw_products_all DIMENSION TEXT
DEFINE aw_products DIMENSION CONCAT (aw_products_all -
aw_prod_category -
aw_prod_subcategory -
aw_prod_id)
DEFINE aw_products.parents RELATION aw_products <aw_products>
DEFINE aw_supplier_id DIMENSION NUMBER (6)
DEFINE aw_prod_id.aw_supplier_id RELATION aw_supplier_id <aw_prod_id>
Assume that you write a program named get_products_hier that consists of the following code.
' get_products_hier Program
ALLSTAT
" Fetch values into the products hierarchy
SQL DECLARE grabprods CURSOR FOR SELECT prod_total, -
prod_category, -
prod_subcategory, -
prod_id -
FROM sh.products
SQL OPEN grabprods
SQL IMPORT grabprods INTO :APPEND aw_products_all -
:APPEND aw_prod_category -
:APPEND aw_prod_subcategory -
:APPEND aw_prod_id
SQL CLOSE grabprods
SQL CLEANUP
" Update the analytic workspace and make the updates permanent
UPDATE
COMMIT
" Fetch values into supplier_id
SQL DECLARE grabsupid CURSOR FOR SELECT supplier_id -
FROM sh.products
SQL OPEN grabsupid
SQL IMPORT grabsupid INTO :APPEND aw_supplier_id
SQL CLOSE grabsupid
SQL CLEANUP
" Update the analytic workspace and make the updates permanent
UPDATE
COMMIT
" Populate self-relation for concat dimension
" and relation between aw_prod_id and aw_supplier_id
SQL DECLARE makerels CURSOR FOR SELECT prod_total, -
prod_category, -
prod_subcategory, -
prod_id, -
supplier_id -
FROM sh.products
SQL OPEN makerels
SQL FETCH makerels LOOP INTO :MATCH aw_products_all -
:MATCH aw_prod_category -
:MATCH aw_prod_subcategory -
:MATCH aw_prod_id -
:MATCH aw_supplier_id -
THEN aw_products.parents(aw_products aw_prod_id) -
= aw_products(aw_prod_subcategory aw_prod_subcategory) -
aw_products.parents(aw_products aw_prod_subcategory) -
= aw_products(aw_prod_category aw_prod_category) -
aw_products.parents(aw_products aw_prod_category) -
= aw_products(aw_products_all aw_products_all) -
aw_prod_id.aw_supplier_id = aw_supplier_id
SQL CLOSE makerels
SQL CLEANUP
" Update the analytic workspace and make the updates permanent
UPDATE
COMMIT
The get_products_hier program copies the data from the dimension tables into the base dimensions of the aw_products concat dimension using SQL FETCH commands with the APPEND keyword. As the base dimensions of aw_products are populated, Oracle OLAP automatically populates aw_products, itself. As the THEN clause of the SQL FETCH statement executes, Oracle OLAP fetches data into the child-parent self-relation for aw_products. This program also populates the aw_supplier_id dimension and its relation.
The SQL IMPORT command retrieves and processes data specified by an explicit SQL cursor. SQL IMPORT assigns the retrieved data to OLAP objects. You use the SQL IMPORT command in combination with other SQL commands to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects". SQL IMPORT is particularly effective in copying fact data from relational tables into analytic workspace variables.
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Note: You cannot transfer data with the following data types: LONG, BLOB, and BFILE. |
Syntax
SQL IMPORT cursor [:var-num-of-rows |num-of-rows[:var-num-of-processed-rows]]-
INTO :targets... [THEN action-statements...]
where:
targets is one or more of the following:
action-statements is one of the following:
Parameters
The name of a declared cursor.
The name of a variable that specifies the number of rows that you want SQL IMPORT to attempt to import.
A numeric constant that specifies the number of rows that you want SQL IMPORT to attempt to import.
When you include the MATCHSKIPERR keyword in the targets parameter, the name of a variable that specifies the actual number of rows that you want SQL IMPORT to import into analytic workspace objects.
Identifies the analytic workspace objects in which you want to store data that is retrieved from a relational table. This list of target analytic workspace objects must correspond in number and data type with the list of table columns specified in the select-statement argument of the SQL DECLARE CURSOR command that declared cursor. A target can be a variable, a qualified data reference, a relation, a dimension, or a composite.
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Important: The order in which you specify the analytic workspace objects affects dimension status. For each dimension value, Oracle OLAP temporarily limits the status of the dimension to the fetched value. Values are assigned to subsequent analytic workspace objects according to this temporary status. |
(Default) Oracle OLAP does not copy values from the corresponding relational table column into the target dimension or surrogate. It only uses the values to align data that is being fetched into dimensioned objects. When a value from the relational database does not match any value in the dimension, an error is signaled.
Oracle OLAP does not copy values from the corresponding relational table column into the target dimension or surrogate. It only uses the values to align data that is being fetched into dimensioned objects. When a value from the relational database does not match any value in the dimension, the value is ignored and processing continues without signaling an error.
The one-based logical position of the value.
Oracle OLAP performs dimension maintenance on the target dimension, adding new values from the corresponding relational table column to the dimension. It uses both old and new dimension values to align data being fetched into dimensioned objects. New values are added to the end of a dimension.
Oracle OLAP assigns the corresponding relational value to the specified surrogate.
The name of the analytic workspace dimension.
The name of an analytic workspace surrogate.
The name of the analytic valueset.
The name of the analytic workspace relation.
The name of a variable.
A QDR is a qualifier that limits one or more of the dimensions of a variable or a relation to a single value. Oracle OLAP evaluates QDRs in a SQL IMPORT statement, as follows:
When the QDR includes an expression, the expression is evaluated only once before the data is retrieved. In other words, the expression is, in essence, a constant.
When the QDR is specified as a relation name, the values of the QDR vary depending on the status of the dimensions of that relation.
Specifies any number of action-statements to be performed each time a row of data is imported and assigned to analytic workspace objects. Action statements may contain simple assignment statements, conditional assignment statements, and assignments across dimensions.
Action statements allow you to examine and manipulate the fetched data on a row-by-row basis. For example, you may want to specify temporary objects as analytic workspace objects and only update your permanent objects once you have performed certain actions on the row of fetched data. However, action statements do not have to reference the imported data. For example, one of your action statements might be an assignment statement that executes a user-defined function (that is, a program) that performs complex processing and then simply increments a counter.
A THEN clause can improve SQL loading performance by eliminating the need for postprocessing upon completion of a SQL IMPORT.
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Note: The syntax of an action statement w ithin SQL IMPORT is essentially the same as the syntax of an action statement within FILEREAD. Exceptions are in the syntax of an assignment statement and the use of the VALUE keyword. In SQL IMPORT action statements, assignments must be explicit; they must include a source, target, and equal sign. In FILEREAD action statements, assignments may be implicit and specify only the target. The VALUE keyword is supported in FILEREAD action statements, but not in SQL IMPORT action statements. When you have already specified action statements for use with FILEREAD, you can reuse the code with SQL IMPORT by simply adjusting the assignment statements and eliminating the VALUE keyword (if necessary). Most of the attributes listed in FILEREAD (except for the attributes that control dimension processing) are not meaningful for SQL loading and are ignored when executing within SQL IMPORT.For best performance, within a THEN clause reference only the data within the imported row. |
In your list of action statements, be sure to process dimensions before variables. Oracle OLAP processes each action statement from left to right for each row in the relational table. When an action statement performs dimension processing, the resulting status remains in effect for subsequent action statements. When you do not first specify action statements that limit a variable's dimensions, Oracle OLAP uses the first value in status to target a cell in the variable. Unless you specify an ACROSS phrase, Oracle OLAP assigns a single value from a row to a single cell in an Oracle OLAP variable. By default, Oracle OLAP does not loop over a variable's dimensions when assigning data to the variable.
An assignment statement (SET) that assigns a value that is the result of an expression to an Oracle OLAP object.
An IF...THEN...ELSE command that performs some action depending on whether a Boolean expression is TRUE or FALSE.
A SQL SELECT statement lets you perform some action based on the value of an expression. A SELECT statement has the following form.
SELECT evaluates the SELECT expression and then sequentially compares the result with the WHEN expressions. When the first match is found, the associated action occurs. When no match is found, the ELSE action (if specified) occurs.
An ACROSS statement causes the following action statement to execute once for every value in status of the ACROSS dimension. When you want the looping to apply to multiple action statements, enclose the action statements in angle brackets. An ACROSS statement has the following form.
ACROSS dimension [limit]:
action-statement
In an ACROSS statement, limit temporarily change the status of dimension, if it is not in a FOR loop over dimension. The new status is in effect only for the duration of the SQL FETCH statement. The format of limit is as follows.
[ADD|COMPLEMENT|KEEP|REMOVE|TO] limit-clause
To specify the temporary status, insert any of the LIMIT command keywords (the default is TO) along with an appropriate list of dimension values or related dimensions. You can use any valid limit clause (see the LIMIT command for further information). The following example limits month to the last six values, no matter what the current status of month is.
ACROSS month last 6: units
You can group several action statements by enclosing them in angle brackets. An action-statement-group has the following form.
<action-statement1 -
[action-statement2 . . .]>
A typical use for action statement groups is after an ACROSS statement. With the angle bracket syntax, you can cause multiple action statements to execute for every value in status of the ACROSS dimension.
Usage Notes
Effect of Order of SQL SELECT Targets on Dimension Status
For each dimension value, Oracle OLAP temporarily limits the status of the dimension to the fetched value. Values are assigned to subsequent analytic workspace objects according to this temporary status.
Working with Boolean Data Variables
You can use Boolean variables as input and target analytic workspace objects for OLAP SQL commands. In OLAP DML input expressions, Oracle OLAP treats Boolean values as INTEGER values with a value of 1 (TRUE) or 0 (FALSE).
As target analytic workspace objects, Boolean variables can receive values from any numeric (or bit) column in a relational table.
Importing Text Data into a DATE Variable
When importing text data into a DATE variable, the current setting of the DATEORDER option is used to interpret the value. For example, a text value of 12-08-96 could be interpreted as December 8, 1996, or August 12, 1996, depending on the setting of DATEORDER.
Examples
Example 10-142 Simple Import
The following program fragment shows the basic steps of declaring a cursor and importing the data. Values from the Prod_ID and Prod_Name columns of the Products relational table in the Sales -History (sh) database are fetched into the prod_id dimension and prod_label analytic workspace variable. The prod_label variable is dimensioned by prod_id.
SQL DECLARE productcur CURSOR FOR SELECT Prod_ID, Prod_Name FROM sh.Products SQL OPEN productdur SQL IMPORT productcur INTO :prod_id, :prod_label SQL CLOSE productcur SQL CLEANUP
The SQL OPEN command activates an explicitly-declared SQL cursor. When the cursor is opened, SQL examines any OLAP DML input expressions used in the definition of the specified cursor, determines the cursor's result set, and leaves the cursor in the open state for use by SQL FETCH or SQL IMPORT. The cursor is positioned before the first row of the result set.
You use the SQL OPEN command in combination with other SQL commands to copy data from relational tables into analytic workspace objects as outlined in "Copying Relational Data into Analytic Workspace Objects".
Syntax
SQL OPEN cursor
Parameters
The name of a cursor previously declared in the same program. You cannot use ampersand substitution.
Examples
Example 10-143 Opening a Cursor Using SQL OPEN
The following program fragment declares and opens a cursor named geolabels.
SQL DECLARE geolabels CURSOR FOR - SELECT Store_ID, Store_Name, City FROM Stores IF SQLCODE NE 0 THEN SIGNAL dclerror 'SQLERRM' SQL OPEN geolabels IF SQLCODE NE 0 THEN SIGNAL operror 'SQLERRM'
Within a program, the SQL PREPARE command precompiles a SQL statement for later execution, in the same program using SQL EXECUTE. Typically, you use SQL PREPARE in programs to optimize the processing of SQL statements that are executed repeatedly, particularly those involving OLAP DML input expressions, such as INSERT, UPDATE, and DELETE.
Syntax
SQL PREPARE statement-name FROM sql-statement [insert-options]
Parameters
A name that you assign to the executable code produced from sql-statement. You can redefine statement-name just by issuing another SQL PREPARE statement.
The SQL statement that you want to precompile for more efficient execution. It cannot contain ampersand substitution or variables that are undefined when the program is compiled.
The following options are optional when sql-statement is an INSERT statement:
DIRECT=YES|NO specifies if the insert is a direct-path INSERT. This option must be the first option specified right aver the values phrase of the INSERT statement.
Setting this option to YES specifies that the insert is a direct-path INSERT. Direct-path INSERT enhances performance during INSERT operations and is similar to the functionality of Oracle's direct-path loader utility, SQL*Loader.
The default value is NO which specifies a normal INSERT.
NOLOG=YES|NO specifies if logging occurs. Setting this option to YES specifies that the redo information is not recorded in the redo log files which makes load-time faster. The default value is NO which specifies logging mode.
PARTITION=(sub)partition-name specifies that only the segments related to the named partition or subpartition are locked. When you specify this option, another session can insert data to unrelated segments in the same table. When you do not specify this option (the default), other sessions cannot insert data into the same table.
Usage Notes
Using Direct-Path INSERT
When performing a direct-path INSERT, data is written directly into data files, bypassing the buffer cache, free space in the existing data is not reused, and the inserted data is appended after existing data in the table.
Restrictions When Using Direct-Path INSERT Direct-path INSERT is subject to several restrictions. When executing a direct-path INSERT using the OLAP DML, transactions in the session issuing the direct-path INSERT must be committed for the INSERT to execute successfully. (You can use the SQL or OLAP DML COMMIT to commit transactions.)
Additionally, the general restrictions that apply to using direct-path INSERT in SQL apply to preparing a direct-pathINSERT using OLAP DML PREPARE statements:
The target table cannot be index organized or clustered.
The target table cannot contain object type or LOB columns.
The target table cannot have any triggers or referential integrity constraints defined on it.
For more information on restrictions when using a direct-path INSERT, see the discussion of the INSERT statement in Oracle Database SQL Language Reference.
Data Type Conversions During Direct-Path Insertion Table 10-11, "Automatic Data Type Conversion During Direct-Path Insertion" shows the automatic data type conversion performed during direct-path insertion.
Table 10-11 Automatic Data Type Conversion During Direct-Path Insertion
| Oracle RDBMS | Oracle OLAP DML |
|---|---|
|
CHAR(n), VARCHAR(n) |
TEXT |
|
LONG |
TEXT with WIDE option |
|
CHAR(8), VARCHAR(8) |
ID |
|
DATE |
DATE |
|
NUMBER(x,x) |
DECIMAL (SHORTDECIMAL) |
|
INTEGER (or NUMBER(38) |
INTEGER (SHORTINTEGER) |
|
NUMBER(1) |
BOOLEAN |
Inserting OLAP Text Data into a Column with a DATE Data Type When inserting text data from Oracle OLAP into a column with a DATE data type, you must use the default date format of DD MMM YY. You can use slashes (/), hyphens (-), or spaces as separators. When the data is in a different format, you can use the Oracle TO_DATE function in a SQL INSERT statement.
Inserting Large Text Values into a CLOB or NCLOB Column To insert more than 2K bytes of text data from an analytic workspace into a CLOB or NCLOB column, use the WIDE keyword before the name of the OLAP DML input expression. When the data type of the OLAP DML input expression is TEXT, then the target data type is CLOB. When the data type of the input expression is NTEXT, then the target data type is NCLOB.
The following is the syntax of an OLAP DML input expression with the WIDE keyword. See Example 10-146, "Using the WIDE Keyword" for an example.
:WIDE input-expression
See Example 10-146, "Using the WIDE Keyword" for an example.
Note that the target table must conform to these guidelines:
Any number and combination of CLOB and NCLOB columns
No LONG columns
The RDBMS imposes some restrictions on large data types. Oracle OLAP does not signal an error when you violate these restrictions. However, you might get unexpected results. Refer to the Oracle Application Developer's Guide for restrictions on large data types.
Calculating the Number of Characters
You can calculate the number of characters that are sent to a database table from an Oracle OLAP variable by using the following formula.
NUMCHARS(variable) + 2 * (NUMLINES(variable) - 1)
This formula counts the extra carriage return and line feed characters that Oracle OLAP inserts between lines when passing the text to the database.
Examples
Example 10-144 Preparing a FOR Loop
To automatically add all the sales people from the salesperson dimension to the relational table, you could write a program and put the SQL INSERT statement in a FOR loop.
FOR salesperson SQL INSERT INTO Sales VALUES (:Salesperson, :Dollars) DIRECT=YES
When a statement includes OLAP DML input expressions and are executed repeatedly, such as in a FOR loop, you can make the statements more efficient by "preparing" the SQL statement first. The INSERT statement becomes part of a PREPARE statement.
SQL PREPARE s1 FROM INSERT INTO Sales VALUES -
(:Salesperson, :Dollars) DIRECT=YES
FOR Salesperson
DO
SQL EXECUTE s1
IF SQLCODE NE 0
THEN BREAK
DOEND
Example 10-145 Updating a Table
The next example shows a simple update of a table using data stored in an analytic workspace. The market dimension is limited to one value at a time in the FOR loop. The SQL phrase WHERE S.Market=:market specifies that the sales value in the row for that market is the value that is changed.
FOR market SQL UPDATE Mkt SET Sales=:Mkt.Sales WHERE S.Market=:market
Like the INSERT statement in the previous example, an UPDATE statement should be used in a PREPARE statement and executed in an ACROSS statement or FOR loop.
SQL PREPARE s2 FROM UPDATE mkt - SET Sales=:mkt.sales WHERE s.market=:market ACROSS market DO 'SQL EXECUTE s1'
Example 10-146 Using the WIDE Keyword
In both of the following statements, WIDE indicates that the target value is CLOB when var1 is TEXT, or NCLOB when var1 is NTEXT.
SQL INSERT INTO CLOB_TEST values (:dim1 :WIDE var1) SQL UPDATE CLOB_TEXT SET clob_col = :WIDE var1 WHERE key = 1
The SQL PROCEDURE command executes procedures stored in the RDBMS.
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Note: You can also create SQL stored procedures using the OLAP DML. See: |
Syntax
SQL PROCEDURE procedure-name (parameters)
where parameters is one or more of the following, separated by commas:
Parameters
The name of the SQL stored procedure.
The name of a variable in the RDBMS.
An OLAP DML expressions such as a OLAP DML variable. See "Using OLAP DML Expressions in OLAP DML SQL Statements" for more information on using OLAP DML expressions in OLAP DML SQL statements.
Usage Notes
Creating SQL Procedures using the OLAP DML
To create a stored procedure using the OLAP DML, issue an OLAP DML SQL statement with a SQL CREATE PROCEDURE statement as its argument. The syntax for coding CREATE PROCEDURE as an argument within an OLAP DML SQL statement is slightly different than the syntax for coding CREATE PROCEDURE in SQL proper. When coded as an arguments to an OLAP DML statements, use a tilde (~) instead of a semicolon as a terminator, and two colons instead of one in an assignment statement. See Example 10-147, "Creating a Stored Procedure".
Restrictions When Calling SQL Procedures using the OLAP DML
A stored procedure called using an OLAP DML SQL PROCEDURE statement cannot contain output variables or transactions.
Examples
Example 10-147 Creating a Stored Procedure
The following example shows the syntax for creating a procedure named new_products.
SQL CREATE OR REPLACE PROCEDURE new_products -
(id CHAR, name CHAR, cost NUMBER) AS -
price NUMBER~ -
BEGIN -
price ::= cost * 2.5~ -
INSERT INTO products -
VALUES(id, name, price)~ -
END~
Example 10-148 Executing a Stored Procedure
The following FOR loop executes a SQL stored procedure named new_products and inserts data stored in dimensions and variables into a relational table. In this example, prod is an Oracle OLAP dimension, and labels.p and cost.p are variables dimensioned by prod.
FOR prod
DO
SQL PROCEDURE new_products(:prod, :labels.p, :cost.p)
IF SQLCODE NE 0
THEN BREAK
DOEND
The SQL SELECT command uses an implicit cursor to copy data from relational tables into analytic workspace objects. You use the SQL SELECT command to copy data from relational tables into analytic workspace objects using an implicit cursor. You can also use copy the data using an explicit cursor using the OLAP DML commands outlined in "Copying Relational Data into Analytic Workspace Objects".
Syntax
SQL SELECT expressions FROM tables -
[WHERE predicates] [GROUP BY expressions] -
[ORDER BY expressions] [HAVING predicates] -
INTO :targets... [THEN action-statements...]
where targets is one or more of the following:
Parameters
A SQL SELECT statement that identifies the data you want to associate with the cursor. For the syntax of an SQL SELECT statement, refer to Oracle Database SQL Language Reference.
Identifies the analytic workspace objects in which you want to store data that is retrieved from a relational table. This list of target analytic workspace objects must correspond in number and data type with the list of table columns specified in the SELECT statement. A target can be a variable, a qualified data reference, a relation, a dimension, or a composite.
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Important: The order in which you specify the analytic workspace objects affects dimension status. For each dimension value, Oracle OLAP temporarily limits the status of the dimension to the fetched value. Values are assigned to subsequent analytic workspace objects according to this temporary status. See "Conjoints as Target Analytic Workspace Objects" and "Composites as Target Analytic Workspace Objects". |
A target must be preceded by a colon. When the target is a dimension, it can include the MATCH and APPEND keywords to specify dimension handling; in this case, the colon precedes the keywords.
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Tip: Since both OLAP DML syntax and SQL WHERE clauses allow you to use AND and OR, construct the targets clause clearly so that Oracle OLAP can identify the end of an OLAP DML input expression. |
(Default) Oracle OLAP does not perform dimension maintenance on the target dimension or surrogate. It uses the incoming values to align data that is being fetched into dimensioned objects. When a value from the relational database does not match any value in the dimension or surrogate, an error is signaled.
Oracle OLAP performs dimension maintenance on the target dimension, adding new values to the dimension. It uses both old and new dimension values to align data being fetched into dimensioned objects. By default, new values are added to the end of a dimension or surrogate. The position can also be used to control how dimension values are processed in action statements.
Assigns the values to the specified surrogate.
You may optionally include a THEN clause to specify any number of action-statements to be performed each time a row of data is fetched and assigned to analytic workspace objects. An action-statement can be one of the following:
Refer to the SQL IMPORT command for a complete description of the syntax of action-statement.
Usage Notes
General Restrictions that APPLY to SQL SELECT
An SQL SELECT statement cannot contain ampersand substitution.
Optimizing Copies
When copying values from relational tables into a multidimensional input variable, list the columns that correspond to the dimensions in an ORDER BY clause in the select-statement argument of the SQL SELECT statement, with the slowest-va3rying dimension first which optimizes performance.
Examples
Example 10-149 Simple select
For example, assume that there is a relational table named sales with the following description.
PROD_ID NOT NULL NUMBER(6) CUST_ID NOT NULL NUMBER TIME_ID NOT NULL DATE CHANNEL_ID NOT NULL CHAR(1) PROMO_ID NOT NULL NUMBER(6) QUANTITY_SOLD NOT NULL NUMBER(3) AMOUNT_SOLD NOT NULL NUMBER(10,2)
Assume also that your analytic workspace contains the following definitions for corresponding analytic workspace objects.
DEFINE aw_prod_id DIMENSION NUMBER (6)
DEFINE aw_cust_id DIMENSION NUMBER (6)
DEFINE aw_date DIMENSION TEXT
DEFINE aw_channel_id DIMENSION TEXT
DEFINE aw_promo_id DIMENSION NUMBER (6)
DEFINE aw_sales_dims COMPOSITE <aw_prod_id aw_cust_id -
aw_channel_id aw_promo_id>
DEFINE aw_sales_quantity_sold VARIABLE NUMBER (3) <aw_date aw_sales_dims -
<aw_prod_id aw_cust_id aw_date aw_channel_id aw_promo_id>>
DEFINE aw_sales_amount_sold VARIABLE NUMBER (10,2) <aw_date aw_sales_dims -
<aw_prod_id aw_cust_id aw_date aw_channel_id aw_promo_id>>
To copy the data for product 415 from the sales table into the analytic workspace objects, you execute the following statement in the OLAP worksheet.
SQL SELECT prod_id cust_id time_id channel_id promo_id quantity_sold -
amount_sold WHERE prod_id = 415 - INTO :aw_prod_id, :aw_cust_id, :aw_date, - :aw_channel_id, :aw_promo_id, :aw_sales_quantity_sold, :aw_sales_amount_sold
The ESCAPEBASE option specifies the type of escape that is produced by the INFILE keyword of the CONVERT function.
Syntax
ESCAPEBASE = 'escape-type'
Parameters
Specify 'd' for decimal escape, 'x' for hexadecimal escape.
The default escape type is decimal, which produces the INTEGER value for a character in the following form.
'\dnnn'
A hexadecimal escape is the INTEGER value for a character in the following form.
'\xnn'
Examples
For an example of using ESCAPEBASE with CONVERT to convert a text value to an escape sequence, see Example 7-50, "Converting Text Values to Escape Sequences".
The COS function calculates the cosine of an angle expression.
Return Value
NUMBER
The result returned by COS is a value with the same dimensions as the specified expression.
Syntax
COS(angle-expression)
Parameters
A numeric expression that contains an angle value, which is specified in radians.
Examples
The $COUNTVAR property specifies the same behavior as that specified by a COUNTVAR clause in an AGGREGATE command or an AGGREGATE function. By adding an $COUNTVAR property to a variable you can ensure this behavior when the variable is aggregated — even when it is aggregated by an AGGREGATE statement does not include the COUNTVAR clause.
The behavior specified by both the $COUNTVAR property and the COUNTVAR clause is that Oracle OLAP uses a variable that you have previously-defined (sometimes called a Countvar variable) to store the non-NA counts of the number of leaf nodes that contributed to aggregate values calculated for RELATION (for aggregation) statements that have an AVERAGE, HAVERAGE, HWAVERAGE, or WAVERAGE operator.
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Note: Typically, you do not use a user-defined Countvar variable to store the counts for average aggregations; instead, you use an Oracle OLAP-created Aggcount variable. You cannot use a Countvar variable when the aggregation specification includes a RELATION (for aggregation) statement with an average operator is for a compressed composite. See "Aggcount Variables" for more information. |
Syntax
You add or delete a $COUNTVAR property to the most recently defined or considered object (see DEFINE and CONSIDER commands) using a PROPERTY statement:
To add the property, issue the following statement.
PROPERTY '$COUNTVAR' countvar
To delete the property, issue the following statement.
PROPERTY DELETE '$COUNTVAR'
Parameters
A TEXT expression that specifies the name of a previously defined Countvar variable. The Countvar variable must be an INTEGER variable with the same dimensions in the same order as the dimensions as the variable on which you add the $COUNTVAR property.
Examples
Example 4-6 Using $COUNTVAR
For a variable named v1, the following statements cause Oracle OLAP to count the number of leaf nodes that contributed to an aggregate value that is the result of the execution of the myaggmap aggmap object by a AGGREGATE function.
CONSIDER v1 PROPERTY '$COUNTVAR' 'mycountvar'
The REPLLINES function replaces one or more lines in a multiline TEXT expression.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments. When all arguments are TEXT values, the return value is TEXT. When all arguments are NTEXT values, the return value is NTEXT. When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
REPLLINES(text-expression lines [start])
Parameters
A multiline text expression in which you want to replace one or more lines.
A text expression that contains one or more lines that replace the existing lines in text-expression.
An INTEGER that represents the line number at which to begin replacing. The position of the first line in text-expression is 1. When you omit this argument, REPLLINES starts with line 1. REPLLINES replaces as many lines of text-expression as are required for the specified new lines.
Examples
Example 8-81 Replacing a Text Line
This example shows how to replace the second line in a multiline TEXT value in a variable called mktglist. Assume first that the statement SHOW mktglist produces the following output.
Salespeople Products Services
By using REPLLINES, you can display a different value for "Products".
SHOW REPLLINES(mktglist, 'advertising', 2)
Salespeople Advertising Services
The AW_ATTACH procedure attaches an analytic workspace to your SQL session so that you can access its contents. The analytic workspace remains attached until you explicitly detach it, or you end your session.
AW_ATTACH can also be used to create an analytic workspace, but the AW_CREATE procedure is provided specifically for that purpose.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_ATTACH (
awname IN VARCHAR2,
forwrite IN BOOLEAN DEFAULT FALSE,
createaw IN BOOLEAN DEFAULT FALSE,
attargs IN VARCHAR2 DEFAULT NULL,
tablespace IN VARCHAR2 DEFAULT NULL);
AW_ATTACH (
schema IN VARCHAR2,
awname IN VARCHAR2,
forwrite IN BOOLEAN DEFAULT FALSE,
createaw IN BOOLEAN DEFAULT FALSE,
attargs IN VARCHAR2 DEFAULT NULL,
tablespace IN VARCHAR2 DEFAULT NULL);
Parameters
Table B-11 AW_ATTACH Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an existing analytic workspace, unless createaw is specified as |
|
|
|
|
|
|
|
|
Keywords for attaching an analytic workspace, such as |
Example
The following commands create an analytic workspace named GLOBAL_TRACKING and copies the contents of GLOBAL into it. The workspace is stored in a table named AW$GLOBAL_TRACKING, which has three partitions and is stored in the user's default tablespace.
EXECUTE dbms_aw.aw_attach('global');
EXECUTE dbms_aw.aw_copy('global', 'global_tracking', NULL, 3);
The ISSESSION function determines whether the current member of a specified dimension is a temporary member (that is, a member added when a MAINTAIN ADD SESSION statement executes).
Return value
BOOLEAN
YES when the member is a temporary member; NO when it is not.
Syntax
ISSESSION( [RECURSIVE]dimension)
Parameters
Specifies that for a dimension with base dimensions, that Oracle OLAP tests the values of the base dimensions when making its determination.
The name of the dimension whose current member value is to be tested by Oracle OLAP.
The NASKIP option controls whether NA values are considered as input to aggregation functions.
|
See also: $NATRIGGER property, NASKIP2 option which controls howNA values are treated with the + (plus) and - (minus) operators, and NASPELL option. |
Data Type
BOOLEAN
Syntax
NASKIP = NO|YES
Parameters
(Default) NA values are considered by aggregation functions. When any of the values being considered are NA, the function returns NA for that value.
NA values are ignored by aggregation functions. Only expressions with actual values are used in calculations.
Usage Notes
Statements Affected by NASKIP
The following OLAP DML statements are affected by NASKIP.
Other statements are not affected by the setting of NASKIP, they always ignore NA values.
Examples
Example 5-69 The Effect of NASKIP on the TOTAL Function
In the demo workspace, the 1997 values for sales are NA. The TOTAL function returns different results depending on the setting of NASKIP.
The statements
ALLSTAT NASKIP = YES SHOW TOTAL(sales)
produce the following result.
63,181,743.50
In contrast, the OLAP DML statements
NASKIP = NO SHOW TOTAL(sales)
produce the following result.
NA
Example 5-70 The Effect of NASKIP on the MOVINGMIN Function
This example aggregates values for three months: the current month and the two months before it. The first report of SALES shows the NA values for months in 1997. When NASKIP is YES, the MOVINGMIN function returns NA only for March 1997 because all the values considered for that month were NA. When NASKIP is NO, the third statement (REPORT DOWN month sales) shows NA values for January through March 1997, because at least one value considered by MOVINGMIN for those months was NA.
LIMIT district TO 'Seattle' LIMIT month TO 'Jul96' TO 'Mar97' REPORT DOWN month sales
The preceding statements produce the following report of SALES data.
DISTRICT: SEATTLE
------------------------SALES-------------------------
-----------------------PRODUCT------------------------
MONTH Tents Canoes Racquets Sportswear Footwear
----- ---------- ---------- ---------- ---------- ---------
Jul96 123,700.17 157,274.03 60,198.52 78,305.97 78,019.87
Aug96 120,650.72 128,660.89 45,046.71 66,853.26 83,347.55
Sep96 97,188.43 122,702.13 42,257.14 63,777.36 99,464.05
Oct96 91,578.77 79,925.93 39,729.25 55,021.85 83,537.58
Nov96 56,044.34 77,357.10 39,024.93 44,004.12 65,216.94
Dec96 41,576.26 67,609.36 36,156.10 40,575.34 62,113.72
Jan97 NA NA NA NA NA
Feb97 NA NA NA NA NA
Mar97 NA NA NA NA NA
The statements
NASKIP = YES REPORT DOWN month MOVINGMIN(sales -2, 0, 1, month)
produce the following report, which shows NA values for March 1997.
DISTRICT: SEATTLE
-----------MOVINGMIN(SALES -2, 0, 1, MONTH)-----------
---------------------PRODUCT--------------------------
MONTH Tents Canoes Racquets Sportswear Footwear
----- ---------- ---------- ---------- ---------- ---------
Jul96 108,663.59 125,823.37 57,666.37 57,713.27 73,085.88
Aug96 119,066.18 128,660.89 45,046.71 60,322.88 78,019.87
Sep96 97,188.43 122,702.13 42,257.14 63,777.36 78,019.87
Oct96 91,578.77 79,925.93 39,729.25 55,021.85 83,347.55
Nov96 56,044.34 77,357.10 39,024.93 44,004.12 65,216.94
Dec96 41,576.26 67,609.36 36,156.10 40,575.34 62,113.72
Jan97 41,576.26 67,609.36 36,156.10 40,575.34 62,113.72
Feb97 41,576.26 67,609.36 36,156.10 40,575.34 62,113.72
Mar97 NA NA NA NA NA
The statements
NASKIP = NO REPORT DOWN month MOVINGMIN(sales -2, 0, 1, month)
produce the following report, which shows NA values for January through March 1997.
DISTRICT: SEATTLE
----------MOVINGMIN(SALES -2, 0, 1, MONTH)-------------
------------------------PRODUCT------------------------
MONTH Tents Canoes Racquets Sportswear Footwear
----- ---------- ---------- ---------- ---------- ----------
Jul96 108,663.59 125,823.37 57,666.37 57,713.27 73,085.88
Aug96 119,066.18 128,660.89 45,046.71 60,322.88 78,019.87
Sep96 97,188.43 122,702.13 42,257.14 63,777.36 78,019.87
Oct96 91,578.77 79,925.93 39,729.25 55,021.85 83,347.55
Nov96 56,044.34 77,357.10 39,024.93 44,004.12 65,216.94
Dec96 41,576.26 67,609.36 36,156.10 40,575.34 62,113.72
Jan97 NA NA NA NA NA
Feb97 NA NA NA NA NA
Mar97 NA NA NA NA NA
The COMPILE command generates compiled code for a compilable object, such as a program, formula, model, or aggmap without running it and saves the compiled code in the analytic workspace. During compilation, COMPILE checks for format errors, so you can use COMPILE to help debug your code before running it. COMPILE records the errors in the current outfile.
However, you are not required to use the COMPILE command before running a compilable object. When you do not use COMPILE, Oracle OLAP automatically compiles a compilable object the first time you run it after entering or changing its contents. This automatic compilation is unnoticeable except for a slight delay while it is happening. Use the OBJ function with the ISCOMPILED keyword to obtain information about the compilation status of a compilable object.
Whether you compile an object explicitly with COMPILE or automatically through running it, the code executes faster whenever you subsequently run the object during the same session, because the code is already compiled. When you update and commit your analytic workspace, the compiled code is saved as part of your analytic workspace and can be used in later sessions. The code thus executes faster the first time it is run in each later session.
Using COMPILE to compile code without running a compilable object is especially useful when you are writing code that is part of a read-only analytic workspace (that is, a analytic workspace that people can use but not update).
Syntax
COMPILE object-name
Parameters
The name of a compilable object that you want to compile.
Usage Notes
Compilation Options
Several options effect compilation. These options are listed in "Compilation Options". By setting one or more of these options you can suppress error messages that appear at compilation time or replace occurrences of THIS_AW with a specified value.
Deleted Objects
When you delete or rename an object in your analytic workspace, Oracle OLAP automatically invalidates the compiled code for every statement in a program and every formula and model that depends on that object. When you try to execute code that refers to the deleted or renamed object, Oracle OLAP tries to compile the code again. Unless you have defined a new object with the same name, you receive an error message now.
When you run a program that contains invalidated code, it is compiled and executed one statement at a time. To save compiled code for the entire program, use the COMPILE command to explicitly compile it.
Multiple Errors in a Line
When a single statement has multiple errors, COMPILE finds only the first error. However, COMPILE continues checking for format errors in subsequent statements.
Declarative Errors
COMPILE handles declarative errors differently in programs and models:
When a program has a declarative error (for example, when a VARIABLE or ARG statement follows executable code), COMPILE signals a trappable error
When a model has a declarative model (for example, when a model statement has a DIMENSION statement following an assignment statement) COMPILE does not signal a trappable error. Instead, the model is not executable.
See the TRAP command for more information on trapping error.s
Advantages of Compiling
Explicit compilation using the COMPILE command offers several advantages over automatic compilation:
For any compilable object, COMPILE generates compiled code without executing the code in the object.
In a program or model, automatic compilation diagnoses an error only in the first statement that contains an error. It then displays the error message and halts the execution of a program or the analysis of a model. So each time a program or model is automatically compiled, only a single error message is displayed. In contrast, COMPILE checks every statement in a program or model for correct format, and generates multiple error messages, one for each statement that contains an error. (In programs, some types of statements cannot be compiled, so they are exceptions. See "Errors COMPILE Does Not Catch".) Since COMPILE shows you every statement that contains at least one error, this minimizes the number of times you must edit the code to correct all errors.
For a model, you may want to examine the results of the compilation or set options for handling simultaneous equations before you run the model.
Errors COMPILE Does Not Catch
Because the COMPILE command does not actually execute code, it can compile code that, for reasons unrelated to format errors, might not be successfully executed when the object were actually run. In a program, for example, you can compile the following statement, even though 'joplin' is not a district.
LIMIT district TO 'joplin'
Although the statement compiles successfully, you get an error message at run time.
Statements Not Compiled
In programs, certain statements cannot be compiled at all, and are therefore interpreted each time they are executed. These include statements that contain ampersand substitution, statements involving analytic workspace operations, and any statement that calls a program as a command. (Statements that call a program as a function or with the CALL command are compiled.)
PRGTRACE Option
You can use the PRGTRACE option to check which statements in a program have been compiled. When you set PRGTRACE to YES and run a program, each statement is recorded in the current outfile before it is executed. A compiled statement is identified with an equal sign.
(PRG= program-name) statement
An uncompiled statement is identified with a colon.
(PRG: program-name) statement
Multiple Analytic Workspaces
When you compile a compilable object that uses objects in another analytic workspace, the second analytic workspace must be attached to your current Oracle OLAP session. You can then run the compilable object with that analytic workspace or another analytic workspace with objects of the same name and type attached. Oracle OLAP checks that the objects have the same name, type (variable, dimension, and so on), data type (INTEGER, TEXT, and so on), and dimensions as the objects used to compile the compilable object.
When you have multiple active analytic workspaces, do not have objects of the same name in both analytic workspaces. For example, when you have an analytic workspace of programs and two analytic workspaces with data about the products Tea and Coffee, both product analytic workspaces can have a MONTH dimension and the programs can refer to MONTH. However, during your session, attach only one product analytic workspace at a time so that there is only one MONTH dimension.
Memory Use
In order for code to compile, all variables referenced in a program (except for variables in lines containing ampersand substitution) must be loaded into memory. Consequently, Oracle OLAP reads the definition of every variable you use and stores it in a portion of available memory that is dedicated for storing object definitions. When the compilation tries to bind a large variable, this may use a large amount of memory and create a large EXPTEMP file. When the compilation tries to bind a large number of large variables, it may fail and Oracle OLAP records an error message such as 'Insufficient Main Memory'. See the LOAD command for more information about loading an object's definition into memory.
Examples
Example 9-69 Compiling a Program
The following is an example of a COMPILE command that compiles the myprog program.
COMPILE myprog
Suppose you misspell the dimension month in a LIMIT command in the myprog program.
LIMIT motnh TO LAST 6
When the COMPILE command encounters this statement, it produces the following message.
ERROR: (MXMSERR00) Analytic workspace object MOTNH does not exist. In DEMO!MYPROG PROGRAM: limit month to last 6
You can edit the program to correct the error and then try to compile it again.
Example 9-70 Finding Program Errors
This example shows a program called salesrpt that contains two errors.
DEFINE salesrpt PROGRAM PROGRAM ROW WIDTH 80 CENTER Monthly Report BLANK 2 ROWW 'Total Sales' TOTAL(sales) END
You can compile the program with the following statement.
COMPILE salesrpt
Oracle OLAP identifies both errors and records the following messages.
ERROR: You provided extra input starting at 'REPORT'. In SALESRPT PROGRAM: ROW WIDTH 80 CENTER Monthly Report ERROR: ROWW is not a command. In SALESRPT PROGRAM: roww 'Total Sales' TOTAL(sales)
You can now edit the program to correct these errors, enclosing 'Monthly Report' in single quotes and correcting the spelling of ROWW. Then you can compile the program again, and save the compiled code as part of your analytic workspace.
The AW_CREATE procedure creates a new, empty analytic workspace and makes it the current workspace in your session.
The current workspace is first in the list of attached workspaces.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
AW_CREATE (
awname IN VARCHAR2 ,
tablespace IN VARCHAR2 DEFAULT NULL ,
partnum IN NUMBER DEFAULT 8 );
AW_CREATE (
schema IN VARCHAR2 ,
awname IN VARCHAR2 ,
tablespace IN VARCHAR2 DEFAULT NULL);
Parameters
Table B-13 AW_CREATE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of a new analytic workspace. The name must comply with the naming requirements for a table in Oracle Database. This procedure creates a table named AW$awname, in which the analytic workspace is stored. |
|
|
The tablespace in which the analytic workspace is created. If you omit this parameter, the analytic workspace is created in your default tablespace. |
|
|
The number of partitions that are created for the |
Example
The following command creates a new, empty analytic workspace named GLOBAL_FINANCE. The new analytic workspace is stored in a table named AW$GLOBAL_FINANCE with eight partitions in the user's default tablespace.
EXECUTE dbms_aw.aw_create('global_finance');
The next command creates an analytic workspace named DEMO in the GLOBAL schema. AW$DEMO has two partitions and is stored in the GLOBAL tablespace.
EXECUTE dbms_aw.aw_create('global.demo', 'global', 2);
The PERMITRESET command causes the values of permission conditions to be reevaluated. Permission conditions consist of one or more Boolean expressions that designate the criteria used by PERMIT commands associated with an object.
When permission conditions are dimensioned, they indicate which values of a dimensioned object PERMIT targets for permission. A single-cell permission condition can indicate any Boolean criterion, such as whether or not a particular user may access the object.
When you want to keep the existing PERMIT commands for an object, but you want the permission conditions associated with them to be recalculated, issue a PERMITRESET statement. The permission for that object is based on the new values of the permission conditions the next time you use the object in an OLAP DML statement.
Syntax
PERMITRESET [object_name] [READ|WRITE]
Parameters
Specifies the name of an object for which permission conditions should be reevaluated. When you do not specify an object name, the permission conditions for all objects are reevaluated.
Causes reevaluation of the permission conditions for PERMIT READ commands only, or for a PERMIT READ statement for the specified object.
Causes reevaluation of the permission conditions for PERMIT WRITE commands only, or for a PERMIT WRITE statement for the specified object.
Examples
Example 10-78 Resetting Permission
In the following example, the user-defined Boolean function usercheck checks the current value of the variable thisuser and returns YES only when it is greater than 100. Access to the variable uservar is only allowed when thisuser is greater than 100. However, when you change the value of thisuser to a value less than or equal to 100 without resetting the permission for uservar, access is still permitted.
The statement
DESCRIBE uservar
produces the following output.
DEFINE USERVAR VARIABLE INTEGER PERMIT READ WHEN usercheck(thisuser)
The statement
SHOW uservar
produces the following output.
5
The statement
DESCRIBE usercheck
produces the following output.
DEFINE USERCHECK PROGRAM BOOLEAN
PROGRAM
ARG thisuser INT
TRAP ON errorexit NOPRINT
IF thisuser GT 100
THEN RETURN YES
ELSE RETURN NO
errorexit:
RETURN NO
END
The statement
DESCRIBE thisuser
produces the following output.
DEFINE THISUSER VARIABLE INTEGER
The statement
SHOW thisuser
produces the following output.
101
The statements
thisuser = 100 SHOW uservar
produces the following output.
5
The statements
PERMITRESET luservar READ SHOW uservar
produce the following error.
ERROR: You do not have permission to read this value of USERVAR
The JOINLINES function joins the values of two or more expressions into a single multiline textual value. When multiline text values are joined, all the lines of the first expression appear first, followed by all the lines of the second expression, and so forth. Normally the arguments for JOINLINES are text values, but they can have other data types.
Return Value
TEXT or NTEXT
When all arguments are TEXT values, the return value is TEXT. When all arguments are NTEXT values, the return value is NTEXT. When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
JOINLINES(first-expression next-expression...)
Parameters
An expression to which JOINLINES adds next-expression. When the expression has a data type other than TEXT or NTEXT, JOINLINES converts it to TEXT. JOINLINES ignores any arguments that have a value of NA.
One or more expressions to join with first-expression. When an expression you want to concatenate has a data type other than TEXT, JOINLINES converts it to TEXT. JOINLINES ignores any arguments that have a value of NA.
Examples
Example 7-138 Joining the Lines of Two Text Expressions
This example shows how to make a new list by adding the value Regions to the end of a variable called mktglist.
mktglist has the following initial values.
Salespeople Products Services
The statement
newlist = JOINLINES(mktglist 'Regions')
assigns the following to newlist.
Salespeople Products Services Regions
The TO_NCHAR function converts a TEXT expression, date, or number to NTEXT in a specified format. This function is typically used to format output data.
Return Value
NTEXT
Syntax
TO_NCHAR(text-exp)
or
TO_NCHAR(datetime-exp, [datetime-fmt,] [option setting]
or
TO_NCHAR(num-exp, [num-fmt,] [nlsparams]
Parameters
A TEXT expression to be converted to NTEXT.
A DATETIME expression to be converted to NTEXT.
A text expression that identifies a datetime format template. This template specifies how the conversion from a DATETIME data type to NTEXT should be performed. For information about datetime format templates, see Table 9-4, "Datetime Format Elements". The default value of datetime-fmt is controlled by the NLS_DATE_FORMAT option.
An OLAP option (such as NLS_DATE_LANGUAGE) and its new setting, which temporarily overrides the setting currently in effect for the session. Typically, this option identifies the language that you want datetime-exp to be translated into. See Example 8-143, "Specifying the Default Language and a Date Format".
Do not specify an option that sets other options. For example, do not set NLS_LANGUAGE or NLS_TERRITORY; set NLS_DATE_LANGUAGE instead.While TO_NCHAR saves and restores the current setting of the specified option so that it has a new value only for the duration of the statement, TO_NCHAR cannot save and restore any side effects of changing that option. For example, NLS_TERRITORY controls the value of NLS_DATE_FORMATE, NLS_NUMERIC_CHARACTERS, NLS_CURRENCY, NLS_CALENDAR, and other options. When you change the value of NLS_TERRITORY in a call to TO_NCHAR, all of these options are reset to their territory-appropriate default values twice: once when NLS_TERRITORY is set to its new value for the duration of the TO_NCHAR statement, and again when the saved value of NLS_TERRITORY is restored.
A numeric expression to be converted to NTEXT.
A text expression that identifies a number format model. This model specifies how the conversion from a numeric data type (NUMBER, INTEGER, SHORTINTEGER, LONGINTEGER, DECIMAL, SHORTDECIMAL) to TEXT should be performed.
The default number format model uses the decimal and thousands group markers identified by NLS_NUMERIC_CHARACTERS option.
A text expression that specifies the thousands group marker, decimal marker, and currency symbols used in num-exp. This expression contains one or more of the following parameters, separated by commas:
NLS_CURRENCY symbol
NLS_ISO_CURRENCY territory
NLS_NUMERIC_CHARACTERS dg
A text expression that specifies the local currency symbol. It can be no more than 10 characters.
A text expression that identifies the territory whose ISO currency symbol is used.
A text expression composed of two different, single-byte characters for the decimal marker (d) and thousands group marker (g).
These parameters override the default values specified by the NLS_CURRENCY, NLS_ISO_CURRENCY, and NLS_NUMERIC_CHARACTERS options.
Examples
Example 8-141 Date Conversion
This statement converts today's date and specifies the format.
SHOW TO_NCHAR(SYSDATE, 'Month DD, YYYY HH24:MI:SS')
The specified date format allows the time to be displayed along with the date.
November 30, 2000 10:01:29
Example 8-142 Converting Numerical Data to NTEXT Data
This statement converts a number to NTEXT and specifies a space as the decimal marker and a period as the thousands group marker.
SHOW TO_NCHAR(1013.50, NA, NLS_NUMERIC_CHARACTERS ' .')
The value 1013.50 now appears like this:
1.013 50
Example 8-143 Specifying the Default Language and a Date Format
The following statements set the default language to Spanish and specify a new date format.
NLS_DATE_LANGUAGE = 'spanish' NLS_DATE_FORMAT = 'Day: Month dd, yyyy HH:MI:SS am'
The following statement:
SHOW TO_NCHAR(SYSDATE)
Displays the current date and time in Spanish:
Viernes : Diciembre 01, 2000 08:21:17 AM
The NLS_DATE_LANGUAGE option changes the language for the duration of the statement. The following statement
SHOW TO_NCHAR(SYSDATE, NA, NLS_DATE_LANGUAGE 'german')
displays the date and time in German:
Freitag : Dezember 01, 2000 08:26:00 AM
The MONITOR command records data on the performance cost of each line in a specified program. To get meaningful information from MONITOR, your session must be the only one running in Oracle OLAP. Furthermore, the accuracy of the results of MONITOR decreases as more processes are started on the host computer.
You first use a MONITOR statement to specify a program for monitoring; then you run the program and use MONITOR again to obtain the results. When the program executes a given line repeatedly, MONITOR records the cumulative cost of all the executions on the single line of its monitor list that is devoted to that program line.
A line of code is considered to have a high performance cost when it takes a long time to execute. Use a TRACKPRG statement to identify programs that have relatively high costs and then use MONITOR to identify the time-consuming lines within those programs. When you want, you can use both TRACKPRG and MONITOR simultaneously.
Syntax
MONITOR ON [programs] | OFF | INIT | FILE [[APPEND] file-name] | RESET
where programs is one of the following:
Parameters
Starts looking for the specified programs to be run so that Oracle OLAP can gather line-by-line timing data in a monitor list. (It continues the current monitoring process without interruption when monitoring is already on, or resumes with a gap when monitoring was off.)
When you do not specify a value for programs, the default is the program or programs specified in the last executed MONITOR ON statement. When there was no such statement in your current session, no data is collected and no error is produced.
Specifies that all of the programs in one or more analytic workspaces are monitored.
The name of one or more analytic workspaces (optionally separated by commas) whose programs you want monitored. When you omit this argument, Oracle OLAP monitors all of the programs in all of the attached analytic workspaces
The name of a specific program that you want monitored.
Stops monitoring programs and freezes any timing data currently in the monitor list which allows you send the list to the current outfile or to a text file either immediately, or later in your session.
(Useful only when monitoring is on.) Retains information about the programs that ares currently specified for monitoring and the Oracle OLAP memory that is allocated for the current monitor list, but discards any timing data currently in the list. In addition, RESET causes MONITOR to again begin waiting for you to run the same programs. When you do, MONITOR automatically gathers new timing data into a new monitor list for the same programs in the same memory allocation as before.
(Useful only when monitoring is on.) Initializes the monitoring environment. Initialization consists of discarding the program names and the timing data associated with the current monitor list, and releasing the Oracle OLAP memory previously used for that list so it can be used for other purposes or for collecting new data in a new monitor list.
Specifies that the timing data that is currently in the monitor list is sent to a file.
Specifies that the timing data is appended to an existing file. When you omit this argument, the new output replaces the current contents of the file.
A text expression that is the name of the file to receive the output. Unless the file is in the current directory, you must include the name of the directory object in the name of the file. When file-name is specified, the data is sent to the named text file. FILE has no effect on the monitor list, so you can send the same list repeatedly to different destinations. When file-name is omitted, Oracle OLAP sends the timing data that is currently in the monitor list to the current outfile.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Usage Notes
Monitor List
Each entry (that is, line) in the monitor list focuses on the execution of a single program line, regardless of how many times it is executed. Each entry is divided into the following four sections:
Cumulative total time of all executions in milliseconds rounded to the nearest 10 millisecond, in columns 1 through 11
Number of times executed, in columns 12 through 18
Line number, in columns 19 through 23
Text of the line, in column 24 and subsequent columns
Here is a sample of MONITOR output with column numbers included for reference.
12345678901234567890123456789012345678901234567890 60 1 1 push name 30 1 2 trap on GETOUT noprint 51 1 3 limit name to obj(type) eq 'DIMENSION' 0 1 4 for name 0 0 5 do 450 6 6 limit &name to ALL ifnone BYPASS 0 0 7 BYPASS: 0 0 8 doend 0 0 9 GETOUT: 0 1 10 pop name
The following is the full description of the program used for the preceding output. Note that in the output, the line with the LIMIT command is truncated because it is too long to fit.
DEFINE allstat PROGRAM LD Program to set the status of all dimensions in the analytic workspace to ALL PROGRAM PUSH NAME TRAP ON getout NOPRINT LIMIT NAME TO OBJ(TYPE) EQ 'Dimension' IFNONE getout FOR NAME DO LIMIT &NAME TO ALL IFNONE bypass bypass: DOEND getout: POP NAME END
Attaching, Detaching, and Reattaching Analytic Workspaces
When Oracle OLAP executes a program in an analytic workspace that has been attached, detached, a new block of data is collected.
Truncated Statement Lines
When a program line is too long, the MONITOR output truncates it. Continuation lines do not appear in the output.
Producing a Report
When you want to produce an Oracle OLAP report from the timing data in the MONITOR file, you can write a program that uses a FILEREAD statement to read the data into an Oracle OLAP variable, and then use Oracle OLAP reporting capabilities to produce a report. You can use the TRACKREPORT program as a model. However, keep in mind that the TRACKREPORT program was written to produce a report on TRACKPRG output, not MONITOR output.
Bracketing Lines
When you just want to time a particular line or group of lines in a program, you can insert MONITOR ON and MONITOR OFF statements in the program to bracket just the line or lines in which you are interested.
Using MONITOR for a Nested Programs
When you do not want to run a nested program by itself, you can specify its name in a MONITOR ON statement and then run the program that calls it. MONITOR gathers timing data only for the specified (nested) program. When the specified program is called more than once, for each program line, MONITOR accumulates the total seconds taken by all the times the line was run and provide the number of times it was run.
When you just want to time a particular execution of a nested program that is called more than once, you can insert MONITOR ON and MONITOR OFF statements in the calling program to bracket the single call in which you are interested.
Using MONITOR with Very Small Programs
You might not be able to reproduce the results exactly for very small programs. When the CPU interrupts processing to do other tasks, that time is a greater percentage of the total execution time.
Unit of Measure for MONITOR
The MONITOR and TRACKPRG commands use milliseconds as the unit for recording execution time. The execution time does not include time spent on I/O and time spent waiting for the next statement.
Examples
Example 10-66 Collecting Timing Data Using MONITOR
In this example, MONITOR is used to collect timing data on the execution of the individual lines of code in prog1 and then to send the data to a text file. The MONITOR ON statement is then used to discard the prog1 timing data and start collecting data on prog2. After the data for prog2 is sent to a second file, MONITOR INIT is used to discard the current monitor list and release the memory used for it.
MONITOR ON prog1 prog1 MONITOR FILE prog1.mon MONITOR ON prog2 prog2 MONITOR OFF MONITOR FILE prog2.mon MONITOR INIT
The MODERROR option determines the action that Oracle OLAP takes when a block of simultaneous equations in a model cannot be solved within a specified number of iterations.
|
See: "Model Options" for descriptions of all of the options that control the solution of simultaneous blocks |
Data Type
ID
Syntax
MODERROR = {'STOP'|'CONTINUE'}
Parameters
(Default) Oracle OLAP sends an error message to the current outfile and stops executing the model.
Oracle OLAP sends a warning message to the current outfile, stops executing the current block, and resumes execution at the next block in the model.
Usage Notes
Block-Solution Failure
When every equation in a simultaneous block passes a convergence test, the block is considered solved. When any equation diverges or fails to converge within a specified number of iterations, the solution of the block fails and an error occurs. MODERROR controls the action that Oracle OLAP takes when an error occurs.
Attaining Convergence for a Simultaneous Block in a Model
When an error occurs, you might be able to attain convergence for the block by changing the value of one or more options that control the solution of simultaneous blocks. For example, you can increase the number of iterations that is attempted or you can change the criteria used in testing for convergence and divergence.
Using 'STOP'
When MODERROR is set to STOP and execution of the model halts because of an error, you can run the MODEL.XEQRPT program to produce a report about the execution of the model. The report specifies the block where the solution failed and shows the values of the model options that were used in solving simultaneous blocks.
Using 'CONTINUE'
When MODERROR is set to CONTINUE and one block in the model is a simultaneous block that either diverges or fails to converge, Oracle OLAP executes any remaining blocks in the model.
Moreover, Oracle OLAP executes the model for the remaining values in the status of any additional dimensions of the solution variable that are not dimensions of the model. In this case, when you run the MODEL.XEQRPT program when Oracle OLAP finishes executing the model, you see a report on the solution for the final values of the additional dimensions.
When the simultaneous blocks in the model converged when the model was executed for the final values of the additional dimensions, then MODEL.XEQRPT reports that the blocks were solved, even though an earlier execution of the model for another dimension value might have failed. When you want to see the MODEL.XEQRPT for the dimension values where the failure occurred, you can set MODERROR to STOP and rerun the model.
Examples
Example 5-52 Debugging a Model
This example assumes that you are connected through OLAP Worksheet and enter the following statements in the Command Input window. The statements set MODERROR to DEBUG so that you can debug the myModel model (which contains a block of simultaneous equations) when the simultaneous block fails to converge.
MODERROR = 'DEBUG' myModel actual
When the simultaneous block fails to converge, you can type an Oracle OLAP or debugger command in the Command Input window in OLAP Worksheet. Since the solution variable, actual, is dimensioned by division, you might want to display the current value of division.
SHOW division Camping
Removes a MODEL (in an aggregation) statement for a specified model that is a sub-object of the cube dimension from the aggregation map of that cube dimension. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL REMOVE_CUBE_MODEL(logical_cube, logical_dim, model_name, is_static_model)
Parameters
Since REMOVE_CUBE_MODEL is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the name of the cube as defined in the Oracle data dictionary.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A text expression that is the name of the logical model that is associated with logical_dim.
A Boolean expression that specifies whether the MODEL statement to be removed is before or after the RELATION (for aggregation) statements in the aggmap for logical_cube.
The default value is TRUE which means that MODEL statement to be removed is before the RELATION statements (that is, model_name is a static model).
Specify FALSE if the MODEL statement you want to remove is after the RELATION statements (that is, model_name is a dynamic model).
The OBJ function returns information about an analytic workspace object.
Return Value
The return value depends on the value specified for choice. Also, when choice is applicable to only a specific type of object, and you specify a different type of object for object-name, then OBJ returns NA unless otherwise noted.
Syntax
OBJ(choice [object-name])
Parameters
A TEXT expression that is the name of the object that you want to retrieve information about.
A keyword or keyword phrase which indicates the type of information you want. See Table 8-2, "Keywords for the choice argument of the OBJ Function" for the syntax, data type of the returned value and description of valid keywords.
Table 8-2 Keywords for the choice argument of the OBJ Function
| Keyword for choice | Data Type | Description of Returned Value |
|---|---|---|
|
ACQUIRED |
BOOLEAN |
Whether the specified object has been acquired for modification in multiwriter mode. For a partitioned variable, returns YES only when all of the partitions of that variable have been acquire. |
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ACQUIREDPARTITIONS |
TEXT (multiline) |
The names of the partitions of the variable specified by object-name that are acquired for modification in multiwriter mode. |
|
AGGMAP |
TEXT (multiline) |
The specification of the specified aggmap. |
|
AGGMAPLIST |
TEXT (multiline) | |
|
ALIASLIST |
TEXT (multiline) |
The names of the alias dimensions for the specified dimension. |
|
ALIASOF |
TEXT |
The name of the base dimension for the specified alias dimension. |
|
AW |
TEXT |
The name of an attached workspace that contains the specified object. When the specified object is in only one attached workspace, AW returns the name of the workspace. When the specified object is in multiple attached workspaces, AW still returns only one workspace name. You must use the AWLIST keyword to get all the relevant workspace names. When the object is not in any attached workspace, AW returns |
|
AWLIST |
TEXT (multiline) |
The names of the attached workspaces that contain an object with the specified name. When you specify a qualified object name for the object, AWLIST returns only the relevant workspace name. When no workspace contains the specified object, AWLIST returns |
|
BTREE |
BOOLEAN |
Whether a BTREE index was defined for the specified conjoint dimension or composite. |
|
CACHEEMPTY |
BOOLEAN |
Whether a session cache has been emptied of data for the specified variable. A cache can be emptied by using a CLEAR statement with the CACHE keyword. When object-name is not a variable or when it has no session cache, then CACHEEMPTY returns |
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CACHECOUNT |
LONG INTEGER |
The number of non- |
|
CHANGED |
BOOLEAN |
Whether the specified variable, relation, dimension, or valueset has been modified since the last UPDATE. |
|
CLASS |
TEXT |
The storage class of the specified object. Possible return values are:
|
|
DATA |
TEXT |
The data type of the specified object.
|
|
DEFINE |
TEXT (multiline) |
The description of the specified object. The value is the same value that DESCRIBE would display for the object minus the words DEFINE and the name of the object. |
|
DFNCHANGED |
BOOLEAN |
Whether the definition of the specified object has changed since the last UPDATE. |
|
DFNDIMS |
TEXT (multiline) |
The names of the dimensions and composites in the dimension list that is used to define the specified object. Note that:
|
|
DIMMAX |
INTEGER |
The number of values in the specified dimension. For other object types, it returns Note: When you use the DIMMAX choice with a dimension that has a read permission that restricts access to the dimension values, the result returned depends on whether the dimension has previously been loaded. Permissions are evaluated when an object is loaded. Generally, the first time you refer to an object in your session, Oracle OLAP loads the object and evaluates its permissions. However, the OBJ function does not load objects, since it is just providing information about them. When you use DIMMAX with a dimension that has not yet been loaded, the result reflects the entire number of values in the dimension, regardless of whether the dimension has read permissions. When a dimension with permissions has been loaded, then the DIMMAX choice reflects the permitted size. To ensure that the DIMMAX choice returns the permitted size, you can execute a LOAD statement before using the OBJ function. |
|
DIMS |
TEXT (multiline) |
The names of the dimensions of the specified object. Specifically:
|
|
DIMTYPE |
TEXT |
The type of the specified dimension. Specifically:
|
|
DISKSIZE |
INTEGER |
The total number of pages used to store the specified object. Note: For a temporary object, OBJ(DISKSIZE) returns a value of 0 (zero), because the values of a temporary object are stored in temporary storage and not in the Database file. |
|
FORMULA |
TEXT | |
|
HASAGGCOUNT |
BOOLEAN |
Whether an Aggcount object is associated with the specified variable. (For more information on Aggcount variables, see "Aggcount Variables".) |
|
HASCACHE |
BOOLEAN |
Whether a session cache that is local to the session has been established to store data for the specified variable. (For more information on the session cache, see "What is an Oracle OLAP Session Cache?".) |
|
HASH |
BOOLEAN |
Whether a HASH index was defined for the specified conjoint dimension or composite. |
|
HASHSIZE |
INTEGER |
The number of pages allocated for the specified hashed dimension's TBLSPACE (that is, the page space containing the anchors for the hash table's K/V node lists). Note that this does not include the number of pages used for the actual Key/Value nodes, which are allocated from the RANSPACE's page space (KVPAGES). |
|
HASPROPERTY prop-name |
BOOLEAN |
Whether the property specified by prop-name exists for the specified object. (Abbreviated HASPRP) |
|
HIDDEN |
BOOLEAN |
Whether the text of the specified program or model has been hidden. (For more information on hiding programs and models, see the HIDE and UNHIDE commands.) |
|
INDEXSIZE |
INTEGER |
The total size of all inversions associated with the specified relation or conjoint dimension. |
|
INORDER |
BOOLEAN |
Whether the logical order of the values of the underlying dimensions of the specified object matches the physical order in the analytic workspace. INORDER returns |
|
ISBY [RECURSIVE] dimname |
BOOLEAN |
When you supply object-name, whether the specified object is dimensioned by, related to, or a surrogate for the specified dimension (dimname). When you supply only dimname, whether an object is dimensioned by the dimension you specify in dimname; or when the object is an aggmap, whether the specified dimension is a dimension of any relations or models in the aggmap.
Specify a value for object-name when the object is a dimension surrogate, variable, relation, or valueset name to learn if that object is dimensioned by or related to or a surrogate for the specified dimension. You can omit object-name when you are looping through the list of workspace objects to obtain information about multiple objects, or when you are using OBJ to limit the NAME dimension. |
|
ISCOMPILED |
BOOLEAN |
Whether the compilation status of the specified compilable object (such as a program, model, or formula). The value returned depends on the type of object and on whether a compilation error was found in that object. For example:
|
|
ISCOMPRESSED |
BOOLEAN |
Whether the specified object is a compressed composite. |
|
ISLATEST |
BOOLEAN |
Whether the specified object is the latest version of the object. This syntax is the equivalent of |
|
ISSOLVED |
BOOLEAN |
When the specified object is a variable which is dimensioned by a compressed composite, whether the variable has been aggregated. |
|
KVSIZE |
INTEGER |
The number of pages currently allocated to hash and BTREE indexes. |
|
LATESTVER |
INTEGER |
The current state of the specified object, referring to the most recently committed version of the object. The returned value is either equal to or greater than the value returned by |
|
LD |
TEXT (multiline) |
The LD (long description) of the specified object. |
|
MODEL |
TEXT (multiline) |
The specification of the specified model. |
|
NACACHECOUNT |
INTEGER |
The total number of |
|
NACACHEEMPTY |
BOOLEAN |
Whether the |
|
NAPAGES |
INTEGER |
The number of pages that contain only |
|
NOHASH |
BOOLEAN |
Whether the specified conjoint dimension uses the NOHASH index algorithm to load and access data. |
|
NUMCELLS |
INTEGER |
The total number of physical cells within the specified variable. Oracle OLAP determines this value by finding the Cartesian product of the |
|
NUMDELS |
DECIMAL |
The number of deleted cells for the specified dimensioned object. |
|
NUMDFNDIMS |
INTEGER |
The number of dimensions or composites in the dimension list used to define the specified object. For this count, each composite counts as one, and the dimensions within the dimension list of the composite are not counted. An object defined with a dimension list could be a variable, relation, formula, valueset, concat or conjoint dimension, dimension surrogate, or composite. When no dimension list was used when defining the object (as for single-cell variables, programs, and so on.), it returns |
|
NUMDIMS |
INTEGER |
The number of dimensions of the specified dimensioned object; or the number of base dimensions of the specified composite. When the specified object is a dimension is a dimension or dimension surrogate, it returns |
|
NUMSEGS |
INTEGER |
The number of analytic workspace segments associated with the specified object when that object has multiple dimensions. (Note that Oracle OLAP uses segments internally to keep track of the physical storage of the object's values. Too many segments may slow the ret rieval of information.) |
|
NUMVALS |
INTEGER |
The number of values or cells in the specified object. For a compressed composite or a variable dimensioned by a compressed composite, returns an |
|
OWNSPACE |
BOOLEAN |
When the specified object is a conjoint dimension or a composite defined with a BTREE index algorithm, whether the object is using private page space to store BTREE nodes. When the specified object is a variable-width text dimension, a relation, or a variable-width text variable, whether the data for the object is stored in one or more private page spaces that are associated with that object. |
|
PARTBY |
TEXT (multiline) |
The names of the partition dimensions of the specified partitioned variable or partition template object. The names are returned as a multiline text value (one line for each dimension). |
|
PARTDIMS partitions |
TEXT (multiline) |
The names of the dimensions of the partitions of the specified partition template or a partitioned variable. The value is returned as a multiline text value (one line for each dimension). partitions is a multiline text value (one line for each partition name) that specifies which partitions you're asking about. When you specify a partition name that is not a valid partition in partitions, an error occurs. |
|
PARTITION partitions |
TEXT (multiline) |
For a partitioned variable or a partition template object, a textual description of the partitions of the specified partition template or a partitioned variable. When called on a partition template, the returned description is similar to the DEFINE PARTITION TEMPLATE statement. When called on a partitioned variable, the returned description is similar to the DEFINE VARIABLE statement. partitions is a multiline text value (one line for each partition name) that specifies which partitions you're asking about.When you specify a partition name that is not a valid partition in partitions, an error occurs. |
|
PARTMETH |
TEXT |
The method ( |
|
PARTNAMES |
TEXT (multiline) |
A multiline Note: Not all of the partitions defined by a partition template necessarily exist in each partitioned variable. Calling |
|
PARTRANGE partitions |
TEXT (multiline) |
The values of the partitions is a multiline text value (one line for each partition name) that specifies which partitions you're asking about. When you specify a partition name that is not a valid partition in partitions, an error occurs. |
|
PERIOD |
TEXT |
When the specified object is a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the type of the dimension plus an indication of multiple periods or phasing, if any. |
|
PHYSMAX |
INTEGER |
The maximum physical value for positions within the specified dimension or composite. |
|
PMTMAINTAIN |
TEXT |
The permission condition for the maintain permission associated with the specified dimension. When there is no maintain permission for the dimension, it returns |
|
PMTPERMIT |
TEXT |
The permission condition for the permit permission associated with the specified object. When there is no permit permission for the object, it returns |
|
PMTREAD |
TEXT |
The permission condition for the read permission associated with the specified object. When there is no read permission for the object, it returns |
|
PMTWRITE |
TEXT |
The permission condition for the write permission associated with the specified object. When there is no write permission for the object, it returns |
|
PRECISION |
INTEGER |
The precision of the specified |
|
PROGRAM |
TEXT (multiline) |
The text of the specified program. |
|
PROPCHANGED |
BOOLEAN |
Whether the properties of the specified object have changed since the last UPDATE. |
|
PROPERTY prop-name |
WORKSHEET |
The value of the specified object's property as specified by prop-name which is a text expression that specifies the name of the property. The data type of the return value is determined at run time. When the named property does not exist, it returns |
|
PROPERTYLIST |
TEXT (multiline) |
The names of the properties associated with the specified object, one property on a line. The names are in uppercase letters and are stored in the collating sequence for ASCII characters. For objects without properties, it returns |
|
PROPERTYTYPE prop-name |
TEXT |
The data type of object's property as specified by prop-name which is a text expression that specifies the name of the property. The type is derived from the expression used in the PROPERTY statement that created the property. Possible return values are |
|
PUSHCOUNT |
INTEGER |
The number of times PUSH has executed for the specified executed (that is, the number of pushed values currently saved for the specified object). |
|
REFERS [RECURSIVE] text-expression |
TEXT (multiline) |
The words found in the specified compilable object (for example, a program) that match the ones you specify in text-expression. REFERS returns
Tip: The search is not case-sensitive; REFERS treats |
|
RELATION relation-query |
TEXT (multiline) |
The default relation (as specified the RELATION command) for the specified object. The values that are returned vary depending on what you specify for relation-query. The syntax for relation-query is: DEFINELIST | DIMLIST | ACTUAL rel-dimname | SPECIFIED rel-dimname where:
|
|
RSSIZE |
INTEGER |
The number of random subset pages used by main object. |
|
SCALE |
INTEGER |
The scale of a |
|
SEGWIDTH {dim-name|ALL} |
TEXT (multiline) |
The default or user-specified segment size of a variable that has multiple dimensions and that is associated with either a particular dimension or all dimensions. Each line begins with a segment-size (up to 11 digits) followed by the name of the associated dimension or composite. The dimension name is not included in the line when you specify a dimension and its dimensioned object. In that case only the segment value is returned. When the segment size is reported as zero, it means the default segment size is in effect, and therefore you may have to use CHGDFN to set an appropriate size for the variable's segments.
|
|
SESSION |
BOOLEAN |
Whether the specified object is a session object. |
|
SHAREMAP |
BOOLEAN |
When the specified object is dimensioned by a compound dimension, whether the compound dimension is shared with other objects. |
|
SPARSE |
TEXT (multiline) |
The composites used in the definition of the specified object. |
|
SURROGATELIST |
TEXT (multiline) |
The surrogates defined for the specified surrogate or dimension. |
|
TRIGGER [triggering-event} |
TEXT (multiline) |
TRIGGER without a triggering-event keyword returns all the triggering-event keywords and trigger programs names associated with the specified object; or Specify the triggering-event using one of the following keywords:
|
|
TYPE |
TEXT |
The object type of the specified object. |
|
UNIQUE |
BOOLEAN |
Whether the specified concat dimension is unique. Returns |
|
UPDATED |
BOOLEAN |
When the analytic workspace is attached in multiwriter mode, whether the specified object been updated. For other attachment modes, returns |
|
VALCOUNT |
INTEGER |
The number of logical uncompressed values in the specified compressed composite. For all other dimensions the result is identical to DIMMAX. |
|
VALSIZE |
INTEGER |
The number of pages used to store the specified object's values. For text dimensions and variables defined without the WIDTH keyword, OBJ(VALSIZE) counts only those pages that contain the four-byte pointers to the text, not the storage for the text itself. For a temporary variable, OBJ(VALSIZE) returns a value of 0 (zero) because the values of a temporary variable are stored in temporary storage and not in the analytic workspace. |
|
VERSION |
INTEGER |
The current state of the attached version of the specified object. (Note that changes that are updated and committed increase this number.) |
|
VNF |
TEXT |
When the specified object is a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR for which you have defined a VNF (value name format), the VNF of the dimension. For other types of objects, it returns |
|
WIDTH |
INTEGER |
The width, in bytes, of the storage area of each value of the specified object:
|
A text expression that contains the name of the object in which you are interested. The object can be in any attached workspace. When you specify object-name as a text literal, you must enclose it in single quotes. (Oracle OLAP automatically converts the name to uppercase.) When you specify the name of a program as the object-name and you omit the quotes, Oracle OLAP runs the program and uses its return value as the name of the object to be supplied as object-name.
You can omit object-name when you are using the OBJ function as part of a statement, such as the LIMIT command, that loops through the NAME dimension. In this case, the return value is dimensioned by the NAME dimension in the current workspace.
Examples
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See also: For examples of using the OBJ function to retrieve default relation information, see Example 10-95, "Specifying a Default Relation Using the Relation Command" |
Example 8-47 Listing Dimensions
Suppose you want a list of all the dimensions in an analytic workspace. First, use a LIMIT command and the OBJ function to limit the status of the NAME dimension. Then use a STATUS statement to produce a list of dimensions. Since the values returned by OBJ(TYPE) are always in uppercase, you must use 'DIMENSION' (not 'dimension') in the LIMIT statement to get a match. The statements
LIMIT NAME TO OBJ(TYPE) EQ 'DIMENSION' STATUS NAME
produce the following output.
The current status of NAME is: PRODUCT, DISTRICT, DIVISION, LINE, REGION, MARKETLEVEL, MARKET, MONTH, YEAR, QUARTER
Example 8-48 Listing Relations
Suppose you want to see the definitions of all the relations in an analytic workspace. Use the LIMIT command and the OBJ function to select these names. Then use DESCRIBE to produce a list of their definitions. The statements
LIMIT NAME TO OBJ(TYPE) EQ 'RELATION' DESCRIBE
produce the following output.
DEFINE REGION.DISTRICT RELATION REGION <DISTRICT> LD REGION for each DISTRICT DEFINE DIVISION.PRODUCT RELATION DIVISION <PRODUCT> LD DIVISION for each PRODUCT DEFINE MLV.MARKET RELATION MARKETLEVEL <MARKET> DEFINE MARKET.MARKET RELATION MARKET <MARKET> LD Self-relation for the Market Dimension
Example 8-49 OBJ With ISBY
For example, the following statement limits NAME to all the objects dimensioned by month.
LIMIT NAME TO OBJ(ISBY 'month')
You can use ISBY to find out if a dimension is a base dimension of a concat or conjoint dimension or a composite. For example, assume that you had a conjoint dimension named proddist whose base dimensions were product and district. In this case, the following statement returns YES.
SHOW OBJ(ISBY 'district' 'proddist')
You can use ISBY to find out if a dimension is a dimension of a relation or a model used in an aggmap. For example, assume that you had an aggmap called myaggmap and you wanted to find out if a dimension named mydimension was used in any relations or models within myaggmap. In this case, you could issue the following statement.
SHOW OBJ(ISBY 'mydimension' 'myaggmap')
To determine whether a specified dimension is a base dimension at any level, you must use ISBY with the RECURSIVE keyword. For example, assume that you had a conjoint dimension named proddist.mon whose base dimensions were proddist and month and a variable proddist.sales dimensioned by proddist. In this case, each of the following statements would return NO.
SHOW OBJ(ISBY 'district' 'proddist.mon') SHOW OBJ(ISBY 'district' 'proddist.sales')
However, when you use ISBY with the RECURSIVE keyword, each of the following statements would return YES.
SHOW OBJ(ISBY RECURSIVE 'district' 'proddist.mon') SHOW OBJ(ISBY RECURSIVE 'district' 'proddist.sales')
Example 8-50 Getting Information about a Variable
This example illustrates the use of several choices of the OBJ function to obtain information about the variable sales. The definition of sales is as follows.
DEFINE sales VARIABLE DECIMAL <month product district> LD Sales Revenue
The statement
SHOW OBJ(TYPE 'sales')
produces the following output.
VARIABLE
The statement
SHOW OBJ(DATA 'sales')
produces the following output.
DECIMAL
The statement
SHOW OBJ(DIMS 'sales')
produces the following output.
MONTH PRODUCT DISTRICT
The statement
SHOW OBJ(ISBY 'product' 'sales')
produces the following output.
YES
The statement
SHOW OBJ(LD 'sales')
produces the following output.
Sales Revenue
Example 8-51 Returning the Name of the Object or the Type of the Objecta
Suppose textvar is a variable whose value is geog, which is the name of a dimension. Whether you enclose the word textvar in quotation marks determines whether the following OBJ function calls return the word VARIABLE (the type of object textvar is) or DIMENSION (the type of object geog is).
SHOW OBJ(TYPE 'textvar') VARIABLE SHOW OBJ(TYPE textvar) DIMENSION
Example 8-52 Using OBJ to Select Objects
This example uses OBJ and DESCRIBE to look at the definitions of all the relations in an analytic workspace. The Oracle OLAP statements
LIMIT NAME TO OBJ(TYPE) EQ 'RELATION' DESCRIBE
produce the following output.
DEFINE REGION.DISTRICT RELATION REGION <DISTRICT> LD REGION for each DISTRICT DEFINE DIVISION.PRODUCT RELATION DIVISION <PRODUCT> LD DIVISION for each PRODUCT DEFINE MLV.MARKET RELATION MARKETLEVEL <MARKET> DEFINE MARKET.MARKET RELATION MARKET <MARKET> LD Self-relation for the Market Dimension
Example 8-53 Counting Compiled Objects
The following statements count how many compilable objects in your workspace are compiled and how many are not compiled. Each statement loops over the objects in the current workspace. The OBJ function returns YES for each object that is compiled, NO for each compilable object that is not compiled, and NA for objects that are not compilable. When NASKIP is YES (the default), the COUNT function in the first statement counts the number of YES values that are returned by OBJ, and in the second statement it counts the number of NO values that are returned.
SHOW COUNT(OBJ(ISCOMPILED)) SHOW COUNT(NOT OBJ(ISCOMPILED))
Example 8-54 OBJ with REFERS
The following statement searches the compilable objects in the current workspace for references to the objects in all the attached workspaces. The output lists the non-compilable objects in the current workspace too, but the return value for them is NA.
REPORT OBJ(REFERS OBJLIST(AW(LIST)))
In the following example, OBJ(REFERS) tells you whether var1, var2, or var3 appears in the myprog program. The return value of OBJ(REFERS) is a multiline text value that contains the references it finds. When only var1 and var3 appear in the program, then the return value contains those two names, each on a separate line. The statement
SHOW OBJ(REFERS 'var1\nvar2\nvar3' 'myprog')
produces the following output.
VAR1 VAR3
When you do not specify the name of a program or formula to be searched, OBJ(REFERS) returns a single-line or multiline text value for each object in the NAME dimension of the current workspace. For objects that are not programs or formulas, NA is returned. The statement
REPORT OBJ(REFERS 'var1\nvar2\nvar3')
produces the following output.
OBJ(REFERS
'var1
var2
NAME var3' )
-------------- ----------
PRODUCT NA
DISTRICT NA
DIVISION NA
LINE NA
QUARTER NA
REGION NA
YEAR NA
MONTH NA
...
MYPROG VAR1
VAR3
VAR1 NA
VAR2 NA
VAR3 NA
Example 8-55 OBJ with PROPERTY
In the following example, OBJ(PROPERTY) returns information about the decplace property of the actual variable. (See the PROPERTY command for more information.) The user created this property to store the number of decimal places and now wants to obtain that value to produce a report of the actual variable.
The statements
CONSIDER actual PROPERTY 'decplace' 4 LIMIT month TO FIRST 1 LIMIT division TO 'Camping' REPORT ACROSS month W 20 DECIMAL OBJ(PROPERTY 'decplace' - 'actual') actual
produce the following output.
DIVISION: CAMPING
-------ACTUAL-------
-------MONTH--------
LINE JAN 95
-------------- --------------------
Revenue 533,362.8800
Cogs 360,810.6600
Gross.Margin 172,552.2200
Marketing 37,369.5000
Selling 89,007.3800
R.D 24,307.5000
Opr.Income 21,867.8400
Taxes 15,970.3900
Net.Income 5,897.4500
Example 8-56 OBJ with SEGWIDTH
The following statements show how to change and display segment size values for all of a variable's dimensions.
CHGDFN sales SEGWIDTH 150 5000 50 SHOW OBJ(SEGWIDTH ALL 'sales')
These statements produce the following output.
150 MONTH 5000 PRODUCT 50 DISTRICT
The following statement shows how to obtain the segment size value for a specific dimension.
SHOW OBJ(SEGWIDTH 'product' 'sales')
This statement produces the following output.
5000
The following statement shows how to obtain a list of segment sizes for every multidimensional variable or relation associated with the dimension.
When object-name is not specified, you must use REPORT rather than SHOW to obtain a value for each object in the NAME dimension.
REPORT OBJ(SEGWIDTH 'product')
This statement produces the following output.
NAME OBJ(SEGWIDTH 'product') -------------- ----------------------- SALES 5000 SALES.FORECAST 5000 SALES.PLAN 5000 SHARE 5000 UNITS 5000 UNITS.M 0 ...
The following statement shows how to produce a list of segment sizes for all dimensions in the current workspace.
REPORT OBJ(SEGWIDTH ALL)
This statement produces the following output.
NAME OBJ(SEGWIDTH ALL)
-------------- -----------------
SALES 150 MONTH
5000 PRODUCT
50 DISTRICT
SALES.FORECAST 150 MONTH
5000 PRODUCT
50 DISTRICT
...
Within an OLAP DML program, the ARGFR function lets you reference the arguments that are passed to a program. The function returns a group of one or more arguments, beginning with the specified argument number, as a single text value. You can use ARGFR only within a program that is invoked as a command, not as a user-defined function or with a CALL statement.
|
Note: Typically, users use an ARGUMENT statement to define arguments in a program, thereby negating the need for using the ARGFR function to reference arguments passed to the program. For more information on how to use ARGUMENT to define arguments that are passed to a program, see "Declaring Arguments that Are Passed Into a Program" . |
Return Value
TEXT
Syntax
ARGFR(n)
Parameters
The number by position of the first argument in the group of arguments you want to reference. ARGFR(1) returns the first argument and all subsequent arguments, ARGFR(2) returns the second argument and all subsequent arguments, and so forth. When there are fewer than n arguments, ARGFR returns a null value. ARGFR also returns a null value when n is 0 (zero) or negative.
Examples
Example 7-22 Passing Arguments Using ARG and ARGFR
Suppose you have a program that produces a sales report. You want to be able to produce this report for any product and any period of months, so you do not want to limit the product and month dimensions to specific values in the program. Instead, you can use the LIMIT command using ARG for the product argument and an ARGFR function for the month argument. This way, these items can be specified when the program is run.
When ARGFR is included in the LIMIT command preceded by an ampersand (&), Oracle OLAP substitutes the values of &ARGFR before the command is executed and, consequently, treats the whole argument as a phrase of the LIMIT command. The salesrprt program has a LIMIT command that includes &ARGFR.
DEFINE salesrpt PROGRAM PROGRAM PUSH product month district TRAP ON cleanup LIMIT product TO UPCASE(ARG(1)) LIMIT month TO &ARGFR(2) LIMIT district TO ALL REPORT grandtotals DOWN district sales cleanup: POP product month district END
The command line for the salesrpt program must include two or more arguments. The first argument is the product for the report, and the second and subsequent arguments are the months. In the LIMIT month statement, the &ARGFR(2) function returns the months that were specified as arguments on the command line.
The following statement executes the salesrpt program, specifying Jan96, Feb96, Mar96, and Apr96 for the values of month.
salesrpt 'Canoes' 'Jan96' TO 'Apr96'
The statement produces the following output.
PRODUCT: CANOES
-------------------SALES------------------
-------------------MONTH------------------
DISTRICT Jan96 Feb96 Mar96 Apr96
------- ---------- ---------- ---------- ---------
Boston 70,489.44 82,237.68 97,622.28 134,265.60
Atlanta 56,271.40 61,828.33 77,217.62 109,253.38
Chicago 48,661.74 54,424.94 68,815.71 93,045.46
Dallas 35,244.72 40,218.43 46,810.68 64,031.28
Denver 44,456.41 50,623.19 57,013.01 78,038.13
Seattle 67,085.12 74,834.29 87,820.04 119,858.56
---------- ---------- ---------- ----------
322,208.83 364,166.86 435,299.34 598,492.41
========== ========== ========== ==========
The following statement specifies the first three months of 1996.
salesrpt 'Tents' quarter 'Q1.96'
The statement produces the following output.
PRODUCT: TENTS
-------------SALES-------------
-------------MONTH-------------
DISTRICT Jan96 Feb96 Mar96
-------------- ---------- ---------- ---------
Boston 50,808.96 34,641.59 45,742.21
Atlanta 46,174.92 50,553.52 58,787.82
Chicago 31,279.78 31,492.35 42,439.52
Dallas 50,974.46 53,702.75 71,998.57
Denver 35,582.82 32,984.10 44,421.14
Seattle 45,678.41 43,094.80 54,164.06
---------- ---------- ---------
260,499.35 246,469.11 317,553.32
========== ========== ==========
The EXTRACT function extracts and returns the value of a specified datetime value from a datetime or interval value expression. This function can be very useful for manipulating datetime values in very large variables.
Return Values
The value returned varies:
When extracting from a datetime with a time zone value, the function returns a value in UTC.
When you extract a TIMEZONE_REGION or TIMEZONE_ABBR (abbreviation), the function returns a a text string that is the appropriate time zone name or abbreviation.
When you extract any of the other values, the function returns a value in the Gregorian calendar.
When the values you specify results in an ambiguity, the function returns NA.
Syntax
EXTRACT(time |timezone_hour_or_nimute |timezone_regn_or_abbr FROM datetime_exp| interval_exp )
Parameters
One of the following keywords: YEAR, MONTH, DAY, HOUR, MINUTE, or SECOND which specify the portion of the time that you want the function to return.
One of the following keywords: TIMEZONE_HOUR or TIMEZONE_MINUTE which specify that you want the function to return either the hour or minute portion of a TIMESTAMP_TZ expression.
One of the following keywords: TIMEZONE_REGION or TIMEZONE_ABBR which specify that you want the function to return a string that is either the region name or its abbreviation.
A DATETIME, TIMESTAMP, TIMESTAMP_TZ, or TIMESTAMP_LTZ expression. See "Datetime Expressions" for information on how to specify these expressions.
A DSINTERVAL or YMINTERVAL expression. See "Interval Expressions" for information on how to specify these expressions.
Usage Notes
The value you are extracting must be a value of the appropriate datetime_exp or interval_exp. For example, you can extract only YEAR, MONTH, and DAY from a DATETIME value. Likewise, you can extract TIMEZONE_HOUR and TIMEZONE_MINUTE only from the TIMESTAMP_TZ data type.
Examples
The SHUTDOWN procedure terminates the current OLAP session.
By default, the SHUTDOWN procedure terminates the session only if there are no outstanding changes to any of the attached read/write workspaces. To terminate the session without updating the workspaces, specify the force parameter.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
SHUTDOWN (
force IN BOOLEAN DEFAULT NO);
Parameters
Table B-29 SHUTDOWN Procedure Parameters
| Parameter | Description |
|---|---|
|
|
When |
Example
The following commands save all changes to the GLOBAL analytic workspace and close the user's OLAP session.
EXECUTE dbms_aw.aw_update('global_finance');
COMMIT;
EXECUTE dbms_aw.shutdown();
The NEW_TIME function converts a date and time from one time zone to another.
Return Value
DATETIME
Syntax
NEW_TIME(datetime-exp this_zone new_zone)
Parameters
A text expression that indicates the time zone from which you want to convert datetime-exp. It must be a valid time zone, as listed in the following table.
A text expression that indicates the time zone into which you want to convert datetime-exp. It is the time zone of the return value. It must be a valid time zone, as listed in Table 8-1, "Time Zones".
| AST | Atlantic Standard Time |
|---|---|
|
ADT |
Atlantic Daylight Time |
|
BST |
Bering Standard Time |
|
BDT |
Bering Daylight Time |
|
CST |
Central Standard Time |
|
CDT |
Central Daylight Time |
|
EST |
Eastern Standard Time |
|
EDT |
Eastern Daylight Time |
|
GMT |
Greenwich Mean Time |
|
HST |
Alaska-Hawaii Standard Time |
|
HDT |
Alaska-Hawaii Daylight Time |
|
MST |
Mountain Standard Time |
|
MDT |
Mountain Daylight Time |
|
NST |
Newfoundland Standard Time |
|
PST |
Pacific Standard Time |
|
PDT |
Pacific Daylight Time |
|
YST |
Yukon Standard Time |
|
YDT |
Yukon Daylight Time |
Examples
Example 8-33 Using the Current Time of day
The SYSDATE function returns the current date and time to the NEW_TIME function.
SHOW new_time(SYSDATE 'EST' 'PST')
When the date and time in Eastern Standard Time are October 20, 2000, at 1:20 A.M., then the date in Pacific Standard Time, which is three hours earlier, is October 19, 2000. Because SYSDATE uses the format specified by NLS_DATE_FORMAT, which by default only shows the date, the time is not displayed.
19-OCT-00
Example 8-34 Specifying the Time of day
In the following example, the TO_DATE function converts a text string to a valid date and time. The TO_CHAR function includes a date format that temporarily overrides the date format specified by the NLS_DATE_FORMAT option.
SHOW TO_CHAR(NEW_TIME(TO_DATE('11-27-00 22:15:00', 'MM-DD-YY HH24:MI:SS'), -
'HST' 'PST') 'MM-DD-YY HH24:MI:SS')
This statement converts November 27 at 10:15 P.M. (22:15:00) Alaska-Hawaii Standard Time to November 28 at 12:15 A.M. (00:15:00) Pacific Standard Time. The date format specified in the TO_CHAR function allows the time to be displayed along with the date.
11-28-00 00:15:00
Alternatively, you can change the value of NLS_DATE_FORMAT.
NLS_DATE_FORMAT = 'MM-DD-YY HH24:MI:SS'
Then this statement produces the same result, without requiring the use of TO_CHAR.
SHOW NEW_TIME(TO_DATE('11-27-00 22:15:00', 'MM-DD-YY HH24:MI:SS'), -
'HST' 'PST')
The SUBSTR functions (SUBSTR, SUBSTRB, and SUBSTRC) return a portion of string, beginning at a specified position in the string. The functions vary in how they calculate the length of the substring to return.
SUBSTR calculates lengths using characters as defined by the input character set.
SUBSTRB calculates lengths using bytes.
SUBSTRC calculates lengths using Unicode complete characters.
Return Value
The return value is the same data type as string.
Syntax
{SUBSTR | SUBSTRB | SUBSTRC }(char, position [, substring_length ])
Parameters
A text expression that is the base string from which the substring is created.
The position at which the first character of the returned string begins.
When position is 0 (zero), then it is treated as 1.
When position is positive, then the function counts from the beginning of string to find the first character.
When position is negative, then the function counts backward from the end of string.
The length of the returned string. SUBSTR calculates lengths using characters as defined by the input character set. SUBSTRB uses bytes instead of characters. SUBSTRC uses Unicode complete characters.
When you do not specify a value for this argument, then the function returns all characters to the end of string. When you specify a value that is less than 1, the function returns NA.
Examples
The AGGMAPINFO function returns information about the specification of an aggmap object in your analytic workspace.
You can get information about an aggregation specification (that is, an aggmap object with a map type of AGGMAP) only after it has been compiled. You can compile an aggregation specification using a COMPILE statement or by including the FUNCDATA keyword when you execute the AGGREGATE command. When an aggregation specification has not been compiled before you use it with the AGGMAPINFO function, then it is compiled by AGGMAPINFO. You do not have to compile an aggmap for use with ALLOCATE.
Return Value
Varies depending on the type of information that is requested. See Table 7-1, "Keywords for the choice Parameter of the AGGMAPINFO function" for more information.
Syntax
AGGMAPINFO (name {choice | {choice-at-position rel-pos} })
Parameters
The name of the aggmap object.
Specifies the type of information returned. See Table 7-1, "Keywords for the choice Parameter of the AGGMAPINFO function", for details.
Table 7-1 Keywords for the choice Parameter of the AGGMAPINFO function
| Keyword | Data Type | Description |
|---|---|---|
|
ADDED_MODELS |
|
The models that are currently added to an aggmap using AGGMAP ADD or REMOVE model statements.The names of the models are returned as a multi-line text string. |
|
AGGINDEX |
|
Indicates the setting for the AGGINDEX statement in the aggmap. A |
|
CHILDREN member-name |
|
The dimension members used in the right-hand side of equations used to calculate temporary calculated members added using MAINTAIN ADD SESSION statements. The names of the members are returned as a multi-line text string. |
|
CUSTOMMEMBERS |
|
The members added using MAINTAIN ADD SESSION statements. The names of the members are returned as a multi-line text string. |
|
DIMENSION |
|
The names of the dimensions of the models or relations used by the aggmap. The names of the members are returned as a multi-line text string. |
|
FCACHE |
|
Indicates whether Oracle OLAP has a cache for the AGGREGATE function. (Applies to AGGMAP type aggmaps only.) |
|
MAPTYPE |
|
The type of the aggmap.
|
|
MODELS |
|
The models in the aggmap. The names of the models are returned as a multi-line text string. |
|
NUMRELS |
|
The total number of RELATION statements in an aggmap specification. |
|
RELATIONS |
|
The name of relation that is specified by a RELATION statement in the aggmap specification. Each statement is displayed on a separate line. |
|
STORE |
|
Indicates whether the CACHE statement in the aggmap is set to STORE. A |
|
VARIABLES |
|
The variables for which this aggmap object has been specified as the default aggmap using AGGMAP ADD or REMOVE model statements or the $AGGMAP property. The names of the variables are returned as a multi-line text string. |
Specifies the exactly which piece of information you want returned.
PRECOMPUTE returns the text of the limit clause that follows the PRECOMPUTE keyword in a RELATION statement. You must use the rel-pos argument to specify a single RELATION statement. Returns NA when the RELATION statement does not have a PRECOMPUTE keyword. (Applies to AGGMAP type aggmaps only.)
RELATION returns the name of the relation that follows the RELATION statement that you specify with the rel-pos argument.
STATUS returns the status list that results from the compilation of the PRECOMPUTE clause in the RELATION statement that you specify with the rel-pos argument. (Applies to AGGMAP type aggmaps only.)
An INTEGER that specifies a RELATION statement in the aggmap. The INTEGER indicates the position of the statement in the list of RELATION statements. You can use the rel-pos argument only with the RELATION, PRECOMPUTE, or STATUS keywords. For example, to get information about the first RELATION statement in an aggmap, use an INTEGER with a value of 1 as the rel-pos argument. To get information about the fourth RELATION statement in an aggmap, use the INTEGER 4, and so on. You may use any INTEGER between 1 and the total number of RELATION statements in an aggmap specification. You can use the NUMRELS keyword to obtain the total number of RELATION statements for an aggmap object.
Examples
Example 7-4 Retrieving Information About an Aggmap Object
Suppose an aggmap named sales.agg has been defined with the following statement.
DEFINE sales.agg AGGMAP <time, product, geography>
Suppose the following specification has been added to sales.agg with an AGGMAP statement.
AGGMAP RELATION time.r PRECOMPUTE (time ne 'Year98') RELATION product.r RELATION geography.r CACHE STORE END
Once a specification has been added to the aggmap, you can use AGGMAPINFO to get information about its specification.
To see the names of the hierarchies that are specified by the RELATION statements, use the following statement.
SHOW AGGMAPINFO(sales.agg RELATIONS)
The following results are displayed.
time.r product.r geography.r
The following statement and result tell you how many RELATION statements are in the aggmap object.
SHOW AGGMAPINFO(sales.agg NUMRELS) 3
The following statement and result verifies that data that is calculated on the fly is stored in the cache for the session. The result is YES because the aggmap contains a CACHE STORE statement.
show AGGMAPINFO(sales.agg STORE) YES
The following statement displays the relation name that is specified in the second RELATION statement in the aggmap.
SHOW AGGMAPINFO(sales.agg RELATION 2) product.r
The following statement displays the limit clause that follows the PRECOMPUTE keyword in the first RELATION statement in the aggmap.
SHOW AGGMAPINFO(sales.agg PRECOMPUTE 1) time NE 'YEAR98'
Suppose the time dimension values are Jan98 to Dec99, Year98, and Year99. The following statement displays the status list for the dimension in the first RELATION statement in the aggmap.
SHOW AGGMAPINFO(sales.agg STATUS 1) Jan98 TO Dec99, Year99
Because the limit clause in the RELATION statement specifies that the time dimension values should not equal Year98, all time dimension values other than Year98 are included in its status.
The following statement displays the aggmap type of sales.agg.
SHOW AGGMAPINFO(sales.agg MAPTYPE) AGGMAP
The FCQUERY function queries the results of a forecast created when the FCEXEC command executed.
You must use the FCQUERY function in combination with other OLAP DML statements as outlined in "Forecasting Programs".
Return Value
The return value depends on the option that you use as described in the tables for this entry.
Syntax
FCQUERY(HANDLELIST|handle-expression option -
[TRIAL trial-num] [CYCLE cycle-num])
Parameters
When you specify the HANDLELIST keyword, the FCQUERY function returns a multiline text expression that is a list of the handles to forecasting contexts that are currently open.
An INTEGER expression that is the handle to forecast context that you want to query and that was previously opened using the FCOPEN function.
The specific information to retrieve:
When you want information about the options specified for the entire forecast, do not use the TRIAL keyword. In this case, option can be any of the options that you can specify using the FCSET command and any of the options listed in Table 7-7, "Options That You Can Specify for the Entire Forecast".
Table 7-7 Options That You Can Specify for the Entire Forecast
| Keyword | Return type | Description |
|---|---|---|
|
HANDLEID |
TEXT |
The name of the forecasting context when a value was specified when the forecasting context was opened using the FCOPEN command; or |
|
TRIALSRUN |
INTEGER |
The number of trials for which data is available; or |
When you want information about a specific trial, use the TRIAL trial-num phrase. In this case, option can be any of the options listed in Table 7-8, "Options That You Can Specify for an Individual Trial".
Table 7-8 Options That You Can Specify for an Individual Trial
| Option | Return Value | Description |
|---|---|---|
|
ALLOCLAST |
BOOLEAN |
Indicates whether the risk of over-adjustment should be reduced by allocating, instead of forecasting, the last cycle. |
|
ALPHA |
DOUBLE |
The value of Alpha for this trial of the forecast. Alpha is the level or baseline parameter that is used for the Single Exponential Smoothing, Double Exponential Smoothing, and Holt-Winters forecasting methods. |
|
BETA |
DOUBLE |
The value of Beta for this trial of the forecast. Beta is the trend parameter that controls the estimate of the trend. Beta is used for the Double Exponential Smoothing and Holt-Winters forecasting methods. |
|
COMPSMOOTH |
BOOLEAN |
Indicates whether optimization should be done on the median smoothed data series. |
|
CYCDECAY |
DOUBLE |
The value of the cyclic decay parameter for this trial of the forecast. Cyclical decay pertains to how seriously Oracle OLAP considers deviations from baseline activity when it performs linear and nonlinear regressions. |
|
GAMMA |
DOUBLE |
The value of Gamma for this trial of the forecast. Gamma is the seasonal parameter that is used for the Holt-Winters forecasting method. |
|
HISTUSED |
INTEGER |
The number of historical periods actually used, after all leading |
|
MAD |
DOUBLE |
The mean absolute deviation (MAD) for this trial of the forecast. |
|
MAPE |
DOUBLE |
The mean average percent error (MAPE) for this trial of the forecast. |
|
MAXFCFACTOR |
DECIMAL |
The upper bound of the forecast data. |
|
METHOD |
TEXT |
The forecasting method that Oracle OLAP used for this trial of the forecast. See the METHOD option of the FCSET command for descriptions of the various methods. |
|
MINFCFACTOR |
DECIMAL |
The lower bound of the forecast data. |
|
MPTDECAY |
DOUBLE |
The value of the parameter that Oracle OLAP used when it adjusted the decay of estimates of base values that were used when it unraveled the predictions on the moving periodic total (MPT) series for this trial of the forecast. |
|
NCYCLES |
INTEGER |
The number of cycles specified using the PERIODICITY argument to FCSET. |
|
PERIODICITY |
INTEGER |
The length, in periods, of one or more cycles. The return value depends on the way you call the FCQUERY function: When you specify the CYCLE argument, PERIODICITY returns the number of periods in the specified cycle. When you do not specify the CYCLE argument and FCSET ALLOCLAST is When you do not specify the CYCLE argument and FCSET ALLOCLAST is |
|
RMSE |
DOUBLE |
The root mean squared error (RMSE) for this trial of the forecast. |
|
SMOOTHING |
BOOLEAN |
Indicates whether Oracle OLAP smoothed the data for this trial of the forecast. |
|
TRANSFORM |
TEXT |
The data filter that Oracle OLAP used for this trial of the forecast. See the TRANSFORM option of the FCSET command for descriptions of the various filters. |
|
TRENDHOLD |
DOUBLE |
The value of the trend hold parameter for this trial of the forecast. trend hold parameter that indicates trend reliability in Double Exponential Smoothing and Holt-Winters forecasting methods. |
An INTEGER expression that is the number of the trial for which you want to retrieve information.
An INTEGER expression that specifies a cycle for which you want information from the PERIODICITY option (see Table 7-8, "Options That You Can Specify for an Individual Trial"). When you specified a series of cycles using the PERIODICITY argument in the FCSET command, then the value of cycle-num indicates the position of the cycle of interest in the specified series. For example, assume that FCSET PERIODICITY <52,7> was specified. In this case, a cycle-num of 1 returns 52 and a cycle-num of 2 returns 7. When you did not specify a series of cycles using the PERIODICITY argument in the FCSET command, then it is unnecessary to specify this argument.
Usage Notes
Using Options
You can retrieve information about the options specified for the entire forecast or information about a specific trial.
When you want information about the options specified for the entire forecast, do not use the TRIAL keyword. In this case, option can be HANDLEID, TRIALSRUN, or any of the options that you can specify using the FCSET command.
When you want information about a specific trial, use the TRIAL trial-num phrase. In this case, option can be ALPHA, BETA, CYCDECAY, GAMMA, MAD, MAPE, METHOD, MPTDECAY, RMSE, SMOOTHING, TRANSFORM, or TRENDHOLD.
Accessing Dimensioned Data
When multiple time series are in status when the FCEXEC command executes, then the TRIALSRUN and the NTRIAL-dimensioned data are also be dimensioned by the extra dimensions of the time-series expression. Although Oracle OLAP treats the value returned by the FCQUERY function as a scalar expression, you can access its dimensioned data in any of the following ways:
In a FOR loop, FCQUERY returns data for the current values of the FOR dimensions
In a QUAL function, FCQUERY returns data for the specified values of the qualified dimensions.
In all other cases, FCQUERY returns data for the first value in status of each of its dimensions.
Examples
Example 7-87 Querying a Forecast
The autofcst program illustrated in Example 9-119, "A Forecasting Program" calls a program named queryall. The queryall program retrieves the characteristics of the trials of the forecast using the following code.
DEFINE queryall PROGRAM
PROGRAM
VARIABLE numtrials INTEGER
VARIABLE loopindx INTEGER
numtrials = FCQUERY(hndl trialsrun)
row numtrials 'TRIALS'
loopindx = 1
WHILE loopindx LE numtrials
DO
ROW loopindx 'METHOD' FCQUERY(hndl method trial loopindx)
ROW loopindx 'TRANSFORM' FCQUERY(hndl transform trial loopindx)
ROW loopindx 'SMOOTHING' FCQUERY(hndl smoothing trial loopindx)
ROW loopindx 'ALPHA' FCQUERY(hndl alpha trial loopindx)
ROW loopindx 'BETA' FCQUERY(hndl beta trial loopindx)
ROW loopindx 'GAMMA' FCQUERY(hndl gamma trial loopindx)
ROW loopindx 'TRENDHOLD' FCQUERY(hndl trendhold trial loopindx)
ROW loopindx 'CYCDECAY' FCQUERY(hndl cycdecay trial loopindx)
row loopindx 'MPTDECAY' FCQUERY(hndl mptdecay trial loopindx)
ROW loopindx 'MAD' FCQUERY(hndl mad trial loopindx)
ROW loopindx 'MAPE' FCQUERY(hndl mape trial loopindx)
ROW loopindx 'RMSE' FCQUERY(hndl rmse trial loopindx)
loopindx = loopindx + 1
DOEND
END
A sample report created from the output of the QUERYALL program follows.
3 TRIALS
1 METHOD HOLT/WINTERS
1 TRANSFORM TRNOSEA
1 SMOOTHING NO
1 ALPHA 0.2
1 BETA 0.3
1 GAMMA 0.3
1 TRENDHOLD 0.8
1 CYCDECAY -1
1 MPTDECAY -1
1 MAD 324.97047
1 MAPE 23.6192147
1 RMSE 389.40202
2 METHOD HOLT/WINTERS
2 TRANSFORM TRNOSEA
2 SMOOTHING NO
2 ALPHA 0.2
2 BETA 0.3
2 GAMMA 0.2
2 TRENDHOLD 0.8
2 CYCDECAY -1
2 MPTDECAY -1
2 MAD 324.97047
2 MAPE 23.6192147
2 RMSE 389.40202
3 METHOD HOLT/WINTERS
3 TRANSFORM TRNOSEA
3 SMOOTHING NO
3 ALPHA 0.2
3 BETA 0.3
3 GAMMA 0.1
3 TRENDHOLD 0.8
3 CYCDECAY -1
3 MPTDECAY -1
3 MAD 324.97047
3 MAPE 23.6192147
3 RMSE 389.40202
The LNNVL function provides a concise way to evaluate a condition when one or both operands of the condition may be null. LNNVL can be used anywhere a scalar expression can appear, even in contexts where the IS [NOT] NULL, AND, or OR conditions are not valid but would otherwise be required to account for potential nulls.
Return Values
TRUE if the condition is false or unknown and FALSE if the condition is true.
Syntax
LNNVL(condition)
Parameters
An expression constructed using any scalar values. Note that you cannot specify an expression that contains AND, OR, or BETWEEN.
Examples
The ORA_HASH function computes a hash value for a given expression. This function is useful for operations such as analyzing a subset of data and generating a random sample.
Return Value
NUMBER
Syntax
ORA_HASH (expr [, max_bucket [, seed_value ] ])
Parameters
The data for which you want the function to compute a hash value. There are no restrictions on the type or length of data represented by expr.
The maximum bucket value returned by the function. You can specify any value between 0 and 4294967295. The default is 4294967295.
A value between 0 and 4294967295. The default is 0. When you want to produce different has values for the same set of data, specify a value for this argument.
The ERRNAMES option controls whether the value of the ERRORTEXT option contains the name of the error (that is, the value of the ERRORNAME option) and the text of the error message.
Data Type
BOOLEAN
Syntax
ERRNAMES = {NO|YES}
Parameters
ERRORTEXT contains only the text of the error message.
(Default) ERRORTEXT contains the name and the text of the error message.
Examples
Example 5-33 ERRORTEXT Value Depending on ERRNAMES Setting
Suppose that you run the following program.
VARIABLE myint INTEGER myint = 35/0 SHOW ERRORTEXT
When the value of ERRNAMES is set to YES, the program returns the following value for ERRORTEXT.
ERROR: (MXXEQ01) A division by zero was attempted. (If you want NA to be returned as the result of a division by zero, set the DIVIDEBYZERO option to YES.)
When the value of ERRNAMES is set to NO, the program returns the following value for ERRORTEXT.
ERROR: A division by zero was attempted. (If you want NA to be returned as the result of a division by zero, set the DIVIDEBYZERO option to YES.)
The FILEMOVE command changes the name or location of a file that you specify. The new file name may be the same or different from the original name.
Syntax
FILEMOVE old-file-name new-file-name
Parameters
A text expression specifying the name of the file you want to move or rename. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use the CDA command to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
A text expression specifying the new name or location for the file. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
Examples
Moving a File
The following statement moves the file log.txt from your session's current directory object to file oldlog.txt in a directory object called backup.
FILECOPY 'log.txt' 'backup/oldlog.txt'
The INSTR functions (INSTR, INSTRB, and INSTRC) search a string for a substring using characters and return the position in the string that is the first character of a specified occurrence of the substring. The functions vary in how they determine the position of the substring to return.
INSTR calculates lengths using characters as defined by the input character set.
INSTRB calculates lengths using bytes.
INSTRC calculates lengths using Unicode complete characters.
Return Value
A nonzero INTEGER when the search is successful or 0 (zero) when it is not.
Syntax
{INSTR | INSTRB | INSTRC} (string , substring [, position [, occurrence]])
Parameters
The text expression to search.
The string to search for.
A nonzero INTEGER indicating where in string the function begins the search. INSTR calculates position using characters as defined by the input character set. INSTRB calculates position using bytes. INSTRC calculates position using Unicode complete characters.
When position is negative, then INSTR counts and searches backward from the end of string. The default value of position is 1, which means that the function begins searching at the beginning of string.
An INTEGER indicating which occurrence of string the function should search for. The value of occurrence must be positive. The default values of occurrence is 1, meaning the function searches for the first occurrence of substring.
Examples
Example 7-127 Using Character Position to Search Forward to Find the Position of a Substring
The following example searches the string "Corporate Floor", beginning with the third character, for the string "or". It returns the position in "Corporate Floor" at which the second occurrence of "or" begins.
SHOW INSTR('Corporate Floor','or', 3, 2)
14
Example 7-128 Using Character Position to Search Backward to Find the Position of a Substring
In this next example, the function counts backward from the last character to the third character from the end, which is the first "o" in "Floor". The function then searches backward for the second occurrence of "or", and finds that this second occurrence begins with the second character in the search string.
SHOW INSTR('Corporate Floor','or', -3, 2)
2
The REGEXP_SUBSTR function searches a string for a substring of a specified pattern and returns that substring.
Return Value
VARCHAR2 | CLOB
Syntax
REGEXP_SUBSTR(source_char, pattern[, position[, occurrence[, match_parameter ]]])
Parameters
The text expression for which the function searches.
The text expression for which the function searches. It is usually a text literal and can contain up to 512 bytes. The function interprets a period as a wildcard character that matches any character
A nonzero integer indicating the character of source_char where the function begins the search. When position is negative, then the function counts and searches backward from the end of string. The default value of position is 1, which means that the function begins searching at the first character of source_char.
An integer indicating which occurrence of pattern the function should search for. The value of occurrence must be positive. The default value of occurrence is 1, which means that the function searches for the first occurrence of pattern.
A text expression that lets you change the default matching behavior of the function. You can specify one or more of the values shown in the following table.
| Value | Specifies |
|---|---|
c | Case-sensitive matching. |
i | Case-insensitive matching. |
m | Treat the source string as multiple lines. The function interprets ^ (caret) and $ (dollar sign) as the start and end, respectively, of any line anywhere in the source string, rather than only at the start or end of the entire source string. By default, the function treats the source string as a single line. |
n | A newline character is among the characters matched by a period (the wildcard character). By default, it is not. |
x | Ignores whitespace characters. |
Examples
(Read-only) The NLS_LANG option specifies the current language, territory, and database character set, which are determined by session-wide globalization parameters.
Data Type
TEXT
Syntax
NLS_LANG
Parameters
See Oracle Database Globalization Support Guide for more information about NLS database parameters.
Examples
The STATLAST function returns the last value in the current status list of a dimension or a dimension surrogate, or in a valueset.
Return Value
The data type returned by STATLAST is either the data type of the dimension or dimension surrogate value or an INTEGER that indicates its position in the default status list of the dimension. See "Automatic Data Conversion of Returned Dimension Values".
Syntax
STATLAST(dimension)
Parameters
A text expression whose value is the name of a dimension, a dimension surrogate, or a valueset.
Usage Notes
Automatic Data Conversion of Returned Dimension Values
The dimension value returned by STATLAST is converted to a number or a text value, as appropriate to the context. Suppose, for example, that jun95 is the sixth month value but the last value in the current status list. The value of STATLAST(month) can be assigned either to a text variable or a numeric variable.
The following statements produce a text output value.
DEFINE textvar TEXT TEXTVAR = statlast(MONTH) SHOW textvar
Jun95
In contrast, these statements produce a numeric output value.
DEFINE intvar INTEGER INTVAR = STATLAST(month) SHOW INTVAR
6
Examples
Example 8-109 Setting Status with STATLAST
The following line from a program uses STATLAST to limit month to the values in the status, beginning with a month that has been stored previously in a variable called onemonth, and ending with the last value in the status.
LIMIT month KEEP onemonth TO STATLAST(month)
STATLAST is used here, rather than a particular month value, so that the limit can work on any status list.
The FPMTSCHED function calculates a payment schedule (principal plus interest) for paying off a series of fixed-rate installment loans over a specified number of time periods. For each time period, you specify the amount of the loans incurred during that time period and a single interest rate that applies to those loans over their lifetime.
FPMTSCHED calculates the payment for a given time period as the sum of the principal and interest due on each loan that is incurred or outstanding in that period.
Return Value
DECIMAL
The result returned by the FPMTSCHED function is dimensioned by the union of all the dimensions of loans and rates and the dimension used as the time-dimension argument.
Syntax
FPMTSCHED(loans, rates, n, [time-dimension] [STATUS])
Parameters
A numeric expression that contains the initial amounts of the loans. When loans does not have a time dimension, or when loans is dimensioned by multiple time dimensions, the time-dimension argument is required.
A numeric expression that contains the interest rates charged for loans. When rates is a dimensioned variable, it can be dimensioned by any dimension, including a different time dimension. When rates is dimensioned by a time dimension, you specify the interest rate in each time period that applies to the loans incurred in that period. The interest rate for the time period in which a loan is incurred applies throughout the lifetime of that loan. The rates are expressed as decimal values; for example, a 5 percent rate is expressed as.05.
A numeric expression that specifies the number of payments required to pay off the loans in the series. The n expression can be dimensioned, but it cannot be dimensioned by the time dimension argument. One payment is made in each time period of the time dimension by which loans is dimensioned or in each time period of the dimension specified in the time-dimension argument. For example, one payment each month is made when loans is dimensioned by month.
The name of the dimension along which the interest payments are calculated. When the time dimension for loans has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional, unless loans has multiple time dimensions.
Specifies that FPMTSCHED should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the payment schedule. By default FPMTSCHED uses the default status list.
Usage Notes
FPMTSCHED and NA Values
When loans has a value other than NA and the corresponding value of rates is NA, an error occurs.
FPMTSCHED is affected by the NASKIP option. When NASKIP is set to YES (the default), and a loan value is NA for the affected time period, the result returned by FPMTSCHED depends on whether the corresponding interest rate has a value of NA or a value other than NA. Table 7-11, "Effect of NASKIP When Loan or Rate Values are NA for a Time Period" illustrates how NASKIP affects the results when a loan or rate value is NA for a given time period.
As an example, suppose a loan expression and a corresponding interest expression both have NA values for 1997 but both have values other than NA for succeeding years. When the number of payments is 3, FPMTSCHED returns NA for 1997, 1998, and 1999. For 2000, FPMTSCHED returns the payment due for loans incurred in 1998, 1999, and 2000.
FPMTSCHED Ignores the Status of the Time Dimension
The FPMTSCHED calculation begins with the first time dimension value, regardless of how the status of that dimension may be limited. For example, suppose loans is dimensioned by year, and the values of year range from Yr95 to Yr99. The calculation always begins with Yr95, even when you limit the status of year so that it does not include Yr95.
However, when loans is not dimensioned by the time dimension, the FPMTSCHED calculation begins with the first value in the current status of the time dimension. For example, suppose loans is not dimensioned by year, but year is specified as time-dimension. When the status of year is limited to Yr97 to Yr99, the calculation begins with Yr97 instead of Yr95.
Examples
Example 7-100 Calculating a Payment Schedule
The following statements create two variables called loans and rates.
DEFINE loans DECIMAL <year> DEFINE rates DECIMAL <year>
Suppose you assign the following values to the variables loans and rates.
year loans rates -------------- ---------- ---------- Yr95 100.00 0.05 Yr96 200.00 0.06 Yr97 300.00 0.07 Yr98 0.00 0.00 Yr99 0.00 0.00
For each year, loans contains the initial value of the fixed-rate loan incurred during that year. For each year, the value of rates is the interest rate that is charged for any loans incurred in that year; for those loans, this same rate is charged each year until the loans are paid off.
The following statement specifies that each loan is to be paid off in three payments, calculates the schedule for paying off the principal and interest on the loans,
REPORT W 20 HEADING 'Payment' FPMTSCHED(loans, rates, 3, year)
and produces the following report.
YEAR Payment -------------- -------------------- Yr95 36.72 Yr96 111.54 Yr97 225.86 Yr98 189.14 Yr99 114.32
The payment for 1995 is the principal due on the loan of $100 incurred in 1995, plus interest on the loan at 5 percent. The payment due in 1996 is the sum of the second payment on the loan incurred in 1995 (principal plus 5 percent interest), plus the first payment on the loan of $200 incurred in 1996 (principal plus 6 percent interest). The 1997 payment is the sum of the third and final payment on the loan incurred in 1995, the second of the three payments on the 1996 loan, and the first payment on the loan of $300 incurred in 1997 (principal plus 7 percent interest). Since the 1995 loan is paid off in 1997, the payment for 1998 covers the principal and interest for the 1996 and 1997 loans. The payment for 1999 is the final payment of principal and interest for the 1997 loan.
The TRANSLATE function replaces all occurrences of each character of one string with the corresponding character in another string.
|
Note: TRANSLATE provides functionality related to that provided by the REPLCHARS function. REPLCHARS lets you substitute a single string for another single string and remove character strings. TRANSLATE lets you make several single-character, one-to-one substitutions in one operation. |
Return value
Text.
Syntax
TRANSLATE ( exp from_string to_string)
Parameters
A text expression in which you want to replace characters.
A text expression that is the characters you want to replace.
A text expression that is the characters to use for replacement in the order of from_string. When you include fewer characters in this argument than are in from_string, the function removes the extra characters in from_string from the return value. Note, however, that to remove all characters in from_string, you cannot specify an empty string for to_string as an empty string is interpreted as a null argument.
Examples
Example 8-151 Replacing several Characters Using TRANSLATE
The following statement translates a book title into a string that could be used (for example) as a filename. The from_string contains three characters: an asterisk, a space, asterisk, and apostrophe (with a backslash as the escape character). The to_string contains only two underscores which leaves the third character in the from_string without a corresponding replacement, so the return value does not contain any apostrophes.
SHOW TRANSLATE ('SQL*Plus User\'s Guide' '* \'' '__')
SQL_Plus_Users_Guide
The REGEXP_REPLACE function searches a string for a substring with a specified pattern and replaces that substring with another substring.
Return Value
VARCHAR2
Syntax
REGEXP_REPLACE(source_char, pattern[, replace_string[, position[, occurrence[, match_parameter ]]]])
Parameters
The text expression for which the function searches.
The text expression for which the function searches. It is usually a text literal and can contain up to 512 bytes. The function interprets a period as a wildcard character that matches any character.
The text that replaces pattern in source_char.
A nonzero integer indicating the character of source_char where the function begins the search. When position is negative, then the function counts and searches backward from the end of string. The default value of position is 1, which means that the function begins searching at the first character of source_char.
An integer indicating which occurrence of pattern the function should search for. The value of occurrence must be positive. The default values of occurrence is 1, meaning the function searches for the first occurrence of pattern.
A text expression that lets you change the default matching behavior of the function. You can specify one or more of the values shown in the following table.
| Value | Specifies |
|---|---|
c | Case-sensitive matching. |
i | Case-insensitive matching. |
m | Treat the source string as multiple lines. The function interprets ^ (caret) and $ (dollar sign) as the start and end, respectively, of any line anywhere in the source string, rather than only at the start or end of the entire source string. By default, the function treats the source string as a single line. |
n | A newline character is among the characters matched by a period (the wildcard character). By default, it is not. |
x | Ignores whitespace characters. |
Example
The following statement
REGEXP_REPLACE('500 Oracle Parkway, Redwood Shores, CA', '( ){2,}', ' ')
eliminates extra spaces and returns the following string
500 Oracle Parkway, Redwood Shores, CA
The BLANK command sends one or more blank lines to the current outfile. BLANK is typically used only in OLAP DML programs. For example, in a report program, BLANK is commonly used to insert blank lines that separate headings from data or that separate groups of data from one another.
Syntax
BLANK [n]
Parameters
An INTEGER expression with a value of 0 (zero) or higher, that specifies how many blank lines should be inserted. When you omit n, Oracle OLAP inserts one blank line. NA produces an error.
Examples
Example 9-57 Inserting Blank Lines
This example inserts two blank lines between the title of a report and the column headings. The following lines are from a report program.
LSIZE = 50 HEADING WIDTH LSIZE CENTER 'Quarterly Sales Report' BLANK 2 ROW WIDTH 20 'Unit Sales' ACROSS month - 'Jan96' TO 'Mar96': month
The program produces the following output.
Quarterly Sales Report
Unit Sales Jan96 Feb96 Mar96
The INSBYTES function inserts one or more bytes into a text expression.
When you are using a single-byte character set, you can use INSCHARS.
Return Value
TEXT
Syntax
INSBYTES(text-expression bytes [after])
Parameters
A TEXT expression into which the bytes are to be inserted. When text-expression is a multiline TEXT value, INSBYTES preserves the line breaks in the returned value.
One or more bytes that you insert into text-expression.
An INTEGER that represents the byte position after which the specified bytes are to be inserted. The position of the first byte in text-expression is 1. To insert bytes at the beginning of the text, specify 0 for after. When you omit this argument, INSBYTES inserts the bytes after the last byte in text-expression.
When you specify a value for after that is greater than the length of text-expression, INSBYTES adds blanks to the last line of text-expression. The number of inserted blanks is the difference between the value of after and the length of text-expression. For example, insbytes('abc' 'def' 4) inserts one blank space before adding def to abc, resulting in.
abc def
Examples
This appendix contains reference documentation for the following SQL functions that you can use to extract multidimensional data from an analytic workspace and present it in the two-dimensional format of a relational table:
OLAP_TABLE is a SQL function that returns a table of objects that can be joined to relational tables and views, and to other tables of objects populated by OLAP_TABLE. Within a SQL statement, you can specify an OLAP_TABLE function call wherever you would provide the name of a table or view
OLAP_TABLE uses a limit map to map dimensions and measures defined in an analytic workspace to columns in a logical table. The limit map combines with the WHERE clause of a SQL SELECT statement to generate a series of OLAP DML LIMIT commands that are executed in the analytic workspace.
OLAP_TABLE can use a limit map with a predefined logical table, or it can use the information in a limit map to dynamically generate a logical table at run time.
Several objects must be predefined within the analytic workspace to support the mapping of dimension hierarchies in the limit map:
a parent relation, which identifies the parent of each dimension member within a hierarchy. See "Parentrel Relation" for more information.
a hierarchy dimension, which lists the hierarchies of a dimension. See "Hierlist Dimension" for more information.
an inhierarchy variable or valueset, which specifies which dimension members belong to each level of a hierarchy. See "Inhier Valueset or Variable" for more information.
a grouping ID variable, which identifies the depth within a hierarchy of each dimension member. See "Gidrel Relation" for more information.
a family relation, which provides the full parentage of each dimension member in a hierarchy. See "Familyrel Relation" for more information.
a level dimension, which lists the levels of a dimension. See "Levellist Dimension" for more information.
The logical table populated by OLAP_TABLE is actually a table type whose rows are user-defined object types, also known as Abstract Data Types or ADTs.
A user-defined object type is composed of attributes, which are equivalent to the columns of a table. The basic syntax for defining a row is as follows.
CREATE TYPE object_name AS OBJECT ( attribute1 datatype, attribute2 datatype, attributen datatype);
A table type is a collection of object types; this collection is equivalent to the rows of a table. The basic syntax for creating a table type is as follows.
CREATE TYPE table_name AS TABLE OF object_name;
OLAP_TABLE can use a limit map with a predefined logical table, or it can use the information in a limit map to dynamically generate a logical table at run time.
|
See Also:
|
You can predefine the table of objects or generate it dynamically. When you create the table type in advance, it is available in the database for use by any invocation of OLAP_TABLE. Queries that use predefined objects typically perform better than queries that dynamically generate the objects.
Example A-1, "Template for Creating a View Using Predefined ADTs" shows how to create a view of an analytic workspace using predefined ADTs.
Example A-1 Template for Creating a View Using Predefined ADTs
SET ECHO ON SET SERVEROUT ON DROP TYPE table_obj; DROP TYPE row_obj; CREATE TYPE row_obj AS OBJECT ( column_first datatype, column_next datatype, column_n datatype); / CREATE TYPE table_obj AS TABLE OF row_obj; / CREATE OR REPLACE VIEW view_name AS SELECT column_first, column_next, column_n FROM TABLE(OLAP_TABLE( 'analytic_workspace', 'table_obj', 'olap_command', 'limit_map')); / COMMIT; / GRANT SELECT ON view_name TO PUBLIC;
Example A-2, "Sample View of the TIME Dimension Using Predefined ADTs" uses OLAP_TABLE with a predefined table type to create a relational view of the TIME dimension in an analytic workspace named MYAW in the MYAW_AW schema.
The first parameter in the OLAP_TABLE call is the name of the analytic workspace. The second is the name of the predefined table type. The fourth is the limit map that specifies how to map the workspace dimension to the columns of the predefined table type. The third parameter is not specified
Example A-2 Sample View of the TIME Dimension Using Predefined ADTs
CREATE TYPE time_cal_row AS OBJECT (
time_id varchar2(32),
cal_short_label varchar2(32),
cal_end_date date,
cal_timespan number(6));
CREATE TYPE time_cal_table AS TABLE OF time_cal_row;
CREATE OR REPLACE VIEW time_cal_view AS
SELECT time_id, cal_short_label, cal_end_date, cal_timespan
FROM TABLE(OLAP_TABLE(
'myaw_aw.myaw duration session',
'time_cal_table',
'',
'DIMENSION time_id from time with
HIERARCHY time_parentrel
INHIERARCHY time_inhier
ATTRIBUTE cal_short_label from time_short_description
ATTRIBUTE cal_end_date from time_end_date
ATTRIBUTE cal_timespan from time_time_span'));
If you do not supply the name of a table type as an argument, OLAP_TABLE uses information in the limit map to generate the logical table automatically. In this case, the table type is only available at run time within the context of the calling SQL SELECT statement.
Example A-3, "Template for Creating a View Using Automatic ADTs" shows how to create a view of an analytic workspace using automatic ADTs.
Example A-3 Template for Creating a View Using Automatic ADTs
SET ECHO ON SET SERVEROUT ON CREATE OR REPLACE VIEW view_name AS SELECT column_first, column_next, column_n FROM TABLE(OLAP_TABLE( 'analytic_workspace', '', 'olap_command', 'limit_map')); / COMMIT; / GRANT SELECT ON view_name TO PUBLIC;
Example A-4, "View of the TIME Dimension Using Automatic ADTs" creates the same view produced by Example A-2, "Sample View of the TIME Dimension Using Predefined ADTs", but it automatically generates the ADTs instead of using a predefined table type. It uses AS clauses in the limit map to specify the data types of the target columns.
Example A-4 View of the TIME Dimension Using Automatic ADTs
CREATE OR REPLACE VIEW time_cal_view AS
SELECT time_id, cal_short_label, cal_end_date, cal_timespan
FROM TABLE(OLAP_TABLE(
'myaw_aw.myaw duration session',
null,
null,
'DIMENSION time_id AS varchar2(32) FROM time WITH
HIERARCHY time_parentrel
INHIERARCHY time_inhier
ATTRIBUTE cal_short_label AS VARCHAR2(32) from time_short_description
ATTRIBUTE cal_end_date AS DATE from time_end_date
ATTRIBUTE cal_timespan AS NUMBER(6) from time_time_span'));
When automatically generating ADTs, OLAP_TABLE uses default relational data types for the target columns unless you override them with AS clauses in the limit map. The default data type conversions used by OLAP_TABLE are described in Table A-1, "Default Data Type Conversions".
OLAP_TABLE uses a limit map to present the multidimensional data from an analytic workspace in tabular form. The limit map specifies the columns of the logical table. You can add a calculated column to your relational view by specifying the OLAP_EXPRESSION function or a related Boolean, text, or date function in the select list of the query. When you specify one of these functions in the select list, OLAP_TABLE generates additional columns for the results of the function.
Before you use one of these expressions, you must specify a ROW2CELL clause in the limit map used by OLAP_TABLE to identifies the RAW column that OLAP_TABLE populates with information used by the OLAP single-row functions.
You can use OLAP DML commands within your SELECT FROM OLAP_TABLE statements as described in:
SQL functions are typically single-row functions return a single result row for every row of a queried table or view. Oracle supports several predefined SQL single-row functions, for example COS, LOG, and ROUND which return numeric data, and UPPER and LOWER which return character data.
Within the context of a SELECT FROM OLAP_TABLE statement, there are four SQL functions that you can use to wrap OLAP DML functions in such a way that the OLAP DML function acts as a single-row function. There are four functions that the results of expressions of different OLAP DML data types: OLAP_EXPRESSION for Oracle OLAP numeric expressions, OLAP_EXPRESSION_BOOL for Oracle OLAP Boolean expressions, OLAP_EXPRESSION_DATE for Oracle OLAP datetime expressions, and OLAP_EXPRESSION_TEXT for Oracle OLAP text expressions. One argument of each of these SQL functions is an OLAP DML function.
You can specify the OLAP_EXPRESSION function and its variants in the same way you specify other Oracle single-row functions, notably in the select list, WHERE, and ORDER BY clauses.
There are several mechanisms for modifying an analytic workspace on the fly during the execution of OLAP_TABLE.
You can use the OLAP_CONDITION SQL function modifies an analytic workspace within the context of a SELECT FROM OLAP_TABLE statement. You can specify OLAP_CONDITION like other Oracle functions, typically in the WHERE clause. Using the OLAP_CONDITION, you can set an option, execute a LIMIT command, execute an OLAP model or forecast, or run a program. The changes made to the workspace can be transitory or they can persist in your session upon completion of the query.
In addition to OLAP_CONDITION, you can use syntax supported by the OLAP_TABLE function itself: The PREDMLCMD and POSTDMLCMD clauses in the limit map, and the olap_command parameter. OLAP_CONDITION has the advantage of portability, since it is not embedded within OLAP_TABLE, and versatility, since it can be applied at different entry points.
OLAP_TABLE saves the status of dimensions in the limit map before executing the LIMIT commands that generate the result set for the query. After the data is fetched, OLAP_TABLE restores the status of the dimensions. You can specify a PREDMLCMD clause in the limit map to cause an OLAP DML command to execute before the dimension status is saved. Modifications resulting from the PREDMLCMD clause remain in the workspace after execution of OLAP_TABLE, unless reversed with a POSTDMLCMD clause. For more information, see limit_map.
The olap_command parameter of OLAP_TABLE specifies an OLAP DML command that executes immediately before the result set is fetched. In some circumstances, the olap_command parameter may contain an OLAP DML FETCH command, which itself manages the fetch. Limits set by the olap_command parameter are only in effect during the execution of OLAP_TABLE. For more information, see olap_command.
The NLS_DUAL_CURRENCY option specifies a second currency symbol that takes the place of the letter U in a number format mode and is used primarily to identify the Euro symbol. (Note that when you want to identify the Euro symbol as the value of NLS_DUAL_CURRENCY, the instance character set must support that symbol.)
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_DUAL_CURRENCY= option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
The LOWCASE function converts all alphabetic characters in a text expression into lowercase.
Return Value
TEXT or NTEXT
When the expression is TEXT, the return value is TEXT. When the expression is NTEXT, the return value is NTEXT
Syntax
LOWCASE(text-expression)
Parameters
The text expression whose characters are to be converted.
Examples
Example 8-16 Converting Part of an Expression to Lowercase
Suppose you get some new data to add to a mailing list. In the existing mailing list, people's names have only the first letter capitalized. In the new data, however, the whole name is capitalized. You can use LOWCASE to make the new data correspond to the current data with a statement similar to the following.
lastname = JOINCHARS(EXTCHARS(lastname, 1, 1), -
LOWCASE(EXTCHARS(lastname, 2, NUMCHARS(lastname))))
The REGEXP_INSTR function searches a string for a substring with a specified pattern and returns the position of that substring.
The function evaluates strings using characters as defined by the input character set.
Return Value
When the pattern is found a NUMBER; otherwise 0.
Syntax
REGEXP_INSTR (source_char, pattern[, position[, occurrence[, return_option[, match_parameter ]]]])
Parameters
The text expression for which the function searches.
The text expression for which the function searches. It is usually a text literal and can contain up to 512 bytes. The function interprets a period as a wildcard character that matches any character.
A nonzero integer indicating the character of source_char where the function begins the search. When position is negative, then the function counts and searches backward from the end of string. The default value of position is 1, which means that the function begins searching at the first character of source_char.
An integer indicating which occurrence of pattern the function should search for. The value of occurrence must be positive. The default values of occurrence is 1, meaning the function searches for the first occurrence of pattern.
Specify 0 (zero) when you want the function to return the position of the first matched character (default), or 1 when you want the function to return the position of the character following the match.
A text expression that lets you change the default matching behavior of the function. You can specify one or more of the values shown in the following table.
| Value | Specifies |
|---|---|
c | Case-sensitive matching. |
i | Case-insensitive matching. |
m | Treat the source string as multiple lines. The function interprets ^ (caret) and $ (dollar sign) as the start and end, respectively, of any line anywhere in the source string, rather than only at the start or end of the entire source string. By default, the function treats the source string as a single line. |
n | A newline character is among the characters matched by a period (the wildcard character). By default, it is not. |
x | Ignores whitespace characters. |
Examples
The following statement
REGEXP_INSTR('Mississippi', 'i', 1, 3)
searches the string Mississippi for the third instance of the letter i, beginning the search at the first letter. It returns the value 8.
The DECODE function compares one expression to one or more other expressions and, when the base expression equals a search expression, returns the corresponding result expression; or, when no match is found, returns the default expression when it is specified, or NA when it is not.
Return Value
The data type of the first result argument.
Syntax
DECODE (expr , search, result [, search , result]... [, default])
Parameters
The expression to be searched. The function automatically converts expr to the data type of the first search value before comparing
An expression to search for. The function automatically each search value to the data type of the first search value before comparing
The expression to return when expression equals search.
An expression to return when expression is not equal to search.
Usage Notes
Order of Value Evaluation
The search, result, and default values can be derived from expressions. The function evaluates each search value only before comparing it to expr, rather than evaluating all search values before comparing any of them with expr. Consequently, the function never evaluates a search when a previous search equals expr.
Examples
Example 7-64 Decoding an ID Field
Assume that your analytic workspace contains the following objects. Note that the inventory_location formula uses the DECODE function to identify text values that correspond to the INTEGER values of warehouse_id.
DESCRIBE
DEFINE product_id DIMENSION TEXT
DEFINE warehouse_id DIMENSION INTEGER
DEFINE inventories VARIABLE DECIMAL <product_id warehouse_id>
DEFINE inventory_location FORMULA TEXT <warehouse_id>
EQ -
DECODE (warehouse_id, 1, 'Southlake', 2, 'San Francisco', 4, 'Seattle', -
'Non domestic')
REPORT inventories
---------------INVENTORIES---------------
---------------PRODUCT_ID----------------
WAREHOUSE_ID 1770 1775
-------------------- -------------------- --------------------
1 30.63 79.02
2 71.49 55.83
3 88.71 68.02
4 86.27 41.86
REPORT inventory_location
WAREHOUSE_ID INVENTORY_LOCATION
-------------------- --------------------
1 Southlake
2 San Francisco
3 Non domestic
4 Seattle
The following reports illustrate how you can use inventory_location to display the decoded values of warehouse_id in a report rather than displaying the actual values of warehouse_id.
LIMIT product_id to '1775'
REPORT DOWN warehouse_id inventories
----INVENTORIES-----
-----PRODUCT_ID-----
WAREHOUSE_ID 1775
-------------------- --------------------
1 79.02
2 55.83
3 68.02
4 41.86
REPORT DOWN inventory_location inventories
----INVENTORIES-----
-----PRODUCT_ID-----
INVENTORY_LOCATION 1775
-------------------- --------------------
Southlake 79.02
San Francisco 55.83
Non domestic 68.02
Seattle 41.86
Example 7-65 DECODE with BITAND
Assume that you have the following objects with the reported values within your analytic workspace.
DEFINE order_id DIMENSION TEXT DEFINE customer_id DIMENSION TEXT DEFINE order_customer COMPOSITE <order_id customer_id> DEFINE order_status VARIABLE NUMBER(2) <order_customer<order_id customer_id>> REPORT DOWN order_customer order_status ORDER_ID CUSTOMER_ID ORDER_STATUS ------------ ------------ ------------ 2458 101 0.00 2397 102 1.00 2454 103 1.00 2354 104 0.00 2358 105 2.00 2381 106 3.00 2440 107 3.00 2357 108 5.00 2394 109 5.00 2435 144 6.00 2455 145 7.00 2356 105 5.00 2360 107 4.00
Assume that the value of order_status is used as a bitmap where the first three bits hold information about the order and the other bits are always 0:
The first bit is used for location information:
0 = Post Office, which corresponds to integer values of 0, 2, 4, and 6.
1 = Warehouse, which corresponds to the integer values of 1, 3, 5, and 7.
The second bit is used for method:
0 = Air, which corresponds to the integer values of 0, 1, 4, and 5.
1 = Ground, which corresponds to the integer values of 2, 3, 6, and 7.
The third bit is used for receipt:
0 = Certified, which corresponds the integer values of 0, 1, 2, and 3.
1 =Insured, which corresponds to the integer values of 4, 5, 6, and 7.
The following formulas use DECODE to substitute the text values for the bit values.
DEFINE location FORMULA DECODE(BITAND(order_status, 1), 1, 'Warehouse', 'PostOffice') DEFINE method FORMULA DECODE(BITAND(order_status, 2), 2, 'Ground', 'Air') DEFINE receipt FORMULA DECODE(BITAND(order_status, 4), 4, 'Insured', 'Certified')
Now, you can issue a report to display the decoded values.
REPORT DOWN order_customer order_status location method receipt ORDER_ID CUSTOMER_ID ORDER_STATUS LOCATION METHOD RECEIPT ------------ ------------ ------------ ------------ ------------ ------------ 2458 101 0.00 PostOffice Air Certified 2397 102 1.00 Warehouse Air Certified 2454 103 1.00 Warehouse Air Certified 2354 104 0.00 PostOffice Air Certified 2358 105 2.00 PostOffice Ground Certified 2381 106 3.00 Warehouse Ground Certified 2440 107 3.00 Warehouse Ground Certified 2357 108 5.00 Warehouse Air Insured 2394 109 5.00 Warehouse Air Insured 2435 144 6.00 PostOffice Ground Insured 2455 145 7.00 Warehouse Ground Insured 2356 105 5.00 Warehouse Air Insured 2360 107 4.00 PostOffice Air Insured
The CALL command invokes a program. When the program has arguments, which are always enclosed in parentheses, it passes these arguments to the called program.
Syntax
CALL program-name [(arg ...)]
Parameters
The name of the program to be called.
One or more optional arguments expected by the called program. These arguments can be declared in the called program with ARGUMENT, or they can be referenced in the program with ARG. If the program uses the ARGUMENT statement, when you use CALL to invoke the program, specify the arguments so that they match the positions of the arguments declared in the called program.
Usage Notes
Dimension Arguments
When you pass a dimension value or dimension name as an argument, you must enclose the exact text value in single quotes, for example, 'Jan96'. When the program arguments are declared with the ARGUMENT statement, you can pass a text expression that evaluates to a text value.
Program Return Values
When you use CALL to invoke a program that returns a value, the return value is discarded. A program can use the CALLTYPE function to determine whether it was invoked as a function, as a command, or by using CALL.
ARGUMENT Command or ARG Function
The called program can process arguments using either the ARGUMENT statement or the ARG function. In a program that has been invoked with CALL or as a function, the ARGS and ARGFR functions always return NA.
When CALL invokes a program whose arguments are not declared with the ARGUMENT statement, the arguments passed can be referenced with the ARG function. However, the ARG function is a text function and, consequently, interprets all arguments passed as text values. When you want to pass NTEXT arguments, be sure to declare them using ARGUMENT instead of using ARG. With ARG, NTEXT arguments are converted to TEXT, and this can result in data loss when the NTEXT values cannot be represented in the database character set.
ARGUMENT Statement Processing
When a program is invoked with CALL or as a function, the following two-step process occurs. When an error occurs in either step, the program is not executed.
The specified data types are established. Argument expressions specified by the calling program are evaluated left to right, and their data types are identified. Any expression representing a dimension value can be a text (TEXT or ID), numeric (INTEGER, DECIMAL, and so on), or RELATION value. An error in one argument expression stops the process.
Each specified data type is matched with the declared data type. Argument expressions are matched by position with the declared arguments in the called program. The first argument expression is matched with the first declared argument variable, the second argument expression is matched with the second declared argument variable, and so on. Each expression is converted in turn to the declared data type of the argument variable.
When an argument variable is declared as a dimension value, the matching value passed from the calling program can be TEXT or ID (representing a value of the specified dimension), numeric (representing a logical dimension position), or RELATION (representing a physical dimension position).When the matching value is a non-integer numeric value (for example, DECIMAL), it is rounded to the nearest INTEGER to represent a logical dimension position.
When an argument variable is declared as something other than a dimension value, and the matching value from the calling program is a RELATION value, an error occurs. When you want to pass a RELATION value that is received as a TEXT argument, use the CONVERT function to convert the value in the program's argument list.
ARGUMENT Statement with Extra Arguments
When the calling program specifies more arguments than are declared in the called program, the extra arguments are ignored. When the calling program specifies fewer arguments than are declared in the called program, the extra argument variables are given NA values.
ARGUMENT Statement Passing by Value
When arguments are declared with the ARGUMENT statement, they are passed by value to a program. Consequently, the called program is given only the value of an argument, without access to any analytic workspace object to which it might be related. However, when the name of an analytic workspace object is specified as an argument enclosed in single quotes, the value of the analytic workspace object is not passed. Instead, the name of the object is passed as a text string. See Example 9-59, "Calling a Program or Function".
Examples
Example 9-59 Calling a Program or Function
This example illustrates how two programs, roundup.p and roundup.f, are used in different ways to evaluate data and produce output.
The roundup.p program accepts the name of a decimal variable as a text string and produces a report of that variable's values rounded to the nearest INTEGER. The roundup.f program also accepts the name of a decimal variable. However, instead of passing the name of the variable as a text string, the variable's value is passed as an argument. roundup.f does not produce a report. Instead, it returns each of the values of the decimal variable, rounded to the nearest INTEGER.
The roundup.p program is invoked using CALL and includes a REPORT statement. In contrast, roundup.f is invoked as a user-defined function whose return value is then used as an argument to a REPORT statement.
The roundup.p program uses ARGUMENT to declare a text argument. When invoked, roundup.p uses the argument as the name of a decimal variable. The calling program passes the name of the variable to give the called program access to all the values of the dimensioned variable. When the calling program passed the variable itself, instead of its name, only a single value would have been accessible to the called program. This program does not return a value; it produces a report.
DEFINE roundup.p PROGRAM INTEGER PROGRAM ARGUMENT varname TEXT Report Down Line Across Month: Heading 'VARNAME' - IF INTPART(&varname) EQ &varname - THEN &varname ELSE INTPART(&varname) + 1 END
The following statements
LIMIT division TO 1
LIMIT month TO 1 TO 4
DECIMALS = 0
CALL roundup.p('actual')
produce the following report.
DIVISION: CAMPING
----------------- Varname------------------
-------------------MONTH-------------------
LINE Jan95 Feb95 Mar95 Apr95
-------------- ---------- ---------- ---------- ----------
revenue 533,363 572,797 707,198 968,858
cogs 360,811 400,902 478,982 641,716
gross.margin 172,553 171,895 228,217 327,143
marketing 37,370 38,867 51,224 69,439
selling 89,008 86,458 102,233 139,567
r.d 24,308 23,400 39,943 57,186
opr.income 21,868 23,171 34,819 60,952
taxes 15,971 16,320 23,030 27,584
net.income 5,898 6,851 11,789 33,368
Another way to produce the same report is to write a user-defined function that can be used as an argument to the REPORT statement as illustrated in the following program named roundup.f.
DEFINE roundup.f PROGRAM INTEGER PROGRAM ARGUMENT realval DECIMAL IF realval EQ INTPART(realval) THEN RETURN INTPART(realval) ELSE RETURN INTPART(realval) + 1 END
The following statements
LIMIT division TO 1 LIMIT month TO 1 TO 4 DECIMALS = 0 REPORT DOWN line ACROSS month: roundup.f(actual)
produce the following report.
DIVISION: CAMPING
------------ ROUNDUP.F(ACTUAL)-------------
-------------------MONTH-------------------
LINE Jan95 Feb95 Mar95 Apr95
-------------- ---------- ---------- ---------- ----------
revenue 533,363 572,797 707,198 968,858
cogs 360,811 400,902 478,982 641,716
gross.margin 172,553 171,895 228,217 327,143
marketing 37,370 38,867 51,224 69,439
selling 89,008 86,458 102,233 139,567
r.d 24,308 23,400 39,943 57,186
opr.income 21,868 23,171 34,819 60,952
taxes 15,971 16,320 23,030 27,584
net.income 5,898 6,851 11,789 33,368
(Compare the roundup.f program with the roundup.p program. roundup.f returns a value; it does not produce a report.)
The SET command, also called an assignment statement or the = command, assigns one or more values to a variable, option, relation, or dimension surrogate. When an object has one or more dimensions, the SET command loops over the values in status for each dimension of the target object and assigns a data value to the corresponding cell of the target object.
When the target is an object defined with a composite in its dimension list, Oracle OLAP automatically creates any missing target cells that are being assigned non-NA values. This step also adds to the composite all the dimension value combinations that correspond to those new cells. Thus, both the target object and the composite might be larger after an assignment. When you want to assign values only to cells that already exist in the target, use the ACROSS keyword.
|
Note: You can use UNRAVEL with SET to assign values of an expression into the cells of a variable when the dimensions of the expression are different from the dimensions of the variable |
Syntax
[SET] target-name [=] expression [ACROSS composite]
Parameters
SET is optional. It is an older command form of this functionality, and is included for compatibility.
The name of the target object where the data is assigned and stored. For a list of analytic workspace objects that can be a target object, see Table 10-9, "Using Objects in Assignment Statements".
The = (assignment or equal) operator assigns one or more values to a variable, option, or relation. See also "Assignment Operator".
The source of the data values to be assigned to the object, see Table 10-9, "Using Objects in Assignment Statements"
When you are assigning data to a variable dimensioned by a composite the default behavior is to loop over all the values in status for each of the base dimensions of the object. Oracle OLAP automatically creates any missing target cells that are being assigned non-NA values, and it automatically adds the required dimension value combinations to the composite.
When you want to assign values only to existing cells of a variable defined with a composite, use the ACROSS keyword, which causes = to change the way it loops for those dimensions of the target that are part of the composite. Instead of looping over all possible combinations of the values in the status of those dimensions, = loops only over those combinations of the values in the status that already exist in the composite.
The ACROSS keyword is intended for specifying a composite. However, when you specify a base dimension of the composite instead, be aware that the assignment statement could add many values to your composite.
Usage Notes
Triggering Program Execution When an Assignment Statement Executes
Using the TRIGGER command, you can make a SET statement an event that automatically executes an OLAP DML program. See "Trigger Programs" for more information
Dimensionality and Performance
When the target has multiple dimensions, the = statement loops over the dimension values in the order in which they were added, regardless of their logical order as reflected by the default status. In a multidimensional case, the looping is over the compound dimension. The first dimension listed in the definition varies the fastest. When you are setting the target to the values of an expression, Oracle OLAP performs much more efficiently when the source expression has the same dimensions, in the same order, as the target.
Differently Dimensioned Variables in an Expression
When an assignment statement involves several differently-dimensioned objects, the calculation can appear complicated. The following list outlines the process followed by a complicated assignment statement. When the statement is A = B, where A is the object being set to the expression B, Oracle OLAP first determines the dimensions of A. Then it determines the status of those dimensions. For each combination of dimension values in the status of those dimensions:
Oracle OLAP determines which single value of A (sometimes called a cell) is going to be set.
For each component of the expression B (each variable, formula, function, qualified data reference, or literal), Oracle OLAP determines the single value that corresponds to the cell of A that is being set. When a component of the expression is not dimensioned or is a literal, Oracle OLAP simply uses its value. When a component of the expression has dimensions different from A, Oracle OLAP uses the first value in the status of these dimensions.
Oracle OLAP performs the specified calculation on the single values obtained in Step 2 and stores the result in the cell of A chosen in Step 1.
Using Objects in Assignment Statements
Table 10-9, "Using Objects in Assignment Statements" outlines the objects that you can use in assignment statements and indicates whether you can use them as a target or source expression.
Table 10-9 Using Objects in Assignment Statements
| Object | Target | Source |
|---|---|---|
|
Composite |
No |
Yes |
|
Dimension |
Only in models |
Yes |
|
Formula |
Yes |
Yes |
|
Function (including OLAP DML program as function) |
No |
Yes |
|
Relation |
Yes |
Yes |
|
Surrogate |
Yes |
Yes |
|
Valueset |
No |
Yes |
|
Variable |
Yes |
Yes |
|
Worksheet |
Yes |
Yes |
Assigning Values to Variables
When you use an = (SET) statement to assign the value of a single-cell expression to a single cell, a single value is stored. However, when you use an = statement to assign the value of a single-cell expression to a target variable that has one or more dimensions, then the assignment loops over the values in status for each dimension of the target variable and assigns a data value to the corresponding cells of the variable.
When you assign a multiline value to a fixed-width text variable, then the variable is set to the first line only. To assign a multiline value to a fixed-width text variable, you use the JOINCHARS function to make the multiline value one line long. For example, suppose you have a non-fixed-width text variable called textvar. The statement
SHOW textvar
produces the following output, in which each line of the value in textvar is shown as a separate line.
This is a variable that has a multiline text value.
To assign this value to a variable called fixedtext with a fixed width of 60 bytes and show the value, you would use the following statements.
fixedtext = JOINCHARS(textvar) SHOW fixedtext
These statements produce the following output, in which the value of textvar is shown as a single line.
This is a variable that has a multiline text value.
When the actual number of bytes in the textvar variable's value exceeds the width of the fixedtext variable, then the value of textvar is truncated when it is stored in fixedtext.
Assigning Values to Relations
You can assign values to a relation using a SET statement as illustrated in Example 10-114, "Assigning Values to a Relation". When executing the assignment statement, a loop is performed over the values in status for each dimension of the target relation and assigns a data value to the corresponding cell of the target relation.
You can assign values to a relation with a text dimension by assigning one of the following:
A text value of the dimension.
An INTEGER that represents the position of the dimension value in the default status list of the dimension.
Assigning Values to Dimensions
The only time you use an = statement to assign a value to a dimension is when the result of a calculation in a model equation is numeric. In this situation, you can use the = operator to assign the results to a dimension value. However, equations (that is, expressions) in models differ in several ways from expressions used in other contexts. See "Rules for Equations in Models" for information on using the assignment statement within models. See the MAINTAIN command for information on how to add values to dimensions in all other cases.
Assigning Values to Dimension Surrogates
You assign values to a dimension surrogate with an = (SET) statement. For example, the following statements define the dimension surrogate storename, which is a TEXT type surrogate for the NUMBER type dimension store_id, assign a value to the fourth position of storename, and then report the value of the surrogate for the fourth value of store_id, which is 100.
DEFINE storename SURROGATE store_id TEXT storename(storename 4) = 'Molly\'s Emporium' REPORT W 25 storename(store_id 100) STORENAME(STORE_ID 100) ------------------------- Molly's Emporium
For example, when you define the INTEGER dimension surrogate intsurr for a NUMBER dimension numdim that has five values, then a report of intsurr produces the following.
INTSURR
-------
1
2
3
4
5
Like a dimension, the values of a dimension surrogate must be unique. However, unlike a dimension, a dimension surrogate can have NA values, unless it is an INTEGER type. The same value can be a value of the dimension and of any of its surrogates.
Using QDRs with the Target of an Assignment Statement
You can use a QDR with the target of an = (SET) statement which lets you assign a value to specific cells in a variable or relation.
The following example assigns the value 10200 to the data cell of the sales variable that is specified in the qualified data reference. When the variable named sales does not already have a value in the cell associated with Boston, Tents, and Jan99, then the value is assigned to the cell and thus it is added to the variable. When a value already exists in the cell, the value 10200 overwrites the previous value.
sales(market 'Boston' product 'Tents' month 'Jan99')= 1020
Expressions Dimensioned Conjoint Dimensions
When an expression is dimensioned by a conjoint dimension, Oracle OLAP uses the dimension's relationship to its base dimension values to assign data to the correct cells. You can set the values of a variable dimensioned by a conjoint dimension to an expression dimensioned by one of its base dimensions. The converse is also true. See "Compacting Your Data".
Rules for Equations in Models
The equations in a model use an OLAP DML assignment statement to assign values to variables or dimension values. Equations in models differ in several ways from equations used in other contexts in Oracle OLAP:
In a model equation, you can use the name of a dimension value anywhere you would normally use the name of a variable. You can base calculations on a dimension value, and you can assign the results of a calculation to a dimension value. When an equation refers directly to one or more dimension values, it is called a dimension-based equation.
You cannot use ampersand substitution in model equations.
You can include a program as a component in a calculation only when it is used as a function.
Within a single dimension-based equation, all the dimension values must belong to the same dimension.
When you assign the results of a calculation to a dimension value, the results must be numeric.
Each dimension on which the model equations are based must be listed in a DIMENSION statement. When the model contains an INCLUDE statement, the appropriate DIMENSION statements must be inherited from the included model. When the model does not contain an INCLUDE statement, it must contain the appropriate DIMENSION statements. When you compile or run the model, Oracle OLAP searches through the dimensions listed in explicit or inherited DIMENSION statement to identify the dimension to which each dimension value belongs.
Dimension Status and Model Equations When a model contains an assignment statement to assigns data to a dimension value, then the dimension is limited temporarily to that value, performs the calculation, and then restores the initial status of the dimension.
Formatting Conjoint Dimension Values A special format is required when dimension-based equations refer to values of a conjoint dimension:
Enclose the entire dimension value specification in angle brackets and then enclose this entire specification in single quotes; do not enclose the individual values in single quotes.
Use the exact upper- and lowercase spellings for the base dimension values.
When the specification includes a text value with an embedded blank, you must separate the dimension values with commas.
For example, assume that item.org is a conjoint dimension with base dimensions item and org. In this case, you use the following format to refer to values of item.org.
'<Expenses, Direct Sales>'
Formatting Text Dimension Values When dimension-based equations refer to text dimension values with embedded blanks or mixed upper- and lowercase letters, enclose the dimension value in single quotes. Use the exact upper- and lowercase spelling for the value.
For example, assume that a text dimension named lineitem contains a value with an embedded blank. In this case, you use the following format.
'Software Revenue'
Specifying DAY, WEEK, MONTH, QUARTER, YEAR Values for a Model Equation When a model equation is based on a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, you must use the dimension's VNF (value name format), rather than a date format, to specify the dimension's values. In addition, the VNF must format dimension values as follows:
The value must start with a letter.
The value can only contain letters, digits, underscores, and periods.
When the WEEK, MONTH, QUARTER, YEAR dimension of type does not have a VNF assigned to it, you can use the default VNF for the dimension. The entry for the VNF command lists the default VNF for each of these dimension types, and it explains how to assign a VNF to a dimension.
The default VNF for DAY dimensions is not acceptable because it specifies a digit as the first character of each dimension value. For a DAY dimension, specify the dimension name and enclose the value in parentheses and single quotes.
For example, for a DAY dimension named daydim, you can use the following format.
daydim('01jul97')
Formatting INTEGER Dimension Values When dimension-based equations refer to values of an INTEGER dimension, enclose the dimension value in single quotes.
For example, for an INTEGER dimension named intdim, use the following format to refer to the first dimension value.
'1'
When the model is based on multiple dimensions, the model compiler might not be able to correctly identify the dimension to which a literal INTEGER value belongs. In this case, specify the name of the dimension and enclose the value in parentheses and single quotes as described in "Formatting Ambiguous Dimension Values".
Formatting Ambiguous Dimension Values In some cases the model compiler might be unable to correctly identify the dimension to which a dimension value belongs. For instance, this can happen under the following circumstances:
Two or more dimensions have a dimension value with the same name.
A DAY dimension uses the default VNF (which starts with a digit).
An INTEGER value could be interpreted either as a position within a dimension or as a literal INTEGER value of a dimension.
In cases such as these, you can avoid ambiguity in model-based equations by following these rules:
Enclose the dimension value in single quotes.
Enclose the quoted value in parentheses.
Precede the parentheses with the name of the dimension.
For example, for an INTEGER dimension named intdim, use the following format to refer to the first dimension value.
intdim('1')
Examples
Example 10-113 Assigning Values to a Variable
For the first example, suppose you have defined two variables, units and price, that are both dimensioned by product. The following example calculates dollar sales (units times price) for each value in the product dimension. Using an assignment statement, it stores the result in the variable sales, which is also dimensioned by product.
sales = units*price
For another example, assume the choicedesc variable is dimensioned by choice. Before you enter data for the variable, the cells of the variable contain only NA values.
CHOICE CHOICEDESC -------------- -------------------- Report NA Graph NA Analyze NA Data NA Quit NA
Suppose you initialize the choicedesc variable using the following statement.
choicedesc = JOINCHARS ('Description for ' choice)
Now all of the choicedesc cells of the variable contain the appropriate values.
CHOICE CHOICEDESC -------------- ------------------------- Report Description for Report Graph Description for Graph Analyze Description for Analyze Data Description for Data Quit Description for Quit
The next example shows an expression that is dimensioned by time, product, and district and is assigned to a new variable. The expression calculates a 2002 sales plan based on unit sales in 2001.
DEFINE units.plan INTEGER <month product district> LIMIT month TO 'DEC02' units.plan = LAG(units 12 month) * 1.15
Example 10-114 Assigning Values to a Relation
Assume that your analytic workspace contains the following definitions for a hierarchical dimension for Geography named geog and a relation named geog_parentrel that contains values that represent the child-parent relationships in the Geography hierarchy.
DEFINE geog DIMENSION TEXT DEFINE geog_parentrel RELATION geog <geog>
You can use the following MAINTAIN ADD statements to populate the hierarchical dimension.
" Populate the geog dimension with values for all levels MAINTAIN geog ADD 'North America' 'Europe' 'United States' 'Canada' 'France' 'Germany' MAINTAIN geog ADD 'Massachusetts' 'California' 'Quebec' 'Ontario' MAINTAIN geog ADD 'Boston''Springfield' 'San Francisco''Los Angeles' 'Toronto' 'Ottawa' MAINTAIN geog ADD 'Montreal''Quebec City' 'Paris' 'Marseilles' 'Bonn' 'Berlin'
You can use the following assignments statements to populate geog_parentrel. Note that you must limit geog to the appropriate values before you assign values to geog_parentrel.
" Limit geog (and therefore geog_parentrel) to countries and assign " parent value (continent name) to those countries in geog_parentrel LIMIT geog to 'United States' 'Canada' geog_parentrel = 'North America' LIMIT geog to ALL LIMIT geog to 'France' 'Germany' geog_parentrel = 'Europe' " Limit geog (and therefore geog_parentrel) to states or provinces and assign " parent value (country name) to those states or provinces in geog_parentrel LIMIT geog to ALL LIMIT geog to 'Massachusetts' 'California' geog_parentrel = 'United States' LIMIT geog to ALL LIMIT geog to 'Quebec' 'Ontario' geog_Chapter 9, "OLAP DML Commands: A-G" = 'Canada' " Limit geog (and therefore geog_parentrel) to cities and assign " parent value (state, province, or country) to those cities in geog_parentrel LIMIT geog to ALL LIMIT geog to 'Boston' 'Springfield' geog_parentrel = 'Massachusetts' LIMIT geog to ALL LIMIT geog to 'San Francisco' 'Los Angeles' geog_parentrel = 'California' LIMIT geog to ALL LIMIT geog to 'Montreal' 'Quebec City' geog_parentrel = 'Quebec' LIMIT geog to ALL LIMIT geog to 'Toronto' 'Ottawa' geog_parentrel = 'Ontario' LIMIT geog to ALL LIMIT geog to 'Paris' 'Marseilles' geog_parentrel = 'France' LIMIT geog to ALL LIMIT geog to 'Bonn' 'Berlin' geog_parentrel = 'Germany' LIMIT geog to ALL
A report of geog_parentrel shows the values have been assigned.
COLWIDTH = 20 REPORT geog_parentrel REPORT geog_parentrel GEOG GEOG_PARENTREL ---------------- -------------------- North America NA Europe NA United States North America Canada North America France Europe Germany Europe Massachusetts United States California United States Quebec Canada Ontario Canada Boston Massachusetts Springfield Massachusetts San Francisco California Los Angeles California Toronto Ontario Ottawa Ontario Montreal Quebec Quebec City Quebec Paris France Marseilles France Bonn Germany Berlin Germany
Example 10-115 Using a Qualified Data Reference
This example uses an assignment statement with a qualified data reference to assign values to the variable budget. The values assigned to one budget line item (Net.Income) are calculated as the difference between two other line items (Opr.Income and Taxes), so you have to use a qualified data reference to obtain the correct data values.
budget(line Net.Income)= budget(line Opr.Income) - budget(line Taxes)
Example 10-116 Assigning Values to Variables with Composites
To have data assigned from sales only into existing data cells of sparse_sales, whose associated dimension values are in status, use the following statement.
sparse_sales = sales ACROSS SPARSE<product market>
The ACROSS keyword is particularly helpful when the source expression is a single value. When there are no limits on the dimensions of sparse_sales, then an assignment statement like the following creates cells for every combination of dimension values because there are no cases where the source expression is NA.
sparse_sales = 0
This defeats the purpose of a dimensioning a variable with a composite.
In contrast, the following statement sets only existing cells of sparse_sales to 0 (zero).
sparse_sales = 0 ACROSS SPARSE<product market>
Example 10-117 Compacting Your Data
Suppose you only sell some of your products in each district. You currently have a variable sales that has data for certain combinations of districts and products and NA values for the rest. You can create a dense array of sales data by defining a composite or a conjoint dimension and using it as a dimension of a new variable. Use an assignment statement to assign the data directly to the new variable. When the values of the composite or conjoint dimension include all the combinations with dataf, you can then delete the original variable and save space in the analytic workspace.
DEFINE proddist DIMENSION <product district> MAINTAIN proddist ADD <'Tents' 'Boston'> <'Canoes' 'Seattle'> - <'Sportswear' 'Atlanta'> DEFINE sales.dense DECIMAL <month proddist> sales.dense = sales LIMIT month TO FIRST 4
Issuing a REPORT sales.dense statement produces the following output.
----------------SALES.DENSE----------------
-----PRODDIST------ -------------------MONTH-------------------
PRODUCT DISTRICT Jan95 Feb95 Mar95 Apr95
-------- ---------- ---------- ---------- ---------- ----------
Tents Boston 32,153.52 32,536.30 43,062.75 57,608.39
Canoes Seattle 64,111.50 71,899.23 83,943.86 14,383.90
Sportswear Atlanta 114,446.26 123,164.92 138,601.64 141,365.66
An alternative method would be to use a composite instead of a conjoint dimension. In this case, you could use the following statements.
DEFINE sales.compact DECIMAL <month SPARSE <product district>> sales.compact = sales
Oracle OLAP automatically creates the unnamed composite when you define sales.compact, and it automatically adds dimension value combinations to the composite when you use an assignment statement. Oracle OLAP creates dimension value combinations only for the non-NA values of sales.
The ISINFINITE function returns a value that indicates if a the value of a numeric expression is infinity.
|
See also: This function provides information similar provided by the SQL IS [NOT] INFINITE floating point condition as described in Oracle Database SQL Language Reference. |
Return Value
BOOLEAN
Returns TRUE when the expression is either +INF (or -INF when NOT is not specified); otherwise it returns FALSE.
|
Note: The OLAP DML converts+INF or -INF values to NA when it performs calculation. Consequently, this function can only possibly return TRUE when executed against data that has been imported into an analytic workspace from a SQL-populated database but not yet used in an OLAP DML calculation. |
Syntax
ISINFINITE(expression)
Parameters
A decimal expression.
The LIKENL option controls whether the LIKE operator recognizes newline characters between lines of a text expression, when deciding whether a text value is like a text pattern. (In the OLAP DML, the representation of a newline character is "\n".)
The LIKENL option applies to the text expressions on either side of the LIKE operator.
Data Type
BOOLEAN
Syntax
LIKENL = {YES|NO}
Parameters
(Default) Specifies that the LIKE operator recognizes newline characters between lines of a text expression.
Specifies that the LIKE operator ignores newline characters between lines of a text expression. Newline characters are ignored in both of the expressions being compared.
Examples
Example 5-42 The Effect of LIKENL
The following statements show the use of the LIKENL option:
The statement
SHOW textvar
produces the following output.
Hello world
The statements
LIKENL = YES SHOW textvar LIKE '%low%'
produce the following output.
NO
The statement
SHOW ' Hello\nworld' LIKE '%\n%'
produces the following output.
YES
The statement
SHOW 'Hello\nworld' LIKE '%low%'
produces the following output.
NO
The statements
LIKENL = NO SHOW textvar LIKE '%low%'
produce the following output.
YES
The statement
SHOW 'Hello\nworld' LIKE '%\n%'
produces the following output.
YES
The statement
SHOW 'Hello\nworld' LIKE '%low%'
produces the following output.
YES
The REGRESS command calculates a simple multiple linear regression. The optional WEIGHTBY keyword lets you calculate a weighted regression when some data points are more reliable than others.
You can then execute REGRESS.REPORT to produce a standard report of the regression. You can also use the INFO function to obtain portions of the results for use in your own customized reports or for further analysis.
|
Tip: To performing more complex regression analysis use a forecasting context as discussed in "Forecasting Programs". |
Syntax
REGRESS [NOINTERCEPT] dependent independent... [WEIGHTBY weight]
Parameters
Directs Oracle OLAP to suppress the constant term (intercept) in the regression equation. The default is to calculate a constant term.
An expression to be used as the dependent variable in the regression.
In calculating the results, REGRESS loops over all the dimensions of the dependent and independent variables.
One or more expressions to be used as the independent variables (regressors) in the regression.
Specifies a weighted regression. The numeric expression weight supplies the weights for each data point (observation). Giving higher weights to more reliable observations results in a higher quality regression. WEIGHTBY must come last in the REGRESS command.
When weight is less than zero for any observation, an error occurs. When weight is equal to zero for any observation, that observation is ignored in the calculation. When WEIGHTBY is omitted, an unweighted regression is calculated.
Usage Notes
Ignoring NA Values
In performing its calculations, the REGRESS command ignores any observation that has an NA value.
Producing a Standard Report
The standard report for a regression shows the coefficient, standard error, and T-ratio for each independent variable; and the R-square, F-Statistic, number of observations, and standard error of estimate for the regression. To produce this report, type the following.
REGRESS.REPORT
Obtaining Results
For information on how to obtain portions of the results of REGRESS for your own reports or further analysis, use an INFO statement.
Examples
Example 10-91 Simple Regression
The following statements limit the product dimension to Canoes, then use regression to investigate the influence of advertising, price, and expense on the sales of canoes.
LIMIT product TO 'Canoes' REGRESS NOINTERCEPT sales advertising price expense
You can now execute REGRESS.REPORT as illustrated in Example 10-93, "Report for a Simple Regression" to see the results of the regression.
Example 10-92 Weighted Regression
The following statements use a weighted regression, in which districts are weighted using a variable called reliability that has the following definition and values.
DEFINE reliability VARIABLE DECIMAL <district> DISTRICT RELIABILITY -------------- ----------- Boston 1.00 Atlanta 0.90 Chicago 1.00 Dallas 0.80 Denver 0.90 Seattle 0.60
The following statements perform the regression.
REGRESS NOINTERCEPT sales advertising price expense - WEIGHTBY reliability
You can now execute REGRESS.REPORT as illustrated in Example 10-93, "Report for a Simple Regression" to see the results of the regression.
The AWWAITTIME option holds the number of seconds that a AW ATTACH command with the WAIT keyword waits for an analytic workspace to become available for access. The default value of AWWAITTIME is 20 seconds.
Data Type
INTEGER
Syntax
AWWAITTIME = seconds
Parameters
The number of seconds to wait for an analytic workspace to be available. The default value is 20 seconds.
Usage Notes
Workspace Sharing
When your user ID has the appropriate access rights and that no user has read/write exclusive access to the workspace, you can get read-only access to an analytic workspace, no matter how many other users are using it. When another user has read/write access and commits the workspace, your view of the workspace does not change; you must detach and reattach the workspace to see the changes.
Examples
The CONSIDER command identifies a definition as the current definition which enables you to add a description, value name format, formula, program, model, permission, or property to the definition with an LD, VNF, EQ, PROGRAM, MODEL, PERMIT, or PROPERTY statement.
Syntax
CONSIDER name
Parameters
The name of a definition in the current workspace or in an attached workspace.
Usage Notes
Replacing a Definition Component
When you use an LD, VNF, EQ, PROGRAM, MODEL, or PERMIT statement to add a component to the current definition, any existing value for that component is discarded and replaced by the new value you specify. For the PROPERTY statement, the value is replaced only when you specify a new value for an existing property name. Definitions can have multiple properties.
Unsuccessful CONSIDER Statements
When the CONSIDER command you issue is unsuccessful, subsequent LD, VNF, EQ, PROGRAM, MODEL, PERMIT, or PROPERTY statements produce an error.
Implicit CONSIDER Statements
The DEFINE, COPYDFN, and RENAME commands automatically issue an implicit CONSIDER command.
Examples
Example 9-71 Adding a Description to an Analytic Workspace Object
This example adds a description (LD) to the definition for district. To add the LD, you must first use CONSIDER to make district the current definition. The statements
CONSIDER district LD Sales Districts DESCRIBE district
produce the following definition.
DEFINE district DIMENSION TEXT LD Sales Districts
The DBMS_AW PL/SQL package provides procedures and functions for interacting with analytic workspaces.
This appendix contains the following topics:
One reference topic for each DBMS_AW subprogram
To interact with Oracle OLAP, you must attach an analytic workspace to your session. When you have DBMS_AW PL/SQL package installed you can perform this task from within SQL*Plus. For example, you can use the following command to attach an analytic workspace with read-only access.
EXECUTE dbms_aw.aw_attach ('awname');
Each analytic workspace is associated with a list of analytic workspaces. The read-only workspace EXPRESS.AW, which contains the OLAP engine code, is always attached last in the list. When you create a workspace, it is attached first in the list by default.
You can reposition an analytic workspace within the list by using keywords such as FIRST and LAST. For example, the following commands show how to move an analytic workspace called MYAW.TEST2 from the second position to the first position on the list.
EXECUTE dbms_aw.execute ('AW LIST'); TEST1 R/O UNCHANGED GLOBAL.TEST1 TEST2 R/O UNCHANGED GLOBAL.TEST2 EXPRESS R/O UNCHANGED SYS.EXPRESS EXECUTE dbms_aw.aw_attach ('test2', FALSE, FALSE, 'FIRST'); EXECUTE dbms_aw.execute ('AW LIST'); TEST2 R/O UNCHANGED GLOBAL.TEST2 TEST1 R/O UNCHANGED GLOBAL.TEST1 EXPRESS R/O UNCHANGED SYS.EXPRESS
From within SQL*Plus, you can rename workspaces and make copies of workspaces. If you have an analytic workspace attached with read/write access, you can update the workspace and save your changes in the permanent database table where the workspace is stored. You must do a SQL COMMIT to save the workspace changes within the database.
The following commands make a copy of the objects and data in workspace test2 in a new workspace called test3, update test3, and commit the changes to the database.
EXECUTE dbms_aw.aw_copy('test2', 'test3'); EXECUTE dbms_aw.aw_update('test3'); COMMIT;
With the DBMS_AW package you can perform the full range of OLAP processing within analytic workspaces. You can import data from legacy workspaces, relational tables, or flat files. You can define OLAP objects and perform complex calculations.
|
Note: If you use theDBMS_AW package to create analytic workspaces from scratch, you may not be able to use OLAP utilities, such as Analytic Workspace Manager and the DBMS_AW Aggregate Advisor, which require analytic workspaces of a particular structure. |
The DBMS_AW package provides several procedures for executing ad hoc OLAP DML commands. Using the EXECUTE or INTERP_SILENT procedures or the INTERP or INTERCLOB functions, you can execute a single OLAP DML command or a series of commands separated by semicolons.
Which procedures you use depends on how you want to direct output and on the size of the input and output buffers. For example, the EXECUTE procedure directs output to a printer buffer, the INTERP_SILENT procedure suppresses output, and the INTERP function returns the session log.
The DBMS_AW package also provides functions for evaluating OLAP expressions. The EVAL_TEXT function returns the result of a text expression, and EVAL_NUMBER returns the result of a numeric expression.
|
Note: Do not confuse theDBMS_AW functions EVAL_NUMBER and EVAL_TEXT with the SQL function OLAP_EXPRESSION. See "OLAP_EXPRESSION" for more information. |
The SQL processor evaluates the embedded OLAP DML commands, either in whole or in part, before sending them to Oracle OLAP for processing. Follow these guidelines when formatting the OLAP DML commands in the olap-commands parameter of DBMS_AW procedures:
Wherever you would normally use a single quote (') in an OLAP DML command, use two single quotes (''). The SQL processor strips one of the single quotes before it sends the OLAP DML command to Oracle OLAP.
In the OLAP DML, a double quote (") indicates the beginning of a comment.
Data can be stored in several different forms in an analytic workspace, depending on whether it is dense, sparse, or very sparse. The Sparsity Advisor is a group of subprograms in DBMS_AW that you can use to analyze the relational source data and get recommendations for storing it in an analytic workspace.
Analytic workspaces analyze and manipulate data in a multidimensional format that allocates one cell for each combination of dimension members. The cell can contain a data value, or it can contain an NA (null). Regardless of its content, the cell size is defined by the data type, for example, every cell in a DECIMAL variable is 8 bytes.
Variables can be either dense (they contain 30% or more cells with data values) or sparse (less than 30% data values). Most variables are sparse and many are extremely sparse.
Although data can also be stored in the multidimensional format used for analysis, other methods are available for storing sparse variables that make more efficient use of disk space and improve performance. Sparse data can be stored in a variable defined with a composite dimension. A composite has as its members the dimension-value combinations (called tuples) for which there is data. When a data value is added to a variable dimensioned by a composite, that action triggers the creation of a composite tuple. A composite is an index into one or more sparse data variables, and is used to store sparse data in a compact form. Very sparse data can be stored in a variable defined with a compressed composite, which uses a different algorithm for data storage from regular composites.
In contrast to dimensional data, relational data is stored in tables in a very compact format, with rows only for actual data values. When designing an analytic workspace, you may have difficulty manually identifying sparsity in the source data and determining the best storage method. The Sparsity Advisor analyzes the source data in relational tables and recommends a storage method. The recommendations may include the definition of a composite and partitioning of the data variable.
The Sparsity Advisor consists of these procedures and functions:
The Sparsity Advisor also provides a public table type for storing information about the dimensions of the facts being analyzed. Three objects are used to define the table type:
DBMS_AW$_COLUMNLIST_TDBMS_AW$_DIMENSION_SOURCE_TDBMS_AW$_DIMENSION_SOURCES_TThe following SQL DESCRIBE statements show the object definitions.
DESCRIBE dbms_aw$_columnlist_t dbms_aw$_columnlist_t TABLE OF VARCHAR2(100) DESCRIBE dbms_aw$_dimension_source_t Name Null? Type ----------------------------------------- -------- ---------------------------- DIMNAME VARCHAR2(100) COLUMNNAME VARCHAR2(100) SOURCEVALUE VARCHAR2(32767) DIMTYPE NUMBER(3) HIERCOLS DBMS_AW$_COLUMNLIST_T PARTBY NUMBER(9) DESCRIBE dbms_aw$_dimension_sources_t dbms_aw$_dimension_sources_t TABLE OF DBMS_AW$_DIMENSION_SOURCE_T
Take these steps to use the Sparsity Advisor:
Call SPARSITY_ADVICE_TABLE to create a table for storing the evaluation of the Sparsity Advisor.
Call ADD_DIMENSION_SOURCE for each dimension related by one or more columns to the fact table being evaluated.
The information that you provide about these dimensions is stored in a DBMS_AW$_DIMENSION_SOURCES_T variable.
Call ADVISE_SPARSITY to evaluate the fact table.
Its recommendations are stored in the table created by SPARSITY_ADVICE_TABLE. You can use these recommendations to make your own judgements about defining variables in your analytic workspace, or you can continue with the following step.
Call the ADVISE_DIMENSIONALITY procedure to get the OLAP DML object definitions for the recommended composite, partitioning, and variable definitions.
or
Use the ADVISE_DIMENSIONALITY function to get the OLAP DML object definition for the recommended composite and the dimension order for the variable definitions for a specific partition.
Example B-1, "Sparsity Advisor Script for GLOBAL" provides a SQL script for evaluating the sparsity of the UNITS_HISTORY_FACT table in the GLOBAL schema. In the GLOBAL analytic workspace, UNITS_HISTORY_FACT defines the Units Cube and is the source for the UNITS variable. UNITS_HISTORY_FACT is a fact table with a primary key composed of foreign keys from four dimension tables. A fifth column contains the facts for Unit Sales.
The CHANNEL_DIM and CUSTOMER_DIM tables contain all of the information for the Channel and Customer dimensions in a basic star configuration. Three tables in a snowflake configuration provide data for the Time dimension: MONTH_DIM, QUARTER_DIM, and YEAR_DIM. The PRODUCT_CHILD_PARENT table is a parent-child table and defines the Product dimension.
Example B-1 Sparsity Advisor Script for GLOBAL
CONNECT global/global
SET ECHO ON
SET LINESIZE 300
SET PAGESIZE 300
SET SERVEROUT ON FORMAT WRAPPED
-- Define and initialize an advice table named AW_SPARSITY_ADVICE
BEGIN
dbms_aw.sparsity_advice_table();
EXCEPTION
WHEN OTHERS THEN NULL;
END;
/
TRUNCATE TABLE aw_sparsity_advice;
DECLARE
dimsources dbms_aw$_dimension_sources_t;
dimlist VARCHAR2(500);
sparsedim VARCHAR2(500);
defs CLOB;
BEGIN
-- Provide information about all dimensions in the cube
dbms_aw.add_dimension_source('channel', 'channel_id', dimsources,
'channel_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('channel_id', 'total_channel_id'));
dbms_aw.add_dimension_source('product', 'item_id', dimsources,
'product_child_parent', dbms_aw.hier_parentchild,
dbms_aw$_columnlist_t('product_id', 'parent_id'));
dbms_aw.add_dimension_source('customer', 'ship_to_id', dimsources,
'customer_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('ship_to_id', 'warehouse_id', 'region_id',
'total_customer_id'));
dbms_aw.add_dimension_source('time', 'month_id', dimsources,
'SELECT m.month_id, q.quarter_id, y.year_id
FROM time_month_dim m, time_quarter_dim q, time_year_dim y
WHERE m.parent=q.quarter_id AND q.parent=y.year_id',
dbms_aw.hier_levels,
dbms_aw$_columnlist_t('month_id', 'quarter_id', 'year_id'));
-- Analyze fact table and provide advice without partitioning
dbms_aw.advise_sparsity('units_history_fact', 'units_cube',
dimsources, dbms_aw.advice_default, dbms_aw.partby_none);
COMMIT;
-- Generate OLAP DML for composite and variable definitions
dimlist := dbms_aw.advise_dimensionality('units_cube', sparsedim,
'units_cube_composite');
dbms_output.put_line('Dimension list: ' || dimlist);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
dbms_aw.advise_dimensionality(defs, 'units_cube');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The script in Example B-1, "Sparsity Advisor Script for GLOBAL" generates the following information.
Dimension list: <channel units_cube_composite<product customer time>> Sparse dimension: DEFINE units_cube_composite COMPOSITE <product customer time> Definitions: DEFINE units_cube.cp COMPOSITE <product customer time> DEFINE units_cube NUMBER VARIABLE <channel units_cube.cp<product customer time>> PL/SQL procedure successfully completed.
This SQL SELECT statement shows some columns from the AW_SPARSITY_ADVICE table, which is the basis for the recommended OLAP DML object definitions.
SELECT fact, dimension, dimcolumn, membercount nmem, leafcount nleaf,
advice, density
FROM aw_sparsity_advice
WHERE cubename='units_cube';
This query returns the following result set:
FACT DIMENSION DIMCOLUMN NMEM NLEAF ADVICE DENSITY -------------------- ------------ ------------ ----- ------ ------------ -------- units_history_fact channel channel_id 3 3 DENSE .46182 units_history_fact product item_id 48 36 SPARSE .94827 units_history_fact customer ship_to_id 61 61 SPARSE .97031 units_history_fact time month_id 96 79 SPARSE .97664
The management of aggregate data within analytic workspaces can have significant performance implications. To determine an optimal set of dimension member combinations to preaggregate, you can use the ADVISE_REL and ADVISE_CUBE procedures in the DBMS_AW package. These procedures are known together as the Aggregate Advisor.
Based on a percentage that you specify, ADVISE_REL suggests a set of dimension members to preaggregate. The ADVISE_CUBE procedure suggests a set of members for each dimension of a cube.
Instructions for storing aggregate data are specified in an analytic workspace object called an aggmap. The OLAP DML AGGREGATE command uses the aggmap to preaggregate the data. Any data that is not preaggregated is aggregated dynamically by the AGGREGATE function when the data is queried.
Choosing a balance between static and dynamic aggregation depends on many factors including disk space, available memory, and the nature and frequency of the queries that run against the data. After weighing these factors, you may arrive at a percentage of the data to preaggregate.
Once you have determined the percentage of the data to preaggregate, you can use the Aggregate Advisor. These procedures analyze the distribution of dimension members within hierarchies and identify an optimal set of dimension members to preaggregate.
Based on a precompute percentage that you specify, the ADVISE_REL procedure analyzes a family relation, which represents a dimension with all its hierarchical relationships, and returns a list of dimension members.
ADVISE_CUBE applies similar heuristics to each dimension in an aggmap for a cube.
Example B-2 uses the following sample Customer dimension to illustrate the ADVISE_REL procedure.
Sample Dimension: Customer in the Global Analytic Workspace
The Customer dimension in GLOBAL_AW.GLOBAL has two hierarchies: SHIPMENTS_ROLLUP with four levels, and MARKET_ROLLUP with three levels. The dimension has 106 members. This number includes all members at each level and all level names.
The members of the Customer dimension are integer keys whose text values are defined in long and short descriptions.
The following OLAP DML commands show information about the representation of the Customer dimension, which is in database standard form.
SET serveroutput ON ---- Number of members of Customer dimension EXECUTE dbms_aw.execute('SHOW STATLEN(customer)') 106 ---- Hierarchies in Customer dimension; EXECUTE dbms_aw.execute('REPORT W 40 customer_hierlist'); CUSTOMER_HIERLIST ---------------------------------------- MARKET_ROLLUP SHIPMENTS_ROLLUP ---- Levels in Customer dimension EXECUTE dbms_aw.execute('REPORT W 40 customer_levellist'); CUSTOMER_LEVELLIST ---------------------------------------- TOTAL_CUSTOMER REGION WAREHOUSE TOTAL_MARKET MARKET_SEGMENT ACCOUNT SHIP_TO ---- Levels in each hierarchy from leaf to highest EXECUTE dbms_aw.execute('REPORT W 20 customer_hier_levels'); CUSTOMER_HIERL IST CUSTOMER_HIER_LEVELS -------------- -------------------- SHIPMENTS SHIP_TO WAREHOUSE REGION TOTAL_CUSTOMER MARKET_SEGMENT SHIP_TO ACCOUNT MARKET_SEGMENT TOTAL_MARKET ---- Parent relation showing parent-child relationships in the Customer dimension ---- Only show the last 20 members EXECUTE dbms_aw.execute('LIMIT customer TO LAST 20'); EXECUTE dbms_aw.execute('REPORT W 10 DOWN customer W 20 customer_parentrel'); -----------CUSTOMER_PARENTREL------------ ------------CUSTOMER_HIERLIST------------ CUSTOMER MARKET_ROLLUP SHIPMENTS_ROLLUP ---------- -------------------- -------------------- 103 44 21 104 45 21 105 45 21 106 45 21 7 NA NA 1 NA NA 8 NA 1 9 NA 1 10 NA 1 11 NA 8 12 NA 10 13 NA 9 14 NA 9 15 NA 8 16 NA 9 17 NA 8 18 NA 8 19 NA 9 20 NA 9 21 NA 10 ---- Show text descriptions for the same twenty dimension members EXECUTE dbms_aw.execute('REPORT W 15 DOWN customer W 35 ACROSS customer_hierlist: <customer_short_description>'); ALL_LANGUAGES: AMERICAN_AMERICA ---------------------------CUSTOMER_HIERLIST--------------------------- -----------MARKET_ROLLUP----------- ---------SHIPMENTS_ROLLUP---------- CUSTOMER CUSTOMER_SHORT_DESCRIPTION CUSTOMER_SHORT_DESCRIPTION --------------- ----------------------------------- ----------------------------------- 103 US Marine Svcs Washington US Marine Svcs Washington 104 Warren Systems New York Warren Systems New York 105 Warren Systems Philladelphia Warren Systems Philladelphia 106 Warren Systems Boston Warren Systems Boston 7 Total Market NA 1 NA All Customers 8 NA Asia Pacific 9 NA Europe 10 NA North America 11 NA Australia 12 NA Canada 13 NA France 14 NA Germany 15 NA Hong Kong 16 NA Italy 17 NA Japan 18 NA Singapore 19 NA Spain 20 NA United Kingdom 21 NA United States
Example B-2 ADVISE_REL: Suggested Preaggregation of the Customer Dimension
This example uses the GLOBAL Customer dimension described in Sample Dimension: Customer in the Global Analytic Workspace.
The following PL/SQL statements assume that you want to preaggregate 25% of the Customer dimension. ADVISE_REL returns the suggested set of members in a valueset.
SET serveroutput ON
EXECUTE dbms_aw.execute('AW ATTACH global_aw.global');
EXECUTE dbms_aw.execute('DEFINE customer_preagg VALUESET customer');
EXECUTE dbms_aw.advise_rel('customer_parentrel', 'customer_preagg', 25);
EXECUTE dbms_aw.execute('SHOW VALUES(customer_preagg)');
31
2
4
5
6
7
1
8
9
20
21
The returned Customer members with their text descriptions, related levels, and related hierarchies, are shown as follows.
| Customer Member | Description | Hierarchy | Level |
|---|---|---|---|
31 | Kosh Enterprises | MARKET_ROLLUP | ACCOUNT |
2 | Consulting | MARKET_ROLLUP | MARKET_SEGMENT |
4 | Government | MARKET_ROLLUP | MARKET_SEGMENT |
5 | Manufacturing | MARKET_ROLLUP | MARKET_SEGMENT |
6 | Reseller | MARKET_ROLLUP | MARKET_SEGMENT |
7 | TOTAL_MARKET | MARKET_ROLLUP | TOTAL_MARKET |
1 | TOTAL_CUSTOMER | SHIPMENTS_ROLLUP | TOTAL_CUSTOMER |
8 | Asia Pacific | SHIPMENTS_ROLLUP | REGION |
9 | Europe | SHIPMENTS_ROLLUP | REGION |
20 | United Kingdom | SHIPMENTS_ROLLUP | WAREHOUSE |
21 | United States | SHIPMENTS_ROLLUP | WAREHOUSE |
The RPAD function returns an expression, right-padded to a specified length with the specified characters; or, when the expression to be padded is longer than the length specified after padding, only that portion of the expression that fits into the specified length.
Return Value
TEXT or NTEXT based on the data type of the expression you want to pad (text-exp).
Syntax
RPAD (text-exp , length [, pad-exp])
Parameters
A text expression to pad.
The total length of the return value as it is displayed on your terminal screen. In most character sets, this is also the number of characters in the return value. However, in some multibyte character sets, the display length of a character string can differ from the number of characters in the string.
When you specify a value for length that is shorter than the length of text-exp, then this function truncates the expression to the specified length.
A text expression that specifies the padding characters. The default value of pad-exp is a single blank.
Examples
The RANDOM function produces a number that is randomly distributed between specified low and high boundaries. Randomly generated numbers are useful when building and duplicating tests of applications. They are especially useful for simulation and forecasting applications.
|
Tip: To compute the number, RANDOM uses the values of the RANDOM.SEED.1 and RANDOM.SEED.2 options and then changes the values for the next time. When you create your own seeds, set the value of both options to odd numbers. This practice enhances the randomness of the numbers that are produced. |
Return Value
DECIMAL
Syntax
RANDOM([lowbound] [highbound])
Parameters
A numeric expression that specifies the lower boundary for the random number series. The default is 0. When lowbound is NA, the RANDOM function produces NA.
A numeric expression that specifies the upper boundary for the random number series. The default is 1. When highbound is NA, the RANDOM function produces NA
Examples
Example 8-64 Producing Random Numbers
This example assigns random numbers between 100 and 200 to a variable called test, which is dimensioned by product.
test = RANDOM(100 200) REPORT test
These statements produce a report such as the following.
PRODUCT TEST -------------- ---------- Tents 122.93 Canoes 176.69 Racquets 168.32 Sportswear 150.92 Footwear 187.46
The BIN_TO_NUM function converts a bit vector to its equivalent number.
BIN_TO_NUM is useful in data warehousing applications for selecting groups of interest using grouping sets.
Return Values
NUMBER
Syntax
BIN_TO_NUM(expression [, expression ]... )
Parameters
An expression that evaluates to either 0 (zero) or 1 (one) which is the value of a bit in the bit vector.
Examples
The REMLINES function removes one or more lines from a multiline TEXT expression and returns the value that remains.
Return Value
TEXT or NTEXT
Syntax
REMLINES(text-expression start [length])
Parameters
A multiline text expression from whose values REMLINES removes one or more lines. When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
An INTEGER that represents the line number at which to begin removing lines. The position of the first line in text-expression is 1.
An INTEGER that represents the number of lines to be extracted. When you do not specify length, only the line at start is removed.
Examples
The NASPELL option controls the spelling that is used for NA values in output.
Data Type
TEXT
Syntax
NASPELL = {'text'|'NA'}
Parameters
The spelling to use for any NA value in output. When you specify an expression rather than a text literal, you can omit the single quotes. The default is NA.
Usage Notes
Setting NASPELL to "0"
Setting NASPELL to the text character 0 (zero) causes NA values to appear as 0. However, they are still treated as NAs in calculations.
Assigning NA Values
NASPELL affects only Oracle OLAP output; it does not affect the way you assign an NA value. For example, even when you have set NASPELL to NONE, you assign an NA value as follows.
var1 = NA
$NATRIGGER Takes Precedence over NASPELL
Oracle OLAP evaluates an $NATRIGGER property expression before applying the NASPELL option. When the $NATRIGGER expression is NA, then the NASPELL option has an effect.
Examples
Example 5-72 Showing NA Values as "NONE"
Suppose you have a variable called current.month, which has a value of NA whenever no current month has been specified. In this case, you would like the value to appear as None rather than NA.
When NASPELL is set to its default value of NA, the OLAP DML statement
SHOW current.month
produces the following output.
NA
In contrast, the OLAP DML statements
NASPELL = 'None' SHOW current.month
produce the following output.
None
The FCSET command specifies the characteristics that you want the Geneva Forecasting engine to use when executing a forecasting context created using a FCOPEN statement.
You must use a FCSET statement in combination with other OLAP DML statements as outlined in "Forecasting Programs".
Syntax
FCSET handle-expression forecast-characteristic
where forecast-characteristic has the following syntax:
Parameters
An INTEGER expression that is the handle to forecast context that you want to query and that was previously opened using the FCOPEN function.
Indicates whether the forecast engine reduces the risk of over-adjustment by allocating or forecasting the last cycle.
NO specifies that the forecast engine forecasts the last cycle. (Default)
YES specifies that the forecast engine forecasts only the average value for one period of the cycle. That average value is then multiplied by factors to give the remaining points in that period. For example, when the last cycle has 24-hour periods, only an average hourly value is forecast, which is then multiplied by 24 hourly factors to give the value for each hour.
For the single exponential smoothing, double exponential smoothing, and Holt-Winters forecasting methods, specifies the value for Alpha which is the baseline parameter that is used for those methods.
ALPHA MAX decimal, specifies the maximum value of Alpha. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value of decimal is 0.3.
ALPHA MIN decimal specifies the minimum value of Alpha. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value of decimal is 0.1.
ALPHA STEP decimal specifies the value of the interval that the forecasting engine uses when it determines the value of Alpha. For decimal, you can specify any decimal value from 0.05 through 0.2 if the value evenly divides the difference between the values of ALPHA MAX and ALPHA MIN. The default value of decimal is 0.1.
Specifies the approach that the forecasting engine takes when it executes the forecast.
'APPAUTO' is the default approach which invokes the Geneva forecasting expert system which tests all of possible forecasting methods and options for these methods and chooses and uses the method that best fits the data. When you specify this value, the expert system ignores any value that you specify for the METHOD keyword.
Once the method is chosen, the expert system chooses alpha, beta, gamma, trend hold, cyclical decay and MPT transformation settings from the maximum and minimum settings you code. To set these values for the APPAUTO approach, you specify the same value for both minimum and maximum. For example, to specify a value of .2 for alpha, set ALPHA MIN to .2 and ALPHA MAX to .2. The expert system uses any other global parameters that you have set. (Default)
'APPMANUAL' indicates that the Geneva Forecasting engine uses the method and options you specify in this FCSET statement when executing the forecast.
For the double exponential smoothing and Holt-Winters forecasting methods, specifies the value of Beta. Beta is the trend parameter that controls the estimate of the trend.
BETA MAX decimal specifies the maximum value of Beta. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value is 0.3.
BETA MIN decimal specifies the minimum value of Beta. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value is 0.1.
BETA STEP decimal specifies the value of the interval that the forecasting engine uses when it determines the value of Beta. For decimal, you can specify any decimal value from 0.05 through 0.2 if the value evenly divides the difference between the values of BETA MAX and BETA MIN. The default value of decimal is 0.1.
Indicates whether optimization should be done on the median smoothed data series.
NO specifies that the methods are done using the original historical time series data. (Default)
YES specifies that optimization is done on the median smoothed data series, which results in more smoothed or "baseline" forecasts.
For linear and nonlinear regression methods, specifies the value of the cyclical decay. Cyclical decay pertains to how seriously the forecasting engine considers deviations from baseline activity when it performs linear and nonlinear regressions.
CYCDECAY MAX decimal, specifies the maximum value of the cyclical decay parameter. For decimal, you can specify any decimal value from 0.2 through 1.0 when the difference between the values of CYCDECAY MIN and CYCDECAY MAX is evenly divided by 0.4. The default value of decimal is 1.0.
CYCDECAY MIN decimal, specifies the minimum value of the cyclical decay parameter. For decimal, you can specify any decimal value from 0.2 through 1.0 when the difference between the values of CYCDECAY MIN and CYCDECAY MAX is evenly divided by 0.4. The default value of decimal is 0.2.
For the Holt-Winters forecasting method, specifies the value of Gamma which is the seasonal parameter used by that method.
GAMMA MAX decimal specifies the maximum value of Gamma. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value of decimal is 0.3.
GAMMA MIN decimal specifies the minimum value of Gamma. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value of decimal is 0.1.
GAMMA STEP decimal specifies the value of the interval that the forecasting engine uses when it determines the value of Gamma. For decimal, you can specify any decimal value from 0.05 through 0.2 when the value evenly divides the difference between the values of GAMMA MAX and GAMMA MIN. The default value of decimal is 0.1.
The number of historical periods. For integer, you can specify any INTEGER value from 1 through 50000, which is the maximum number of time dimension values that can be present in the time-series expression specified in the FCEXEC command. (Note that the number of forecast periods is derived by subtracting the value of HISTPERIODS from the STATLEN of the dimension of the time-series expression.)
Specifies the upper bound on the forecast data. The number you specify for decimal indicates a multiple of the largest value in the historical series. For example, when you specify 10.0, the upper bound is 10 times the largest value in the historical series. The default value is 100.0.
Specifies the forecasting method that you want the forecasting engine to use. Values that you specify for method are ignored unless the value of APPROACH is set to 'APPMANUAL'.
You can specify one of the following keywords for method:
AUTOMATIC specifies that the forecasting engine determines and uses the method that is the best fit for the data. (Default)
LINREG specifies the linear regression method in which a linear relationship (y=a*x+b) is fitted to the data.
NLREG1 specifies a nonlinear regression method in which a linear relationship (y'=a*x'+b) is fitted to a transformation of the original data; in this case, x'=log(x) and y'=log(y) which results in the development of a polynomial model between x and y(y=c*x^a).
NLREG2 specifies a nonlinear regression method in which a linear relationship (y'=a*x'+b) is fitted to a transformation of the original data; in this case, x'=x and y'=ln(y) which results in the development of an exponential model between x and y(y=c*e^ax).
NLREG3 specifies a nonlinear regression method in which a linear relationship (y'=a*x'+b) is fitted to a transformation of the original data; in this case, x'=log(x) and y'=y which results in the development of a logarithmic model between x and y(y=a*log(x)+b).
NLREG4 specifies a nonlinear regression method in which a linear relationship (y'=a*x'+b) is fitted to a transformation of the original data; in this case, x'=1/x and y'=1/y which results in the development of an asymptotic curve (y=x/(a+bx)).
NLREG5 specifies a nonlinear regression method in which a linear relationship (y'=a'*x+b) is fitted to a transformation of the original data; in this case, x'=x and y'=ln(y/(K-y)) which results in the development of an exponential asymptotic curve (y=cKe^ax/(1+ce^ax)).
SESMOOTH specifies the single exponential smoothing method in which the current estimate is taken as a geometrically weighted average of past values, and all future values are given this same value. This method is intended for short term forecasts of non-seasonal data.
DESMOOTH specifies the double exponential smoothing method in which the current estimate is taken as a geometrically weighted average of past values, and this is added to a trend term calculated by the same method. Single exponential smoothing is therefore applied to both the series and the trend term.
CROSTON specifies the Croston's Intermittent Demand method. The Croston's Intermittent Demand method is a forecasting method which is a variant of exponential smoothing that can be used for intermittent data (that is data where more than half of the observations are zero). This method first estimates the interval between positive demands, and then estimates the magnitude of the demand when positive.
HOLT/WINTERS specifies the Holt-Winters method that is used on seasonal data, in which double exponential smoothing methods with trend damping are combined with multiplicative seasonal factors, which are estimated using single exponential smoothing.
Specifies the lower bound on the forecast data. The number you specify indicates a multiple of the smallest value in the historical series. For decimal, you can specify any decimal value from 0.0 through 1.0. For example, when you specify 0.5 the lower bound is half the smallest value in the historical series. The default value of decimal is 0.0.
Specifies the value of the parameter that the forecasting engine uses when it adjusts the decay of estimates of base values that it uses when it unravels the predictions on a moving periodic total (MPT) series.
MPTDECAY MAX decimal specifies the maximum value of the parameter that the forecasting engine uses when it adjusts the decay of estimates of base values that it uses when it unravels the predictions on a moving periodic total (MPT) series. For decimal, you can specify any decimal value from 0.2 through 1.0 when the difference between the values of MPTDECAY MIN and MPTDECAY MAX is evenly divided by 0.4. The default value of decimal is 1.0.
MPTDECAY MIN decimal specifies the minimum value of the parameter that the forecasting engine uses when it adjusts the decay of estimates of base values that it uses when it unravels the predictions on a moving periodic total (MPT) series. For decimal, you can specify any decimal value from 0.2 through 1.0 when the difference between the values of MPTDECAY MIN and MPTDECAY MAX is evenly divided by 0.4. The default value of decimal is 0.2.
Specifies the number of trials that the forecasting engine runs to determine the forecast. For integer, you can specify any INTEGER value from 1 through 3. The default value of decimal is 3.
Specifies either the number of periods for a single cycle or the number of periods in each of a set of nested cycles.
You do not have to specify this parameter when you are using a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. In this case, the forecasting engine derives the periodicity from the number of time dimension periods that constitute a year (for example, there are 52 WEEK periods in a year).
When you are not using a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, the default value for cycle-spec is 1, which specifies that the data is not grouped at all (that is, each period is logically independent).
Cycles are groupings of time periods that repeat through the time span of the data. For example, daily periods can be grouped into a weekly cycle and weekly periods can be grouped into a yearly cycle. In this case, the cycles are said to be nested, with the yearly cycle more aggregate than the weekly cycle, and the weekly cycle more detailed than the yearly cycle. By specifying cycles at a more detailed level, you allow OLAP to conduct a finer-grained search for factors that affect the data.
To specify a single cycle, set cycle-spec to an INTEGER from 1 through 25000. The INTEGER indicates the number of periods into which the cycle should be divided. For example, the INTEGER 12 specifies that the cycle should be divided into 12 periods.
To specify a series of nested cycles, set cycle-spec to a series of up to six INTEGER values enclosed in parentheses and separated by commas. Each value in the series is the number of periods in a nested cycle. The cycles are ordered from most aggregate to least aggregate. For example, when cycle-spec is (52,7), this indicates two cycles in which the most aggregate cycle is divided into 52 periods and each of those periods is divided into seven periods. In this example, the year is divided into 52 weeks, and each of those weeks is divided into seven days.
Specifies the ratio of the size of the window that the forecasting engine uses for smoothing and the total number of historical periods. The forecasting engine uses this value to determine the number of backcast periods. You can specify any decimal value from 1/26 through 1/2. The default value of decimal is 1/3.
Indicates whether the forecasting engine should smooth the data for the forecast. The default value is NO. Specify YES when you want the forecasting engine to smooth the data.
The data filter that the forecasting engine uses when executing the forecast.
'TRNOSEA' indicates that the forecasting engine does not seasonally adjust the data. (Default)
'TRSEA' indicates that the forecasting engine transforms using a filter that seasonally adjusts the data.
'TRMPT' indicates that the forecasting engine transforms using a moving periodic total (MPT) filter.
For the double exponential smoothing and Holt-Winters forecasting methods, specifies the value of the trend hold parameter that indicates trend reliability for those methods.
TRENDHOLD MAX decimal specifies the maximum value of the trend hold parameter. For decimal, you can specify any decimal value from 0.0 through 1.0. The default value of decimal is 0.8.
TRENDHOLD MIN decimal specifies the minimum value of the trend hold parameter. For decimal, you can specify any decimal value from 0.0 through 1. 0. The default value of decimal is 0.4.
TRENDHOLD STEP decimal specifies the value of the interval that the forecasting engine uses when it determines the value of the trend hold parameter. For decimal, you can specify any decimal value from 0.1 through 0.2. The value of decimal must evenly divide the difference between the values of TRENDHOLD MAX and TRENDHOLD MIN. The default value of decimal is 0.2.
Specifies the number of points that the forecasting engine uses when it determines median values when it performs median smoothing. Median smoothing eliminates extreme variations in the data by replacing each data point in a series by the median value of itself and its neighbors. For integer, you can specify any INTEGER value from 1 through 13. The default value of integer is 3.
Examples
For an example of a forecasting program, see Example 9-119, "A Forecasting Program".
The EXISTS function determines whether an object is defined in any attached workspace. The EXISTS function is useful in a program to test whether a definition exists before you try to use it.
Return Value
BOOLEAN
Syntax
EXISTS(name-expression)
Parameters
A text expression that specifies the name you want to test.
Usage Notes
Specifying More Than One Name
When name-expression contains multiple object names, EXISTS returns NO even when all the objects specified by name-expression exist in attached workspaces.
Examples
The NLS_DATE_LANGUAGE option specifies the language for days, months, and similar language-dependent datetime format elements.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_DATE_LANGUAGE = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS parameters, including valid values.
Examples
This chapter contains the following topics:
The OLAP DML is the original language for defining Oracle OLAP objects and manipulating Oracle OLAP data.
There are two major types of OLAP DML statements:
OLAP DML statements that work against Oracle OLAP cubes and cube dimensions that have been previously defined in the Oracle data dictionary using the OLAP API. For an introduction to these statements, see "Cube-Aware OLAP DML Statements".
OLAP DML statements that create and manipulate lower-level OLAP objects that are defined and stored in an analytic workspace. For an introduction to these statements, see "OLAP DML Statements that Work Directly on Analytic Workspace Objects".
OLAP cubes are first-class Oracle OLAP objects and are defined in the Oracle data dictionary. Some OLAP DML statements work against cubes and other first-class OLAP objects.
The following OLAP DML programs work with previously-defined OLAP cubes and cube dimensions.
Typically, these programs take, as input, the Oracle data dictionary name of an OLAP cube or cube dimension. When the programs execute they not only make the necessary changes to the cube or cube dimension, they also make changes to all of the analytic workspace objects that underlie these cubes and cube dimensions.
Also, you can use the OBJORG function in OLAP DML statements that are not cube-aware to specify the analytic workspace objects that underlie OLAP cubes and cube dimensions.
Historically, OLAP DML statements did not work against first-level OLAP objects as defined in the OLAP data dictionary. Instead, OLAP DML statements create and manipulate lower-level OLAP objects that are defined and stored in an analytic workspace. This remains the case for most OLAP DML statements today.
|
Note: Unless otherwise stated, statements and information provided in this manual applies to OLAP DML statements that are not cube-aware (that is, OLAP DML statements work directly on analytic workspace objects). |
For OLAP DML statements that work directly on analytic workspace objects, if an object name is needed as input to the statement, the object name is the name of an object as defined in the analytic workspace, not as defined in the Oracle data dictionary.
You can use these OLAP DML statements to create programs that analyze analytic workspace data without using SQL, Java, the OLAP API, or the Oracle OLAP tools. You can use the OLAP DML to define the analytic workspaces and the objects that are stored in analytic workspaces. For example, you can:
Create an analytic workspace as described in "Defining a New Analytic Workspace".
Define the multidimensional data objects in an analytic workspace using the DEFINE command.
Define calculation objects and programs that analyze the data as described in Chapter 3, "Formulas, Models, Aggregations, and Allocations".
Populate and analyze the data in the multidimensional data objects.
The basic syntactic units of the OLAP DML are options, properties, commands, functions, and programs. All of these are sometimes collectively referred to as OLAP DML statements.
OLAP DML Options
An OLAP DML option is a special type of analytic workspace object that specifies the characteristic of some aspect of how Oracle OLAP calculates or formats data or what Oracle OLAP operations are activated. Some options are read-only, while others are read/write options for which you can specify values. Read/write options have default values.
You cannot define your own options as part of an analytic workspace. However, you can use any of the options that are defined as part of the Oracle OLAP DML. The options are documented as reference topics in Chapter 5, "OLAP DML Options".
OLAP DML Properties
A property is a named value that is associated with a definition of an analytic workspace object. You can name, create, and assign properties to an object using an OLAP DML PROPERTY command.
Properties that begin with a $ (dollar sign) are recognized by Oracle OLAP as system properties. You cannot create system properties; however, in some cases you can assign system properties to objects. These system properties are documented as reference topics in Chapter 4, "OLAP DML Properties".
OLAP DML Functions
OLAP functions work in much the same way as commands in other programming languages. They initiate action and return a value. The one exception is the looping nature of OLAP DML functions as discussed in "OLAP DML Statements Apply to All of the Values of a Data Object".
Most of the OLAP DML functions are standard text and calculation functions. Other OLAP DML functions return more complex information.Additionally, you can augment the functionality of the OLAP DML by writing an OLAP DML program for use as a function.
The built-in OLAP DML functions are documented as reference topics in Chapter 7, "OLAP DML Functions: A - K" and Chapter 8, "OLAP DML Functions: L - Z".
OLAP DML Commands
OLAP DML commands work in much the same way as commands in other programming languages—the one exception is the looping nature of OLAP DML commands as discussed in "OLAP DML Statements Apply to All of the Values of a Data Object".
Many OLAP DML commands perform complex actions. Some of these commands are data definition commands like the AW command which you use to create an analytic workspace and the DEFINE command which you use to define objects within an analytic workspace. Other OLAP DML commands are data manipulation commands. Some commands are recognized by Oracle OLAP as events that can trigger the execution of OLAP DML programs. (See "Trigger Programs" for more information.) Additionally, you can augment the functionality of the OLAP DML by writing an OLAP DML program for use as a command.
The built-in OLAP DML commands are documented as reference topics in Chapter 8, Chapter 9, "OLAP DML Commands: A-G" and Chapter 10, "OLAP DML Commands: H-Z".
OLAP DML Programs
Several OLAP DML programs are provided as part of the OLAP DML. Some of these programs produce reports that you can print or see online. Other programs provided as part of the OLAP DML perform standard calculations of use to programmers and database administrators. For more information on the programs delivered with the OLAP DML, see "Programs Provided With the OLAP DML".
You can also write your own OLAP DML programs to augment the functionality of the OLAP DML as described in Chapter 6, "OLAP DML Programs".
The simplest way to execute OLAP DML statement is by using the OLAP Worksheet. The OLAP Worksheet is delivered as part of the Analytic Workspace Manager. To open the OLAP worksheet from within the Analytic Workspace Manager:
Connect to an Oracle Database.
Select a Schema.
Select Tools, then OLAP Worksheet.
You can also execute OLAP DML statements from with SQL and Java:
Using the PL/SQL DBMS_AW package you can execute OLAP DML statements as described in "Embedding OLAP DML in SQL Statements".
Using SPL_Executor delivered as part of Oracle OLAP Java API you can embed OLAP DML statements within a Java program.
Conceptually, an analytic workspace is that portion of Oracle Database that is used by Oracle OLAP to perform OLAP analysis. Physically, an analytic workspace is stored in the Database as LOBs in a table named AW$workspacename.
An analytic workspace also contains the following types of objects and the OLAP DML definitions for these objects:
Multidimensional data objects that contain the data to analyze and the results of the analysis.
Calculation objects (that is, formulas, models, aggregations, and allocations) that contain OLAP DML statements that specify the analysis.
OLAP DML programs that perform complex analysis.
Since an analytic workspace is physically stored as a table in an Oracle Database, you need SQL GRANT privileges to work with an analytic workspace. The privileges you need vary depending on whether the analytic workspace is in a schema that you own or in a schema that you do not own:
When you are the owner of the schema, you only need SQL GRANT privileges when you want to create an analytic workspace or attach an analytic workspace. The privileges you must be granted to perform these tasks and the OLAP DML commands that relate to these tasks are outlined in the following table.
When you are not the owner of the schema, you need SQL GRANT privileges to create an analytic workspace, to attach an analytic workspace in ASOF mode, to drop an analytic workspace, and to truncate an analytic workspace as shown in the following table.
| Task | OLAP DML Command | SQL GRANT Privileges Needed |
|---|---|---|
| Create an analytic workspace | AW CREATE | CREATE ANY TABLE, SELECT ANY TABLE, UPDATE ANY TABLE |
| Attach an analytic workspace AS OF | AW ATTACH with ASOF keyword | FLASHBACK ANY TABLE |
| Delete an analytic workspace | AW DELETE | DROP ANY TABLE |
| Truncate an analytic workspace | AW TRUNCATE | TRUNCATE ANY TABLE |
Note that Oracle Database does not turn on roles when you run a named PL/SQL procedure. In this case, the you must have the CREATE TABLE privilege directly.
You can use the OLAP DML to create analytic workspaces. To create an analytic workspace, issue an AW command with the CREATE keyword, followed by an UPDATE statement and a COMMIT statement.
Before you can work with a previously-defined analytic workspace, you must first attach in by issuing an AW ATTACH statement. You can attach an analytic workspace in any of the following attachment modes:
Read-only—Users can make private changes to the data in the workspace to perform what-if analysis but cannot commit any of these changes.
Read/write access mode—Only one user can have an analytic workspace open in read/write at a time. The user has to commit either all or none of the changes made to the workspace.
Read/write exclusive access mode—The read/write exclusive attach mode is not compatible with any other access modes. A user cannot attach an analytic workspace in read/write exclusive mode when another user has it attached in any mode. Only one user can have an analytic workspace open in read/write exclusive at a time. The user has to commit either all or none of the changes made to the workspace.
Multiwriter access mode—an analytic workspace that is attached in multiwriter mode can be access simultaneously by several sessions. In multiwriter mode, users can simultaneously modify the same analytic workspace in a controlled manner by specifying the attachment mode (read-only or read/write) for individual variables, relations, valuesets, and dimensions.
For more information on the various attachment modes, see the syntax and notes for the AW ATTACH statement.
Table 1-1, "Statements for Viewing Information About an Analytic Workspace" lists the OLAP DML statements that you can use to view information about an analytic workspace
Table 1-1 Statements for Viewing Information About an Analytic Workspace
| Statement | Description |
|---|---|
|
|
Returns information about currently attached workspaces. |
|
AWDESCRIBE program |
Sends information about the current analytic workspace to the current outfile. |
|
EXISTS function |
Returns a value that indicates whether an object is defined in any attached workspace. |
|
LISTBY program |
Lists all objects in an analytic workspace that are dimensioned by or related to one or more specified dimensions or composites. |
|
LISTNAMES program |
Lists the names of the objects in an analytic workspace. |
|
OBJ function |
Returns information about an analytic workspace object. |
|
OBJLIST function |
Lists the objects that are in one or more workspaces that you specify. |
|
DESCRIBE command |
Lists the simple definition of one or more workspace objects. |
|
FULLDSC program |
Lists the complete definition of one or more workspace objects, including the properties and triggers of the object(s). |
A relational database typically stores data values in tables that represent third normal form data. In this type of implementation, the values of key columns of a relational database table are unique values of a single level of data. For example, at one level in the relational database you might have a table with a key column named City that contains the names of cities and at the next highest level in the database a table with a key column named state that contains the names of states, and so on and so on.
In an analytic workspace the objects that hold the data to analyze are arrays called variables. The keys into variables are stored in other objects which act as the dimensions of the variables. To support performant OLAP analysis, values from multiple levels are stored within a single dimension called a hierarchical dimension. For example, an analytic workspace might have a hierarchical dimension named geog that had as values the names of both cities and states.
The objects that store values that relate values of two or more dimensions are called relations. Thus the one-to-many relationship between values of different levels in a hierarchical dimension are stored in an analytic workspace. For example, the relationship between the city and state values in a hierarchical geog dimension would be stored in an analytic workspace relation typically called a parentrel relation. (See "Parentrel Relation" for more information.)
Additional analytic workspace objects are typically defined to keep additional information about the hierarchical dimension. Several important OLAP DML commands and functions (such as the LIMIT command) presume the existences of these objects in your analytic workspace as the name of these objects is one argument in the syntax of the statement.
The data objects that you define using the OLAP DML are multidimensional objects that are stored in an analytic workspace. When you use OLAP DML statements to perform operations against these multidimensional data objects, those operations apply all at once to entire set of values contained by these objects.
The OLAP DML supports the use of the following types of analytic workspace data objects:
|
Tip: You can use the OBJORG function to specify analytic workspace objects that underly cubes and cube dimensions. |
The most important data object in an analytic workspace is the variable. A variable is an object that stores data. All of the data in a variable must have the same data type. Typically, you use variables to contain data values that quantify a particular aspect of your business For example, your business might have several categories of transactions (measured in dollars, units, percentages, and so on) and each category is stored in its own variable. For example, you might record sales data in dollars (a sales variable) and units (a units variable).
Since the OLAP DML is a multidimensional programming language, variables are multidimensional and correspond to what other OLAP languages sometimes call measures. Conceptually, you can think of a variable with two dimensions as a table, a variable with three dimensions as a cube, and so on. Physically, variables are stored as multidimensional arrays with the actual structure of the arrays determined by the object by which the variable is dimensioned.
The scope and permanence of a variable can vary. A permanent variable is a variable for which both the variable values and definitions are stored in an analytic workspace. Temporary variables have values only during the current session. When you update and commit the analytic workspace, only the definitions of temporary variables are saved. When you exit from the analytic workspace, the data values are discarded. You can also define variables in programs.
You can define scalar variables (and frequently do) in programs, but most variables that you define using the OLAP DML are dimensioned variables. Dimensioned variables are arrays that hold multiple values. The indexes or dimensions of the variable provide the organization for the variable. The values of the dimension are similar to keys in a relational table; in that they uniquely identify a data value. For example, if you have sales variable that is dimensioned by time, geography, and product dimensions, then each combination of the values of time, geography, and product identifies a value in sales. (Note that the indexes of variable s are not actually the values of the dimension, but, instead, are the INTEGER positions of the values in the dimension.)
Variables can be dimensioned by either flat or hierarchical dimensions. A flat dimension exists when the values within a dimension are all at the same. level; no value is the child or parent of another value. A hierarchical dimension exists when the values with a single dimension are in a one-to-many (parent-to-child) relationship with each other.
A hierarchical d imension is a means of organizing and structuring this type of data within a single dimension. You can then use it to dimension a variable that contains data for all the levels. Some dimensions have multiple hierarchies. You specify the parent-to-child relationships of the dimension values by creating a self-relation.You use a hierarchical dimension to define a variable that contains data of varying levels of aggregation within a single variable. Storing all of these values in a single variable affords a quicker response time for users who want to view the data, particularly when the variable is large.
Frequently, the cells in the variable that correspond to upper level values in the hierarchical dimension contain the sum or total of the values in the cells of the variable that correspond to the lower level dimension values. For example, in a sales variable that is defined with a hierarchical dimension representing time, the cells of the variable for each quarter might represent the total sales for the months in the quarter.
After you have defined a variable with hierarchical dimensions, you can add variable data to the lowest level of the hierarchy, and then calculate or aggregate the values for the higher levels of the hierarchy. Conversely, you can distribute or allocate data from higher levels to lower levels of the hierarchy.
How variable and relation data is actually structured and stored is dependent on what type of object you use to dimension the variable or relation and the order in which those objects appear in the definition of the variable or relation Variables can be dimensioned by simple dimensions, concat dimensions, composites, partition templates, and alias dimensions. The object that by which you choose to dimension a variable determines how the data of the variable is stored.
Simple Dimensions
The members of a simple dimension are data values that all have the same data type. When a variable is dimensioned by a simple dimension, there is one cell in the variable for every member of the dimension. When there is a dimension member for which the variable has no data, Oracle OLAP stores NA values in the variable for that empty value. (Note that if storing these NA values would result in a full page of NA values that Oracle OLAP does not actually store the values.) Oracle OLAP does not store NA values when there is a range.)
Concat Dimensions
You define concat dimensions over previously-defined simple dimensions or conjoint dimensions. Consequently, the base dimensions of a concat dimension can be of different data types. You can represent a hierarchy with a concat dimension that is has two or more simple flat dimensions among its base dimensions. You can use concat dimensions to easily map dimensions in an analytic workspace to columns in relational tables and thereby promote more efficient loading of data from the relational structures into the analytic workspace structures.
Composites
You define composites over previously-defined dimensions or other composites. Conceptually, you can think of a composite consisting of two structures:
The composite object itself. The composite contains the dimension-value combinations (that is, a composite tuples) that Oracle OLAP uses to determine the structure of any variables dimensioned by the composite.
An index between the composite values and its base dimension values.
For a variable that is dimensioned by composite, Oracle OLAP does not create a cell for every value in the base dimensions as it would if the variable was dimensioned by a simple dimension. Instead, it creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; Data for the variable is stored in order, cell by cell, for each tuple in the composite. From the perspective of data storage, each combination of base dimension values in a composite is treated like the value of a regular dimension. Consequently, when you define a variable with one regular dimension and one composite, the data for the variable is stored as though it was a two-dimensional variable. Using composites to reduce the number of elements created for a variable results in more efficient data storage.
Partition Templates
You define a partition template over previously-defined dimensions or composites. A partition template is a specification for the partitions of a partitioned variable. A partitioned variable is stored as multiple rows in the relational table of LOBs that is the analytic workspace—each partition is a row in the table.
Alias Dimensions
An alias dimension is an alias for a simple dimension. An alias dimension has the same type and values as its base dimension. Typically, you define an alias dimension when you want to dimension a variable by the same dimension twice.
A relation is an object that establishes a correspondence between the values of a given dimension and the values of that same dimension or other dimensions in the analytic workspace. Relations are dimensioned arrays. Each cell in a relation holds the index of the value of a dimension. You can define relations between two or more dimensions, multiple relations between a set of dimensions, or a dimension with itself (a self-relation).
Most frequently, a relation is a self-relation for a hierarchical dimension. By creating a relation between values in a dimension that participate in a one-to-many (parent-to-child) relationship, you can organize your data by the child values and view aggregates of data by the parent values. For example, you can create a geog.parent relation for a geography dimension to define the relationships between the city and state values in geography. In this way you can organize the data by city and view the aggregates of data by state.
The OLAP DML provides the following special data objects that you use not when you are defining your variables, but instead, when you are querying them,
Valueset Objects
A valueset is a list of dimension values for one or more previously-defined dimensions. You use a valueset to save dimension status lists across sessions.
Surrogates
A dimension surrogate is an alternative set of values for a previously-defined dimension. You cannot dimension a variable by a surrogate, but you can use a surrogate rather than a dimension in a model, in a LIMIT command, in a qualified data reference, or in data loading with statements such as FILEREAD, FILEVIEW, SQL FETCH, and SQL IMPORT.
Typically, variables are dimensioned by hierarchical objects. For example, you might have a sales variable that is dimensioned by geog, time, and product. The geog dimension might have two hierarchies (one for political divisions and another for sales regions) and each of these hierarchies could have several levels with the top level of the political geography hierarchy being All Country and the top level of the sales geography hierarchy being All Regions. Example 1-1, "Defining and Populating a Hierarchical Dimension Named geog" illustrates defining and populating this type of hierarchical geography dimension.
Example 1-1 Defining and Populating a Hierarchical Dimension Named geog
DEFINE geog DIMENSION TEXT LD A dimension with two hierarchies for geography "Populate the dimension with City, State, Region, and Country values MAINTAIN geog ADD 'Boston' 'Springfield' 'Hartford' 'Mansfield' 'Montreal' 'Walla Walla' 'Portland' 'Oakland' 'San Diego' 'MA' 'CT' 'WA' 'CA' 'Quebec' 'East' 'West' 'All Regions' 'USA' 'Canada' 'All Country' "Display the values in geog REPORT geog GEOG -------------- Boston Springfield Hartford Mansfield Montreal Walla Walla Portland Oakland San Diego MA CT WA CA Quebec East West All Regions USA Canada All Country
Typically, after you define a hierarchical dimension, you define the following objects for that dimension:
hierlist dimension that lists the names of the hierarchies for the dimension. See "Hierlist Dimension" for more information and an example.
parentrel relation that defines the hierarchies. A dimension is only a hierarchical dimension when it has a parentrel defined for it. See "Parentrel Relation" for more information and an example.
levellist relation that lists the names of all of the levels of all of the hierarchies. See "Levellist Dimension" for more information and an example.
hierlevels valueset that is the values of the levels of each hierarchy. See "Hierlevels Valueset" for more information and an example.
inhier valueset or variable that identifies the values of each hierarchy. See "Inhier Valueset or Variable" for more information and examples.
levelrel relation that relates each value of the hierarchical dimension to its level in the hierarchy. See "Levelrel Relation" for more information and an example.
familyrel relation that is each hierarchical dimension value and its related values. See "Familyrel Relation" for more information and an example.
gidrel relation that is the grouping ids of each value within each hierarchy. See "Gidrel Relation" for more information and an example.
A hierlist dimension is a TEXT dimension in the analytic workspace that has as values the names of the hierarchies of a hierarchical dimension. For example, if the company has a different calendar and fiscal year, the time dimension for that company would have two hierarchies: one for calendar and another for year. The hierlist dimension that supported that time hierarchy would have two values: Calendar and Fiscal.
For consistency's sake, analytic workspaces include a hierlist dimension for every hierarchical dimension -- even when that hierarchical dimension has only one hierarchy.
Example 1-2, "Defining and Populating a hierlist Dimension Named geog_hierlist" illustrates defining and populating this type of dimension.
Example 1-2 Defining and Populating a hierlist Dimension Named geog_hierlist
DEFINE geog_hierlist DIMENSION TEXT LD List of Hierarchies for geog dimension "Populate the geog_hierlist dimension MAINTAIN geog_hierlist ADD 'Political_Geog' 'Sales_Geog' "Display the values of the geog_hierlist dimension REPORT geog_hierlist GEOG_HIERLIST -------------- Political_Geog Sales_Geog
A parentrel relation is a relation between the hierarchical dimension and itself (a self-relation) and the hierlist dimension. It identifies the parent of each dimension member within a hierarchy.
Example 1-3, "Defining and Populating a parentrel Relation named geog_parentrel" illustrates defining and populating this type of relation.
Example 1-3 Defining and Populating a parentrel Relation named geog_parentrel
"Define the relation
DEFINE geog_parentrel RELATION geog <geog geog_hierlist>
LD Self-relation for geog showing parents of each value
"Populate each cell in the relation "with the parent of the geog value
"This example using assignment statement with QDRs to do that
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Boston') = 'MA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Hartford') = 'CT'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Springfield') = 'MA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Mansfield') = 'CT'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Montreal') = 'Quebec'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Walla Walla') = 'WA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Portland') = 'WA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Oakland') = 'CA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'San Diego') = 'CA'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'CT') = 'East'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'MA') = 'East'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'WA') = 'West'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'CA') = 'West'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'Quebec') = 'East'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'East') = 'All Regions'
geog_parentrel (geog_hierlist 'Sales_Geog' geog 'West') = 'All Regions'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Boston') = 'MA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Hartford') = 'CT'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Springfield') = 'MA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Mansfield') = 'CT'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Montreal') = 'Quebec'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Walla Walla') = 'WA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Portland') = 'WA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Oakland') = 'CA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'San Diego') = 'CA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'CT') = 'USA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'MA') = 'USA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'WA') = 'USA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'CA') = 'USA'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Quebec') = 'Canada'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'USA') = 'All Country'
geog_parentrel (geog_hierlist 'Political_Geog' geog 'Canada') = 'All Country'
"Display the values of geog_parentrel
REPORT DOWN geog W 20 geog_parentrel
-------------GEOG_PARENTREL--------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston MA MA
Springfield MA MA
Hartford CT CT
Mansfield CT CT
Montreal Quebec Quebec
Walla Walla WA WA
Portland WA WA
Oakland CA CA
San Diego CA CA
MA USA East
CT USA East
WA USA West
CA USA West
Quebec Canada East
East NA All Regions
West NA All Regions
All Regions NA NA
USA All Country NA
Canada All Country NA
All Country NA NA
A levellist dimension is a TEXT dimension that has as values the names all of the levels of the hierarchies of a hierarchical dimension.
Example 1-4, "Defining and Populating a levellist Dimension Named geog_levellist" illustrates defining and populating this type of dimension.
Example 1-4 Defining and Populating a levellist Dimension Named geog_levellist
DEFINE geog_levellist DIMENSION TEXT LD List of levels used by hierarchies of the geog dimension "Populate the geog_levellist dimension with the names of the levels of both the "Political_Geog and Sales_Geog hierarchies MAINTAIN geog_levellist ADD 'All Country' 'Country' 'All Regions' 'Region' MAINTAIN geog_levellist ADD 'State-Prov' 'City' "Display the values of the geog_levellist dimension REPORT geog_levellist GEOG_LEVELLIST -------------- All Country Country All Regions Region State-Prov City
A hierlevels valueset is those values of the hierlevels dimension (typically ordered from bottom to top) that are included in each hierarchy of the hierarchical dimension.
Example 1-5, "Defining and Populating a hierlevels Valueset named geog_hierlevels" illustrates defining and populating this type of valueset.
Example 1-5 Defining and Populating a hierlevels Valueset named geog_hierlevels
DEFINE geog_hierlevels VALUESET geog_levellist <geog_hierlist>
"Using LIMIT populate the valueset with the appropriate values for each hierarchy
LIMIT geog_hierlevels TO ALL
LIMIT geog_hierlevels (geog_hierlist 'Political_Geog') TO 'City' 'State-Prov' 'Country' 'All Country'
LIMIT geog_hierlevels (geog_hierlist 'Sales_Geog') TO 'City' 'State-Prov' 'Region' 'All Regions'
"Display the values in the valueset
REPORT W 22 geog_hierlevels
GEOG_HIERLIST GEOG_HIERLEVELS
-------------- ----------------------
Political_Geog City
State-Prov
Country
All Country
Sales_Geog City
State-Prov
Region
All Regions
An inhier valueset is those values of the inhier dimension that are in each hierarchy. Example 1-6, "Defining and Populating an inhier Valueset Named geog_inhier" illustrates defining and populating this type of valueset.
An inhier variable is a BOOLEAN variable that is dimensioned by the hierarchical dimension and the hierlist dimension. For each hierarchy, it has a TRUE value for each dimension value that is in that hierarchy. Example 1-7, "Defining and Populating an inhier Variable Named geog_inhiervar" illustrates defining and populating this type of valueset
Example 1-6 Defining and Populating an inhier Valueset Named geog_inhier
"Define the valueset
DEFINE geog_inhier VALUESET geog <geog_hierlist>
"Using LIMIT commands, populate the valueset
LIMIT geog_inhier (geog_hierlist 'Political_Geog') REMOVE 'East' 'West' 'All Regions'
LIMIT geog_inhier (geog_hierlist 'Sales_Geog') REMOVE 'Canada' 'USA' 'All Country'
"Display the values in the valueset
REPORT W 20 geog_inhier
GEOG_HIERLIST GEOG_INHIER
-------------- --------------------
Political_Geog Boston
Springfield
Hartford
Mansfield
Montreal
Walla Walla
Portland
Oakland
San Diego
MA
CT
WA
CA
Quebec
USA
Canada
All Country
Sales_Geog Boston
Springfield
Hartford
Mansfield
Montreal
Walla Walla
Portland
Oakland
San Diego
MA
CT
WA
CA
Quebec
East
West
All Regions
Example 1-7 Defining and Populating an inhier Variable Named geog_inhiervar
DEFINE geog_inhiervar VARIABLE BOOLEAN <geog geog_hierlist>
"Using LIMIT commands and assignment statements, populate
" the variable
LIMIT geog_hierlist TO ALL
LIMIT geog_hierlist TO 'Political_Geog'
LIMIT geog TO 'East' 'West' 'All Regions'
geog_inhiervar = FALSE
LIMIT geog COMPLEMENT
geog_inhiervar = TRUE
LIMIT geog_hierlist TO ALL
LIMIT geog_hierlist TO 'Sales_Geog'
LIMIT geog TO ALL
LIMIT geog TO 'Canada' 'USA' 'All Country'
geog_inhiervar = FALSE
LIMIT geog COMPLEMENT
geog_inhiervar = TRUE
LIMIT geog TO ALL
LIMIT geog_hierlist TO ALL
"Display the values of the variable
REPORT DOWN geog geog_inhiervar
---GEOG_INHIERVAR----
----GEOG_HIERLIST----
Political_
GEOG Geog Sales_Geog
-------------- ---------- ----------
Boston yes yes
Springfield yes yes
Hartford yes yes
Mansfield yes yes
Montreal yes yes
Walla Walla yes yes
Portland yes yes
Oakland yes yes
San Diego yes yes
MA yes yes
CT yes yes
WA yes yes
CA yes yes
Quebec yes yes
East no yes
West no yes
All Regions no yes
USA yes no
Canada yes no
All Country yes no
A levelrel relation is a relation between the levellist and hierlist dimensions that records the level for each member of the hierarchical dimension
Example 1-8, "Defining and Populating a levelrel Relation named geog_levelrel" illustrates defining and populating this type of relation.
Example 1-8 Defining and Populating a levelrel Relation named geog_levelrel
"Define the relation
DEFINE geog_levelrel RELATION geog_levellist <geog geog_hierlist>
LD Level of each dimension member for geog
"Populate the relation
"This example uses assignment statements with QDRs to populate
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Boston') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Hartford') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Springfield') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Mansfield') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Montreal') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Walla Walla') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Portland') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Oakland') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'San Diego') = 'City'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'CT') = 'State-Prov'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'MA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'WA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'CA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'Quebec') = 'State-Prov'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'East') = 'Region'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'West') = 'Region'
geog_levelrel (geog_hierlist 'Sales_Geog' geog 'All Regions') = 'All Regions'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Boston') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Hartford') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Springfield') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Mansfield') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Montreal') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Walla Walla') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Portland') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Oakland') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'San Diego') = 'City'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'CT') = 'State-Prov'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'MA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'WA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'CA') = 'State-Prov'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Quebec') = 'State-Prov'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'USA') = 'Country'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'Canada') = 'Country'
geog_levelrel (geog_hierlist 'Political_Geog' geog 'All Country') = 'All Country'
"Display the values
REPORT DOWN geog W 20 geog_levelrel
--------------GEOG_LEVELREL--------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston City City
Springfield City City
Hartford City City
Mansfield City City
Montreal City City
Walla Walla City City
Portland City City
Oakland City City
San Diego City City
MA State-Prov State-Prov
CT State-Prov State-Prov
WA State-Prov State-Prov
CA State-Prov State-Prov
Quebec State-Prov State-Prov
East NA Region
West NA Region
All Regions NA All Regions
USA Country NA
Canada Country NA
All Country All Country NA
The familyrel relation is a relation between the hierarchical dimension and the levellist and hierlist dimensions that provides the full parentage of each dimension member in the hierarchy.
Example 1-9, "Defining and Populating a familyrel Relation named geog_familyrel" illustrates defining and populating this type of relation.
Example 1-9 Defining and Populating a familyrel Relation named geog_familyrel
"Define the relation
DEFINE geog_familyrel RELATION geog <geog geog_levellist geog_hierlist>
LD FEATURES Family/AncesK try structure for the geog dimension
"Populate the relation using the HIERHEIGHT command
HIERHEIGHT geog_parentrel INTO geog_familyrel USING geog_levelrel
"Display the values of the familyrel relation
"First the values for the Political_Geog hierarchy are displayed
"Then the values for the Sales_Geog hierarchy
REPORT DOWN geog W 12 geog_familyrel
GEOG_HIERLIST: Political_Geog
-------------------------------GEOG_FAMILYREL--------------------------------
-------------------------------GEOG_LEVELLIST--------------------------------
GEOG All Country Country All Regions Region State-Prov City
-------------- ------------ ------------ ------------ ------------ ------------ ------------
Boston All Country USA NA NA MA Boston
Springfield All Country USA NA NA MA Springfield
Hartford All Country USA NA NA CT Hartford
Mansfield All Country USA NA NA CT Mansfield
Montreal All Country Canada NA NA Quebec Montreal
Walla Walla All Country USA NA NA WA Walla Walla
Portland All Country USA NA NA WA Portland
Oakland All Country USA NA NA CA Oakland
San Diego All Country USA NA NA CA San Diego
MA All Country USA NA NA MA NA
CT All Country USA NA NA CT NA
WA All Country USA NA NA WA NA
CA All Country USA NA NA CA NA
Quebec All Canada NA NA Quebec NA
Countries
East NA NA NA NA NA NA
West NA NA NA NA NA NA
All Regions NA NA NA NA NA NA
USA All Country USA NA NA NA NA
Canada All Country Canada NA NA NA NA
All Country All Country NA NA NA NA NA
GEOG_HIERLIST: Sales_Geog
-------------------------------GEOG_FAMILYREL--------------------------------
-------------------------------GEOG_LEVELLIST--------------------------------
GEOG All Country Country All Regions Region State-Prov City
-------------- ------------ ------------ ------------ ------------ ------------ ------------
Boston NA NA All Regions East MA Boston
Springfield NA NA All Regions East MA Springfield
Hartford NA NA All Regions East CT Hartford
Mansfield NA NA All Regions East CT Mansfield
Montreal NA NA All Regions East Quebec Montreal
Walla Walla NA NA All Regions West WA Walla Walla
Portland NA NA All Regions West WA Portland
Oakland NA NA All Regions West CA Oakland
San Diego NA NA All Regions West CA San Diego
MA NA NA All Regions East MA NA
CT NA NA All Regions East CT NA
WA NA NA All Regions West WA NA
CA NA NA All Regions West CA NA
Quebec NA NA All Regions East Quebec NA
East NA NA All Regions East NA NA
West NA NA All Regions West NA NA
All Regions NA NA All Regions NA NA NA
USA NA NA NA NA NA NA
Canada NA NA NA NA NA NA
All Country NA NA NA NA NA NA
A gidrel relation is a relation between a NUMBER dimension, the hierarchical dimension, and the hierlist dimension that contains the grouping ID of each dimension member in each hierarchy of the hierarchical dimension. It also has a $GID_DEPTH property that identifies the depth within a hierarchy of each dimension member.
Example 1-10, "Defining and Populating a gidrel Relation named geog_gidrel" illustrates defining and populating this type of relation.
Example 1-10 Defining and Populating a gidrel Relation named geog_gidrel
"Create a dimension that has values that are numbers
DEFINE gid_dimension DIMENSION NUMBER (38,0)"Add values to that dimension
"This example uses MAINTAIN ADD to add a few numbers
MAINTAIN gid_dimension ADD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
"Define the gidrel relation
DEFINE geog_gidrel RELATION gid_dimension <geog geog_hierlist>
"Display the complete definition of the geog_gidrel relation
"Note that it has no properties
DEFINE GEOG_GIDREL RELATION GID_DIMENSION <GEOG GEOG_HIERLIST>
"Populate the gidrel relation using the GROUPINGID command
GROUPINGID geog_parentrel INTO geog_gidrel USING geog_levelrel INHIERARCHY geog_inhier
"Display the values of the geog_gidrel relation
REPORT down geog w 20 geog_gidrel
---------------GEOG_GIDREL---------------
--------------GEOG_HIERLIST--------------
GEOG Political_Geog Sales_Geog
-------------- -------------------- --------------------
Boston 0 0
Springfield 0 0
Hartford 0 0
Mansfield 0 0
Montreal 0 0
Walla Walla 0 0
Portland 0 0
Oakland 0 0
San Diego 0 0
MA 1 1
CT 1 1
WA 1 1
CA 1 1
Quebec 1 1
East NA 3
West NA 3
All Regions NA 7
USA 3 NA
Canada 3 NA
All Country 7 NA
"Display the complete definition of the geog_gidrel relation
"Note that it now has a $GID_DEPTH property
DEFINE GEOG_GIDREL RELATION GID_DIMENSION <GEOG GEOG_HIERLIST>
PROPERTY '$GID_DEPTH' 4
The OLAP DML is a multidimensional language. Consequently, operations in the OLAP DML apply all at once to an entire set of values. Again, conceptually, you can think of these operations as applying to the values in all of the cells in a variable; or, physically, you can think of these operations as applying to all of the elements in the array that is the variable. Consequently, if you use the OLAP DML assignment statement (that is, SET or =), then you do not need to code explicit loops to assign values to all of the elements in a variable. Instead, when you issue a statement against an object that has one or more dimensions, the statement loops over the values in status for each dimension of the object and performs the requested operation.
Assume, for example, that there is a dimension named prodid that has three values, Prod01, Prod02, and Prod03, and you have a variable named quantity that is dimensioned by prodid. As the following code snippet illustrates, if Prod01, Prod02, and Prod03 are all in status, when you assign the value 3 to quantity, Oracle OLAP assigns the value 3 to all of the elements in quantity.
quantity = 3 REPORT quantity PRODID QUANTITY -------------- ---------- PROD01 3.00 PROD02 3.00 PROD03 3.00
Other OLAP DML statements (for example, REPORT, ROW, and FOR) also loop through all of the in status elements of a dimensioned object when they execute.
By default, statements loop through the values of a dimensioned object using the order in which the dimensions of the object are listed in the definition of the object. Also, when a variable is dimensioned by a composite, most looping statements loop through the variable as though it was not dimensioned by a composite, but was, instead, dimensioned by the base dimensions of the composite.
The OLAP DML provides ways for you to change the default looping behavior or to explicitly request looping:
ACROSS phrase—Some looping command (such as assignment statements that you use to assign values) have an ACROSS phrase that you can use to specify non-default looping behavior. For detailed documentation of the ACROSS phrase, see the SET (=) command.
ACROSS command—When an OLAP DML statement is not a looping statement or does not include an ACROSS phrase, you can request looping behavior by coding the DML statement as an argument of the ACROSS command.
Oracle OLAP keeps track of the values of a dimension that are accessible to the user using lists, called "status lists", for each defined dimension.
Oracle OLAP keeps track of the values of a dimension are accessible to the user using lists, called "status lists" for each defined dimension. There are two kinds of status lists: default status lists and current status lists. The values in the current status lists of the dimensions in an analytic workspace determine the set of data that is available to the OLAP DML at any given moment in time.
The default status list of a dimension is the list of all of the values of the dimension that have read permission, in the order in which the values are stored, when you first attach an analytic workspace. You can change the default status list of a dimension in the following ways:
You can add, delete, move, merge, and rename values in a dimension by using the MAINTAIN command or adding dimension values in other ways (for example, using a SQL FETCH statement).
You can change the read permission of values that are associated with a dimension by using a PERMIT or PERMITRESET statement.
The current status list of a dimension is an ordered list of currently accessible values for the dimension. Values that are in the current status list of a dimension are said to be "in status." When you first attach an analytic workspace, the default and current status lists of each dimension are the same.
The current status list of a dimension determines the accessibility of the data in the analytic workspace:
For dimensions, only those dimension values that are in the current status list are visible and accessible to OLAP DML expressions.
For dimensioned objects like variables, only those data values that are indexed by dimension values in the current status list are visible and accessible to OLAP DML expressions. As a loop is performed through a dimensioned object, the order of the dimension values in the current status list is used to determine the order in which the values of the object are accessed.
Note that a dimension and any surrogate for that dimension share the same status. Setting the status of a dimension surrogate sets the status of its dimension and setting the status of a dimension sets the status of any dimension surrogates for it. Throughout this documentation, references to dimensions apply equally to dimension surrogates, except where noted. Additionally, composites are not dimensions, and therefore they do not have any independent status. The values of a composite that are "in status" are determined by the status of the base dimensions of the composite.
|
Note: Whether or not a dimension value is in status merely restricts the OLAP DML's view of the value during a given session; it does not permanently affect the values that are stored in the analytic workspace. |
Since the current status list of a dimension determines the accessibility of the data in the analytic workspace, the way to work with a subset of analytic workspace data is to change the current status lists of one or more dimensions.
You change the change the values and the order of the values in the current status list of a dimension using the LIMIT command. The LIMIT command is a very complex OLAP DML command that lets you specify what values you want in the current status list by specifying the values explicitly or implicitly using relations. At it simplest level, Example 10-20, "Using LIMIT to Partially Populate Variables" illustrates how you can use the LIMIT command to change the current status list of a dimension so you can work with a subset of data.
There are several different ways that you can save the current status of a dimension. The scope of each way is different:
Any session—To save the current status for use in any session, create a named valueset with that status. Use a DEFINE VALUESET command to define the valueset. Use a LIMIT command to assign the values to the valueset.
Current session—To save, access, or update the current status for use in the current session, then use a named context. Use the CONTEXT command to define the context.
Current program—To save the current status for use in the current program, then use the PUSHLEVEL and PUSH commands. You can restore the current status values using the POPLEVEL and POP commands.
Sometimes you want to have an individual OLAP DML statement or expression work against a subset of data without actually changing the current status list of a dimension. To support this need, some OLAP DML statements allow you to specify the name of a previously-defined valueset object instead of the name of a dimension. Additionally, on-the-fly, you can specify a data subset without changing the current status list of dimensions using one of the following:
The CHGDIMS function which, during the evaluation of expression, changes the dimensionality of an expression or changes the dimension status.
The LIMIT function which, during the evaluation of expression, returns the dimension or dimension surrogate values that result from a specified LIMIT command or a specified dimension status stack.
Use a qualified data reference (QDR) which is a way of limiting one or more dimensions of an expression to a single value when you want to specify a single value of a data object without changing the current status.
Frequently you first populate the base values of your variables from relational tables or from flat files. You then calculate other values from these base values using OLAP DML calculation objects. For example, you might define aggregation objects to aggregate the values that are higher up the hierarchy.
You can also assign values to variables, relations, and dimension surrogates using assignment statements (see SET and SET1) and add values to dimensions using MAINTAIN statements.
The INTERPCLOB function executes one or more OLAP DML commands and returns the session log in which the commands are executed. It is typically used in applications when the 4K limit on input for the INTERP function may be too restrictive.
This function does not return the output of the OLAP DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
You can use the INTERPCLOB function as an argument to the PRINTLOG procedure in this package to view the session log. See the example.
Syntax
INTERPCLOB (
olap-commands IN CLOB)
RETURN CLOB;
Parameters
Table B-25 INTERPCLOB Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
Returns
The log for the Oracle OLAP session in which the OLAP DML commands were executed.
Example
The following sample SQL*Plus session creates an analytic workspace named ELECTRONICS, imports its contents from an EIF file stored in the dbs directory object, and displays the contents of the analytic workspace.
SET serverout ON size 1000000 EXECUTE dbms_aw.printlog(dbms_aw.interpclob('AW ATTACH global; DESCRIBE')); DEFINE GEN_OBJ_ROLES DIMENSION TEXT DEFINE GEN_AW_OBJS VARIABLE TEXT <GEN_OBJ_ROLES> DEFINE ALL_DIMENSIONS DIMENSION TEXT DEFINE DIM_OBJ_LIST DIMENSION TEXT DEFINE DIM_AW_OBJS VARIABLE TEXT <ALL_DIMENSIONS DIM_OBJ_LIST> . . .
The EDIT command displays an OLAP Worksheet Edit window. The command is available only when you are using OLAP Worksheet to access Oracle OLAP.
For information about using an OLAP Worksheet Edit window, see the OLAP Worksheet Help.
Syntax
EDIT {PROGRAM|MODEL|AGGMAP|FORMULA} object-name
Parameters
Indicates whether the object to be edited is a program, a model, an aggmap, or a formula.
A text expression that specifies the name of an existing program, model, aggmap, or formula. Before editing one of these objects, use a DEFINE statement to create it in an analytic workspace.
Usage Notes
Editing a Newly Defined Aggmap to Code an Allocation Specification
When an aggmap is first defined it does not have any contents and its type is NA. When you use the EDIT command for an aggmap whose type has not yet been specified, OLAP Worksheet automatically makes the aggmap an aggregation specification by inserting an AGGMAP statement into the contents of the aggmap.
Consequently, when you plan to use an aggmap as an allocation specification, use the following statements to identify it as an allocation specification before the first time you open an OLAP Worksheet Edit window for it.
CONSIDER aggmap-name
ALLOCMAP 'END'
Examples
OLAP_EXPRESSION is a SQL function that dynamically executes an OLAP DML boolean expression within the context of an OLAP_TABLE function. In addition to returning a custom measure, you can use this function in the WHERE and ORDER BY clauses to modify the result set of the query of the analytic workspace.
OLAP_EXPRESSION_TEXT returns character data. To return text, boolean, or date data, use OLAP_EXPRESSION_TEXT, OLAP_EXPRESSION_BOOL, or OLAP_EXPRESSION_DATE SQL functions.
Before you use this function, you must specify a ROW2CELL clause in the limit map used by OLAP_TABLE. ROW2CELL identifies a RAW column that OLAP_TABLE populates with information used by the OLAP single-row functions.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL Worksheet. |
Returns
An evaluation of numeric_expression for each row of the table object returned by the OLAP_TABLE function.
OLAP_EXPRESSION returns numeric data. To return text, boolean, or date data, use the OLAP_EXPRESSION_TEXT, OLAP_EXPRESSION_BOOL, or OLAP_EXPRESSION_DATE functions.
Syntax
OLAP_EXPRESSION(
r2c IN RAW(32),
numeric_expression IN VARCHAR2)
RETURN NUMBER;
Parameters
The name of a column specified by a ROW2CELL clause in the limit map. See "ROW2CELL Clause" of OLAP_TABLE
An OLAP DML expression that returns a numeric result.
Examples
The following script was used to create the view unit_cost_price_view, which is used in Example A-12, "OLAP_EXPRESSION: Time Series Function in a WHERE Clause" and Example A-13, "OLAP_EXPRESSION: Numeric Calculation in an ORDER BY CLause" to illustrate the use of OLAP_EXPRESSION. For information about creating views of analytic workspaces, see "Creating Relational Views Using OLAP_TABLE".
Sample View: MYAW.UNIT_COST_PRICE_VIEW
-- Create the logical row
CREATE TYPE unit_cost_price_row AS OBJECT (
aw_unit_cost NUMBER,
aw_unit_price NUMBER,
aw_product VARCHAR2(50),
aw_time VARCHAR2(20),
r2c RAW(32));
/
-- Create the logical table
CREATE TYPE unit_cost_price_table AS TABLE OF unit_cost_price_row;
/
-- Create the view
CREATE OR REPLACE VIEW unit_cost_price_view AS
SELECT aw_unit_cost, aw_unit_price, aw_product, aw_time, r2c
FROM TABLE(OLAP_TABLE(
'myaw DURATION SESSION',
'unit_cost_price_table',
'',
'MEASURE aw_unit_cost FROM price_cube_unit_cost
MEASURE aw_unit_price FROM price_cube_unit_price
DIMENSION product WITH
HIERARCHY product_parentrel
INHIERARCHY product_inhier
ATTRIBUTE aw_product FROM product_short_description
DIMENSION time WITH
HIERARCHY time_parentrel
INHIERARCHY time_inhier
ATTRIBUTE aw_time FROM time_short_description
ROW2CELL r2c'));
/
The following query shows some aggregate data in the view.
SQL>SELECT * FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('2000', '2001', '2002', '2003')
ORDER BY aw_time;
AW_UNIT_COST AW_UNIT_PRICE AW_PRODUCT AW_TIME R2C
------------ ------------- ---------- ------- -----
211680.12 224713.71 Hardware 2000 00...
195591.60 207513.16 Hardware 2001 00...
184413.05 194773.78 Hardware 2002 00...
73457.31 77275.06 Hardware 2003 00...
Example A-12 OLAP_EXPRESSION: Time Series Function in a WHERE Clause
This example uses the view described in "Sample View: MYAW.UNIT_COST_PRICE_VIEW".
The following SELECT statement calculates an expression with an alias of PERIODAGO, and limits the result set to calculated values greater than 50,000. The calculation uses the LAG function to return the value of the previous time period.
SQL>SELECT aw_time time, aw_unit_cost unit_cost,
OLAP_EXPRESSION(r2c,
'LAG(price_cube_unit_cost, 1, time,
LEVELREL time_levelrel)') periodago
FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND OLAP_EXPRESSION(r2c,
'LAG(price_cube_unit_cost, 1, time,
LEVELREL time_levelrel)') > 50000;
This SELECT statement produces these results.
TIME UNIT_COST PERIODAGO -------------------- ---------- ---------- 2003 73457.31 184413.05 2004 73457.31 1999 231095.4 162526.92 2000 211680.12 231095.4 2001 195591.6 211680.12 2002 184413.05 195591.6 Q2-99 57587.34 57856.76 Q3-99 59464.25 57587.34 Q4-99 56187.05 59464.25 Q1-00 53982.32 56187.05 Q2-00 53629.74 53982.32 Q3-00 53010.65 53629.74 Q4-00 51057.41 53010.65 Q1-01 49691.22 51057.41
Example A-13 OLAP_EXPRESSION: Numeric Calculation in an ORDER BY CLause
This example uses the view described in "Sample View: MYAW.UNIT_COST_PRICE_VIEW".
This example subtracts costs from price, and gives this expression an alias of MARKUP. The rows are ordered by markup from highest to lowest.
SQL>SELECT aw_time time, aw_unit_cost unit_cost, aw_unit_price unit_price,
OLAP_EXPRESSION(r2c,
'PRICE_CUBE_UNIT_PRICE - PRICE_CUBE_UNIT_COST') markup
FROM unit_cost_price_view
WHERE aw_product = 'Hardware'
AND aw_time in ('1998', '1999', '2000', '2001')
ORDER BY OLAP_EXPRESSION(r2c,
'PRICE_CUBE_UNIT_PRICE - PRICE_CUBE_UNIT_COST') DESC;
This SELECT statement produces these results.
TIME UNIT_COST UNIT_PRICE MARKUP -------------------- ---------- ---------- --------- 1999 231095.40 245412.91 14317.51 2000 211680.12 224713.71 13033.59 2001 195591.60 207513.16 11921.56 1998 162526.92 173094.41 10567.49
The STARTOF function returns the starting date of a time period in a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR.
|
Important: You can only use this function with dimensions of type DAY, WEEK, MONTH, QUARTER, or YEAR.You cannot use this function for time dimensions that are implemented as hierarchical dimensions of type TEXT. |
Return Value
DATE or text
Syntax
STARTOF(dwmqy-dimension)
Parameters
A dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. When you have explicitly defined your own relation between dimensions of this type, you can use the name of this time relation here.
Usage Notes
How STARTOF Works
STARTOF returns the first date of the time period that is first in the current status list of the dimension.
Phased or Multiple Periods
STARTOF is particularly useful when the dimension has a phase that differs from the default or when the time periods are formed from multiple weeks or years. For example, when the dimension has four-week time periods, the STARTOF function identifies the starting date of a particular four-week period.
Format of the Result Returned by STARTOF
When you display the result returned by STARTOF, the date is formatted according to the date template in the DATEFORMAT option. When the day of the week or the name of the month is used in the date template, the day names specified in the DAYNAMES option and the month names specified in the MONTHNAMES option are used. You can use the result returned by STARTOF anywhere that a DATE value is expected.
Retrieving the Last Valid Date of a Time Period
The ENDOF function, which returns the last date of a time period.
Examples
Example 8-105 Finding the Fiscal Year Starting Date
The following statements define a year dimension (called FYEAR, for a fiscal year that ends in June), specify how the year is formatted, add dimension values for fiscal years 1996 through 1998, and produce a report of the starting date of each fiscal year.
DEFINE fyear DIMENSION YEAR ENDING June VNF 'FY<ff>' MAINTAIN fyear ADD '30JUN96' '30JUN98' REPORT W 14 STARTOF(fyear)
These statements produce the following output.
FYEAR STARTOF(FYEAR) --------- -------------- FY96 01JUL95 FY97 01JUL96 FY98 01JUL97
The following table describes the subprograms provided in DBMS_AW.
Table B-1 DBMS_AW Subprograms
| Subprogram | Description |
|---|---|
|
ADD_DIMENSION_SOURCE Procedure |
Populates a table type named |
|
|
Suggests how to preaggregate a cube, based on a specified percentage of the cube's data. |
|
ADVISE_DIMENSIONALITY Function |
Returns a recommended composite definition for the cube and a recommended dimension order. |
|
ADVISE_DIMENSIONALITY Procedure |
Generates the OLAP DML commands for defining the recommended composite and measures in a cube. |
|
ADVISE_PARTITIONING_DIMENSION Function |
Identifies the dimension that the Sparsity Advisor partitioned over. |
|
ADVISE_PARTITIONING_LEVEL Function |
Returns the level used by the Sparsity Advisor for partitioning over a dimension. |
|
|
Suggests how to preaggregate a dimension, based on a specified percentage of the dimension's members. |
|
|
Analyzes a fact table for sparsity and populates a table with the results of its analysis. |
|
|
Attaches an analytic workspace to a session. |
|
|
Creates a new analytic workspace and populates it with the object definitions and data from another analytic workspace. |
|
|
Creates a new, empty analytic workspace. |
|
|
Deletes an analytic workspace |
|
|
Detaches an analytic workspace from a session. |
|
|
Changes the name of an analytic workspace. |
|
|
Returns the name of the tablespace in which a particular analytic workspace is stored. |
|
|
Saves changes made to an analytic workspace. |
|
|
Converts an analytic workspace from 9i to 10g storage format. |
|
|
Returns the result of a numeric expression in an analytic workspace. |
|
|
Returns the result of a text expression in an analytic workspace. |
|
|
Executes one or more OLAP DML commands. Input and output is limited to 4K. Typically used in an interactive session using an analytic workspace. |
|
|
Returns the session log from the last execution of the |
|
|
Executes the OLAP DML commands specified in a file. |
|
|
Executes one or more OLAP DML commands. Input is limited to 4K and output to 4G. Typically used in applications when the 4K limit on output for the |
|
|
Executes one or more OLAP DML commands. Input and output are limited to 4G. Typically used in applications when the 4K input limit of the |
|
|
Executes one or more OLAP DML commands and suppresses the output. Input is limited to 4K and output to 4G. |
|
|
Returns a boolean indicating whether or not the OLAP option is installed in the database. |
|
|
Returns a boolean indicating whether or not the OLAP option has been initialized in the current session. |
|
|
Prints a session log returned by the |
|
|
Executes one or more OLAP DML commands. |
|
|
Shuts down the current OLAP session. |
|
SPARSITY_ADVICE_TABLE Procedure |
Creates a table which the |
|
|
Starts an OLAP session without attaching a user-defined analytic workspace. |
The FILECOPY command copies the contents of one file (the source file) to another file (the target file). When the target file already exists, the file is overwritten with the copy.
Syntax
FILECOPY source-file-name target-file-name
Parameters
A text expression specifying the name of the file you want to copy from. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use the CDA command to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
A text expression specifying the name of the file you want to copy to. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
Examples
The OKFORLIMIT option controls whether you can limit the dimension you are looping over within an explicit FOR loop.
|
Tip: To set the status of the dimension you are looping over in a loop that is generated by a REPORT statement, use a TEMPSTAT statement. |
Data Type
BOOLEAN
Syntax
OKFORLIMIT = {NO|YES}
Parameters
(Default) You cannot limit the dimension you are looping over within an explicit FOR loop.
You can limit the dimension you are looping over within an explicit FOR loop.
Examples
The SORT function returns the dimension or dimension surrogate values that result from a specified SORT command.
Return value
The return value varies depending on the use of the function:
When the SORT function is an argument to an OLAP DML statement (including a user-defined command or function) that expects a valueset, it returns a valueset. When the SORT function returns an empty valueset, it returns it as a valueset with null status.
When you include the INTEGER keyword, the SORT function returns the position numbers of the values as INTEGERS.
In all other cases, the SORT function returns either a TEXT value. When it returns a TEXT value that represents empty status, it returns the value as NA.
Syntax
SORT([INTEGER]dimension [byhierarchy] [bycriterion...])
where:
byhierarchy is an optional phrase that uses a parent relation to arrange the order of values in the current status list of a hierarchical dimension or its dimension surrogate, or to assign values to a valueset, based on family relationships within the hierarchy. You can include only one byhierarchy phrase in a SORT statement. It must be the first phrase in a SORT statement.
HIERARCHY parent-relation [INVERT] [DEPTH n] [SORTORPHANS]
bycriterion uses an explicit criterion to arrange the order of values in the current status list of a dimension or its dimension surrogate, or to assign values to a valueset. You can include as many bycriterion phrases as you want in a SORT statement.
{A|D} [NAFIRST] criterion
Parameters
See the SORT command for a complete description of all arguments except INTEGER.
When you use the INTEGER keyword, the function returns the position numbers of the values in the default dimension status rather than the names. When you use INTEGER with a valueset, the function returns the position numbers of the values in the default dimension status, not in the valueset.
The ROWIDTOCHAR function converts a value of the ROWID data type to a value of the TEXT data type.
Return Value
TEXT
The result of this conversion is always in the national character set and is 18 characters long.
Syntax
ROWIDTOCHAR (rowid)
Parameters
The value of type ROWID to convert.
Examples
Example 8-91 Converting ROWID Data to TEXT or NTEXT Data
Assume the following your analytic workspace has the following object definitions.
DEFINE myrowid DIMENSION ROWID DEFINE mytext VARIABLE TEXT DEFINE myntext VARIABLE NTEXT
Now you populate myrowid which has a datatype of ROWID using a MAINTAIN statement. Then you use the ROWIDTOCHAR function to populate mytext which has a data type of TEXT and ROWIDTONCHAR function to populate myntext which has a data type of NTEXT. Reports show that all of the variables are populated.
MAINTAIN myrowid ADD CHARTOROWID('AAAFd1AAFAAAABSAA/')
mytext = ROWIDTOCHAR (myrowid)
myntext = ROWIDTONCHAR (myrowid)
MYROWID
------------------------------
AAAFd1AAFAAAABSAA/
MYTEXT
------------------------------
AAAFd1AAFAAAABSAA/
MYNTEXT
------------------------------
AAAFd1AAFAAAABSAA/
The SMALLEST function returns the smallest value of an expression. You can use this function to compare numeric values or date values.
Return Value
The data type of the expression. It can be INTEGER, LONGINT, DECIMAL, or DATE.
Syntax
SMALLEST(expression [CACHE] [dimension...])
Parameters
The expression whose smallest value is to be returned.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of expression and another dimension that you want as a dimension of the result.
By default, SMALLEST returns a single value. When you indicate one or more dimensions for the result, SMALLEST tests for values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of expression or related to one of its dimensions.
|
Tip: When you specify a dimension that is not an actual dimension of expression, but, instead, is dimension that is related to a dimension of expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
NA Values and SMALLEST
SMALLEST is affected by the NASKIP option in the same manner as other aggregate functions. When NASKIP is set to YES (the default), SMALLEST ignores NA values and returns the smallest value or values that are not NA. When NASKIP is set to NO, SMALLEST returns NA when any value of the expression is NA. When all the values of the expression are NA, SMALLEST returns NA for either setting of NASKIP.
Examples
Example 8-101 Finding the Month with the Least Amount of Sportswear Sales
This example uses the SMALLEST function to find the smallest monthly sportswear sales for three districts during the first half of 1996. To see the smallest sales figure for each district, specify district as the dimension of the results.
LIMIT product TO 'Sportswear' LIMIT district TO FIRST 3 LIMIT month TO 'Jan96' TO 'Jun96' REPORT HEADING 'Smallest Sales' SMALLEST(sales district)
The preceding statements produce the following output.
Smallest
DISTRICT Sales
-------------- ----------
Boston 57,079.10
Atlanta 129,616.08
Chicago 77,489.51
The JOINCOLS function joins the corresponding lines of two or more multiline text values. The function returns a multiline text value composed of the concatenated lines up to a length of 498 bytes (the maximum length of a single concatenated line).
The number of lines in the return value is always the same as that in the argument expression that has the most lines. When a given argument expression has fewer lines, JOINCOLS repeats its last line in each subsequent line of the return value. This repeating feature is useful when an argument expression is a single-line separator, such as a space or hyphen. See Example 7-137, "Joining the Columns of Two Text Expressions".
Return Value
TEXT or NTEXT
When all arguments are TEXT values, the return value is TEXT. When all arguments are NTEXT values, the return value is NTEXT. When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
JOINCOLS(first-expression, next-expression...)
Parameters
An expression whose lines JOINCOLS joins with those of next-expression. When the expression has a data type other than TEXT or NTEXT, JOINCOLS converts it to TEXT. JOINCOLS ignores any arguments that have a value of NA
One or more expressions to join with first-expression. When an expression you want to concatenate has a data type other than TEXT or NTEXT, JOINCOLS converts it to TEXT. JOINCOLS ignores any arguments that have a value of NA
Examples
Example 7-137 Joining the Columns of Two Text Expressions
In the following example, each line in citylist is joined with a quoted text value, and the corresponding line from cityreps.
citylist has the following values.
Boston Houston Chicago Denver
cityrep has the following values.
Brady Lopez Alfonso Cody
The JOINCOLS function
JOINCOLS(citylist ' -- ' cityreps)
returns the following.
Boston -- Brady Houston -- Lopez Chicago -- Alfonso Denver -- Cody
The MULTIPATHHIER option specifies that a given cell that contains detail data can have multiple paths into a cell that contains aggregated data. Certain calculations require this kind of multiple-path aggregation.
Data Type
BOOLEAN
Syntax
MULTIPATHHIER = {YES|NO}
Parameters
Allows a detail data cell to aggregate in multiple paths to the same ancestor cell.
(Default) Disallows a detail data cell to aggregate in multiple paths to the same ancestor cell.
Usage Notes
When to Use MULTIPATHHIER
The only time you set the MULTIPATHHIER option to YES is when a calculation requires the use of multiple paths.
Interpreting an XSHIERCK01 Error Message
When you use the AGGREGATE command, dimension hierarchies are automatically checked for circularity. When MULTIPATHHIER is set to NO, or when the default of NO has not been changed, then the following error message is displayed when a detail data cell uses multiple paths to the same aggregate data cell.
ERROR: (XSHIERCK01) One or more loops have been detected in your hierarchy n over N. The loops include 2 items (UNDIRECTED: X and Y).
In the preceding error message, X is the name of the detail data cell, and Y is the name of the ancestor cell into which the detail data cell takes multiple paths to aggregate. For more information, see Example 5-68, "Defining Multiple Paths in a Hierarchy".
This error message is displayed because the multiple paths taken by the detail data cell have been interpreted as a circular hierarchy. When this is a mistake and you did not intend to create multiple paths, then change the hierarchy. Otherwise, set the MULTIPATHHIER option to YES.
Examples
Example 5-68 Defining Multiple Paths in a Hierarchy
This example shows how you can define multiple paths in a hierarchy, the error message that results when you attempt to aggregate data, how to interpret that message, and how to resolve the problem.
The following statements create two paths from a detail data cell to an ancestor cell that contains aggregated data.
DEFINE geog TEXT DIMENSION DEFINE path INTEGER DIMENSION DEFINE geog.geog RELATION geog <geog path> MAINTAIN geog ADD 'A1' 'b1' 'b2' 'Top' MAINTAIN path ADD 2 geog.geog(geog 'A1' path 1) = 'B1' geog.geog(geog 'A1' path 2) = 'B2' geog.geog(geog 'B1' path 1) = 'Top' geog.geog(geog 'B2' path 1) = 'Top'
First, a geography dimension named geog and a second dimension named path are defined.
A relation named geog.geog is defined, in which the geography dimension is dimensioned by itself and the path dimension.
Dimension values named A1, B1, B2, and Top are added to the geog dimension.
Two dimension values are added to the path dimension. Because path was defined with an INTEGER data type, the dimension values that are automatically assigned to it are the INTEGER values 1 and 2.
Finally, the hierarchy for the geog dimension is created. The A1 dimension value is the detail data. The B1 and B2 dimension values are the second level of the hierarchy. The Top dimension value is the top of the hierarchy.
A1 has two aggregation paths: A1 aggregates into B1, which aggregates into Top; A1 aggregates into B2, which aggregates into Top.
The following statements define a variable named myvar, assign a data value of 1 to its detail data level (A1), and define an aggmap for that variable.
DEFINE myvar INTEGER VARIABLE <geog> myvar(geog 'A1') = 1 DEFINE myvar.aggmap <geog> AGGMAP 'RELATION geog.geog'
An attempt to aggregate myvar generates the following error message.
AGGREGATE myvar USING myvar.aggmap ERROR: (XSHIERCK01) One or more loops have been detected in your hierarchy GEOG.GEOG over GEOG. The loops include 2 items (UNDIRECTED: A1 and TOP).
The multiple paths of aggregation that have been created for A1 have been interpreted as a circular hierarchy, because the MULTIPATHHIER option is currently set to NO.
When you had made a mistake and created these multiple paths by mistake, you would fix the problem in the hierarchy.
However, in this case, the multiple paths have been created because a calculation requires them. Therefore, the solution is to set MULTIPATHHIER to YES. Now you can execute the AGGREGATE command without error.
The BMARGIN option defines the number of blank lines for the bottom margin of output pages. BMARGIN is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and DESCRIBE. The BMARGIN option is usually set in the initialization section of report programs.
Data Type
INTEGER
Syntax
BMARGIN = n
Parameters
An INTEGER expression that specifies the number of lines to set aside for the bottom margin in a report. The default is 1.
Usage Notes
Setting BMARGIN for a File
To set BMARGIN for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set BMARGIN to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, BMARGIN returns to its default value of 1 for the file.
When you set BMARGIN for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE statements that send output to a file. That is, the value of BMARGIN is automatically saved for the default outfile
Examples
This chapter contains the following topics:
One topic for each of the OLAP DML options, arranged alphabetically beginning with ALLOCERRLOGFORMAT.
For other OLAP DML reference topics, see Chapter 4, "OLAP DML Properties", Chapter 7, "OLAP DML Functions: A - K", Chapter 8, "OLAP DML Functions: L - Z", Chapter 9, "OLAP DML Commands: A-G", and Chapter 10, "OLAP DML Commands: H-Z".
An OLAP DML option is a special type of analytic workspace object that specifies the characteristic of some aspect of how Oracle OLAP calculates or formats data or what Oracle OLAP operations are activated. Some options are read-only, while others are read/write options for which you can specify values. Read/write options have default values.
You can use the SET (=) command to retrieve the value of an option into a predefined variable and to specify a new value for a read/write option. Use the SHOW command to display the value of an option.
A B C D E I L M N O P R S T U V W Y Z
A
B
C
D
E
I
L
M
N
O
P
R
S
T
U
V
W
Y
Z
Analytic Workspace Options
Globalization Support
Multi-Language Support Options
Aggregation Options
Allocation Options
Model Options
Compilation Options
Error Options
Debugging Options
SQL Embed Options
File Reading and Writing Options
EIF Options
Report Options
NA Values Options
Date-only Data Type Options
Datetime Options
Numeric Options
RANK Function Monitoring Options
The FILEPAGE command forces a page break in your output when PAGING is on. FILEPAGE can send the page break conditionally, depending on how many lines are left on the current page
Syntax
FILEPAGE fileunit [n]
Parameters
A fileunit number assigned to a file that is opened in WRITE or APPEND mode by a previous call to the FILEOPEN function or by the OUTFILE command.
A positive INTEGER expression that indicates a page break should occur when there are fewer than n lines left on the page. When the number of lines left equals or exceeds n, or n equals zero, no page break occurs. When n is greater than PAGESIZE, a page break occurs when LINENUM is not zero. When n is negative or omitted, a page break always occurs.
Oracle OLAP calculates the number of available lines left on the page using the values of the options that specify the page size, the current line number, and the bottom margin. The number, which is stored in LINELEFT, is calculated according to the following formula.
LINESLEFT = PAGESIZE - LINENUM - BMARGIN
Usage Notes
Using PAGE Instead of FILEPAGE
The PAGE command has the same effect as specifying the FILEPAGE command for the fileunit number OUTFILEUNIT, which is the number of the current outfile destination. The following two statements are equivalent.
FILEPAGE OUTFILEUNIT PAGE
Examples
Example 9-123 Using the FILEPAGE Command
In the following program fragment, you might send a FILEPAGE statement when you know the next group of products does not fit on the page. The program takes as arguments the name of the output file, and three month dimension values.
fil.unit = FILEOPEN(ARG(1) WRITE)
LIMIT month TO &ARG(2) &ARG(3) &ARG(4)
COMMAS = NO
DECIMALS = 0
FOR district
DO
FILEPAGE fil.unit STATLEN(product)
FOR product
DO
FIL.TEXT = product
FOR month
JOINCHARS(fil.text ' ' CONVERT(sales TEXT))
FILEPUT fil.unit fil.text
DOEND
FILEPUT fil.unit ''
DOEND
FILECLOSE fil.unit
The UNIQUELINES function removes duplicate lines in a multiline text value and sorts the lines in ascending order. The function returns a multiline text value composed of the resulting lines.
Return Value
TEXT or NTEXT
Syntax
UNIQUELINES(text-expression)
Parameters
A multiline text expression from which UNIQUELINES removes duplicate lines and in which it sorts the remaining lines. UNIQUELINES is case-sensitive when it checks for duplicates, and it compares all characters, including spaces.
When you specify a TEXT expression, the return value is TEXT. When you specify an NTEXT expression, the return value is NTEXT.
Examples
Example 8-156 Removing Duplicate Text Lines
In the following example, one line is removed from the value of officelist, and the lines are sorted.
The statement
SHOW officelist
produces the following output.
MIAMI Providence Miami Baltimore Saratoga Baltimore
The statement
show uniquelines(officelist)
produces the following output.
Baltimore Miami MIAMI Providence Saratoga
The UPDATE_DIMENSION_MEMBER program sets the level and the parent of an OLAP cube dimension member in one or more hierarchies.
|
Note: You cannot use this program to modify a cube dimension if a materialized view exists for that cube dimension or any cube in which it participates. |
Syntax
CALL UPDATE_DIMENSION_MEMBER(member_id, logical_dim, hier_list, level_name, -
parent-member_id [, auto_compile ])
Parameters
Since UPDATE_DIMENSION_MEMBER is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is the member for which you want to set the level and parent information.
A text expression that is the Oracle data dictionary name of the cube dimension being modified.
A multi-line text expression consisting of the Oracle data dictionary names of all of the hierarchies that you want to set the level and parent for the dimension member. Specify one hierarchy name per line.
When you want to specify information for the member in all hierarchies of the cube dimension, specify NA.
For level hierarchies, a text value that specifies the hierarchy level at which the program will set the member of the cube dimension. For level hierarchies, the value you specify for level_name must be:
Compatible with the value you specify for parent_member_id
At the same hierarchy level as the existing cube dimension member since a cube dimension member cannot be in two different levels across hierarchies.
When the member participates in a value hierarchy (that is, when there are no levels), specify NA.
A text expression that specifies the value of the member which is the parent of the dimension member that you want to add to the hierarchy of the cube dimension. Specify NA when you want to add the dimension member as the top member.
A Boolean expression that specifies whether or not you want your changes to take effect immediately. The default value is TRUE in which case all of the changes to the analytic workspace that are needed to add the cube dimension member happen now. Specify FALSE only when, for performance reasons, you want to make a bulk set of changes before issuing a compile. In this case, you need to explicitly compile the cube dimension before the values of the analytic workspace objects take effect (for example, before attribute values are spread down or for time dimension valuesets to be updated), as described in "Explicitly Compiling a Cube Dimension".
Examples
Example 10-170 Changing the Hierarchy of an OLAP Cube Dimension
Assume that you have a hierarchical cube dimension named my_time and you want to change its hierarchy by moving the value L3_2 from the top-level to being a child of L2_2.
Execute the following SQL statement to report on the values of the my_time cube dimension before the move.
select dim_key||' '||level_name||' '||parent
from my_time_lvl_hier_view
order by dim_key asc;
DIM_KEY||''||LEVEL_NAME||''||PARENT
--------------------------------------------------------------------------------
L1_0 L1
L1_1 L1
L2_1 L2 L1_1
L2_2 L2 L1_1
L3_1 L3 L2_1
L3_2 L3 L2_1
L3_3 L3 L2_1
L3_4 L3 L2_2
L3_5 L3 L2_2
9 rows selected.
Issue the following PL/SQL statement that calls the user-written MOVE_L3_3 program to make the move.
exec dbms_aw.execute('call my_util_aw!move_l3_3');
As you can see from the following definition of the MOVE_L3_3 program, the actual move is performed by a CALL to the PDATE_DIMENSION_MEMBER program provided with the OLAP DML.
DEFINE MOVE_L3_3 PROGRAM
PROGRAM
" Change the parent of L3_2 to L2_2
CALL UPDATE_DIMENSION_MEMBER('L3_3', 'my_time', NA, 'L3', 'L2_2')
UPDATE
C0MMIT
END
Issue the following statement to report the values of the my_time dimension after the move
select dim_key||' '||level_name||' '||parent
from my_time_lvl_hier_view
order by dim_key asc;
DIM_KEY||''||LEVEL_NAME||''||PARENT
--------------------------------------------------------------------------------
L1_0 L1
L1_1 L1
L2_1 L2 L1_1
L2_2 L2 L1_1
L3_1 L3 L2_1
L3_2 L3 L2_1
L3_3 L3 L2_2
L3_4 L3 L2_2
L3_5 L3 L2_2
9 rows selected.
Issue the following statement to solve my_cube with new hierarchy of my_time.
exec dbms_cube.build(script => 'MY_CUBE USING (SOLVE)', add_dimensions => false);
Issue the following statement to report on the values of sales and moving_sales (the measures in my_cube) now that my_time has a new hierarchy.
select my_time||' '||lpad(sales, 2)||' '||lpad(moving_sales, 2)
from my_cube_view
order by my_time asc;
MY_TIME||''||LPAD(SALES,2)||''||LPAD(MOVING_SALES,2)
--------------------------------------------------------------------
L1_0 24 24
L1_1 14 38
L2_1 2 2
L2_2 12 14
L3_1 1 1
L3_2 1 2
L3_3 10 11
L3_4 1 11
L3_5 1 2
9 rows selected.
The REPLACE function returns a specified character each time a specified string is replaced with another string; or removes all occurrences of a specified string.
REPLACE provides functionality related to that provided by the TRANSLATE function. TRANSLATE provides single-character, one-to-one substitution. REPLACE lets you substitute one string for another as well as to remove character strings.
Return Value
The same data type as char.
Syntax
REPLACE ( char, search_string [, replacement_string ])
Parameters
A text expression that is the character that you want returned when a replacement is made.
A text expression that is the string you want to replace. When you specify NA, then the function returns char.
A text expression that is the string with which you want to replace search_string. When you do not specify a value for this argument or when you specify the value of NA, all occurrences of search_string are removed.
The REPORT command produces a formatted report for one or more data expressions. REPORT automatically loops over the dimensions of the expression. REPORT sends the output to the current outfile.
Syntax
REPORT [NOHEAD] [GRANDTOTALS] [[SUBTOTALS] {GROUP group-dimension}...] -
[[SUBTOTALS] [attributes] DOWN down-dimension] -
[[ROWTOTALS] { ACROSS across-dimension [limit-clause]: }... ] -
[SUBTOTALS] [attributes] expression(s)
Parameters
When you specify only the expression argument, REPORT produces a report with the layout described in "Default Layout". When you specify some but not all of the dimensions of an expression in GROUP, DOWN, or ACROSS phrases, REPORT follows the default layout as closely as possible with the unspecified dimensions.
Specifies that the report should contain no initial blank line and no headings. NOHEAD overrides any HEADING arguments you specify for the attributes argument and suppresses all headings that the REPORT command normally generates automatically.
Includes a grand total for each numeric column at the end of your report.
Includes subtotals for numeric columns. A row of dashes precedes each row of subtotals. When you specify SUBTOTALS for an expression or DOWN phrase, you get subtotals for each GROUP dimension (or composite). When you specify SUBTOTALS for a GROUP phrase, you get subtotals for the specified dimension and for any slower-varying GROUP dimensions. The subtotals for a group appear at the bottom of the last slice in the group.
Produces a separate group, or two-dimensional slice, of the data for each value of group-dimension. You can use the GROUP phrase more than once to specify multiple GROUP dimensions (or composites). In this case, you produce a separate slice for each combination of the values of the GROUP dimensions.
The name of a dimension or composite from which to retrieve the values to use as group labels, or one or more TEXT expressions that are the actual values you want to use as group labels:
When group-dimension is the name of a composite or a conjoint dimension, Oracle OLAP creates a separate group for each base dimension.
When group-dimension is a TEXT expression, the expression must be dimensioned only by the desired GROUP dimension, and each value of the expression should be descriptive text that corresponds to its associated dimension value.
The dimensions that you specify in a GROUP phrase are not required to be relevant to the data they loop over. See "Specifying Extra Dimensions".
Specifies that the report includes row labels (that is, one or more columns on the left side of your report that label the other values). You can have only one DOWN phrase.
The name of a dimension or composite from which to retrieve the values to use as row labels, or one or more TEXT expressions that are the actual values you want to use as row labels.
When down-dimension is the name of a non-conjoint dimension, REPORT produces only one column of row labels.
When down-dimension is the name of a composite or a conjoint dimension, Oracle OLAP creates a separate column for each base dimension.
When down-dimension is a TEXT expression, the expression must be dimensioned only by the desired DOWN dimension, and each value of the expression must be descriptive text that corresponds to its associated dimension value.
The dimensions that you specify in a DOWN phrase are not required to be relevant to the data they loop over. See "Specifying Extra Dimensions".
Includes a column headed "TOTAL" at the right side of the report with a total for each numeric row. Including a row total in your report does not imply either column subtotals or a grand total.
Produces a row of column headings across the top of your report, one for each value in dimension. Under each heading, REPORT produces a column of data for the data expression you specify. You can have multiple ACROSS phrases (or composites) in the report.
The name of a dimension or composite from which to retrieve the values to use as column headings, or one or more TEXT expressions that are the actual values you want to use as column headings.
When across-dimension is the name of a composite or a conjoint dimension, Oracle OLAP creates a separate heading column for each base dimension.
When across-dimension is a TEXT expression, the expression must be dimensioned only by the desired across-dimension, and each value of the expression should be descriptive text that corresponds to its associated dimension value. For information on providing formatted labels for a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, see "Formatting DAY, WEEK, MONTH, QUARTER, and YEAR Dimension Values".
The dimensions that you specify in an ACROSS phrase are not required to be relevant to the data they loop over. See "Specifying Extra Dimensions".
When you specify a dimension in the ACROSS phrase, the temporary status of that dimension during the execution of the execution of the REPORT statement. (You cannot include a limit-clause argument when you specify a composite in the ACROSS phrase.)
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
When the limits you specify result in an empty status for the dimension, an error occurs (regardless of the setting of the OKNULLSTATUS option). However, when you include the phrase IFNONE label, the error is suppressed and execution of your program branches to the specified label, where you can handle the error.
One or more format attributes from Table 10-4, "Formal Attributes for Data Values in a Report" that specify how to format the data. For information on providing formatted labels for a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR, see "Formatting DAY, WEEK, MONTH, QUARTER, and YEAR Dimension Values".
|
Tip: When a variable has a formatting property attached to its definition, you can use the OBJ function to obtain the value of that property and use it as the value of an attribute in a REPORT statement. |
When you do not specify any attributes, Oracle OLAP formats the data values using the default format described in "Default Layout". In this case, Oracle OLAP automatically determines the width of the columns, the number of decimal places, whether commas are used to mark thousands in numeric values, and so on.
Table 10-4 Formal Attributes for Data Values in a Report
| Attribute | Meaning |
|---|---|
|
HEADING 'text' |
Specifies text to use instead of default column headings. When you use the HEADING attribute, the position of the heading you specify varies depending on how many expressions it must span in your report. Consequently, your heading may or may not replace a default heading. Also, when you use the HEADING attribute to specify a column title that is wider than the column width, the text of the title wraps within the width of its column. |
|
WIDTH n |
(Abbreviated: W.) Makes the column n spaces wide. The maximum width is 4,000 characters. Columns with a width of 0 (zero) are suppressed.(See also: "Default Values for the Width Attribute".) |
|
TRUNCATE |
(Abbreviated: TRUNC.) Truncates a character value to the column width when it does not fit in the column. |
|
NOTRUNCATE |
(Abbreviated: NOTRUNC) Creates additional lines when the character value does not fit in the column. (Default.) |
|
CENTER |
(Abbreviated: C.) Centers the value within its column. |
|
LEFT |
(Abbreviated: L.) Left-justifies the value within its column. (Default for text data.) |
|
RIGHT |
(Abbreviated: R.) Right-justifies the value within its column. (Default for numeric and Boolean data.) |
|
SPACE n |
(Abbreviated: SP.) Precedes the column with the specified number of spaces. (By default, REPORT precedes the first column by 0 spaces, and other columns by 1 space.) |
|
FILL 'char' |
Puts char into unused positions in the column. (The default fill character is a space.) |
|
COMMA |
Marks thousands and millions with commas or the character currently recorded in the THOUSANDSCHAR option. Overrides the setting of the COMMAS option. |
|
NOCOMMA |
Does not marks thousands and millions. Overrides the setting of the COMMAS option. |
|
PAREN |
Uses parentheses to indicate negative numbers. Overrides the setting of the PARENS option |
|
NOPAREN |
Uses the minus sign to indicate negative numbers. Overrides the setting of the PARENS option. |
|
DECIMAL n |
(Abbreviated: D.) Shows n decimal places. Decimal places are separated using the character currently recorded in the DECIMALCHAR option. Overrides the value of the DECIMALS option. Note: REPORT suppresses decimal places in row and column totals of integer data unless you specify the DECIMAL attribute for the totaled expression. Additionally, when you set the DECIMAL attribute to |
|
MDECIMAL n |
Shows n decimal places in numbers formatted with M-notation; n can be any number from 0 to 16, or 255. |
|
NODECIMAL |
Shows the number of decimal places specified by the setting of the DECIMALS option. (Default.) |
|
EDECIMAL n |
Shows n decimal places in numbers formatted with E-notation; n can be any number from 0 to 16, or 255. |
|
ENOTATION |
Always uses scientific notation, also called exponential notation or E-notation (appends "E", and includes a sign before the exponent, for example, |
|
NOENOTATION |
Does not use E-notation; instead, uses to conditional M-notation. |
|
CENOTATION |
Conditionally uses E-notation, when needed to make a value fit in a column. |
|
MNOTATION |
Always uses M-notation (divides values by one million and appends "M"). |
|
NOMNOTATION |
Does not use M-notation; instead, uses asterisks for oversize values. |
|
CMNOTATION |
Conditionally uses M-notation, when needed to make a value fit in a column. (Default.) |
|
FOLDDOWN |
For a multiline character value, places the first line on the row with the other values, and places additional lines below the rest of the row; also strips any leading or trailing spaces. (Default.) |
|
FOLDUP |
For a multiline character value, places all but the last line above the rest of the row, and the last line on the row with the other values; also strips any leading or trailing spaces. |
|
INDENT n |
Indents the value n spaces within its column. The default is 0. |
|
LEADINGZERO |
Puts a leading zero before decimal numbers between -1 and 1. |
|
NOLEADINGZERO |
Suppresses leading zeros before decimal numbers between -1 and 1. |
|
CNLEADINGZERO |
Puts a leading zero before decimal numbers between -1 and 1 when it does not cut off any significant digits. (Default.) |
|
LSET 'text' |
Adds text to the left of the value. When you use LSET with an expression that contains |
|
NOLSET |
Does not add anything to the left of the value. (Default.) |
|
RSET 'text' |
Adds text to the right of the value. When you use RSET with an expression that contains |
|
NORSET |
Does not add anything to the right of the value. (Default.) |
|
NASPELL 'text' |
Uses text instead of |
|
NONASPELL |
Spells |
|
YESSPELL 'text' |
Uses text for |
|
NOSPELL 'text' |
Uses text for |
|
ZSPELL 'text' |
Uses text instead of zero numeric values. Overrides the setting of the ZSPELL option. |
|
NOZSPELL |
Spells zero numeric values as specified by the ZSPELL option. (Default.) |
|
OVER textexp |
Overlines the value with the value of a character expression (textexp). When textexp is a literal value, it must be enclosed in single quotes. Useful literal values include: To overline only when a condition is met, for textexp use:
|
|
UNDER textexp |
Underlines the value with the value of a character expression (textexp). When textexp is a literal value, it must be enclosed in single quotes. Useful literal values include: To underline only when a condition is met, for textexp use: |
|
VALONLY |
Used with the UNDER and OVER attributes, underline or overline the value only. |
|
NOVALONLY |
Used with the UNDER and OVER attributes, underlines or overlines the entire width of the column. (Default.) |
The data to be shown in the report. The way the data looks depends on its data type and the attributes you specify.
|
Note: The REPORT command is not equipped to deal with NTEXT values. Do not include them in any part of a report. |
You can specify multiple expressions and these expressions do not have to have the same dimensions:
When you have several data expressions in your REPORT statement, you can specify different format attributes before each. When you want attributes to apply to two or more data expressions, enclose the expressions in angle brackets (< >).
attributes <expression1, expression2>
Attributes outside the brackets apply to all the expressions within the brackets. However, you can also specify attributes for only one expression (even an attribute that contradicts one that applies to the group) within the brackets by including them immediately before the expression.
attributes0 <attributes1 expression1, expression2>
In this case, attributes0 applies to both expression1 and expression2; while attributes1 only applies to expression1.
|
Tip: To create running totals, use the RUNTOTAL function. |
Usage Notes
Report Options
Several options effect reports created using the OLAP DML. These options are listed in "Report Options".
Default Layout
When you do not specify any of the layout phrases (GROUP, DOWN, or ACROSS), REPORT tries to format its output compactly (typically, a two-dimensional report of the data with one dimension down the side and the others across the top, much like a spreadsheet). Any additional dimensions of the data form "slices" or separate two-dimensional segments, like a series of spreadsheets. By default, REPORT uses the following rules to determine the layout:
The fastest-varying dimension in an expression (the one that appears first in the definition of that expression) goes across, the next fastest goes down, and any remaining dimensions become GROUP slices.
The order of dimensions in a list of two or more expressions is a simple combination of the dimensions that appear in the definitions of the component expressions. The original order is preserved as far as possible, subject to the rule that repeated mentions of the same dimension are dropped. For example, the dimensions of the combined variables price and industry.sales, where price has the dimensions <month product> and industry.sales has the dimensions <quarter product region>, are <month product quarter region>.
When you produce a report of data for a variable dimensioned by a composite, REPORT automatically breaks out the data by the base dimensions of the composite that is used in the definition of the variable. When a particular combination of base dimension values does not exist in the composite, the report shows NA for the corresponding data cell. See Example 10-104, "Reporting Data Dimensioned by Composites".
Default Values for the Width Attribute
When you omit the WIDTH attribute for an ACROSS phrase, the default width is the value of the COLWIDTH option (default is 10).
When you omit the WIDTH attribute for a DOWN phrase or when you specify a simple dimension in the DOWN phrase, the default width is the value of the LCOLWIDTH option (d,Cefault is 14).
When you omit the WIDTH attribute for a DOWN phrase that specifies a conjoint dimension or a composite, the default label width is the width of the COLWIDTH option and there is a separate column for each base dimension. You can provide a different width for each base dimension column by using the KEY function. You can produce a label column for each base dimension with the KEY function and use a separate WIDTH attribute for each column. For example, assume that proddist is a composite with the base dimensions product and district. In this case, you can use a statement similar to the following one.
REPORT DOWN < W 8 KEY(proddist, product) - W 12 KEY(proddist, district) > . . .
When you use the default line width of 80 characters (determined by the LSIZE option) and the default column width settings (with a single label column of 14 characters) a line of output can accommodate the labels column and six data columns.
The combined width of all the columns of a report cannot be greater than 4,000 characters.
When a numeric value is too large to fit into a data column, REPORT rounds it off to the nearest million with the symbol M at the right side of the cell. When a value is still too large, REPORT replaces the value with a series of asterisks.
Formatting DAY, WEEK, MONTH, QUARTER, and YEAR Dimension Values
When you use a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR as the dimension in an ACROSS, DOWN, or GROUP phrase, you can use the CONVERT function to override the dimension's VNF (or the default VNF) and provide your own format for the dimension value names. To override the VNF, use the CONVERT function with a vnf argument instead of the dimension argument to the ACROSS, DOWN, or GROUP keyword. For example, in a report of units data, you can format the labels for the month dimension by using the following statement.
REPORT HEADING 'Month' DOWN - CONVERT(month TEXT '<mtextl> <yyyy>') units
Specifying Extra Dimensions
The REPORT command uses whatever dimensions you specify in laying out the report, regardless of whether the expressions to be shown are dimensioned by these dimensions. When an expression is not dimensioned by one or more of the dimensions specified, the values of that expression are repeated for each value of the extra dimension. This fact is sometimes useful for comparisons. SeeExample 10-103, "Repeating Price Data".
Examples
Example 10-100 Creating a Default Report
This example shows how to look at product prices for the first three months of 1996. You can use REPORT in its simplest form, without changing the default layout
LIMIT month TO 'Jan96' TO 'Mar96' REPORT price
These statements produce the following output.
--------------PRICE-------------
--------------MONTH-------------
PRODUCT Jan96 Feb96 Mar96
--------------- ---------- ---------- ----------
Tents 165.50 165.75 165.13
Canoes 200.25 200.09 200.05
Racquets 55.02 55.03 55.00
Sportswear 50.03 50.02 50.00
Footwear 38.01 38.01 38.01
Example 10-101 Including Column Totals
This example looks at unit sales for three districts for the first half of 1996, with district across the report and a subtotal for each column. (By default, months would be arranged across the report, since month is the fastest-varying dimension of units.) To make the report more compact, specify a smaller column width of 8 characters.
LIMIT month TO 'Jan96' TO 'Jun96' LIMIT district TO 'Boston' 'Chicago' 'Dallas' REPORT SUBTOTALS W 8 DOWN month - ACROSS district: W 8 units
These statements produce the following output.
PRODUCT: TENTS
----------UNITS-----------
---------DISTRICT---------
MONTH Boston Chicago Dallas
-------- -------- -------- --------
Jan96 307 189 308
Feb96 209 190 324
Mar96 277 257 436
Apr96 372 318 560
May96 525 433 744
Jun96 576 466 838
-------- -------- -------- --------
TOTAL 2,266 1,853 3,210
...
REPORT produces a similar slice for each product.
Example 10-102 Comparing Two Variables
This example compares actual sportswear sales with the projected sales plan, looking only at whole-dollar figures. It reports the actual and planned values side-by-side for May and June, 1996, and provides a grand total of sales and planned sales for all districts.
LIMIT product TO 'Sportswear' LIMIT month TO 'May96' 'Jun96' LIMIT district TO ALL REPORT GRANDTOTALS W 12 DOWN district ACROSS month: - DECIMAL 0 <sales sales.plan>
These statements produce the following output.
PRODUCT: SPORTSWEAR
-------------------MONTH-------------------
--------May96-------- --------Jun96--------
DISTRICT SALES SALES.PLAN SALES SALES.PLAN
------------ ---------- ---------- ---------- ----------
Boston 72,617 69,623 79,630 73,569
Atlanta 161,537 148,823 177,967 157,939
Chicago 101,873 94,545 112,793 97,427
Dallas 170,939 165,449 175,066 164,192
Denver 89,971 91,880 97,237 94,729
Seattle 57,713 55,905 60,323 56,808
---------- ---------- ---------- ----------
654,651 626,224 703,017 644,664
========== ========== ========== ==========
Example 10-103 Repeating Price Data
This example compares sales across three districts, and it includes the unit price beside each sales figure for close comparison within each district. The REPORT statement specifies two expressions, sales and price. Since sales has three dimensions, month, product, and district, the report shows these three dimensions. However, price is not dimensioned by district. Therefore, the report repeats the values of price for each district. The report for January 1995 shown.
LIMIT district TO FIRST 3 LIMIT product TO ALL LIMIT month TO 'Jan95' REPORT GROUP month W 10 DOWN product ACROSS district: - <W 9 sales W 6 price>
These statements produce the following output.
MONTH: Jan95
-------------------DISTRICT------------------------
-----Boston----- ----Atlanta----- -----Chicago----
PRODUCT SALES PRICE SALES PRICE SALES PRICE
---------- --------- ------ --------- ------ --------- ------
Tents 32,153.52 160.77 40,674.20 160.77 29,098.94 160.77
Canoes 66,013.92 190.24 49,462.88 190.24 45,277.56 190.24
Racquets 52,420.86 52.84 54,798.82 52.84 54,270.39 52.84
Sportswear 53,194.70 48.54 114,446.26 48.54 72,123.47 48.54
Footwear 91,406.82 36.10 100,540.28 36.10 90,287.70 36.10
Example 10-104 Reporting Data Dimensioned by Composites
In this example, d.sales is a variable whose dimension list includes the dimension month and the unnamed composite SPARSE <product district>. The unnamed composite contains no values for the base dimension combinations for the Boston and Chicago districts and the Tents, Racquets, And Footwear products. When you use the default form of the REPORT command to produce a report of d.sales data, REPORT breaks out the report by month and by the base dimensions of the unnamed composite (product and district). For the combinations of base dimension values that do not exist in the composite, the report shows NA for the corresponding data cells.
LIMIT month TO 'Jan96' TO 'Mar96' LIMIT district TO 'Boston' 'Chicago' REPORT d.sales
These statements produce the following output.
DISTRICT: Boston
------------D.SALES-------------
-------------MONTH--------------
PRODUCT Jan96 Feb96 Mar96
-------------- ---------- ---------- ----------
Tents NA NA NA
Canoes 70,489 82,238 97,622
Racquets NA NA NA
Sportswear 57,079 63,122 67,006
Footwear NA NA NA
DISTRICT: Chicago
------------D.SALES-------------
-------------MONTH--------------
PRODUCT Jan96 Feb96 Mar96
-------------- ---------- ---------- ----------
Tents NA NA NA
Canoes 48,662 54,425 68,816
Racquets NA NA NA
Sportswear 77,490 85,879 85,308
Footwear NA NA NA
By specifying the composite in an ACROSS, DOWN, or GROUP phrase, you can override the default format of REPORT and break out the d.sales data by its composite. In this case, the report only includes the data cells for which the composite contains values.
REPORT DOWN SPARSE <product district> d.sales
This statement produces the following report.
------------D.SALES-------------
-------------MONTH--------------
PRODUCT DISTRICT Jan96 Feb96 Mar96
---------- ---------- ---------- ---------- ----------
Canoes Boston 70,489 82,238 97,622
Sportswear Boston 57,079 63,122 67,006
Canoes Chicago 48,662 54,425 68,816
Sportswear Chicago 77,490 85,879 85,308
The SET_PROPERTY program modifies the values of the $LOOP_DENSE or $LOOP_VAR properties of a derived measure of a cube as defined in the Oracle data dictionary. The changes made when this program executes are not transactional; an automatic COMMIT is executed as part of the program.
Syntax
CALL SET_PROPERTY(property_name, logical_cube, meas_name, property_value)
Parameters
Since SET_PROPERTY is an OLAP DML program with arguments, you invoke it using the OLAP DML CALL statement.
A text expression that is either $LOOP_VAR or $LOOP_DENSE.
A text expression that is the Oracle data dictionary name of the cube that contains meas_name.
A text expression that is the Oracle data dictionary name of the derived measure for which you want to modify the value of either the $LOOP_VAR or $LOOP_DENSE property.
A text expression that is a valid value for the property you specified in property_name. For valid values, see $LOOP_DENSE or $LOOP_VAR.
The NLS_LANGUAGE option specifies the current language for the session. the setting of this option determines the value of the SESSION_NLS_LANGUAGE option.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_LANGUAGE = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about NLS database parameters.
Examples
Example 5-76 Effects of Changing NLS_LANGUAGE
In this example, the NLS_LANG option is initially set to:
AMERICAN_AMERICA.WE8ISO8859P1
The value of YESSPELL is yes.
A change to the language setting:
NLS_LANGUAGE = 'FRENCH'
changes the value of NLS_LANG to
FRENCH_AMERICAN.WE8ISO8859P1
The value of YESSPELL is now oui.
The YRABSTART option sets the specific 100-year period associated with years that are read or displayed using a two-digit abbreviation.
Data Type
INTEGER
Syntax
YRABSTART = year
Parameters
A four-digit INTEGER expression that indicates the year at which the 100-year period begins. You can specify any value in the range 1000 to 9999. However, when you specify a value greater than 9900 for year, requests to read or display two-digit year values that correspond to a year later than 9999 result in a return value of NA. The default is 1950; two-digit year abbreviations are interpreted as being in the range 1950 to 2049 unless a different range is set through YRABSTART.
Examples
The INSLINES function inserts one or more lines into a multiline text expression.
Return Value
TEXT or NTEXT
This function accepts TEXT values and NTEXT values as arguments. The data type of the return value depends on the data type of the values specified for the arguments:
When all arguments are TEXT values, the return value is TEXT.
When all arguments are NTEXT values, the return value is NTEXT.
When the arguments include both TEXT and NTEXT values, the function converts all TEXT values to NTEXT before performing the function operation, and the return value is NTEXT.
Syntax
INSLINES(text-expression lines [after])
Parameters
A multiline expression into whose values one or more lines are to be inserted.
An expression that represents one or more lines of text that you insert into text-expression.
An INTEGER that represents the line number after which the specified lines are to be inserted. The position of the first line in text-expression is 1 (one). To insert lines at the very beginning, specify 0 (zero) for after. When you omit this argument, INSLINES inserts the new lines after the last line of text-expression.
Examples
Example 7-122 Inserting Text Lines
This example shows how to insert a new line into a multiline text value in a variable called mktglist with the following value.
Salespeople Products Services
The INSLINES function
INSLINES(mktglist, 'Advertising', 2)
returns the following.
Salespeople Products Advertising Services
The RECURSIVE option controls the ability of a formula or $NATRIGGER expression to call itself.
Syntax
RECURSIVE = {YES|NO}
Parameters
Specifying YES allows a formula or $NATRIGGER expression to call itself. Set this option to YES when you define a formula or an expression for the $NATRIGGER property that uses a recursive method of computation.
(Default) Specifying NO prevents a formula or $NATRIGGER expression from calling itself. When you attempt to evaluate a recursive formula or $NATRIGGER expression, then Oracle OLAP displays an error message, which states that the RECURSIVE option is currently set to NO. Until the workspace contains a recursive formula or $NATRIGGER expression, keep this option set to NO to detect errors that could result in infinite looping behavior.
Usage Notes
For Formulas and $NATRIGGER Expressions Only
When you set RECURSIVE to YES, only formulas and $NATRIGGER property expressions are affected. This option does not affect programs; that is, a program can be recursive regardless of the setting of the RECURSIVE option unless the program is a $NATRIGGER expression. A $NATRIGGER expression cannot call itself unless the RECURSIVE option is YES.
Limiting $NATRIGGER Recursion
You can limit the depth of recursion for $NATRIGGER property expressions with the TRIGGERMAXDEPTH option, which sets the maximum number of $NATRIGGER expressions that Oracle OLAP executes simultaneously.
The FILEDELETE command deletes a file from the operating system disk space.
Syntax
FILEDELETE file-name
Parameters
A text expression specifying the name of the file you want to delete. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
|
Note: Directory objects are defined in the database, and they control access to directories and file in those directories. You can use the CDA command to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Examples
The NASKIP2 option controls how NA values are treated in arithmetic operations with the + (plus) and - (minus) operators. The result is NA when any operand is NA unless NASKIP2 is set to YES.
Data Type
BOOLEAN
Syntax
NASKIP2 = YES|NO
Parameters
Zeroes are substituted for NA values in arithmetic operations using the + (plus) and - (minus) operators. The two special cases of NA + NA and NA - NA both result in NA.
(Default) NA values are treated as NAs in arithmetic operations using the + (plus) and - (minus) operators. When any of the operands being considered is NA, the arithmetic operation evaluates to NA.
Usage Notes
Operators in Function Arguments
NASKIP2 is independent of NASKIP. NASKIP2 applies only to arithmetic operations with the + (plus) and - (minus) operators. NASKIP applies only to aggregation functions. However, when an expression argument to an aggregation function contains a+ (plus) and - (minus) operator, the results of the calculation depend on both NASKIP and NASKIP2. See Example 5-71, "Effects of NASKIP and NASKIP2 When an Expression in an Aggregation Function Contains a Negative Values".
How NASKIP2 Works
The following four lines show four steps in the evaluation of a complex expression that contains NAs when NASKIP2 is set to YES.
3 * (NA + NA) - 5 * (NA + 3)
3 * NA - 5 * 3
NA - 15
-15
Examples
Example 5-71 Effects of NASKIP and NASKIP2 When an Expression in an Aggregation Function Contains a Negative Values
In the following examples, INTEGER variables X and Z, dimensioned by the INTEGER dimension INTDIM, have the values shown in the second and third columns of the report. The sum of X + Z is given for each combination of NASKIP and NASKIP2 settings, starting with their defaults. The example also shows that when the + (plus) operator is used in the expression argument to the TOTAL function, the results that are returned by TOTAL depend on the settings of both NASKIP and NASKIP2.
NASKIP Set to YES, NASKIP2 Set to NO
In this example, NASKIP is set to YES, which means NA values are ignored by the TOTAL function. NASKIP2 is set to NO, which means that the result of a + (plus) operation is NA when any of the operands are NA.
NASKIP = YES NASKIP2 = NO COLWIDTH = 5 REPORT LEFT W 6 DOWN intdim x, z, x + z
These statements produce the following output. With NASKIP2 set to NO, the expression X + Z evaluates to NA when either X or Z is NA.
INTDIM X Z x + z ------ ----- ----- ----- 1 NA 2 NA 2 3 NA NA 3 7 6 13
The following statement uses a + (plus) operator within the expression argument to the TOTAL function.
SHOW TOTAL(x + z)
This statement produces the following result.
13
The next statement uses the + (plus) operator to add the results that are returned by two TOTAL functions.
SHOW TOTAL(x) + TOTAL(z)
This statement produces the following result.
18
NASKIP Set to YES, NASKIP2 Set to YES
In this example, NASKIP is set to YES, which means NA values are ignored by the TOTAL function. NASKIP2 is set to YES, which means that NA values are ignored by the + (plus) operator
NASKIP = YES NASKIP2 = YES REPORT LEFT W 6 DOWN intdim x, z, x + z
These statements produce the following output. With NASKIP2 set to YES, NA values are ignored when the expression X + Z is evaluated.
INTDIM X Z X + Z ------ ----- ----- ----- 1 NA 2 2 2 3 NA 3 3 7 6 13
The following statement uses a + (plus) operator within the expression argument to the TOTAL function.
SHOW TOTAL(x + z)
This statement produces the following result.
18
The next statement uses the + (plus) operator to add the results that are returned by two TOTAL functions.
SHOW TOTAL(x) + TOTAL(z)
This statement produces the following result.
18
NASKIP Set to NO, NASKIP2 Set to YES
In this example, NASKIP is set to NO, which means that when any values considered by the TOTAL function are NA, TOTAL returns NA. NASKIP2 is set to YES, which means that NA values are ignored by the + (plus) operator.
NASKIP = NO NASKIP2 = YES REPORT LEFT W 6 DOWN intdim x, z, x + z
These statements produce the following result.
INTDIM X Z X + Z ------ ----- ----- ----- 1 NA 2 2 2 3 NA 3 3 7 6 13
The following statement uses a + (plus) operator within the expression argument to the TOTAL function.
SHOW TOTAL(x + z)
This statement produces the following result.
18
The next statement uses the + (plus) operator to add the results that are returned by two TOTAL functions.
SHOW TOTAL(x) + TOTAL(z)
This statement produces the following result.
NA
NASKIP Set to NO, NASKIP Set to NO
In this example, NASKIP is again set to NO, which means that when any values considered by the TOTAL function are NA, TOTAL returns NA. NASKIP2 is also set to NO, which means that the result of a + (plus) operation is NA when any of the operands are NA.
NASKIP = NO NASKIP2 = NO REPORT LEFT W 6 DOWN intdim x, z, x + z
These statements produce the following result.
INTDIM X Z X + Z ------ ----- ----- ----- 1 NA 2 NA 2 3 NA NA 3 7 6 13
The following statement uses a + (plus) operator within the expression argument to the TOTAL function.
SHOW TOTAL(x + z)
This statement produces the following result.
NA
The next statement uses the + (plus) operator to add the results that are returned by two TOTAL functions.
SHOW TOTAL(x) + TOTAL(z)
This statement produces the following result.
NA
The TO_CHAR function converts a DATETIME, number, or NTEXT expression to a TEXT expression in a specified format. This function is typically used to format output data.
Return Value
TEXT
Syntax
TO_CHAR(datetime-exp, [datetime-fmt,] [option setting])
or
TO_CHAR(num-exp, [num-fmt,] [nlsparams])
or
TO_CHAR(ntext-exp)
Parameters
A DATETIME expression to be converted to TEXT.
A text expression that identifies a datetime format template. This template specifies how the conversion from a DATETIME data type to TEXT should be performed. For information about datetime format templates, see Table 9-4, "Datetime Format Elements". The default value of datetime-fmt is controlled by the NLS_DATE_FORMAT option.
An OLAP option (such as NLS_DATE_LANGUAGE) and its new setting, which temporarily overrides the setting currently in effect for the session. Typically, this option identifies the language that you want datetime-exp to be translated into. See Example 8-138, "Displaying the Current Date and Time in Spanish".
Do not specify an option that set other options. For example, do not set NLS_DATE_LANGUAGE or NLS_TERRITORY; set NLS_DATE_LANGUAGE instead. While TO_CHAR saves and restores the current setting of the specified option so that it has a new value only for the duration of the statement, TO_CHAR cannot save and restore any side effects of changing that option. For example, NLS_TERRITORY controls the value of NLS_DATE_FORMAT, NLS_NUMERIC_CHARACTERS, NLS_CURRENCY, NLS_CALENDAR, and other options. When you change the value of NLS_TERRITORY in a call to TO_CHAR, all of these options are reset to their territory-appropriate default values twice: once when NLS_TERRITORY is set to its new value for the duration of the TO_CHAR statement, and again when the saved value of NLS_TERRITORY is restored.
A numeric expression to be converted to TEXT.
A text expression that identifies a number format model. This model specifies how the conversion from a numeric data type (NUMBER, INTEGER, SHORTINTEGER, LONGINTEGER, DECIMAL, SHORTDECIMAL) to TEXT should be performed.
The default number format model uses the decimal and thousands group markers identified by NLS_NUMERIC_CHARACTERS.
A text expression that specifies the thousands group marker, decimal marker, and currency symbols used in num-exp. This expression contains one or more of the following parameters, separated by commas:
NLS_CURRENCY symbol
NLS_ISO_CURRENCY territory
NLS_NUMERIC_CHARACTERS dg
A text expression that specifies the local currency symbol. It can be no more than 10 characters.
A text expression that identifies the territory whose ISO currency symbol is used.
A text expression composed of two different, single-byte characters for the decimal marker (d) and thousands group marker (g).
These parameters override the default values specified by the NLS_CURRENCY, NLS_ISO_CURRENCY, and NLS_NUMERIC_CHARACTERS options.
An NTEXT expression to be converted to TEXT. A conversion from NTEXT to TEXT can result in data loss when the NTEXT value cannot be represented in the database character set.
Usage Notes
How TO_CHAR Handles Numerical Data Types
The TO_CHAR function converts INTEGER, SHORTINTEGER, LONGINTEGER, DECIMAL, and SHORTDECIMAL values to NUMBER before converting them to TEXT. Thus, TO_CHAR converts NUMBER values faster than other numeric data types.
Possible Effects of TO_CHAR Rounding
All number format models cause the number to be rounded to the specified number of significant digits. Table 8-17, "Possible Effects of Rounding" identifies some effects of rounding.
Table 8-17 Possible Effects of Rounding
| IF num-exp | THEN the return value |
|---|---|
|
has more significant digits to the left of the decimal place than are specified in the format, |
appears as pound signs ( |
|
is a very large positive value that cannot be represented in the specified format, |
is a tilde ( |
|
is a very small negative value that cannot be represented in the specified format, |
is a negative sign followed by a tilde ( |
Examples
Example 8-136 Converting a Date to CHAR
This statement converts today's date and specifies the format.
SHOW TO_CHAR(SYSDATE, 'Month DD, YYYY HH24:MI:SS')
The specified date format allows the time to be displayed along with the date.
November 30, 2000 10:01:29
Example 8-137 Converting a Numerical Value to Text
This statement converts a number to text and specifies a space as the decimal marker and a period as the thousands group marker.
SHOW TO_CHAR(1013.50, NA, NLS_NUMERIC_CHARACTERS ' .')
The value 1013.50 now appears like this:
1.013 50
Example 8-138 Displaying the Current Date and Time in Spanish
The following statements set the default language to Spanish and specify a new date format.
NLS_DATE_LANGUAGE = 'spanish' NLS_DATE_FORMAT = 'Day: Month dd, yyyy HH:MI:SS am'
The following statement displays the current date and time in Spanish.
SHOW TO_CHAR(SYSDATE) Viernes : Diciembre 01, 2000 08:21:17 AM
The NLS_DATE_LANGUAGE option changes the language for the duration of the statement. The following statement displays the date and time in German.
SHOW TO_CHAR(SYSDATE, NA, NLS_DATE_LANGUAGE 'german') Freitag : Dezember 01, 2000 08:26:00 AM
The CORRELATION function returns the correlation coefficients for the pairs of data values in two expressions. A correlation coefficient indicates the strength of relationship between the data values. The closer the correlation coefficient is to positive or negative 1, the stronger the relationship is between the data values in the expressions. A correlation coefficient of 0 (zero) means no correlation and a +1 (plus one) or -1 (minus one) means a perfect correlation. A positive correlation coefficient indicates that as the data values in one expression increase (or decrease), the data values in the other expression also increase (or decrease). A negative correlation coefficient indicates that as the data values in one expression increase, the data values in other expression decrease.
Return Value
DECIMAL
Syntax
CORRELATION(expression1 expression2 [PEARSON|SPEARMAN|KENDALL] -
[BASEDON dimension-list])
Parameters
A dimensioned numeric expression with at least one dimension in common with expression2.
A dimensioned numeric expression with at least one dimension in common with expression1.
Calculates the Pearson product-moment correlation coefficient. Use this method when the data is interval-level or ratios, such as units sold and price for each unit, and the data values in the expressions have a linear relationship and are distributed normally.
Calculates Spearman's rho correlation coefficient. Use this nonparametric method when the expressions do not have a linear relationship or a normal distribution. In computing the correlation coefficient, this method ranks the data values in expression1 and in expression2 and then compares the rank of each element in expression1 to the corresponding element in expression2. This method assumes that most of the values in the expressions are unique.
Calculates Kendall's tau correlation coefficient. This nonparametric method is similar to the SPEARMAN method in that it also first ranks the data values in expression1 and in expression2. The KENDALL method, however, compares the ranks of each pair to the successive pairs. Use this method when few of the data values in expression1 and in expression2 are unique.
An optional list of dimensions along which CORRELATION computes the correlation coefficient. Both expression1 and expression2 must be dimensioned by all of the dimension-list dimensions. CORRELATION correlates the data values of expression1 to those of expression2 along all of the dimension-list dimensions. CORRELATION returns an array that contains one correlation coefficient for each cell that is dimensioned by all of the dimensions of expression1 and expression2 except those in dimension-list.
When you do not specify a dimension-list argument, then CORRELATION computes the correlation coefficient over all of the common dimensions of expression1 and expression2. When all of the dimensions of the two expressions are the same, then CORRELATION returns a single correlation coefficient. When either expression contains dimensions that are not shared by the other expression, then CORRELATION returns an array that contains one correlation coefficient for each cell that is dimensioned by the dimensions of the expressions that are not shared.
Usage Notes
The Effect of NASKIP on CORRELATION
CORRELATION is affected by the NASKIP option. When NASKIP is set to YES (the default), then CORRELATION ignores NA values. When NASKIP is set to NO, then an NA value in the expressions results in a correlation coefficient of NA.
Examples
Example 7-51 Correlating with the PEARSON Method
Assume that your analytic workspace contains two variables named units and price. The two dimensions of the price variable, month and product, are shared by the units variable, which has a third dimension, district.
The following CORRELATION statement does not specify a dimension-list argument. The output of the CORRELATION function in the statement is one correlation coefficient for each of the dimension values in the dimension that the variables do not have in common.
REPORT CORRELATION(units price pearson)
The preceding statement produces the following output.
CORRELATION
(UNITS
PRICE
DISTRICT PEARSON)
-------------- -----------
Boston -0.75
Atlanta -0.85
Chicago -0.83
Dallas -0.66
Denver -0.83
Seattle -0.69
The following statements limit the month and product dimensions.
LIMIT month to 'Jan96' TO 'Mar96' LIMIT product TO 'Tents' TO 'Racquets'
The following statement reports the correlation coefficient based on the product dimension for the limited dimension values that are in status.
REPORT CORRELATION(units price pearson basedon product)
CORRELATION(UNITS PRICE PEARSON-
--------BASEDON PRODUCT)--------
-------------MONTH--------------
DISTRICT Jan96 Feb96 Mar96
-------------- ---------- ---------- ----------
Boston -0.96 -0.90 -0.89
Atlanta -0.97 -0.97 -0.97
Chicago -0.96 -0.95 -0.95
Dallas -0.98 -0.98 -0.99
Denver -0.97 -0.97 -0.97
Seattle -0.89 -0.83 -0.83
The following statement reports the correlation coefficient based on the month dimension for the limited dimension values.
REPORT CORRELATION(units price pearson basedon month)
CORRELATION(UNITS PRICE PEARSON-
---------BASEDON MONTH)---------
------------PRODUCT-------------
DISTRICT Tents Canoes Racquets
-------------- ---------- ---------- ----------
Boston -0.59 -0.92 -0.55
Atlanta -0.73 -0.83 0.03
Chicago -0.91 -0.84 -0.68
Dallas -0.86 -0.92 0.31
Denver -0.98 -0.94 -0.67
Seattle -0.98 -0.89 -0.70
The DATEORDER option holds three characters that indicate the intended order of the month, day, and year components of the DATE-only values in an analytic workspace for those cases in which their interpretation is ambiguous. Oracle OLAP automatically refers to DATEORDER whenever you enter an ambiguous DATE-only value or convert one from a text value. For information about date values, see "Date-only Data Type".
Data Type
ID
Syntax
DATEORDER = order
Parameters
One of the following text expressions: 'MDY', 'DMY', 'YMD', 'YDM', 'MYD', 'DYM'. Each letter represents a component of the date. M stands for the month, D for the day, and Y for the year. The default date order is 'MDY'.
Usage Notes
Ambiguous Dates
When you enter an unambiguous DATE-only value or convert a text value that has only one interpretation as a date, it is handled without consulting the DATEORDER option. For example, in 03-24-97 the 97 can only refer to the year. Considering what is left, the 24 cannot refer to the month, so it must be the day. Only 03 is left, so it must be the month. When, however, the interpretation is ambiguous, as in the value 3-5-97, the current value of DATEORDER is used to interpret the meaning of each component.
DATEORDER and TEXT-to-DATE-only Conversion
When you use a text value where a DATE-only value is expected, or when you store a text value in a DATE-only variable, the text value must conform to a style listed "Date-only Input Values". Oracle OLAP automatically converts the text value to a DATE-only value. When the meaning of the text value is ambiguous, the current setting of DATEORDER is used to interpret the value.
To override the current DATEORDER setting in converting a text value to a DATE-only value, use the CONVERT function with the date-order argument.
Essential Date Components
Suppose you want to assign a date value to a DAY, WEEK, MONTH, QUARTER, or YEAR dimension using a MAINTAIN statement or to a valueset using the LIMIT command. When you specify the value in the form of a DATE-only expression or a text literal, Oracle OLAP uses the DATEORDER option to interpret the value. When supplying a text literal, you can use any valid input style for dates. However, you must supply only the date components that are necessary for identifying a time period in the particular type of dimension or valueset you are using. For example, for a MONTH dimension or its valueset, you can specify a complete date, such as 30jun97, or you can provide only the essential components, such as jun97 or 0697.
DWMQY Dimension Phases
The DATEORDER option is used to interpret a phase argument to a DEFINE DIMENSION statement for DAY, WEEK, MONTH, QUARTER, and YEAR dimensions.
Examples
Example 5-15 Changing the Date Order
The following statements define and assign a value to a DATE-only variable, specify the date format and the date order, and send the output to the current outfile.
DEFINE datevar VARIABLE DATE dATEFORMAT = '<MTXT> <D>, <YYYY>' DATEORDER = 'MDY' DATEVAR = '3 5 1997' SHOW DATEVAR
These statements produce the following output.
MAR 5, 1997
The following statements change the date order, and, therefore, the way the same value of the DATE-only variable is interpreted.
DATEORDER = 'DMY' SHOW DATEVAR
These statements produce the following output.
MAY 3, 1997
The CHARTOROWID function converts a value from a text data type to ROWID data type.
Return Value
ROWID
Syntax
CHARTOROWID(char)
Parameters
A text expression to convert.
Examples
Example 7-43 Converting a Value from Text to a Rowid
Assume that your analytic workspace contains the erowid dimension with the following definition.
DEFINE erowid DIMENSION ROWID
As the following code illustrates, you can add text values to it using the CHARTOROWID function.
MAINTAIN erowid ADD CHARTOROWID('AAAFd1AAFAAAABSAA/')
REPORT erowid
EROWID
------------------------------
AAAFd1AAFAAAABSAA/
The OLAP_RUNNING function returns a boolean indicating whether or not the OLAP option has been initialized in the current session. Initialization occurs when you execute an OLAP DML command (either directly or by using an OLAP PL/SQL or Java package), query an analytic workspace, or execute the STARTUP Procedure.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
OLAP_RUNNING( )
RETURN BOOLEAN;
Returns
TRUE if OLAP has been initialized in the current session, or FALSE if it has not.
Example
The following PL/SQL script tests whether the OLAP environment has been initialized, and starts it if not.
BEGIN
IF dbms_aw.olap_running() THEN
dbms_output.put_line('OLAP is already running');
ELSE
dbms_aw.startup;
IF dbms_aw.olap_running() THEN
dbms_output.put_line('OLAP started successfully');
ELSE
dbms_output.put_line('OLAP did not start. Is it installed?');
END IF;
END IF;
END;
/
OLAP started successfully
The HIERSHAPE function identifies if a hierarchical dimension has a specified shape.
Return Value
BOOLEAN
Syntax
HIERSHAPE(parent-relation[(qdr)] {LEVEL | RAGGED | SKIPLEVEL | REGULAR} USING levelrel -
[INHIERARCHY inhvalueset] LEVELORDER levelvalueset)
Parameters
A text expression that is the name of the child-parent self-relation for the hierarchical dimension. (See "Parentrel Relation".)
A text expression that is the name of a QDR that qualifies parent-relation.
This option determines of all of the members are part of the same level as defined by the levelrel.
A hierarchy where leaf-nodes are located at different levels within the hierarchy.
A hierarchy where one or more leaf nodes link to a higher-level parent above its next most obvious level.
A traditional level-based hierarchy where each child has a parent at the next level up in the hierarchy.
A text expression that is the name of the level relation for the hierarchical dimension. (See "Levelrel Relation".)
A text expression that is the name of the inhier valueset for the hierarchical dimension. (See "Inhier Valueset or Variable".)
A text expression that is the name of the hierlevels valueset for the hierarchical dimension. (See "Hierlevels Valueset".)
Usage Notes
Star-consistent Hierarchies
A dimension is "star consistent" when the hierarchies it represents can be implemented as a star table (that is, when a single column defines each level so there is no partial membership in a level based on hierarchy). A dimension is "star inconsistent" when it cannot.For example, assume there is a dimension with members A, B, C, D. When some customer have a "mid" level consisting of A and B in hierarchy 1 and C and D in hierarchy 2. This dimension is star inconsistent because in a star table, you would only have a single column to represent the "mid" level and its inclusion means that both hierarchies would contain all the members of that level.
The MODTOLERANCE option is used in testing whether each equation in a simultaneous block of a model has converged. MODTOLERANCE determines how closely the results of an equation must match between successive iterations for the equation to be considered to have converged.
Data Type
INTEGER
Syntax
MODTOLERANCE = {n|3}
Parameters
An INTEGER value to use in testing for convergence. As Oracle OLAP calculates each equation in a simultaneous block, it constructs a comparison value that is based on the results of the equation for the current iteration and the previous iteration. When the comparison value passes a tolerance test, the equation is considered to have converged.
The comparison value that is tested is as follows.
(thisResult - prevResult) / (prevResult+ MODGAMMA)
where thisResult is the result of this iteration and prevResult is the result of the previous iteration
In the preceding calculation, MODGAMMA is an INTEGER option that controls the degree to which the comparison value represents the absolute amount of change between iterations versus the proportional change. The default value of MODGAMMA is 1.
In the tolerance test, Oracle OLAP tests whether the comparison value is less than 10 to the negative power of MODTOLERANCE. The calculation for this test is as follows.
Comparison value < 10**-MODTOLERANCE
An equivalent way of writing this calculation is as follows.
Comparison value < (1 / (10**MODTOLERANCE))
For the equation to be considered to have converged, the comparison value must meet the test described earlier. The default value of MODTOLERANCE is 3. With this default, the comparison value meets the test when it is less than 0.001.
Usage Notes
Failure to Converge
When an equation fails to converge after a specified number of iterations, an error occurs. The MODMAXITERS option controls the maximum number of iterations that are attempted. The MODERROR option controls the action that Oracle OLAP takes when an error occurs.
Precision of Results
Since MODTOLERANCE controls how closely results of an equation must match between iterations, it therefore controls the precision of the results of the solution. A small value of MODTOLERANCE results in less precision, while a large value provides more precision.
Large and Small Values
When a model contains some equations with large values and some equations with very small values, it might be preferable to increase the value of the MODGAMMA option rather than decreasing MODTOLERANCE. By increasing MODGAMMA, you might be able to force equations with small values to converge more quickly while retaining the precision of equations with large values.
Faster Convergence During Development
While you are developing a model, you might want to use a small value for MODTOLERANCE. While this gives less precise results, the model equations converges more quickly. After you have debugged the model, you can increase the value of MODTOLERANCE and thereby increase the precision of the final results.
Options for Controlling the Solution of Simultaneous Blocks
For a list of all the options that you can use to control the solution of simultaneous blocks, see "Model Options".
Examples
Example 5-61 Using the Default MODTOLERANCE Value
The following statements specify a trace for a model called income.plan, specify that the Gauss-Seidel method should be used for solving simultaneous blocks, limit a dimension, and run the model.
MODTRACE = YES MODSIMULTYPE = 'GAUSS' LIMIT division TO 'Camping' income.plan budget
These statements produce the following output.
(MOD= INCOME.PLAN) BLOCK 1: SIMULTANEOUS
(MOD= INCOME.PLAN) ITERATION 1: EVALUATION
(MOD= INCOME.PLAN) marketing = .15 * net.income
(MOD= INCOME.PLAN) BUDGET(LINE MARKETING MONTH 'JAN97' ITER 1) = 11887.403671736
...
(MOD= INCOME.PLAN) BUDGET(LINE MARKETING MONTH 'JAN97' ITER 6) = 73379.713232251
...
(MOD= INCOME.PLAN) BUDGET(LINE MARKETING MONTH 'JAN97' ITER 7) = 73474.784648631
...
(MOD= INCOME.PLAN) BUDGET(LINE MARKETING MONTH 'JAN97' ITER 8) = 73446.025848156
(MOD= INCOME.PLAN) END BLOCK 1
In the trace, you can see the results that were calculated for the Marketing line item in the final three iterations over a block of simultaneous equations.
MODTOLERANCE is set to its default value of 3. Consequently, for an equation to pass the convergence test, its comparison value must be less than 0.001. In the seventh iteration, Oracle OLAP calculates the comparison value for Marketing as follows.
(73474.784648631100 - 73379.713232251300) / (73379.713232251300 + 1) = 0.0013
This comparison value is greater than 0.001, so it did not pass the test for convergence.
In the eighth iteration, Oracle OLAP calculated the comparison value as follows.
(73446.025848156700 - 73474.784648631100) /(73474.784648631100 + 1) = 0.0004
Since this comparison value is less than 0.001, it passed the convergence test.
Example 5-62 Setting MODTOLERANCE to Speed Up the Convergence of a Model
The following statements change the MODTOLERANCE value and run the income.bud model.
MODTOLERANCE = 2 income.plan budget
With MODTOLERANCE set to 2, any comparison value of less than 0.01 passes the test for convergence. In this example, the equation for Marketing passes the test in the seventh iteration.
The MODEL command enters a completely new specification into a new or existing model object. When the model already has a specification, Oracle OLAP overwrites it. To use MODEL to assign an model specification to a model object, the definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
An alternative to a MODEL statement is an EDIT MODEL statement, which is available only in OLAP Worksheet. An EDIT MODEL statement opens an Edit window in which you can add, delete, or change the specification for a model object.
Adding a specification to a model object is just one step in modeling data. For more information on models, see "OLAP DML Model Objects".
Syntax
MODEL specification
Parameters
A multiline text expression that contains one or more of the following OLAP DML statements:
The maximum number of lines you can have in a model is 4,000. Each statement is a line of the multiline text expression. When coding an ALLOCMAP statement at the command line level, separate statements with newline delimiters (\n), or use JOINLINES.
For a discussion of designing a model specification, see "Model Specification".
Usage Notes
Model Specification
The model specification consists of the following OLAP DML statements:
One of the following:
Exactly one INCLUDE statement that specifies the name of another model to include. See "Nesting Models" for more information.
One or more DIMENSION (in models) statements coded following the "Guidelines for Writing DIMENSION Statements in a Model".
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Note: When a model contains an INCLUDE statement, then it cannot contain any DIMENSION statements. However, the model referenced in the INCLUDE statement or the root model in a hierarchy must contain the DIMENSION statements needed by the parent model(s). |
One or more SET commands or equations written following the "Rules for Equations in Models".
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See also: "Dimension Status and Model Equations" for information on how Oracle OLAP processes equations in a model. |
A final END statement that indicates the end of the model specification. (Omit when coding the specification in an Edit window of the OLAP Worksheet.)
The maximum number of lines you can have in a model is 4,000.
MODEL Statement in an Aggregation Specification
Within an aggmap, you can use a special MODEL statement to execute a predefined model. (See the MODEL (in an aggregation) statement under the AGGMAP command for more information.
Methods of Calculating Data Within a Variable
Both models and aggmap objects calculate data values within a variable based on relationships among dimension members. When a parent-child relationship exists among dimension members (that is, the dimension has a hierarchical structure) and all aggregate values can be calculated using the same method, then you can use a RELATION statement within an aggregation specification to calculate the values. However, when the dimension is not hierarchical and different equations are needed to calculate the values, then you must define a model. You can use a MODEL (in an aggregation) to execute the MODEL within an aggregation specification or you can run a model at the command line using the syntax shown in "Running a Model".
Deleting a Model Specification
You can remove the specification of a model without deleting the model definition. Consider the model with a CONSIDER statement. Then issue a MODEL statement and enter the word END as the model specification.
Examples
Example 10-55 Model Specified in a Program
In the following example, a simple model is created (or overwritten) in a program called myprog. The first line in the program defines or considers the model. The second line contains the MODEL statement, which provides the lines of the model.
This model calculates the line items in a budget. The model equations are based on a line dimension.
DEFINE myprog PROGRAM
PROGRAM
IF NOT EXISTS('myModel')
THEN DEFINE myModel
ELSE CONSIDER myModel
MODEL JOINLINES(-
'DIMENSION line month' -
'Opr.Income = Gross.Margin - Marketing' -
'Gross.Margin = Revenue - Cogs' -
'Revenue = LAG(Revenue, 1, month) * 1.02' -
'Cogs = LAG(Cogs, 1, MONTH) * 1.01' -
'Marketing = LAG(Opr.Income, 1, month) * 0.20' -
'END')
END
Example 10-56 Model from an Input File
This example presents the text of the same simple model, but it is stored in an ASCII disk file called budget.txt.
DEFINE income.budget MODEL MODEL DIMENSION line month Opr.Income = Gross.Margin - Marketing Gross.Margin = Revenue - Cogs Revenue = LAG(Revenue, 1, month) * 1.02 Cogs = LAG(Cogs, 1, month) * 1.01 Marketing = LAG(Opr.Income, 1, month) * 0.20 END
To include the income.budget model in your analytic workspace, execute the following statement in which myinpfiles is a directory object.
INFILE 'myinpfiles/budget.txt'
Example 10-57 Creating a Model
Suppose that you define a model, called income.calc, that calculates line items in the income statement.
define income.calc model ld Calculate line items in income statement
After defining the model, you can use a MODEL statement or the OLAP Worksheet editor to enter the specification for the model. A model specification can contain DIMENSION commands, assignment statements and comments. All the DIMENSION commands must come before the first equation. For the current example, you can specify the lines shown in the following model.
DEFINE INCOME.CALC MODEL LD Calculate line items in income statement MODEL DIMENSION line net.income = opr.income - taxes opr.income = gross.margin - (marketing + selling + r.d) gross.margin = revenue - cogs END
When you write the equations in a model, you can place them in any order. When you compile the model, either by issuing a COMPILE statement or by running the model, Oracle OLAP identifies the logical order in which the model equations are solved. When the calculated results of one equation are used as input to another equation, then the equations are solved in the order in which they are needed.
To run the income.calc model and use actual as the solution variable, you execute the following statement.
income.calc actual
When the solution variable has dimensions other than the dimensions on which model equations are based, then a loop is performed automatically over the current status list of each of those dimensions. For example, actual is dimensioned by month , division, and line. When division is limited to ALL, and month is limited to OCT96 to DEC96, then the income.calc model is solved for the three months in the status for each of the divisions.
Example 10-58 Building a Scenario Model
Suppose, for example, you want to calculate profit figures based on optimistic, pessimistic, and best-guess revenue figures for each division. The steps for building this scenario model are explained in the following example.
You can call the scenario dimension scenario and give it values that represent the scenarios you want to calculate.
These commands give scenario the values optimistic, pessimistic and bestguess.
DEFINE scenario DIMENSION TEXT LD Names of scenarios MAINTAIN scenario ADD optimistic pessimistic bestguess
These commands create a variable named plan dimensioned by three other dimensions (month, line, and division) in addition to the scenario dimension.
DEFINE plan DECIMAL <month line division scenario> LD Scenarios for financials
For this example, you must enter input data, such as revenue and cost of goods sold, into the plan variable.
For the best-guess data, you can use the data in the budget variable. Limit the line dimension to the input line items, and then copy the budget data into the plan variable.
LIMIT scenario TO 'BESTGUESS' LIMIT line TO 'REVENUE' 'COGS' 'MARKETING' 'SELLING' 'R.D' plan = budget
You might want to base the optimistic and pessimistic data on the best-guess data. For example, optimistic data might be fifteen percent higher than best-guess data, and pessimistic data might be twelve percent less than best-guess data. With line still limited to the input line items, execute the following commands.
plan(scenario 'OPTIMISTIC') = 1.15 * plan(scenario 'BESTGUESS') plan(scenario 'PESSIMISTIC') = .88 * plan(scenario 'BESTGUESS')
The final step in building a scenario model is to write a model that calculates results based on input data. The model might contain calculations very similar to those in the budget.calc model shown earlier in this chapter.
You can use the same equations for each scenario or you can use different equations. For example, you might want to calculate the cost of goods sold and use a different constant factor in the calculation for each scenario. To use a different constant factor for each scenario, you can define a variable dimensioned by scenario and place the appropriate values in the variable. When the name of your variable is cogsval, then your model might include the following equation for calculating the cogs line item.
cogs = cogsval * revenue
By using variables dimensioned by scenario, you can introduce a great deal of flexibility into your scenario model.
Similarly, you might want to use a different constant factor for each division. You can define a variable dimensioned by division to hold the values for each division. For example, when labor costs vary from division to division, then you might dimension cogsval by division and by scenario.
When you run your model, you specify plan as the solution variable. For example, when your model is called scenario.calc, then you solve the model with this statement.
scenario.calc plan
A loop is performed automatically over the current status list of each of the dimensions of plan. Therefore, when the scenario dimension is limited to ALL when you run the scenario.calc model, then the model is solved for all three scenarios: optimistic, pessimistic, and bestguess.
The DIMENSION statement at the beginning of a model tells Oracle OLAP the names of one or more dimensions to which the model assigns data or to which it refers in dimension-based equations. A dimension-based equation assigns the results of a calculation to a target that is represented by one or more values of a dimension.
Syntax
DIMENSION dimension1 [, dimensionN]
Parameters
One or more dimensions, including base dimensions of composites, on which model equations are based. You can specify the name of a dimension surrogate instead of the dimension for which is a surrogate. You can then use the values of the surrogate instead of the values of the dimension.
Usage Notes
Dimension-Based Equations in Models
When an equation (SET) assigns data to a dimension value or refers to dimension values in its calculations, it is called a dimension-based equation. Note that a dimension-based equation does not have to refer to the dimension itself, but only to the values of the dimension. Therefore, when the model contains any dimension-based equations, you must specify the name of each of these dimensions in a DIMENSION statement at the beginning of the model s that Oracle OLAP can determine the dimension to which each dimension value belongs. You can specify the name of a dimension surrogate instead of the dimension for which it is a surrogate. You can then use the values of the surrogate instead of the values of the dimension.
In addition, when a model contains any dimension-based equations, you must supply the name of a solution variable when you run the model. The solution variable is both the source and the target of data for the model. It holds the input data used in dimension-based calculations, and Oracle OLAP stores the calculation results in designated values of the solution variable. The solution variable is generally dimensioned by all the dimensions on which the model equations are based. For example, in a financial application, the model might be based on the line dimension, and the solution variable might be actual, which has line as one of its dimensions.
Dimension-based equations provide flexibility in modeling. Since you do not have to specify the modeling variable until you solve a model, you can run the same model with different solution variables. For example, you might run the same model with the actual variable, with a "best case" budget variable, and with a "worst case" budget variable.
A dimension must be specified in a DIMENSION statement when a dimension-based equation refers to a value of the dimension either as a source of the data used in the calculation or as the target to which the results are assigned. In the following example, Gross.Margin, Revenue, and Cogs are values of the line dimension, so line is specified in a DIMENSION statement.
DIMENSION line Gross.Margin = Revenue - Cogs
Dimension is a Function Argument
A dimension must be specified in a DIMENSION statement when the dimension is an argument to a function that uses a dimension value as its data source. In the following example, month must be specified in a DIMENSION statement.
DIMENSION line, month Revenue = lag(Revenue, 1, month) * 1.05
The writer of the preceding model expects to use a solution variable that is dimensioned by line and month. Therefore, when the model is run, the LAG function operates on a solution variable that has the specified time dimension (month) as one of its dimensions. However, since the model compiler cannot anticipate the time dimension of the solution variable, you must specify it in a DIMENSION statement. When you fail to include month in a DIMENSION statement, an error occurs when you attempt to compile the model.
In a function that operates on time-series data (such as MOVINGTOTAL or LAG), the dimension argument is optional when the dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. For example, you can omit month from the LAG function in the preceding example. However, you must still specify the appropriate time dimension in a DIMENSION statement.
Solution Variable
When you run a model that contains dimension-based equations, you specify a solution variable, which is both the source and the target of data for the model. The solution variable is generally dimensioned by all the dimensions that are listed in the DIMENSION commands used in the model. Or, when a solution variable is dimensioned by a composite, the DIMENSION commands can list base dimensions of the composite. The DIMENSION commands can be explicit in the model or inherited through an included model. See "Incompatibility with INCLUDE".
Working with Composites
When you expect to run a model with a solution variable that has a composite in its dimension list, you can specify a base dimension of the composite in a DIMENSION statement. Your model equations assign results to values of the base dimension. Oracle OLAP automatically creates any new values that are needed in the composite.
Multiple DIMENSION Commands
You can include a separate DIMENSION statement for every dimension referred to or used in dimension-based equations, or you can specify all the dimensions in a single DIMENSION statement.
Location of Commands
You must place all the DIMENSION commands at the beginning of the model, before any equations.
Incompatibility with INCLUDE
When a model contains an INCLUDE statement, it cannot contain any DIMENSION commands. The INCLUDE statement specifies another model to include in the current model. In this case, the current model inherits its DIMENSION commands, if any, from the included model. For more information in including models, see the INCLUDE statement under the MODEL command.
Inherited DIMENSION commands must satisfy all the requirements specified for explicit DIMENSION commands. See "Guidelines for Writing DIMENSION Statements in a Model".
Dimension Order
When multiple dimensions are specified by the DIMENSION commands in a model, the order in which the dimensions are listed is important:
When a model equation contains a name that might be a dimension value, Oracle OLAP searches through the dimensions that appear in the model's explicit or inherited DIMENSION commands, in the order you list the dimensions, to determine whether the name matches a dimension value of a listed dimension. The search concludes as soon as a match is found. Therefore, when two or more listed dimensions have a dimension value with the same name, Oracle OLAP assumes that the value belongs to the dimension specified earliest in a DIMENSION statement. When the name does not match a value of a listed dimension, Oracle OLAP then searches through the variables in the attached workspaces to find a match.
When model equations assign results to values of a target dimension, Oracle OLAP constructs code that loops over the values of the other, non-target, dimensions listed in the DIMENSION commands. The non-target dimension listed first in the DIMENSION commands is treated as the slowest-varying dimension. For example, when MONTH is the first non-target dimension listed in a DIMENSION statement and DIVISION is the second, Oracle OLAP loops through all the divisions for the first month, then all the divisions for the second month, and so on.
Guidelines for Writing DIMENSION Statements in a Model
When you write DIMENSION statements, keep these points in mind:
In the DIMENSION statements, you must list the names of all the dimensions on which model equations are based. In the following example, gross.margin, revenue, and cogs are values of the line dimension, so line is specified in a DIMENSION statement.
DIMENSION line gross.margin = revenue - cogs
DIMENSION statements must also list any dimension that is an argument to a function that refers to a dimension value. In the following example, month must be specified in a DIMENSION statement.
DIMENSION line, month revenue = LAG(revenue, 1, month) * 1.05
When a model equation assigns results to a dimension value, then code is constructed that loops over the values of any of the other nontarget dimensions listed in the DIMENSION statements. The nontarget dimension listed first in the DIMENSION statements is treated as the slowest-varying dimension.
A model executes most efficiently when you observe the following guidelines for coordinating the dimensions in DIMENSION statements and the dimensions of the solution variable:
List the target dimension of the model as the first dimension in the DIMENSION statements and as the last dimension in the definition of the solution variable.
In DIMENSION statements, list the nontarget dimensions in the reverse order of their appearance in the definition of the solution variable. Consequently, the fastest-varying and slowest-varying nontarget dimensions are in the same order in the model and in the solution variable.
When the solution variable has dimensions that are not used or referred to in model equations, then do not include them in DIMENSION statements.
When your analytic workspace contains a variable whose name is the same as a dimension value, or when the same dimension value exists in two different dimensions, then there could be ambiguities in your model equations. Since you can use a variable and a dimension value in the same way in a model equation, a name might be the name of a variable, or it might be a value of any dimension in your analytic workspace.
Your DIMENSION statements are used to determine whether each name reference in an assignment statement is a variable or a dimension value. "Compiling Models" explains how the name references are resolved.
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See Also: "OLAP DML Model Objects", SET, and MODEL for information on:
|
Examples
Example 10-59 Simplified Model for Budget Estimates
The following statements define a simplified model that estimates budget values for the items on an income statement.
DEFINE income.budget MODEL LD Model for estimating budget line items MODEL dimension line, month Revenue = 1.05 * LAG(Revenue 1 month) Gross.Margin = Revenue - Cogs Opr.Income = Gross.Margin - (Marketing + Selling + R.D) Net.Income = Opr.Income - Taxes END
The model equations are based on the line dimension, so line is specified in the DIMENSION statement. The dimension month is the time dimension in the LAG function that operates on REVENUE values, so month is also specified in the DIMENSION statement.
When you run the model, Oracle OLAP loops over the values in the current status of the month dimension.
The INCLUDE statement includes one model within another model. You can use the INCLUDE statement only within models.
Use INCLUDE to create modular models by placing equations that are common to several models, in a separate model for inclusion on other models as needed. The INCLUDE statement also facilitates what-if analyses. An experimental model can draw equations from a base model and selectively replace them with new equations
Syntax
INCLUDE model
Parameters
The name of a model to include in the current model. The current model is referred to as the parent model. The model that you include is referred to as the base model.
Usage Notes
Guidelines for Coding INCLUDE Statements in a Model
Follow these guidelines for using INCLUDE statements in models:
A model can contain only one INCLUDE statement.
The INCLUDE statement must be before any equations in the model.
A model that contains an INCLUDE statement cannot contain any DIMENSION statements.
How to Nest Models
You can nest models by placing an INCLUDE statement in a base model. For example, model myModel1 can include model myModel2, and model myModel2 can include model myModel3. The nested models form a hierarchy. In this example, myModel1 is at the top of the hierarchy, and myModel3 is at the root. A base model cannot include a model at a higher level in the hierarchy. In the preceding example, myModel2 cannot include myModel1, and myModel3 cannot include myModel1 or myModel2.
Dependencies Among Equations
When compiling a model that contains an INCLUDE statement, the compiler considers the dependencies among the equations from all the included models when it orders and blocks the equations. Therefore, when you run the MODEL.COMPRPT program to examine the results of the compilation or when you set the MODTRACE option to YES before running the parent model, you might find that equations from different levels in the hierarchy of included models are interspersed. See Example 10-61, "Producing a Compilation Report".
When the compiler finds no dependencies among the equations from the included models, it executes the equations in the root model first and the equations in the parent model last.
Compiling a Parent Model
When you compile a parent model, the compiler compiles all the base models under it in the included hierarchy when compiled code does not already exist. When the compiler detects an error in an included model, neither it nor any model above it in the hierarchy is compiled. When the root model of the included hierarchy contains an error, the higher-level models are unable to inherit any DIMENSION statements from the root model. In this case, the compiler might report an error in a parent model when the source of the error is actually in the root model. For example, the compiler might report that a target dimension value does not exist in any attached analytic workspace. On the other hand, when the compiler detects an error in a parent model but finds no errors in the included models, the included models are compiled even though the parent model is not.
Masking Equations
To support what-if analyses, Oracle OLAP allows equations in a model to mask prevRious equations. The previous equations can come from the same model or from included models. A masked equation is not executed. When you run the MODEL.COMPRPT program after compiling the model, the masked equation is not shown in the report on the compiled model.
Masking can take place when an equation assigns a value to a variable or dimension value that is also the target of a previous equation. The masking rules are as follows:
When the target in the earlier equation is qualified the same as the target in the later equation, the earlier equation is masked and the later equation is executed. The following example illustrates two equations with targets that are identically qualified.
Equation from a base model: BUDGET(LINE REVENUE) = 5000 Equation from the parent model: BUDGET(LINE REVENUE) = 3500
In this example, the equation from the base model is masked and the equation from the parent model is executed.
When the target in the earlier equation is more qualified than the target in the later equation, the earlier equation is masked. The later equation is executed.
The target that is more qualified is the one that affects the fewest dimension values. Consider the following equations from a base model and a parent model.
Equation from a base model: BUDGET(LINE REVENUE) = 2500 Equation from the parent model: BUDGET = 4000
The equation from the base model is more qualified because it assigns data only for the REVENUE value of the LINE dimension. The equation from the parent model assigns data to all the values of the LINE dimension. In this example, the equation from the base model is masked and the equation from the parent model is executed.
When the target in the earlier equation is less qualified than the target in the later equation, no masking takes place. Both equations are executed.
Consider the following equations from a base model and a parent model.
Equation from a base model: BUDGET = LAG(ACTUAL, 1, MONTH) Equation from the parent model: BUDGET(LINE REVENUE) = 6500 Equation from the parent model: BUDGET(LINE COGS) = 4000
The equation from the base model assigns data to all the values of the LINE dimension. The equations from the parent model are more qualified because each assigns data only for a single value of the LINE dimension. In this example, the equation from the base model is executed first, and then the equations from the parent model are executed.
This functionality enables you to assign a large number of values with one equation and use subsequent equations to replace or test individual values.
When the target in the earlier equation is qualified differently from the target in the later equation, no masking takes place. Both equations are executed. In the following example, both equations are executed.
Equation from a base model: BUDGET(LINE REVENUE) = 5000 Equation from the parent model: BUDGET(LINE COGS) = 4500
Examples
Example 10-60 Including a Model
This example shows a parent model named income.plan that includes a base model named base.lines.
DEFINE income.plan MODEL MODEL INCLUDE base.lines revenue = LAG(revenue, 1, month) * 1.02 cogs = LAG(cogs, 1, month) * 1.01 taxes = 0.3 * opr.income END DEFINE BASE.LINES MODEL MODEL DIMENSION line month net.income = opr.income - taxes opr.income = gross.margin - marketing gross.margin = revenue - cogs END
Example 10-61 Producing a Compilation Report
The following statements compile the parent model and produce a compilation report.
COMPILE income.plan MODEL.COMPRPT income.plan
These statements produce the following output.
MODEL INCOME.PLAN <LINE MONTH>
BLOCK 1 (SIMPLE)
INCOME.PLAN 2: revenue = lag(revenue, 1, month) * 1.02
INCOME.PLAN 3: cogs = lag(cogs, 1, month) * 1.01
BASE.LINES 4: gross.margin = revenue - cogs
BASE.LINES 3: opr.income = gross.margin - marketing
INCOME.PLAN 4: taxes = 0.3 * opr.income
BASE.LINES 2: net.income = opr.income - taxes
END BLOCK 1
The DIVIDEBYZERO option controls the result of division by zero. (Note that division by zero includes raising zero to a negative power; for example, 0 ** -2.)
Data Type
BOOLEAN
Syntax
DIVIDEBYZERO = YES|NO
Parameters
Allows division by zero. A statement involving division by zero executes without error; however, the result of the division by zero is NA. When you are dividing by a dimensioned variable or expression, setting DIVIDEBYZERO to YES enables you to get results for most of the expression's values when a few calculations might involve dividing by zero.
(Default) Disallows division by zero. A statement involving division by zero stops executing and produces an error message.
Examples
Example 5-24 The Effect of DIVIDEBYZERO
This example shows the effect of changing the value of the DIVIDEBYZERO option.
When you execute a SHOW statement, such as the following, without changing the DIVIDEBYZERO option from its default value of NO, Oracle OLAP attempts to divide 100 by 0 and then produces an error message.
SHOW 100 / 0
When you change DIVIDEBYZERO to YES, the same statement executes without error and produces NA as the result of the division. The statements
DIVIDEBYZERO = YES SHOW 100 / 0
produce the following result.
NA
The ADVISE_DIMENSIONALITY function returns an OLAP DML definition of a composite dimension and the dimension order for variables in the cube, based on the sparsity recommendations generated by the ADVISE_SPARSITY procedure for a particular partition.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
ADVISE_DIMENSIONALITY (
cubename IN VARCHAR2,
sparsedfn OUT VARCHAR2
sparsename IN VARCHAR2 DEFAULT NULL,
partnum IN NUMBER DEFAULT 1,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Parameters
Table B-4 ADVISE_DIMENSIONALITY Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) in which the definition of the composite dimension is stored. |
|
|
An object name for the composite. The default value is |
|
|
The number of a partition. By default, you see only the definition of the first partition. |
|
|
The name of a table created by the |
Example
The following PL/SQL program fragment defines two variables to store the recommendations returned by the ADVISE_DIMENSIONALITY function. SPARSEDIM stores the definition of the recommended composite, and DIMLIST stores the recommended dimension order of the cube.
DECLARE
sparsedim VARCHAR2(500);
dimlist VARCHAR2(500);
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dimlist := dbms_aw.advise_dimensionality('units_cube', sparsedim);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
dbms_output.put_line('Dimension list: ' || dimlist);
END;
/
The program uses DBMS_OUTPUT.PUT_LINE to display the results of the analysis. The Sparsity Advisor recommends a composite dimension for the sparse dimensions, which are PRODUCT, CUSTOMER, and TIME. The recommended dimension order for UNITS_CUBE is CHANNEL followed by this composite.
Sparse dimension: DEFINE units_cube.cp COMPOSITE <product customer time> Dimension list: channel units_cube.cp<product customer time>
The next example uses the Sparsity Advisor to evaluate the SALES table in the Sales History sample schema. A WHILE loop displays the recommendations for all partitions.
DECLARE
dimlist VARCHAR2(500);
sparsedim VARCHAR2(500);
counter NUMBER(2) := 1;
maxpart NUMBER(2);
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
SELECT MAX(partnum) INTO maxpart FROM sh_sparsity_advice;
WHILE counter <= maxpart LOOP
dimlist := dbms_aw.advise_dimensionality('sales_cube', sparsedim,
'sales_cube_composite', counter, 'sh_sparsity_advice');
dbms_output.put_line('Dimension list: ' || dimlist);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
counter := counter+1;
END LOOP;
dbms_aw.advise_dimensionality(defs,'sales_cube', 'sales_cube_composite',
'DECIMAL', 'sh_sparsity_advice');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The Sparsity Advisor recommends 11 partitions; the first ten use the same composite. The last partition uses a different composite. (The SH_SPARSITY_ADVICE table shows that TIME_ID is dense in the last partition, whereas it is very sparse in the other partitions.)
Dimension list: sales_cube_composite<time channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <time channel product promotion customer>
Dimension list: sales_cube_composite<time channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <time channel product promotion customer>
.
.
.
Dimension list: time sales_cube_composite<channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <channel product promotion customer>
The NLS_SORT option specifies the sequence of character values used when sorting or comparing text. The value of NLS_SORT affects the GT, GE, LT, and LE operators, SORT command, and the SORTLINES function.
Within a session, you can dynamically modify the value of this option using the OLAP DML syntax show below or by using the SQL statement ALTER SESSION SET option = value.
Data Type
TEXT
Syntax
NLS_SORT = option-value
Parameters
See Oracle Database Globalization Support Guide for more information about the NLS_SORT parameter.
Examples
Example 5-78 Binary and Linguistic Sorts
A dimension named words has the following values.
cerveza, Colorado, cheremoya, llama, luna, lago
This example shows the results of a binary sort.
NLS_SORT = 'BINARY' SORT words A words STATUS words The current status of WORDS is: Colorado, cerveza, cheremoya, lago, llama, luna
A Spanish language sort results in this order.
NLS_SORT = 'SPANISH' SORT words A words STATUS words The current status of WORDS is: cerveza, cheremoya, Colorado, lago, llama, luna
An extended Spanish language sort results in this order.
NLS_SORT = 'XSPANISH' SORT words A words STATUS words The current status of WORDS is: cerveza TO cheremoya, lago TO llama
The HIERCHECK function checks the hierarchy in the specified relation or all of the relations of the specified aggmap to see if there is any circularity. A hierarchical dimension's parent relation specifies the parent for each of the dimension's values. (Circularity occurs when a dimension value has inadvertently been specified as its own ancestor or descendant in the parent relation. )
You can also specify that HIERCHEK check the hierarchy for other conditions.
Return Value
BOOLEAN
Syntax
As Command
HIERCHECK parent-relation [STATUS|NOSTATUS|valueset-name] [MULTIPATH] [CONSISTENT]-
[BALANCED levelrelation-name]
or
HIERCHECK aggmap-name [MULTIPATH] [CONSISTENT]levelrelation-name]
Parameters
A text expression indicating the name of the parent relation to be checked.
A text expression indicating the name of the aggmap. HIERCHECK checks all of the relations in the aggmap.
Specifies that HIERCHECK uses the current status of the relation dimension.
Specifies the values of the relation dimension that HIERCHECK considers in status.
Specifies that HIERCHECK uses the default status of the relation dimension.
Specifies that HIERCHECK checks whether there are multiple paths from any child to its parent.
Specifies that HIERCHECK checks whether the hierarchy is consistent. If the hierarchy is consistent, that means all nodes in the different hierarchies should have the same children.
Using the level relation identified by levelrel-name, specifies that HIERCHECK checks to see if all of the following are true:
All of the elements of a hierarchy which have an NA level are either roots with no leaves or leaves.
All of the elements of a hierarchy at the same (non NA) level have the same depth from the root (roots) of the hierarchy.
Elements of a hierarchy for different levels (non NA) have a different depth.
Usage Notes
Why Use HIERCHECK
It is a good strategy to use HIERCHECK at the time you build your hierarchies as a way to verify that they are valid. In other words, do not attempt to roll up a variable's data unless you have verified that its dimensions' hierarchies are structured correctly. For example, the AGGREGATE command uses HIERCHECK to prevent infinite looping once the statement has been executed. Check a parent relation for loops after you set up the levels of a hierarchical dimension, before you load data into any variable that is dimensioned by the hierarchical dimension, or before you use the AGGREGATE command for the first time with a variable. Although it is possible to roll up a variable without first having checked the parent relations of all of its hierarchical dimensions with HIERCHECK, make it a practice to use HIERCHECK first.
Status When Using HIERCHECK with an Aggmap
When there is any valueset inside a relation in aggmap, HIERCHECK uses this valueset to determine the status of the dimension of the relation. In all other cases, HIERCHECK uses the default status of the relation dimension.
For all dimensions other than relation dimensions, HIERCHECK uses the current status of the dimension.
Error Messages Triggered by HIERCHECK
When you use HIERCHECK, it signals an error when it finds a loop in the parent relation and stops execution (that is, HIERCHECK always stops in the first error message). The error message identifies the dimension values that are involved in the loop, the name of the hierarchy (referred to as the "extra dimension values") in which the loop occurs (when the parent relation has one or more named hierarchies), and the name of the parent relation in which the loop was found. When a parent relation has no loops, no message is displayed. See Example 7-108, "Checking for Loops".
Examples
Example 7-108 Checking for Loops
This example shows how to create a parent relation and check it for loops. You would begin by defining a dimension and adding values to it.
DEFINE geography DIMENSION ID MAINTAIN geography ADD 'U.S.' MAINTAIN geography ADD 'East' 'Central' 'West' MAINTAIN geography ADD 'Boston' 'Atlanta' 'Chicago' 'Dallas' 'Denver' 'Seattle'
Next, relate the dimension to itself. The following statement defines a parent relation called GEOG.GEOG, which relates the GEOGRAPHY dimension to itself.
define geog.geog RELATION geography <geography>
You would then specify the hierarchy of the dimension values. In this example, there are three levels in the hierarchy: country, regions, and cities. When you specify the hierarchy, you assign parent dimension values (such as East) to child dimension values (such as Boston) for every level except the highest level. To do this, you store values in the relation. First, group the children with a LIMIT command, then assign a parent to those children.
LIMIT geography TO 'East' 'Central' 'West' geog.geog = 'U.S.' LIMIT geography TO 'Boston' 'Atlanta' geog.geog = 'East' LIMIT geography TO 'Chicago' 'Dallas' geog.geog = 'Central' LIMIT geography TO 'Denver' 'Seattle' geog.geog = 'West'
Now you can check for loops in the parent relation geog.geog, as shown by the following statement.
HIERCHECK geog.geog
In this case, HIERCHECK produces no message output, which means there are no loops in geog.geog. It sets HIERCHK.LOOPFND to NO, and leaves HIERCHK.LOOPVALS and HIERCHK.XTRADIMS set to NA.
Now suppose the following mistake had been made in the storing of values in the relation.
LIMIT geography TO 'East' 'Central' 'West' geog.geog = 'East'
The preceding statements inadvertently make East its own parent, which would cause an aggregation to loop infinitely. When you now check the geog.geog relation for loops, the following statement produces the following error message.
HIERCHECK geog.geog ERROR: HIERCHECK has detected one or more loops in the hierarchy represented by GEOG.GEOG. The values involved are 'East'.
The NUMBYTES function counts the number of bytes in a text expression. When the value is a multiline text value, NUMBYTES returns the total number of bytes in all the lines. The result returned by NUMBYTES has the same dimensions as the specified expression.
Return Value
INTEGER
Syntax
NUMBYTES(text-expression)
Parameters
The TEXT expression whose bytes are to be counted.
Examples
Example 8-42 Counting the Bytes in the Longest Name
You would like to know the length of the names of your products so you can specify the appropriate width for the label column in a report. You can use the NUMBYTES function in combination with the LARGEST function to find the length of the longest label. Then use that value to set the column size. The following statements in a program find the longest name and use the byte count to format a report.
firstcol = LARGEST(NUMBYTES(name.product))+1
LIMIT month TO FIRST 3
FOR product
DO
ROW WIDTH FIRSTCOL name.product WIDTH 6 ACROSS month -
FIRST 3: units
DOEND
When the program is run, it produces the following output.
3-Person Tents 200 203 269 Aluminum Canoes 347 400 482 Tennis Racquets 992 1,076 1,114 Warm-up Suits 1,096 1,214 1,294 Running Shoes 2,532 2,405 2,775
The CHGDIMS function changes the dimensionality of an expression or changes the dimension status during the evaluation of expression.
Return Value
Data type of the original expression.
Syntax
CHGDIMS (expression, limit-type)
where limit-type is one of the following:
[CACHE] LIMITSAVE valueset-list
[CACHE] LIMIT valueset-list
TO dimension-list
ADD dimension-list
Parameters
The expression you want to modify.
Specifies that Oracle OLAP caches the result of the limit and saves it for use in subsequent executions of CHGDIMS until the OLAP DML statement that called CHGDIMS finishes execution.
Specifies that Oracle OLAP sets the value of dimension status for expression to the position before the CHGDIMS command executed (that is, specifying LIMITSAVE does not change the current dimension status value). For example, you specify CHGDIMS with LIMITSAVE if expression is the LAG function so that the lag is from the current value; or if you are coding CHGDIMS inside of an outer loop, like a SQL SELECT statement, and you want to keep the dimension status value set by the outer loop.
Specifies the Oracle OLAP sets the value of dimension status for expression to the first position in the new status before evaluating expression in much the same way as if a LIMIT TO command was issued just before evaluating expression.
The name of a valueset or a LIMIT function.
Specifies that Oracle OLAP evaluate expression as though the dimensions of expression are the dimensions specified by dimension-list.
Specifies that Oracle OLAP evaluateexpression as though the dimensions of expression are the dimensions of expression plus the dimensions specified by dimension-list
Examples
Assume that you have the following objects in your analytic workspace.
DEFINE PRODUCT DIMENSION TEXT DEFINE GEOG DIMENSION TEXT DEFINE SALES VARIABLE INTEGER <PRODUCT GEOG>
Assume, also, that the sales variable has the following values.
-------------------SALES-------------------
------------------PRODUCT------------------
GEOG Trousers Skirts Dresses Shoes
-------------- ---------- ---------- ---------- ----------
USA 13 20 32 18
Canada 17 32 15 28
The following lines of code show how the value returned by a TOTAL(sales) expression varies depending on how you qualify that expression.
"Total over all dims with standard status SHOW TOTAL(sales) 175 "Total over all dims using new status for product SHOW CHGDIMS(TOTAL(sales) LIMIT(product TO FIRST 2))) 82 "Total just over product SHOW TOTAL(CHGDIMS(sales TO product)) 83
Used for debugging and testing variables defined with null tracking, the function identifies if a value is a NA2 value or a non-NA value.
Return Values
INTEGER
0 for a non-NA value, 2 if the NA value is an NA2 value, or 1 for all other NA values
Syntax
NAFLAG (expression)
Parameters
An OLAP DML expression.
Examples
The ADVISE_SPARSITY procedure analyzes a fact table for sparsity using information about its dimensions provided by the ADD_DIMENSION_SOURCE procedure. It populates a table created by the SPARSITY_ADVICE_TABLE procedure with the results of its analysis.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Output Description
Table B-9 describes the information generated by ADVISE_SPARSITY.
Table B-9 Output Column Descriptions
| Column | Data Type | NULL | Description |
|---|---|---|---|
|
|
|
|
The values of cubename in calls to |
|
|
|
|
The values of fact in calls to |
|
|
|
|
The logical names of the cube's dimensions; the dimensions described in calls to |
|
|
|
The names of dimension columns in fact (the source fact table), which relate to a dimension table. | |
|
|
|
The names of the dimension tables. | |
|
|
|
The total number of dimension members at all levels. | |
|
|
|
The number of dimension members at the leaf (or least aggregate) level. | |
|
|
|
|
The sparsity evaluation of the dimension: |
|
|
|
|
The recommended order of the dimensions. |
|
|
|
A number that provides an indication of sparsity relative to the other dimensions. The larger the number, the more sparse the dimension. | |
|
|
|
|
The number of the partition described in the |
|
|
|
A list of all dimension members that should be stored in this partition. This list is truncated in SQL*Plus unless you significantly increase the size of the | |
|
|
|
A list of top-level dimension members for this partition. |
Syntax
ADVISE_SPARSITY (
fact IN VARCHAR2,
cubename IN VARCHAR2,
dimsources IN dbms_aw$_dimension_sources_t,
advmode IN BINARY_INTEGER DEFAULT ADVICE_DEFAULT,
partby IN BINARY_INTEGER DEFAULT PARTBY_DEFAULT,
advtable IN VARCHAR2 DEFAULT NULL);
Parameters
Table B-10 ADVISE_SPARSITY Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of the source fact table. |
|
|
A name for the facts being analyzed, such as the name of the logical cube in the analytic workspace. |
|
|
The name of the object type where the |
|
|
The level of advise you want to see. Select one of the following values: DBMS_AW.ADVICE_DEFAULTDBMS_AW.ADVICE_FASTDBMS_AW.ADVICE_FULL |
|
|
A keyword that controls partitioning. Use one of the following values:
|
|
|
The name of a table created by the procedure for storing the results of analysis. |
Example
The following PL/SQL program fragment analyzes the sparsity characteristics of the UNITS_HISTORY_FACT table.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE for each dimension in the cube
.
.
.
dbms_aw.advise_sparsity('units_history_fact', 'units_cube', dimsources,
dbms_aw.advice_default);
END;
/
The following SELECT command displays the results of the analysis, which indicate that there is one denser dimension (CHANNEL) and three comparatively sparse dimensions (PRODUCT, CUSTOMER, and TIME).
SELECT fact, dimension, dimcolumn, membercount nmem, leafcount nleaf, advice, density
FROM aw_sparsity_advice
WHERE cubename='units_cube';
FACT DIMENSION DIMCOLUMN NMEM NLEAF ADVICE DENSITY
-------------------- ------------ ------------ ----- ------ ------------ ----------
units_history_fact channel channel_id 3 3 DENSE .86545382
units_history_fact product item_id 36 36 SPARSE .98706809
units_history_fact customer ship_to_id 61 62 SPARSE .99257713
units_history_fact time month_id 96 80 SPARSE .99415964
The ALLOCERRLOGHEADER option determines the column headings for the error log that you specify with the ERRORLOG argument to the ALLOCATE command. To specify additional formatting for the error log, use the ALLOCERRLOGFORMAT option.
Syntax
ALLOCERRLOGHEADER = text
Parameters
Characters that determine the content and formatting of the column headers that are the first line of the error log that you specify with the ALLOCATE command. (See ALLOCERRLOGFORMAT for a list of the characters you can use.)
When you specify NA as the value for this option, then ALLOCATE does not write any header to the error log. The following is the default value of ALLOCERRLOGHEADER.
'Dim Source Basis\n%-8d %-8v %-8b Description\n -------- -------- -------- -----------'
Examples
Example 5-2 Setting the ALLOCERRLOGHEADER Option
The following statements define the heading for the error log specified by an ALLOCATE statement and show the value of the ALLOCERRLOGHEADER option.
ALLOCERRLOGHEADER = 'Dim Source Basis\n %-8d %-8v %-8b Description \n -------- -------- -------- -----------' SHOW ALLOCERRLOGHEADER
The preceding statement produces the following results.
Dim Source Basis %-8d %-8s %-8b Description -------- -------- -------- -----------
An allocation operation that has a variable named budget as both the source and basis objects and which encounters a deadlock when allocating down the division dimension produces the following entry in the error log.
Dim Source Basis Division Budget Budget Description -------- -------- -------- ----------- Accdiv 650000 NA A deadlock occurred allocating data (5)
(Read-only) The SQLCODE option holds the value returned by the Oracle RDBMS after the most recently attempted SQL operation.
Return Value
INTEGER. 0 after a successful operation, -1 after an error, or 100 after all requested rows have been fetched.
Syntax
SQLCODE
Usage Notes
Handling SQL Errors
Oracle OLAP does not signal an error when SQLCODE becomes nonzero. Therefore, your program must test the value of SQLCODE and take the appropriate action. Since each SQL operation sets SQLCODE, you must test for errors after each operation to avoid missing an error condition.
|
Tip: After an error, the SQLERRM option typically contains an error message. |
You can write programs that look for a specific error code. For example, the most common warning code is 100, which indicates that the cursor reached the end of its table selection and the FETCH statement is complete.
Examples
The PAGESIZE option specifies the size of a page of output. The value of PAGESIZE is the number of output lines to be produced on each page. PAGESIZE is usually used in the initialization section of report programs. The PAGESIZE option is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and LISTNAMES. PAGESIZE also controls the LINELEFT option. When PAGESIZE is changed, Oracle OLAP adjusts LINELEFT accordingly.
Data Type
INTEGER
Syntax
PAGESIZE = n
Parameters
An INTEGER expression that specifies the number of output lines on a page; n includes the top and bottom margins (controlled by the TMARGIN and BMARGIN options). The default is 66 lines, which is suitable for printing report output on 8 1/2" by 11" paper.
Usage Notes
Usable Output Lines with Standard Heading and Default Settings
When you use the standard heading and the default settings for the PAGESIZE, TMARGIN, and BMARGIN options, the total number of usable output lines is 61.
Output Lines
Lines from PAGESIZE 66
Lines for TMARGIN - 2
Lines for the standard heading - 2
Lines for BMARGIN - 1
Lines available for output 61
Eliminating Headings and Page Breaks
You can produce pages with no headings by using the statement PAGEPRG='NONE' or suppress page breaks entirely by using the statement PAGING = NO.
Setting PAGESIZE for a File
To set PAGESIZE for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set PAGESIZE to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, PAGESIZE returns to its default value of 66 for the file.
When you set PAGESIZE for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE commands that send output to a file. That is, the value of PAGESIZE is automatically saved for the default outfile.
Examples
The TRUNCATE function (abbreviated as TRUNC) truncates either a number or a datetime value. Because the syntax of the TRUNC function is different depending on the whether it is being used for a number or a date and time value, two separate entries are provided:
The TRUNCATE (datetime) function returns date with the time portion of the day truncated to the unit specified by the format model.
Return Value
DATETIME
Syntax
TRUNC (datetime_exp, [fmt])
Parameters
A datetime expression that identifies a date and time number.
A text expression that specifies a format model shown in Table 8-13, "Datetime Format Templates for the ROUND and TRUNC Date Functions". A format model indicates how the date and time number should be truncated. If you omit fmt, then date is truncated to the nearest day.
Examples
Example 8-152 Truncating to the Nearest Year
When the value of the NLS_DATE_FORMAT option is DD-MON-YY, then this statement:
SHOW TRUNC (TO_DATE('27-OCT-92'),'YEAR')
returns this value:
01-JAN-92
Example 8-153 Truncating Using Different Formats
Assume the following option values, variables, and values are in your analytic workspace.
SHOW NLS_DATE_FORMAT DD-MON-RR DEFINE MYDATETIME VARIABLE DATETIME DATE_FORMAT = 'MON-RRRR-DD-HH24' mydatetime = CURRENT_TIMESTAMP SHOW mydatetime = 'AUG-2006-07-14'
As the following SHOW statements illustrate, the value you specify for the format argument of TRUNCATE function determines the value returned by that function.
SHOW TRUNCATE(mydatetime, 'MON') 01-AUG-06 SHOW TRUNCATE(mydatetime, 'DD') 07-AUG-06 SHOW TRUNCATE(mydatetime) = 'AUG-2006-07-00'
When you specify a number as an argument, the TRUNCATE function truncates a number to a specified number of decimal places.
Return Value
DECIMAL
Syntax
TRUNC (number, truncvalue)
Parameters
The number to truncate. The value specified for number must be followed by a comma.
An INTEGER value that specifies the number of places to the right or left of the decimal point to which number should be truncated. When truncvalue is positive, digits to the right of the decimal point are truncated. When it is negative, digits to the left of the decimal point are truncated (that is, made zero). When truncvalue is omitted, number is truncated to 0 decimal places.
Examples
The INTERP function executes one or more OLAP DML commands and returns the session log in which the commands are executed. It is typically used in applications when the 4K limit on output for the EXECUTE procedure may be too restrictive.
Input to the INTERP function is limited to 4K. For larger input values, refer to the INTERPCLOB function of this package.
This function does not return the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
You can use the INTERP function as an argument to the PRINTLOG procedure in this package to view the session log. See the example.
|
Note: You cannot execute this function from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
INTERP (
olap-commands IN VARCHAR2)
RETURN CLOB;
Parameters
Table B-24 INTERP Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
Returns
The log file for the Oracle OLAP session in which the OLAP DML commands were executed.
Example
The following sample SQL*Plus session attaches the GLOBAL analytic workspace and lists the members of UNITS_CUBE.
SET serverout ON EXECUTE dbms_aw.printlog(dbms_aw.interp('AW ATTACH global; REPORT units_cube')); UNITS_CUBE -------------- TIME CUSTOMER PRODUCT CHANNEL
The SYSINFO function provides information about the Oracle user ID for the current session.
Return Value
TEXT
Syntax
SYSINFO (keyword)
where keyword is one of the following:
Parameters
Returns a TEXT value that indicates the user ID under which the Oracle Database session is running which is the same value that is returned by USERID.
Returns a multiline TEXT value that lists the roles that apply to the user ID of the session.
Returns a multiline TEXT value that lists the profiles that apply to the user ID of the session.
Returns TEXT value that indicates the operating system user name under which the Oracle Database server is running.
Returns a TEXT value that is the instance name of the Oracle Database server.
Returns a TEXT value that is the operating system id number of your Oracle Database session.
Returns a TEXT value that is the host name of the Oracle Database server.
Returns a TEXT value that is identifies the client which is connecting to the Oracle Database.
Returns a TEXT value that is the host name of the client.
Returns a TEXT value that is the operating system user name of the client.
Returns a TEXT value that is the terminal name of the client.
Examples
(Read-only) The TRACEFILEUNIT option records the unit number of the Oracle trace file which is a writable output file that collects information about the activity in the Oracle session.
Syntax
TRACEFILEUNIT
Usage Notes
Use of the TRACEFILEUNIT Value
The unit number stored in the TRACEFILEUNIT option can be useful because you might want to set the POUTFILEUNIT option to its value. You might also set the OUTFILE or DBGOUTFILE options to this number.
Examples
The TO_BINARY_DOUBLE function converts a text or numeric expression to a DECIMAL numeric expression.
Return Value
DECIMAL
Syntax
TO_BINARY_DOUBLE(expr [, fmt [, nlsparam ] ])
Parameters
A text or numeric expression. When expr is a text expression, the function converts the following case-insensitive values to particular values:
INF to positive infinity
-INF to negative infinity
NaN to NaN (not a number)
A text expression that specifies a number format model. This argument is valid only when expr is a text expression.
The default number format model uses the decimal and thousands group markers identified by NLS_NUMERIC_CHARACTERS.
|
Note: You cannot use a floating-point number format element (F, f, D, or d) in a text expression. |
A text expression that specifies how the function uses the thousands group marker, decimal marker, and currency symbols when converting a text expression. This argument is valid only when expr is a text expression. This expression contains one or more of the following parameters, separated by commas:
NLS_CURRENCY symbol
NLS_ISO_CURRENCY territory
NLS_NUMERIC_CHARACTERS dg
The MAXFETCH option sets an upper limit on the size of a data block generated by a FETCH statement specified in the OLAP_command parameter of the OLAP_TABLE function.
|
See also: For more information on using FETCH statements, see FETCH command. For more information on theOLAP_TABLE function, see Appendix A, "OLAP_TABLE SQL Functions". |
Return Value
INTEGER
Syntax
MAXFETCH = integer-expression
Parameters
An INTEGER expression representing the maximum size in bytes of a data block generated by FETCH. The minimum value for MAXFETCH is 1K (approximately 1,000 bytes), and the maximum value is 2GB (approximately 2,000,000,000 bytes). The default value of MAXFETCH is 256K.
Usage Notes
Improving Performance of Queries Using OLAP_TABLE
The setting of MAXFETCH can effect the performance of queries using the OLAP_TABLE function. Large queries with joins of OLAP_TABLE function may run faster with higher settings. However, larger settings use more memory which can cause slower performance when there are multiple users. The setting of MAXFETCH does not affect a SELECT using only one OLAP_TABLE function.
MAXFETCH can cause a FETCH error
When FETCH cannot package a data block within the size limit set by MAXFETCH, it produces an error, and no data is returned to the client. By setting MAXFETCH, you can produce an error, rather than run out of memory, when you attempt to fetch too much data.
Examples
Limiting Data Blocks to 4K
The following statement limits the size of data blocks to 4K.
MAXFETCH = 4096
The STATUS program sends to the current outfile the status of one or more dimensions, dimension surrogates, or valuesets, or the status of all dimensions in an analytic workspace.
When you specify one or more dimension, dimension surrogate, or valueset names, Oracle OLAP produces the status of only those objects. When you use the AW keyword and specify the name of an attached analytic workspace, Oracle OLAP produces the status of every dimension in that analytic workspace. When you do not specify any argument, STATUS produces the current status of all the dimensions (not dimension surrogates or valuesets) in the current analytic workspace. However, STATUS does not display the status of the NAME dimension unless you specify STATUS NAME.
|
Tip: Use STATLIST rather than STATUS when you want to control the width or placement of the display. |
Return Value
TEXT
Syntax
STATUS name... | AW [workspace-name]
Parameters
The name of a dimension or valueset in the analytic workspace. You can also specify the name of a dimensioned analytic workspace object, such as a variable, formula, relation, or named composite. In this case, the status of each dimension of name is produced, unless the dimension is included in an unnamed composite.
Specifies that STATUS should produce the status of every dimension in workspace-name; workspace-name is the name of an analytic workspace.
Usage Notes
STATUS Output
When all values of a dimension are in the current status or in a valueset, in the original order, STATUS displays ALL. STATUS shortens any series of three or more values in their original order to value-1 TO value-n. In the case of the dimension NAME, however, STATUS does not shorten a series of three or more values.
Status When an Object Has No Values
When a dimension, dimension surrogate, or valueset has no values (for example, a recently defined object for which you have not yet supplied values), STATUS produces NULL for that dimension, dimension surrogate, or valueset. When you are in an analytic workspace in which no objects have been defined, STATUS produces the message, There are no dimensions in your current analytic workspace.
Examples
Example 10-150 Discovering the Current Status of Certain Dimensions
Use STATUS to produce the current status of the dimensions month and district.
The following statement
STATUS month district
produces this output.
The current status of MONTH is: Jan95 TO Dec96 The current status of DISTRICT is: Boston, Chicago, Denver
Example 10-151 Discovering the Status of the Dimensions of a Variable
Use STATUS to produce the current status of all the dimensions of the variable sales.
The following statement
STATUS sales
produces this output.
The current status of MONTH is: Jan95 TO Dec96 The current status of PRODUCT is: ALL The current status of DISTRICT is: Boston, Chicago, Denver
The DBTIMEZONE function returns the value of the Database time zone.
Return Values
A time zone offset (a character type in the format '[+|-]TZH:TZM') or a time zone region name, depending on how the user specified the database time zone value in the most recent CREATE DATABASE or ALTER DATABASE statement.
Syntax
DBTIMEZONE
Examples
The FORECAST.REPORT program produces a standard report of a forecast created using the FORECAST command.
The report shows the parameters of the forecast, including the forecast formula and Mean Absolute Percent Error, followed by a display of the forecasted values.
Syntax
FORECAST.REPORT
Examples
Example 9-141 Report of Forecast Using the EXPONENTIAL Method
Assume that you have performed the forecast illustrated in Example 9-139, "Using the EXPONENTIAL Method". Running the FORECAST.REPORT program for that forecast produces the following report.
Forecasting Analysis
====================
Variable to Forecast: SALES
Forecast dimension: MONTH
Forecast method: EXPONENTIAL
Mean absolute percent error: 16.64%
Forecast Equation: SALES = 87718.0009541883 *
(1.00553383457899 ** MONTH)
MONTH Actual Value Fitted Value
-------------------- ------------ ------------
Jan95 72,123.47 88,203.42
Feb95 80,071.75 88,691.52
Mar95 78,812.69 89,182.33
Apr95 97,413.26 89,675.85
May95 94,406.65 90,172.10
... ... ...
Dec96 72,095.02 100,140.38
... ... ...
Example 9-142 Report of Forecast Using the WINTERS Method
Assume that you have performed the forecast illustrated in Example 9-140, "Using the WINTERS Method". Running the FORECAST.REPORT program for that forecast produces the following report.
Forecasting Analysis
====================
Variable to Forecast: SALES
Forecast dimension: MONTH
Forecast method: WINTERS
Alpha: 0.50
Beta: 0.50
Gamma: 0.50
Periodicity: 12
Mean absolute percent error: 0.20%
MONTH Actual Value Fitted Value
-------------------- ------------ ------------
Jan95 72,123.47 72,154.67
Feb95 80,071.75 80,027.51
Mar95 78,812.69 79,171.08
Apr95 97,413.26 97,200.81
May95 94,406.65 94,464.71
.... ... ...
Dec97 77,867.23
This chapter contains the following topics:
One topic for each of the OLAP DML system properties, arranged alphabetically beginning with $AGGMAP.
For other reference topics for the OLAP DML, see Chapter 5, "OLAP DML Options", Chapter 7, "OLAP DML Functions: A - K", Chapter 7, "OLAP DML Functions: A - K", Chapter 9, "OLAP DML Commands: A-G", and Chapter 10, "OLAP DML Commands: H-Z".
A property is a named value that is associated with a definition of an analytic workspace object. You can name, create, and assign properties to an object using an OLAP DML PROPERTY command.
Properties that begin with a $ (dollar sign) are recognized by Oracle OLAP as system properties. You cannot create system properties; however, in some cases you can assign system properties to objects. In particular, you can assign system properties that interact with the OLAP DML.
The OLAP DML provides system properties that set or retrieve values that influence how the OLAP DML performs the following:
Aggregation Properties
Allocation Property
Grouping Id Properties
Formula Properties
Language Property
NA Value Properties
Depending on the syntax you specify, the ROUND function performs a numeric operation or a date and time operation. Because the syntax for the ROUND function differs for each type of operation, there are two topics for the ROUND function:
The ROUND (datetime) function returns date rounded to the unit specified by the format model fmt. The value returned is always of data type DATETIME, even if you specify a different datetime data type for date.
Return Value
DATETIME
Syntax
ROUND(datetime_exp, [format ])
Parameters
A datetime expression that identifies a date and time number.
A text expression that specifies a format model shown in the following table. A format model indicates how the date and time number should be rounded.
If you omit this argument, then datetime-exp is rounded to the nearest day.
Table 8-13 lists the format models you can use with the ROUND and TRUNC date functions and the units to which they round and truncate dates. The default model, 'DD', returns the date rounded or truncated to the day with a time of midnight.
Table 8-13 Datetime Format Templates for the ROUND and TRUNC Date Functions
| Format Model | Rounding or Truncating Unit |
|---|---|
CC SCC |
One greater than the first two digits of a four-digit year |
SYYYY YYYY YEAR SYEAR YYY YY Y |
Year (rounds up on July 1) |
IYYY IY IY I |
ISO Year |
Q |
Quarter (rounds up on the sixteenth day of the second month of the quarter) |
MONTH MON MM RM |
Month (rounds up on the sixteenth day) |
WW |
Same day of the week as the first day of the year |
IW |
Same day of the week as the first day of the ISO year |
W |
Same day of the week as the first day of the month |
DDD DD J |
Day |
DAY DY D |
Starting day of the week |
HH HH12 HH24 |
Hour |
MI |
Minute |
The starting day of the week used by the format models DAY, DY, and D is specified implicitly by the initialization parameter NLS_TERRITORY.
Examples
Example 8-83 Rounding to the Nearest Year
When the value of the NLS_DATE_FORMAT option is DD-MON-YY, then this statement:
SHOW ROUND (TO_DATE('27-OCT-92'),'year')
returns this value:
01-JAN-93
Example 8-84 Rounding to Different Formats
Assume that you have a variable named mydatetime with the following definition and value defined in your analytic workspace.
DEFINE MYDATETIME VARIABLE DATETIME DATE_FORMAT = 'MON-RRRR-DD-HH24' mydatetime = CURRENT_TIMESTAMP SHOW mydatetime = 'AUG-2006-07-13'
As the following SHOW statements illustrate, depending on what date format value you specify, the ROUND function returns different values for the mydatetime variable.
SHOW ROUND(mydatetime, 'RRRR') 01-JAN-07 SHOW ROUND(mydatetime, 'MON') 01-AUG-06 SHOW ROUND(mydatetime, 'DD') 08-AUG-06 SHOW ROUND(mydatetime) = 'AUG-2006-08-00'
When a number is specified as an argument, the ROUND function returns the number rounded to the nearest multiple of a second number you specify or to the number of decimal places indicated by the second number.
Return Value
DECIMAL (when the round type is MULTIPLE)
NUMBER (when the round type is DECIMAL)
Syntax
ROUND(number_exp roundvalue) [MULTIPLE|DECIMAL]
Parameters
An expression that identifies the number to round.
A value that specifies the basis for rounding.
When the round type is MULTIPLE:
number_exp is rounded to the nearest multiple of roundvalue.
roundvalue can be an INTEGER or decimal number.
When the round type is DECIMAL:
roundvalue specifies the number of places to the right or left of the decimal point to which number_exp should be rounded. When roundvalue is positive, digits to the right of the decimal point are rounded. When it is negative, digits to the left of the decimal point are rounded.
When roundvalue is omitted, number_exp is rounded to 0 decimal places.
roundvalue must be an INTEGER.
(Default) Specifies that rounding is performed by rounding to the nearest multiple of roundvalue.
Specifies that rounding is performed by rounding to the number of decimal places indicated by roundvalue.
Usage Notes
Using ROUND to Compare Expressions
A DECIMAL value might be stored in a slightly different form than shows up at the level of significant digits you are using. This small difference can cause unexpected results when you are comparing two expressions. The problem can occur even when you are comparing INTEGER expressions that involve calculations because many calculations are done only after converting INTEGER values to DECIMAL values. You do not generally see the difference in reports because reports usually show only two or three decimal places.
For example, when you compare two numbers with the EQ or NE operators, you probably want to ignore any difference caused by the least significant digits. When expense was stored as 100.00000001, the least significant digit would not be ignored by the simple form of the comparison.
The statement
SHOW expense EQ 100.00
produces the following result.
NO
However, you can use ROUND to force EQ or NE to ignore the least significant digits.
SHOW ROUND(expense, .01) EQ 100.00
This statement produces the following result.
YES
Using ABS to Compare Expressions
When speed of calculation is important in your application, you may want to use the ABS function with LT to compare numbers, instead of using ROUND with EQ or NE.
Examples
Example 8-85 Rounding to Different Multiples
The following statements show the results of rounding the expression 2/3 to different multiples. The value of the DECIMALS setting is 2.
The statement
SHOW ROUND(2/3, .01)
produces the following result.
0.67
The statement
SHOW ROUND(2/3, .1)
produces the following result.
0.70
The statement
SHOW ROUND(2/3, .5)
produces the following result.
0.50
Example 8-86 Rounding to the Nearest Thousand
The following example shows sales rounded to the nearest thousand.
LIMIT month TO FIRST 4 LIMIT district TO FIRST 1 REPORT ROUND(sales 1000)
These statements produce the following output.
DISTRICT: BOSTON
-------------ROUND(SALES 1000)-------------
-------------------MONTH-------------------
PRODUCT Jan95 Feb95 Mar95 Apr95
-------------- ---------- ---------- ---------- ----------
Tents 32,000.00 33,000.00 43,000.00 58,000.00
Canoes 66,000.00 76,000.00 92,000.00 126,000.00
Racquets 52,000.00 57,000.00 59,000.00 69,000.00
Sportswear 53,000.00 59,000.00 63,000.00 68,000.00
Footwear 91,000.00 87,000.00 100,000.00 108,000.00
Example 8-87 Rounding to the Nearest Multiple of 12
To show units rounded to the nearest multiple of 12, use the following statements.
LIMIT month TO FIRST 4 LIMIT district TO FIRST 1 REPORT DECIMAL 0 ROUND(units 12)
These statements produce the following output.
DISTRICT: BOSTON
--------------ROUND(UNITS 12)--------------
-------------------MONTH-------------------
PRODUCT Jan95 Feb95 Mar95 Apr95
-------------- ---------- ---------- ---------- ----------
Tents 204 204 264 360
Canoes 348 396 480 660
Racquets 996 1,080 1,116 1,308
Sportswear 1,092 1,212 1,296 1,404
Footwear 2,532 2,400 2,772 2,976
The EIFEXTENSIONPATH option contains a list of directory objects that identify the locations where EIF extension files should be created.
Data Type
TEXT
Syntax
EIFEXTENSIONPATH = path-expression
Parameters
A text expression that contains one or more directory object names. When you specify multiple aliases, you must enter each one on a separate line. Specify multiple aliases in the order in which they should be used for storing EIF extension files.
Usage Notes
When Extension Files Are Created
When the size of an EIF file grows beyond the size specified for EIF files by the FILESIZE argument to the EXPORT (EIF) command, or the current disk or location becomes full, an EIF extension file is created.
Before creating a new extension file, the location specified by EIFEXTENSIONPATH is checked for sufficient disk space. The required amount of disk space is the amount specified for FILESIZE in the EXPORT (EIF). When no value has been specified for FILESIZE, then a check is made for at least 80K of disk space (the minimum size allowed by FILESIZE). When there is insufficient disk space, checking continues through the list until a location with enough available disk space is found.
Multiple Paths in EIFEXTENSIONPATH
When EIFEXTENSIONPATH contains multiple directory objects, the first extension file is created in the first alias in the list. The second extension file is created in the second alias on the list, and so on. When the end of the list is reached, the process starts over again at the beginning. When EIFEXTENSIONPATH contains a single directory object, all extension files are created in that location.
Examples
The HIERHEIGHT function returns the value of a node at a specified level for the first value in the current status list of a hierarchical dimension.
To populate a previously-defined relation with the values of a specified hierarchical dimension by level, use the HIERHEIGHT command.
Return Value
The data type returned by HIERHEIGHT is the data type of the dimension value of parentrel.
Syntax
HIERHEIGHT(fparentrel [,] level)
Parameters
A child-parent self-relation for the hierarchical dimension. See "Parentrel Relation" for more information.
An INTEGER value that represents a level of the hierarchical dimension. The value 1 (one) represents the lowest-level of the hierarchical dimension.
Usage Notes
Limiting the Hierarchical Dimension
The HIERHEIGHT function always returns a single value of the hierarchical dimension. When you do not limit the hierarchical dimension to a single value before calling the HIERHEIGHT function, the HIERHEIGHT function executes against the first value in the current status list of the dimension. Typically, you either limit the hierarchical dimension to a single value before you call the HIERHEIGHT function or you use the HIERHEIGHT function after a FOR statement to execute the HIERHEIGHT function for each value of the hierarchical dimension.
Examples
Example 7-109 Using HIERHEIGHT as a Simple Command
Assume that your analytic workspace has a hierarchical dimension named geography and a relation named g0.stanparent that is a self-relation of the geography values for the Standard hierarchy of geography.
DEFINE g0.newparent RELATION geography <geography> LD Parent-child when hierarchy of geography is 1
Issuing a statement like REPORT g0.stanparent displays the values in g0.stanparent.
GEOGRAPHY G0.STANPARENT ---------------- ---------------- World NA Americas World Canada Americas Toronto Canada Montreal Canada Ottawa Canada ... ... USA Americas Boston USA LosAngeles USA ... ... Mexico Americas Mexicocity Mexico Argentina Americas BuenosAires Argentina Brazil Americas Saopaulo Brazil Colombia Americas Bogota Colombia Australia World East.Aust Australia Sydney East.Aust Madrid Spain Budapest Hungary Athens Greece Vienna Austria Melbourne East.Aust Central.aust Australia ... ... Perth West.Aust Bombay India Malaysia Asia Europe World France Europe Caen France Paris France
Now you limit geography to the value Americas by issuing the following OLAP DML statement.
LIMIT geography TO 'Americas'
When you use the HIERHEIGHT function to find the node for Americas for the lowest-level of the hierarchy (level 1) by issuing the following OLAP DML statement.
REPORT HIERHEIGHT(g0.stanparent 1)
The following report is produced.
HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA
When you use the HIERHEIGHT function to find the node for Americas for the highest-level of the hierarchy (level 4) by issuing the following OLAP DML statement.
REPORT HIERHEIGHT(g0.stanparent 4)
The following report is produced.
HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ World
When you use the HIERHEIGHT function to find the node for Americas for the levels 2 and 3 of the hierarchy by issuing the following OLAP DML statements.
REPORT HIERHEIGHT(g0.stanparent 2) REPORT HIERHEIGHT(g0.stanparent 3)
The following reports are produced.
HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ Americas
Notice that the output for each level corresponds in between the values that are created for a relation created using HIERHEIGHT command. For example, assume you created a relation named geog.stanhierrel for the standard hierarchy for geography and limit geography to 'Americas. A report of geog.stanhierrel would show the same geography values for each level.
LIMIT geography TO 'AMERICAS'
REPORT DOWN geography geog.stanhierrel
---------------------------GEOG.STANHIERREL--------------------
----------------------------GEOG.LVLDIM------------------------
GEOGRAPHY 1 2 3 4
---------------- ---------------- ---------------- ---------------- ------------
Americas NA NA Americas World
Example 7-110 Using HIERHEIGHT After a FOR Statement
Assume that your analytic workspace has the following program named findnodes that finds the nodes of all of the geography values in status.
DEFINE FINDNODES PROGRAM PROGRAM VARIABLE level INTEGER FOR geography DO counter = 1 WHILE counter LE statlen(geog.lvldim) DO REPORT HIERHEIGHT(g0.stanparent level) level = level + 1 DOEND DOEND END
Assume also that you limit geography to Americas and Asia and call the HIERHEIGHT function for each level of the Standard hierarchy by issuing the following OLAP statements.
LIMIT geography TO 'Americas', 'Asia' CALL findnodes
The output of the findnodes program for the geography values Americas and Asia is follows. The program first reports on the value of each level for Americas is provided. Then it reports on the value of each level for Asia.
HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ Americas HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ World HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ NA HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ Asia HIERHEIGHT(G0.STANPARENT COUNTER) ------------------------------ World
Notice that the output for each level corresponds in between the values that are created for a relation created using the HIERHEIGHT command
LIMIT geography TO 'Americas' 'Asia'
REPORT DOWN geography geog.stanhierrel
---------------------------GEOG.STANHIERREL--------------------
----------------------------GEOG.LVLDIM------------------------
GEOGRAPHY 1 2 3 4
---------------- ---------------- ---------------- ---------------- ------------
Americas NA NA Americas World
Asia NA NA Asia World
The COPYDFN program defines a new object in the analytical workspace and uses the same definition as a specified object in the current workspace or in an attached workspace.
COPYDFN copies the DEFINE, LD, and PROPERTY lines for any type of object, and it copies the formula (EQ) of a formula object, and the value name format (VNF) of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. COPYDFN also copies the text of a program or model. COPYDFN does not copy the PERMIT lines for any object, and it does not copy the compiled code of a formula, program, or model.
Syntax
COPYDFN newobject oldobject
Parameters
The name of the new object to define.
The name of the object whose definition you want to copy.
Examples
Example 9-74 Copying Programs
The following statements use COPYDFN to create a program, called newprog, which is a copy of an existing one called oldprog. You could then edit newprog to create a slightly different program. The oldprog program has the following definition.
DEFINE oldprog PROGRAM LD Shows total sales for the top five months from high to low PROGRAM LIMIT district TO 'BOSTON' LIMIT month TO TOP 5 BASEDON TOTAL(sales, month) REPORT TOTAL(sales, month) END
The statements
COPYDFN newprog oldprog DESCRIBE newprog
produce the following definition for newprog.
DEFINE newprog PROGRAM LD Shows total sales for the top five months from high to low PROGRAM LIMIT district TO 'BOSTON' LIMIT month TO TOP 5 BASEDON TOTAL(sales, month) REPORT TOTAL(sales, month) END
The LIMIT BASEDIMS command sets the current status list of one or more base dimensions of a composite, conjoint dimension, concat dimension, or a partition template based on the selected values of that object.
You use LIMIT BASEDIMS to produce a status of dimension values for each dimension that exists in the sparse object's tuples, possibly filtered by some arbitrary input status. You can also use the this command to assign a value to one or more valuesets for the base dimensions.
Values that are in the current status list of a dimension are said to be "in status." The status of the base dimensions of a composite, conjoint dimension, concat dimension, or a partition template is determined by the current status of its base dimensions.
|
See also: For more information on working with dimension status, see "OLAP DML Statements Apply to All of the Values of a Data Object" and LIMIT command. |
Syntax
LIMIT BASEDIMS {<dimlist>}TO object [ [KEEP] limit-clause ]
Parameters
A space-delimited list of objects that identifies the base dimensions for which you want Oracle OLAP to change status and the valuesets for which you want Oracle OLAP to add values. Within dimlist, you can specify the following values:
The default value of dimlist is the completely expanded list of the base dimensions of object.
The name of a composite, a conjoint dimension, a concat dimension, or a partition template object.
Specifies that Oracle OLAP performs the selection based on the current dimension status of the base dimensions of the object. KEEP preserves the current order of values among the values that remain in the status.
Specifies how Oracle OLAP should select values from object to modify the current status lists of the base dimensions.
The syntax of limit-clause is the same syntax as any of the non-positional limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
When this optional argument is not specified, Oracle OLAP sets the status of the base dimensions to the current status of the dimensions.
The EIFTYPES option holds a list of the types of objects that are contained in the list produced by the EIFNAMES option. The types are listed in the same order as the corresponding object names in the EIFNAMES list.
Data Type
TEXT
Syntax
EIFTYPES
Examples
Example 5-30 Checking What You Have Imported
Suppose you have exported the units variable and the productset valueset from an analytic workspace named demo to a file called myfile.eif. After importing the contents of the file into a new workspace, you can use the EIFNAMES and EIFTYPES options to see the names and object types of the objects you have just imported.
Create the workspace and import the objects with these statements.
AW CREATE mytest IMPORT ALL FROM EIF FILE 'myfile.eif'
Send the names of the imported objects to the current outfile with this statement
SHOW EIFNAMES
to produce this output.
DISTRICT PRODUCT MONTH UNITS PRODUCTSET
Send the types of the imported objects to the current outfile with this statement
SHOW EIFTYPES
to produce this output.
DIMENSION DIMENSION DIMENSION VARIABLE VALUESET
The DEPRSOYD function calculates the depreciation expenses for a series of assets. DEPRSOYD uses the sum-of-years'-digits method, as described in "Calculation Method Used by DEPRSOYD", to depreciate the assets over the specified lifetime of the assets. The starting and ending values are specified for the assets acquired in each time period.
Return Value
DECIMAL, dimensioned by all the dimensions of start-exp.
Syntax
DEPRSOYD(start-exp end-exp n [STATUS] [{FULL|HALF| portion-exp} [time-dimension]])
Parameters
A numeric expression that contains the starting values of the assets. The start-exp expression must be dimensioned by a time dimension. For each value of the time dimension, start-exp contains the initial value of the assets acquired during that time period. In addition to a time dimension, start-exp can also have non-time dimensions.
A numeric expression that contains the ending values of the assets. The end-exp expression must be dimensioned by the same dimensions as start-exp. For each value of the time dimension, end-exp contains the final (or salvage) value for the assets acquired during that time period. Each value of start-exp must have a corresponding end-exp value. For example, when the assets acquired in 1995 have a salvage value of $200, then the value of end-exp for 1995 is $200.
An INTEGER expression that contains the depreciation lifetime of the assets. The n expression can have any of the non-time dimensions of start-exp, but it cannot have a time dimension.
Specifies that DEPRSOYD should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the depreciation expenses. By default DEPRSOYD uses the default status list.
(Default) Specifies that the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges the full amount to all of the assets in the series.
Specifies that half of the full amount of a time period's depreciation expense is charged to the time period in which assets were acquired. Charges half the full amount to all of the assets in the series. When you specify HALF as the portion of depreciation expenses to charge to the period of acquisition, the HALF factor is applied to each period. Half of each period's full depreciation expense is rolled to the next period, and the final half period of depreciation expense takes place in the n + 1 time period. You might want to use HALF when assets are acquired during the second half of the time period.
When you want to charge the full amount for some assets and half the amount for other assets, you can supply a portion-exp expression that is dimensioned by any of the non-time dimensions of start-exp. The portion-exp expression must be a text expression with values of FULL or HALF.
The name of the time dimension by which start-exp and end-exp are dimensioned.When the time dimension has a type of DAY, WEEK, MONTH, QUARTER, or YEAR, the time-dimension argument is optional.
Usage Notes
Calculation Method Used by DEPRSOYD
DEPRSOYD calculates the depreciation expense for a given time period as the sum of that period's depreciation expenses for all assets in the series that are not yet fully depreciated. The first period of depreciation for an asset is the period in which it was acquired.
For each time period in the lifetime of an asset, DEPRSOYD bases the depreciation expense calculation on a specific cut of the total amount to be depreciated. The value of the cut is such that the full depreciation expense can be achieved over the lifetime of an asset by multiplying the cut by the number of time periods not yet depreciated.
For example, when the lifetime of an asset is 5 years, then DEPRSOYD calculates the cut, x, as follows.
5x + 4x + 3x + 2x + 1x = total depreciation
In this case, the cut is 1/15th of the total depreciation. When the initial asset is $1,000 and its salvage value is $100, then the total depreciation is $900.00, and x is $60 ($900/15). For the first time period, the depreciation is $300 ($60 x 5). For the second time period, the depreciation is $240 ($60 x 4) and so on.
DEPRSOYD and NA Values
When a value of start-exp is NA and the corresponding value of end-exp is not NA, an error occurs. Similarly, when a value of end-exp is NA and the corresponding value of start-exp is not NA, an error occurs.
DEPRSOYD is affected by the NASKIP option when a value of start-exp and the corresponding value of end-exp are both NA. When NASKIP is YES (the default), DEPRSOYD treats the values as zeros when calculating the depreciation expenses. When NASKIP is NO, DEPRSOYD returns NA for all affected time periods.
Examples
Example 7-73 Using DEPRSOYD to Calculate Depreciation Expenses for Assets Acquired in a Single Period
This example shows how to use DEPRSOYD to calculate depreciation expenses for assets acquired in a single time period.
The following statements create two variables called assets and salvage.
DEFINE assets DECIMAL <year> DEFINE salvage DECIMAL <year>
Suppose you assign the following values to the variables assets and salvage.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 0.00 0.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00
The variable assets contains the starting value of assets acquired in 1995. The variable salvage contains the ending value of the assets acquired in 1995.
The following statement reports the values of assets and salvage, and uses DEPRSOYD to calculate depreciation expenses for each year, specifying an asset lifetime of 5 years.
REPORT assets salvage W 12 HEADING 'Depreciation' -
DEPRSOYD(assets salvage 5 FULL year)
This statement produces the following report.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100.00 380.00 Yr96 0.00 0.00 240.00 Yr97 0.00 0.00 180.00 Yr98 0.00 0.00 120.00 Yr99 0.00 0.00 60.00 Yr00 0.00 0.00 0.00
Example 7-74 Using DEPRSOYD to Calculate the Depreciation Expenses for Assets Acquired in Multiple Periods
You can also use DEPRSOYD to calculate the depreciation expenses for a series of assets. Suppose you change the values for the year 1997 in the variables assets and salvage to the values shown in the following report.
YEAR ASSETS SALVAGE -------------- ---------- ---------- Yr95 1,000.00 100.00 Yr96 0.00 0.00 Yr97 500.00 50.00 Yr98 0.00 0.00 Yr99 0.00 0.00 Yr00 0.00 0.00 Yr01 0.00 0.00 Yr02 0.00 0.00
Now assets and salvage contain nonzero values for 1995 and for 1997.
The following statement reports asset and salvage values along with depreciation expenses for the assets. Note that the call to DEPRSOYD to calculate the depreciation expenses specifies an asset lifetime of 5 periods (in this case, years).
REPORT assets salvage W 12 HEADING 'Depreciation' -
DEPRSOYD(assets salvage 5 FULL year)
This statement produces the following output.
YEAR ASSETS SALVAGE Depreciation -------------- ---------- ---------- ------------ Yr95 1,000.00 100.00 300.00 Yr96 0.00 0.00 240.00 Yr97 500.00 50.00 330.00 Yr98 0.00 0.00 240.00 Yr99 0.00 0.00 160.00 Yr00 0.00 0.00 60.00 Yr01 0.00 0.00 30.00 Yr02 0.00 0.00 0.00
Notice that as a result of the second asset, the depreciation expenses increase in 1997. The depreciation is the total depreciation of $180.00 ($60 x 3) for the first asset and $150.00 ($30 x 5) for the second asset.
The STATRANK function returns the position of a dimension or dimension surrogate value in the current status list or in a valueset.
Return Value
INTEGER
Syntax
STATRANK(dimension [value])
Parameters
A text expression whose value is the name of a dimension, dimension surrogate, or valueset.
The value you want to check, which is an appropriate data type for dimension. For example, value can be a text expression for an ID or TEXT dimension, an INTEGER for an INTEGER dimension, a date for a time dimension, or a combination of values enclosed by angle brackets for conjoint or concat dimensions. The value of a text expression must have the same capitalization as the actual dimension value. When you use a text expression, it must be a single-line value.
When you specify the value of a conjoint dimension, be sure to enclose the value in angle brackets, and separate the base dimension values with a comma and space. When you specify the value of a concat dimension, be sure to enclose the value in angle brackets, and separate the base dimension name from the value with a colon and space.
When you do not specify value, STATRANK returns the position of the current value. When you specify the name of a valid dimension value that is not in the current status list or in the valueset, STATRANK returns NA.
Examples
Example 8-116 Using STATRANK to Identify Position Numbers
Suppose you want to produce a report of the top five months by total sales, displayed in order as a numbered list. You can use STATRANK to number each month. Assume that you have written a report program with the following definition and contents.
DEFINE sales.rpt PROGRAM
PROGRAM
LIMIT month TO TOP 5 BASEDON TOTAL(sales, month)
SHOW 'Top five months by total sales:'
for month
ROW WIDTH 4 JOINCHARS(STATRANK(month) '.') WIDTH 5 month
END
The report program produces the following output.
Top five months by total sales: 1. Jul96 2. Jun96 3. Jul95 4. Aug96 5. Jun95
After executing the sales.rpt program, you can use a SHOW statement with the STATRANK function to learn the position of a particular month within the top five months by total sales.
The following statement
SHOW STATRANK(month Jun96)
produces this output.
2
Example 8-117 Using STATRANK When the Dimension Is a Conjoint Dimension
When the dimension that you specify is a conjoint dimension, then the entire value must be enclosed in single quotes.
For example, suppose the analytic workspace has a region dimension and a product dimension. The region dimension values include East, Central, and West. The product dimension values include Tents, Canoes, and Racquets.
The following statements define a conjoint dimension, and add values to it.
DEFINE reg.prod DIMENSION <region product> MAINTAIN reg.prod ADD <'East', 'Tents'> <'West', 'Canoes'>
To specify base positions, use a statement such as the following. Because the position of East in the region dimension is 1 and the position of Tents in the product dimension is 1, the following statement returns the position of the corresponding reg.prod value.
SHOW STATRANK(reg.prod '<1, 1>') 1
To specify base text values, use a statement such as the following.
SHOW STATRANK(reg.prod '<\'East\', \'Tents\'>') 1
Example 8-118 Using STATRANK When the Dimension Is a Concat Dimension
When the dimension that you specify is a concat dimension, then the entire value must be enclosed in single quotes. The following statement defines a concat dimension named reg.prod.ccdim that has as its base dimensions region and product.
DEFINE reg.prod.ccdim DIMENSION CONCAT(region product)
A report of reg.prod.ccdim returns the following.
REG.PROD.CCDIM ---------------------- <Region: East> <Region: Central> <Region: West> <Product: Tents> <Product: Canoes> <Product: Racquets>
To specify a base dimension position, use a statement such as the following. Because the position of racquets in the product dimension is 3, the statement returns the position in reg.prod.ccdim of the <product: Racquets> value.
SHOW STATRANK(reg.prod.ccdim '<product: 3>') 6
To specify base dimension text values, use a statement such as the following.
SHOW STATRANK(reg.prod.ccdim '<product: Tents>') 4
The INTPART function calculates the integer part of a decimal number by truncating its decimal fraction.
Return Value
INTEGER
Syntax
INTPART(expression)
Parameters
The decimal expression whose integer part is to be returned.
Usage Notes
Large Values
When expression has a value larger than is allowed for an INTEGER (a value between -2,147,483,647 and 2,147,483,647), INTPART returns an NA value.
Examples
The NLS_CHARSET_ID function returns the character set identification number corresponding to a specified character set name.
Return Value
INTEGER when you specify a valid value for the name of the character set, a number; otherwise NA.
Syntax
NLS_CHARSET_ID (charset_name)
Parameters
A VARCHAR2 text expression that is a valid character set name or one of the following values:
CHAR_CS which specifies that the function return the database character set identification number of the server.
NCHAR_CS which specifies that the function return the national character set id number of the server.
The OBJORG function takes, as input, the name of an OLAP cube or cube dimension as defined in the Oracle data dictionary (sometimes called a "logical OLAP object") and returns information about the lower-level, "physical," analytic workspace objects by which that cube or cube dimension is implemented.
Use this function in OLAP DML statements that require an analytic workspace object name rather than an OLAP cube or cube dimension name.
Return value
Analytic workspace object name or TEXT; or NA if an analytic workspace has the requested definition information, but the field is empty.
Syntax
OBJORG(keyword [OWNER owner ] top-level-object-name [ sub-object-name ] )
Parameters
The valid keywords vary by the type of top-level-object or sub-object specified, as documented in:
Table 8-4, "Keywords when the top-level-object is a Cube and the sub-object is a Measure".
Table 8-6, "Keywords when the top-level-object is a Cube Dimension".
Table 8-3 Keywords when the top-level-object is a Cube
| Keyword | Returns |
|---|---|
|
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The aggmap for the cube. (Note: The function will never return NA when you specify this keyword.) |
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When a composite is used for the cube, the name of the composite; or NA if the cube's sparsity type is DENSE, or if the cube is partitioned. (See also the keyword |
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(Property.) The DML data type used for all of the cube's measures; or NA if there is no such single data type (that is, if different measures have different data types). |
|
|
When the value returned for the keyword |
|
|
The text variable, dimensioned by |
|
|
The analytic workspace dimension that contains the names of the partitions for the cube; or NA if the cube is not partitioned. |
|
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The relation, dimensioned by |
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The partition template relating each cube partition to its corresponding analytic workspace dimension values; or NA if the cube is not partitioned. |
|
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When the cube has a storage type, the variable (of that type) that stores all of the cube's measures; or NA when it does not. |
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(Property.) The cube sparsity type. Valid values are: COMPRESSED, SPARSE, DENSE, or SPARSE_GLOBAL. Corresponds to column SPARSE_TYPE in the USER_CUBES and ALL_CUBES views. |
Table 8-4 Keywords when the top-level-object is a Cube and the sub-object is a Measure
| Keyword | Returns |
|---|---|
|
|
When the value returned when you specify the |
|
|
The aggmap for the measure, if the measure has one; otherwise returns NA. (Note that when the measure has no aggmap, then the cube's aggmap is used.) |
Table 8-5 Keywords when the top-level-object is Cube and the sub-object is a Dimension Calculation Model
| Keyword | Returns |
|---|---|
|
|
If the cube's consistent solve specification specifies an aggregation at a specific level, the valueset consisting of all members of the dimension that belong to that level; otherwise, NA. |
|
|
The valueset containing the names of all hierarchies of the analytic workspace dimension over which the cube is aggregated. (Note that when you specify this keyword, the function never returns NA.) |
|
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If at least one of the cube's measures has an |
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When the cube organization specifies a precompute condition, the valueset containing all members of the dimension that satisfy that condition; otherwise NA. (In particular, when the cube organization specifies a precompute percent, returns NA.) |
Table 8-6 Keywords when the top-level-object is a Cube Dimension
| Keyword | Returns |
|---|---|
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The analytic workspace physical dimension corresponding to this logical dimension. (Note that when you specify this keyword, the function never returns NA.) |
|
|
The variable, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The dimension containing all hierarchies for this dimension. (Note that when you specify this keyword, the function never returns NA.) |
|
|
The valueset, dimensioned by |
|
|
The variable, dimensioned by |
|
|
The valueset, dimensioned by |
|
|
The dimension containing all levels for this dimension. (Note that when you specify this keyword, the function never returns NA, even if the dimension has no levels.) |
|
|
The relation, dimensioned by the |
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
|
|
The relation, dimensioned by |
Table 8-7 Keywords when the top-level-object is a Cube Dimension and the sub-object is a Base Attribute
| Keyword | Returns |
|---|---|
|
|
The value returned varies depending on whether or not the dimension is indexed.
(Note that when you specify this keyword, the function never returns NA.) |
|
|
When the attribute is indexed, the dimension that stores all of the attributes values; otherwise NA. |
|
|
When the attribute is a unique key attribute, the relation, dimensioned by |
|
|
When the attribute is a unique key attribute (that is, indexed), the relation, dimensioned by |
Table 8-8 Keywords when the top-level-object is a Cube Dimension and the sub-object is a Dimension Level
| Keyword | Returns |
|---|---|
|
|
The surrogate for the owning dimension's |
The owner of the cube or cube dimension identified by top-level-object. If you do not include this clause, the function uses the current owner.
A text expression that specifies the name of the cube or the cube dimension for which information is requested.
A text expression that specifies the name of the "logical" OLAP sub-object, if any, for which information is requested. Valid values vary depending on whether the top-level-object is a cube or a cube dimension:
When top-level-object is a cube, you can specify the name of a measure or dimensionality
When top-level-object is a cube dimension, you can specify the name of a base attribute, hierarchy, dimension level, or dimension calculation model.
Examples
Examples of using OBJORG with various keyword appear in several sample OLAP DML programs described within this manual:
For examples of using OBJORG with the Dim keyword, see the following sample OLAP DML programs:
ADD_L1_2 program in Example 9-5, "Adding Members to an OLAP Cube Dimension"
REMOVE_L2_1 program in Example 10-98, "Removing OLAP Cube Dimension Members From a Hierarchy"
SETUP_PRE_MODEL and SETUP_POST_MODEL programs in Example 10-118, "Creating Static and Dynamic Models for an OLAP Cube"
ADD_L1_2_DATES program in Example 10-169, "Updating the Attributes of an OLAP Cube Dimension"
For an example of using OBJORG with the Measure keyword, see the ADD_L1_2 program in Example 9-5, "Adding Members to an OLAP Cube Dimension".
For an example of using OBJORG with the Parentrel keyword, see the REMOVE_L2-1 program in Example 10-98, "Removing OLAP Cube Dimension Members From a Hierarchy".
For examples of using OBJORG with the Attribute keyword, see the following sample programs:
SETUP_POST_MODEL program in Example 10-118, "Creating Static and Dynamic Models for an OLAP Cube"
ADD_L1_2_DATES program in Example 10-169, "Updating the Attributes of an OLAP Cube Dimension"
Within an OLAP DML program, the GOTO command alters the sequence of statement execution within a program.
Syntax
GOTO label
Parameters
The name of a label elsewhere in the program constructed following the "Guidelines for Constructing a Label". Execution of the program branches to the line directly following the specified label.
Note that label, as specified in GOTO, must not be followed by a colon. However, the actual label elsewhere in the program must end with a colon.
Usage Notes
Guidelines for Constructing a Label
When you use control structures to branch to a particular location, you must provide a label for the location to identify it clearly. When creating a label, follow these guidelines:
The first character in the label must be a letter, period (.), or underscore (_).
The remaining characters in a label can be any combination of letters, numbers, periods, or underscores.
A label must be followed immediately by a colon (:).
Ensure that the first eight bytes in the label are unique. (Remember that, in your character set, a byte might or might not be equivalent to one character.) A label can contain up to 3999 bytes (the maximum length of a text line minus 1 byte for the colon that identifies a label). However, because only the first eight bytes of a label name are used, you can experience problems with label names greater than eight bytes when the first eight bytes are not unique.
Missing GOTO Label
When an actual label that corresponds to label does not exist elsewhere in the same program, execution stops with an error.
GOTO with IF and WHILE
A GOTO statement can be used with IF...THEN...ELSE or WHILE to set up conditional branching, using the following syntax.
IF boolean-expression
THEN GOTO label1
ELSE GOTO label2
However, to preserve the clarity of your programming logic, minimize your use of GOTO. You can often replace GOTO with one or more statements executed conditionally using FOR, IF...THEN...ELSE, or WHILE. You can also use a SWITCH command to handle different cases within the same program.
GOTO with FOR
You can use a GOTO statement in a FOR loop to branch within, or out of, the loop which changes the sequence of statement execution, depending on where the GOTO statement and the label are positioned.
A GOTO in a FOR loop that branches to a label within the same loop makes execution continue at the label without affecting the current dimension status. Subsequent repetitions of the loop continue normally. To branch to the end of the loop, just before the DOEND statement, consider using a CONTINUE statement instead.
A GOTO in a FOR loop that branches to a label outside the loop terminates the effect of the FOR statement. Execution continues at the specified label and dimension status is restored to what it was before the loop. To branch to the statement immediately following the DOEND of a loop, consider using a BREAK statement instead.
When you use a GOTO statement outside a FOR loop to branch into the loop (that is, to a label inside the loop), an error occurs after execution passes through the rest of the loop once.
TEMPSTAT and GOTO Statements
Within a FOR loop of a program, when a DO ... DOEND phrase follows TEMPSTAT, status is restored when the DOEND, BREAK, or GOTO is encountered.
Alternatives to GOTO Statement
While GOTO makes it easy to branch within a program, frequent use of it can obscure the logic of your program, making it difficult to follow its flow, particularly when you have a complex program with several labels and GOTO statements that skip over large portions of code.
To keep the logic of your programs clear, minimize your use of GOTO.
Sometimes a GOTO statement is the best programming technique, but often there are better alternatives. For example:
Instead of using GOTO statements in a FOR statement, you can often place your alternative sets of statements between DO ... DOEND statements within an IF...THEN...ELSE command itself.
When each set of statements is long or you want to use them in multiple places in your program, then you might consider placing them in subprograms. Then, you can use an IF...THEN...ELSE command to choose between two different programs, or use a SWITCH command to choose among many different programs.
Example 9-137, "Using a FOR Statement for Looping Over Values" illustrates how the FOR command loops over values. Example 9-138, "Using DO/DOEND in a FOR Loop" illustrates using DO ... DOEND within a FOR loop.
Examples
Example 9-144 Using GOTO with IF
This example shows a program that produces a report for one of three areas, depending on what argument the user supplies when running the program. When the user specifies EAST, WEST, or CENTRAL, execution branches to a corresponding label, and the statements following it (statement group 1, 2, or 3) are executed. When the user specifies anything else, execution branches to the argerror label, after which statements handle the error.
DEFINE flexrpt PROGRAM
PROGRAM
IF NOT INLIST('East\nWest\nCentral', UPCASE(ARG(1)))
THEN GOTO argerror
SWITCH &UPCASE(ARG(1))
DO
CASE 'EAST':
..." (statement group 1)
BREAK
CASE 'WEST':
... "(statement group 2)
BREAK
CASE 'CENTRAL':
..." (statement group 3)
BREAK
DOEND
argerror:
..." statements to handle error)
END
The EVERY function returns YES when every value of a Boolean expression is TRUE, or NO when any value of the expression is FALSE.
Return Value
BOOLEAN
Syntax
EVERY(boolean-expression [CACHE] [dimension...])
Parameters
The Boolean expression whose values are to be evaluated.
Specifies slightly different internal behavior. Specify this keyword only when the original performance is extremely slow.
The name of a dimension of the result; or, the name of a relation between one dimension of boolean-expression and another dimension that you want as a dimension of the result.
By default, EVERY returns a single YES or NO value. When you indicate one or more dimensions for the result, EVERY tests for TRUE values along the dimensions that are specified and returns an array of values. Each dimension must be either a dimension of boolean-expression or related to one of its dimensions.
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Tip: When you specify a dimension that is not an actual dimension of boolean-expression, but, instead, is dimension that is related to a dimension of boolean-expression and when there are multiple relations between the two dimensions, Oracle OLAP uses the default relation between the dimensions to perform the calculation. (See the RELATION command for more information on default relations.) When you do not want Oracle OLAP to use this default relation, specify the related dimension by specifying the name of a specify relation. |
Usage Notes
The Effect of NASKIP on EVERY
EVERY is affected by the NASKIP option. When NASKIP is set to YES (the default), EVERY ignores NA values and returns YES when every value of the expression that is not NA is TRUE and returns NO when any values are not TRUE. When NASKIP is set to NO, EVERY returns NA when any value of the expression is NA. When all the values of the expression are NA, EVERY returns NA for either setting of NASKIP.
Examples
Example 7-77 Testing for All-True Values by District
You can use the EVERY function to test whether each district's sales of sportswear have exceeded $50,000 in every month. To have the results dimensioned by district, specify district as the second argument to EVERY.
LIMIT product TO 'Sportswear' REPORT HEADING 'Top Sales' EVERY(sales GT 50000, district)
The preceding statements produce the following output.
DISTRICT Top Sales -------------- ---------- Boston No Atlanta Yes Chicago Yes Dallas Yes Denver Yes Seattle NO
Example 7-78 Testing for All-True Values by Region
You might also want to find out the regions for which every district has sportswear sales that exceed $50,000 in every month. Since the region dimension is related to the district dimension, you can specify region instead of district as a dimension for the results of EVERY.
REPORT HEADING 'Top Sales' EVERY(sales GT 50000, region)
The preceding statement produces the following output.
REGION Top Sales -------------- ---------- East No Central Yes West NO
The LEAD function returns the values of a dimensioned variable or expression at a specified offset of a dimension after the current value of that dimension. Typically, you use the LEAD function to retrieve values for a future time period.
Return Value
The data type of the variable argument or NA when you try to retrieve a value from beyond the last period defined for the time dimension.
Syntax
LEAD(variable, n, [time-dimension], [[STATUS|NOSTATUS|limit-clause] )
Parameters
A variable or expression that is dimensioned by dimension.
The offset (that is, the number of dimension values) to lead. LEAD uses this value to determine the number of values that LEAD should go ahead in dimension to retrieve the value of variable. To count the values, LEAD uses the default status, unless you use the STATUS keyword or the limit-clause argument to specify a different dimension status.
Normally, n is a positive INTEGER that indicates the number of time periods (or dimension values) after the current one. When you specify a negative value for n, it indicates the number of time periods before the current one. In effect, using a negative value for n turns LEAD into a LAG function.
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Note: When using LEAD in a model, see "Ensuring One-Way Dimensional Dependence" for information on how to code a value forn so that Oracle OLAP does not use simultaneous blocks when solving the model. |
The dimension along which the lead occurs. While this can be any dimension, it is typically a hierarchical time dimension of type TEXT that is limited to a single level (for example, the month or year level) or a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR.
When variable has a dimension with a type of DAY, WEEK, MONTH, QUARTER, or YEAR and you want LEAD to use that dimension, you can omit the dimension argument.
Specifies that LEAD should use the current status list (that is, only the dimension values currently in status in their current status order) when computing the lead.
Specifies that LEAD should use the default status (that is, a list all the dimension values in their original order) when computing the lead.
Specifies that LEAD should use the default status limited by limit-clause when computing the lead.
The syntax of limit-clause is the same syntax as any of the limit-clause arguments in the various forms of the LIMIT command (that is, the syntax of the LIMIT command after the limit-type argument such as "TO"). For the syntax of these arguments, see LIMIT (using values) command, LIMIT using LEVELREL command, LIMIT (using parent relation), LIMIT (using related dimension) command, LIMIT NOCONVERT command, and LIMIT command (using POSLIST).
To specify that LAG should use the current status limited by limit-clause when computing the lag, specify a LIMIT function for limit-clause.
Examples
Example 8-6 Using LEAD
Assume that you have a sales variable that is dimensioned by three dimensions of the TEXT type (named product, district, and time). The time dimension is a hierarchical dimension with the following values.
1999 2000 Jan1999 Feb1999 ... Dec1999 Jan2000 Feb2000 ... Dec2000
Also, assume that there is a dimension named timelevels that contains the names of the levels of the time dimension (that is, Month and Year) and a relation named timelevelrel that is dimensioned by time and that has values from timelevels (that is, the related dimension of timelevelrel is timelevels). A report of timelevelrel shows these relationships.
TIME TIMELEVELREL -------------- ------------ 1999 Year 2000 Year Jan1999 Month Feb1999 Month ... ... Dec1999 Month Jan2000 Month Feb2000 Month ... ... Dec2000 Month
Suppose you want to compare racquet sales in Dallas for the first two months of 1999 with sales for the corresponding months of 2000. You can use the LEAD function to produce the values from 2000 in the same report with the 1999 values. The following statements
LIMIT product TO 'Racquets' LIMIT district TO 'Dallas' LIMIT time TO 'JAN1999' 'FEB1999' REPORT DOWN time sales HEADING 'Following Year' LEAD(sales, 12, time, time LEVELREL timelevelrel)
produce this report.
DISTRICT: DALLAS
-------PRODUCT-------
------RACQUETS-------
TIME SALES Following Year
-------------- ---------- ---------------------
Jan2000 118,686.75 125,879.86
Feb2000 142,305.99 150,833.64
The USETRIGGERS option determines if a trigger program as triggers execute.
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Tip: Oracle OLAP does not support recursive triggers. Set the USETRIGGERS option toNO before you issue the same DML statement within a trigger program that triggered the program itself. For example, assume that you have written a TRIGGER_DEFINE program. Within the TRIGGER_DEFINE program, you must set the USETRIGGERS option to NO before you issue a DEFINE statement |
Data Type
BOOLEAN
Syntax
USETRIGGERS = {NO|YES}
Parameters
(Default) Trigger programs execute.
Trigger programs do not execute.
Examples
The MAXBYTES function counts the number of bytes in the longest line of a multiline text expression. The result returned by MAXBYTES has the same dimensions as the specified expression.
Return Value
INTEGER
Syntax
MAXBYTES(text-expression)
Parameters
The TEXT expression whose bytes for each line are to be counted.
Examples
Example 8-22 Finding the Length of the Longest Line Using Bytes
You would like to know the length of the longest line in a text variable called mytext. The following example shows the value of the variable and the result returned by MAXBYTES.
The statement
SHOW mytext
produces the following output.
This is a multiline text variable. The longest line is this one in the middle. The third line is short.
The statement
SHOW MAXBYTES(mytext)
produces the following output.
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The ALLOCERRLOGFORMAT option determines the contents and the formatting of the error log that you specify with the ERRORLOG argument to the ALLOCATE command.
Syntax
ALLOCERRLOGFORMAT = text
Parameters
Characters that determine the contents and formatting of the error log that you specify with an ERRORLOG statement in an ALLOCMAP command. By placing an INTEGER value before the formatting character, you can specify the number of characters that the object occupies in the error log. You can specify escape sequences as formatting characters. For valid escape sequences, see "Escape Sequences". Table 5-1, "Characters for Specify the Contents of the Error Log for ALLOCATE" lists the characters that specify the contents of the error log. The default value of ALLOCERRLOGFORMAT is the following.
'%8p %8y %8z %e (%n)'
Table 5-1 Characters for Specify the Contents of the Error Log for ALLOCATE
| Character | Output Specified |
|---|---|
|
b |
The basis object being processed. |
|
c |
The child node of the dimension being processed. |
|
d |
The name of the dimension being processed. |
|
e |
A description of the error encountered. |
|
n |
The error code of the error encountered. |
|
p |
The parent node of the dimension being processed. |
|
r |
The name of the relation being allocated down. |
|
s |
The source object being processed. |
|
t |
The target object being processed. |
|
n |
The basis value of the child cell receiving the allocation. |
|
y |
The source value of the parent cell being allocated. |
|
z |
The basis value of the parent cell being allocated. |
Examples
Within a program triggered by an Assign event for an object, assigns a value to the triggering object.
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Note: The USETRIGGERS option must be set to its default value ofTRUE for a TRIGGERASSIGN to execute |
Data Type
The data type of the object to which Oracle OLAP assigns the value.
Syntax
TRIGGERASSIGN value
Parameters
The value that you want assigned.
Examples
Example 10-166 Assigning an Alternative Value using an Assign Trigger
Assume that you have objects with the following descriptions in your analytic workspace.
DEFINE GEOG.D DIMENSION TEXT DEFINE TIME.D DIMENSION TEXT DEFINE TIME.PARENTREL RELATION TIME.D <TIME.D> DEFINE SALES VARIABLE DECIMAL <GEOG.D TIME.D> DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D>
Assume also that you have populated the sales variable with the values shown in the following report, but that you have not yet populated the modified_sales variable.
-----------------------SALES-----------------------
----------------------GEOG.D-----------------------
TIME.D Boston Medford San Diego Sunnydale
------------ ------------ ------------ ------------ ------------
Jan76 1,000.00 2,000.00 3,000.00 4,000.00
Feb76 2,000.00 4,000.00 6,000.00 8,000.00
Mar76 3,000.00 6,000.00 9,000.00 12,000.00
76Q1 NA NA NA NA
Now you want to assign values to the modified_sales variable using various expressions, however, you want to ensure that the values never are less than or equal to 1,000. You can assure this processing by taking the following steps:
Create the following program that checks for values less than or equal to 1000 condition.
DEFINE TRIGGER_ASSIGN_MODIFIED_SALES PROGRAM
PROGRAM
ARGUMENT datavalue DECIMAL
IF datavalue LE 1000
THEN TRIGGERASSIGN 1000
show 'description of triggering object = '
DESCRIBE &TRIGGER(NAME)
SHOW JOINCHARS ('calltype = ' CALLTYPE)
SHOW JOINCHARS ('triggering event = ' TRIGGER(EVENT))
SHOW JOINCHARS ('triggering subevent = ' TRIGGER(SUBEVENT))
SHOW JOINCHARS ('value passed to program = ' datavalue)
SHOW ' '
END
Issue the following statements to add an Assign trigger to the modified_sales variable. The trigger_assign_modified_sales program is the trigger program.
CONSIDER modified_sales TRIGGER ASSIGN trigger_assign_modified_sales
Assign values to modified_sales.
modified_sales = sales - 1000
This statement triggers the execution of the trigger_assign_modified_sales program for each value that Oracle OLAP assigns.
description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 0.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 1,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 2,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 3,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 1,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 3,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 5,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 7,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 2,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 5,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 8,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = 11,000.00 description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program = description of triggering object = DEFINE MODIFIED_SALES VARIABLE DECIMAL <GEOG.D TIME.D> TRIGGER ASSIGN TRIGGER_ASSIGN_MODIFIED_SALES calltype = TRIGGER triggering event = ASSIGN triggering subevent = value passed to program =
The following report of modified_sales shows that all values are at least 1,000.
------------------MODIFIED_SALES-------------------
----------------------GEOG.D-----------------------
TIME.D Boston Medford San Diego Sunnydale
------------ ------------ ------------ ------------ ------------
Jan76 1,000.00 1,000.00 2,000.00 3,000.00
Feb76 1,000.00 3,000.00 5,000.00 7,000.00
Mar76 2,000.00 5,000.00 8,000.00 11,000.00
76Q1 NA NA NA NA
The CHANGEDVALUES function identifies if any value in a variable has changed (or the number of values that have changed) since the last time a variable was aggregated.
Return Value
BOOLEAN unless you specify NUMBER for returntype.
When the function returns a BOOLEAN value, that value is TRUE when any value has changed since the variable was last aggregated, FALSE when no values have changed, or NA when the function cannot determine if any values have changed or not.
When the function returns a NUMBER value, that value is the number of values that have changed since the variable was last aggregated.
Syntax
CHANGEDVALUES ( variable [(PARTITION partition [,PARTITION partition]...)] [returntype] )
Parameters
The name of the variable to check for changed values.
The name of one or more partitions of variable, separated by commas, to check for changed values.
NUMBER when you want the function to return a numeric value that is the number of values that have changed. When you want the function to return whether or not any value has changed since the last aggregation, specify BOOLEAN or leave this argument empty as BOOLEAN is the default value for returntype.
The LIMITMAPINFO function returns the analytic workspace expression that a specified limit map uses to map data into a specified column of a relational table.
Return Value
A TEXT expression.
Syntax
LIMITMAPINFO ([aw], limit-map, column-name)
Parameters
The name of the analytic workspace that contains the analytic workspace object.
The limit map as a text expression.
The name of the column of a relational table as it appears in limit-map.
Examples
Example 8-11 Retrieving the Name of a Dimension
Assume that you have an analytic workspace named myaw that contains a text variable named mylimitmap that is a limit map that maps some analytic workspace data to a relational table with a column named et_product.
MEASURE sales FROM aw_f.sales DIMENSION et_chan FROM aw_channel WITH HIERARCHY aw_channel.parent GID gid_chan FROM aw_channel.gid DIMENSION et_prod FROM aw_product WITH HIERARCHY aw_product.parent GID gid_prod FROM aw_prod.gid DIMENSION et_geog FROM aw_geography WITH HIERARCHY aw_geography.parent GID gid_geog FROM aw_geog.gid DIMENSION et_time FROM aw_time WITH HIERARCHY time.parent GID gid_time FROM aw_time.gid
To retrieve the name of the analytic workspace object from which data for the et_prod column is retrieved, you issue the following OLAP DML statement.
show LIMITMAPINFO ('myaw', mylimitmap, 'et_prod')
The following value displays because the et_prod column is mapped to the aw_product dimension.
aw_product
The TMARGIN option defines the number of blank lines for the top margin of output pages, above the running page heading. In other words, the top margin lines are produced before the program that is defined by PAGEPRG, if any, is run.
TMARGIN is meaningful only when PAGING is set to YES and only for output from statements such as REPORT and DESCRIBE. The TMARGIN option is usually set in the initialization section of report programs.
Data Type
INTEGER
Syntax
TMARGIN = n
Parameters
An INTEGER expression that specifies the number of lines to set aside for the top margin in a report. The default is 2.
Usage Notes
Setting TMARGIN for a File
To set TMARGIN for a file, first make the file your current outfile by specifying its name in an OUTFILE statement, then set TMARGIN to the desired value. The new value remains in effect until you reset it or until you use an OUTFILE statement to direct output to a different outfile. When you direct output to a different outfile, TMARGIN returns to its default value of 2 for the file.
When you set TMARGIN for the default outfile, the new value remains in effect until you reset it, regardless of intervening OUTFILE commands that send output to a file. That is, the value of TMARGIN is automatically saved for the default outfile.
Examples
When an analytic workspace is attached in multiwriter mode, the RELEASE command changes the access mode of the specified variables, relations, valuesets, dimensions, or one or more partitions in a variable from read/write (acquired) access to read-only access.
Syntax
RELEASE objects
Parameters
One or more variables, relations, valuesets, dimension names, or analytic workspace names, separated by commas, that you want to release. To specify individual partitions of a partitioned variable, use the following syntax.
variable_name (PARTITION partition_name [, PARTITION partition_name ]...)
Precede each analytic workspace name with AW using the following syntax:
AW analytic workspace name
When you specify an analytic workspace in this list, all acquired objects in that analytic workspace are released after all pending changes are made to them. All changes made to the variables, relations, valuesets, or dimensions before a RELEASE statement executes are preserved as private changes after the release statement.
Usage Notes
Releasing Non-Updated or Uncommitted Objects
Similarly to using an AW DETACH statement for analytic workspaces that has been updated. Using RELEASE for objects that have been updated does not allow others to acquire the object until you commit or roll back the transaction. It may still be useful to release an object that has been updated before a commit when one wants to make further what-if changes and later needs to use UPDATE to update all acquired variables.
Releasing a Dimension Causes the Dimension to Revert
When you release an acquired dimension, the dimension is automatically reverted (see the REVERT command for an explanation of what it means to revert a dimension).
As the following code illustrates, releasing an acquired dimension causes an automatic revert.
User A issues the following OLAP DML statements.
AW ATTACH myworkspace MULTI ACQUIRE RESYNC time WAIT MAINTAIN time ADD 'Y2002' actuals (time 'Y2002', ...) = 37 REPORT time --> ..., 'Y2002' ... report SHOW actuals (time 'Y2002', ...) --> 37 RELEASE time REPORT time --> ... (no 'Y2002') AW ATTACH myworkspace MULTI ... report ACQUIRE RESYNC actuals, time WAIT MAINTAIN time ADD 'Y2002' actuals (time 'Y2002', ...) = 37 REPORT time --> ..., 'Y2002' SHOW actuals (time 'Y2002', ...) --> 37 ... report REVERT time REPORT time --> ... (no 'Y2002') MAINTAIN time ADD 'Y2002' ... report REPORT time --> ..., 'Y2002' SHOW actuals (time 'Y2002', ...) --> NA ... report
Examples
Example 10-96 Two Users Modifying Different Objects in the Same Analytic Workspace
A classic use of multiwriter attachment mode is to allow two users to modify two different objects in the same analytic workspace. For example, assume that an analytic workspace has two variables: actuals and budget. Assume also that one user (user A) wants to modify actuals, while another user (user B) wants to modify budget. In this case, after attaching the analytic workspace in the multiwriter mode, each user acquires the desired variable, performs the desired modification, updates, commits the changes, and then, either detaches the workspace or releases the acquired variable.
User A executes the following statements.
AW ATTACH myworkspace MULTI ACQUIRE actuals ... make modifications UPDATE MULTI actuals COMMIT RELEASE actuals AW DETACH myworkspace
While, at the same time, User B executes the following statements.
AW ATTACH myworkspace MULTI ACQUIRE budget ... make modifications UPDATE MULTI budget COMMIT RELEASE budget AW DETACH myworkspace
Example 10-97 Using RELEASE After UPDATE But Before COMMIT
Using a RELEASE statement does not always allow other users to acquire the released variable. For example, when you have updated a variable but have not committed the changes, the execution of a RELEASE statement has no effect on other users until a commit occurs. However, when you use a simple UPDATE to update all acquired variables, it can be useful to release a variable after updating it but before committing it. When a variable is released after the first update, it is not be included in the list of updated variables for the second update. The following code illustrates situations where user B1 releases budget at different times.
Assume that User B1 issues the following statements
AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT make changes C1 RELEASE budget UPDATE make changes C2 UPDATE COMMIT
User B2 could issue the following statements
AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT
User B2 gets budget and sees no changes and issues the following statements.
... AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT make changes C1 UPDATE RELEASE budget make changes C2 UPDATE COMMIT ... AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT
Alternatively, User B2 gets budget and sees changes C1 and issues the following statements.
AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT make changes C1 UPDATE make changes C2 RELEASE budget UPDATE COMMIT ... AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT
Or, as another alternative, User B2 gets budget and sees changes C1 and issues the following statements.
AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT make changes C1 UPDATE make changes C2 UPDATE COMMIT RELEASE budget ... AW ATTACH myworkspace MULTI ACQUIRE RESYNC budget WAIT
At this point, User B2 gets budget and sees changes C2
The CHGDFN command enables you to change certain aspects of the definitions of analytic workspace objects.
Before you can use CHGDFN to change the definition of an object, use CONSIDER to make that object definition the current definition.
|
Note: You cannot use CHGDFN to change definitions of objects that are in an analytic workspace that is attached in multiwriter mode. |
Syntax
CHGDFN desired-change
where desired-change is one of the following:
varname SEGWIDTH length dim...
partitioned-varname {DROP | ADD } (partition-instance...)
partition-template {DEFINE | DELETE [CLEAR] } (partition-instance...)
partition-template RENAME PARTITION old-name new-name
{conjoint | composite} {HASH | BTREE | NOHASH}
concat BASE ADD dimensionlist
conjoint COMPOSITE
composite DIMENSION
dimension NTEXT | TEXT | NUMBER [p, s]
dwmqy-dimname { {BEGINNING | ENDING} phase | {EARLIER | LATER} n}
concat [NOT] UNIQUE
varname {ADD |DROP} AGGCOUNT
varname [DROP] NULLTRACKING
Parameters
The name of the variable whose segment size you want to set.
Indicates explicit sizing of a variable's segments. See "Understanding Variable Segments" for more information.
Specifies the name of a partitioned variable whose partitions you want to modify.
Removes or adds the specified partitions from the partitioned variable. See the DEFINE VARIABLE command for a complete description of the partition-instance argument.
Removes or adds the specified partitions from the partition template object. See the DEFINE PARTITION TEMPLATE command for a complete description of the partition-instance argument.
When you include the optional CLEAR keyword, Oracle OLAP also drops any corresponding partitions in the variables that are partitioned using the partition template object. In other words, including CLEAR is the same as issuing an additional CHGDFN statements to DROP the partition from the variables partitioned by it.
Renames the specified partitions in the partition template object.
Adds the dimension or dimensions specified by dimensionlist to the base dimensions of the concat dimension.When you add one or more dimensions as base dimensions of a concat, then Oracle OLAP appends the dimensions to the existing list of base dimensions of the concat. Objects that are dimensioned by the concat, or objects that are dimensioned by a concat that has the altered concat as a base dimension, gain additional NA values. You cannot add as a base dimension a dimension that is already a component of the concat dimension.
Segment width is specified as the maximum number of values in each segment for each dimension or composite in the variable's dimension list. The first length-dim is the number of values for the dimension or composite in the first position of the dimension list in the variable's definition (that is, the fastest-varying dimension or composite), the second length-dim is the number of values for the dimension or composite in the second position in the dimension list, and so on.
For the index syntax, the name of the conjoint dimension or composite whose index algorithm you want to change. For the conjoint-to-composite syntax, the name of the conjoint dimension you want to change to a composite. For the composite-to-dim syntax, the name of the composite you want to change to a conjoint dimension. You cannot change a conjoint dimension to a composite when the conjoint is a dimension of a formula.
Indicates the index algorithm used to load and access values of your conjoint dimension or composite without losing data in objects defined with the conjoint or composite. A composite cannot be changed to NOHASH. A conjoint can be changed to NOHASH only when it was originally defined as HASH. See "Changing the Index Algorithm of a Conjoint from BTREE to NOHASH".
HASH, NOHASH, and BTREE are different index algorithms used to load and access the values of a conjoint dimension or composite. (BTREE64 can only be used with composites.) HASH is the default for conjoints. The default for composites is determined by the SPARSEINDEX option, which has a default value of BTREE. The index algorithm affects the performance of loading and accessing large conjoints or composites. Performance varies depending on your system configuration, the organization of your data, and the design of your application.
BTREE is a standard indexing method that is recommended for composites and conjoint dimensions. Use BTREE as the default unless you are an advanced user and have a special need that requires HASH or NOHASH. BTREE tends to group similar values, which results in better locality of access.
BTREE 64 can only be used with composites. It specifies the creation of a highly-scalable b-tree index to relate composite values to base dimension values. For a variable that is dimensioned by a BTREE64 composite, like a BTREE composite, Oracle OLAP creates array elements (that is, variable cells) only for those dimension values that are stored in the tuples of the composite; it does not create a cell for every value in the base dimensions. However, unlike a BTREE composite, a BTREE64 composite supports b-trees greater than 2 gigabytes
HASH is a standard indexing method that can be used for composites or conjoint dimensions that have only 2 or 3 base dimensions. One advantage to using HASH is that it results in a small amount of code. However, HASH is generally not recommended. Using HASH results in a very large index table, which can be too large to fit into memory.
NOHASH can only be used with conjoint dimensions. It can be advantageous to use NOHASH when there is little memory available and the conjoint dimension has only 2 or 3 base dimensions.Also, you can use NOHASH when you load a very large initial amount of data. When you use NOHASH, the data is loaded in a way that makes it easy to access that data after it has been loaded. Once the data is loaded, change the definition of the conjoint dimension back to BTREE to ensure good performance. Otherwise, performance is likely to suffer, especially when the conjoint dimension has 4 or more base dimensions. See "Changing the Index Algorithm of a Conjoint from BTREE to NOHASH".
|
Tip: You can do performance testing to determine which algorithm provides the best performance for your situation. For example, suppose a data load executes well at first, then slows down drastically. Use CHGDFN to change the index algorithm from BTREE to NOHASH. Try the data load again to determine whether or not using NOHASH improves performance. You can then use CHGDFN to change the index algorithm back to BTREE. Note, however, that changing the index algorithm of a large conjoint dimension or composite from one algorithm type to another may take a considerable amount of time and that the CHGDFN command cannot be interrupted. |
Indicates changing a conjoint dimension into a named composite. There are some restrictions on changing conjoint dimensions to composites; when a conjoint has the NOHASH index algorithm or when it has permissions, you cannot change it to a composite.
Indicates changing a named composite into a conjoint dimension.
The name of a composite that has a composite as a base dimension.
|
Note: In Oracle Database 11g, you cannot define a nested composite. Consequently, you only use the UNNEST keyword with nested composites that were defined in an earlier release and then imported into Oracle Database 11g. |
The name of a TEXT, NTEXT or NUMBER dimension
Specifies that the statement changes the data type of a TEXT dimension to NTEXT
Specifies that the statement changes the data type of a NTEXT dimension to TEXT
Specifies that the statement changes the data type of a TEXT, NTEXT, or NUMBER dimension to NUMBER with the precision specified by p and the scale specified by s.
Specifies or changes the phase of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR.
Specifies the beginning phase or ending phase of a dimension of type DAY, WEEK, MONTH, QUARTER, or YEAR. You must specify the phase as a date, giving the month, day, and year, enclosed in single quotes, using any of the input styles that are valid for variable values with a data type of DATE. When you specify a date with an ambiguous meaning (such as '03 05 97'), the date is interpreted according to the current setting of the DATEORDER option. For more information about specifying dates, see the DATEORDER option.
n is an INTEGER expression that increments or decrements the period on which the DAY, WEEK, MONTH, QUARTER, or YEAR dimension's phase begins or ends. For example, for a WEEK dimension whose current begin phase is Monday, specify LATER 2 to change the phase to Wednesday.
When you include NOT, changes a unique concat dimension to a nonunique concat. When you do not include NOT, changes a nonunique concat dimension to a unique concat dimension. See the DEFINE DIMENSION CONCAT command for more information on concat dimensions.
Adds an Aggcount variable to the specified variable. See the WITH AGGCOUNT phrase of the DEFINE VARIABLE command for more information about Aggcount variables.
Removes an Aggcount variable from the specified variable. See the WITH AGGCOUNT phrase of the DEFINE VARIABLE command for more information about Aggcount variables.
Adds NA2 bits to the specified variable if the variable does not have NA2 bits. For more information on NA2 bits and null tracking, see "NA2 Bits and Null Tracking" .
Removes NA2 bits to the specified variable if the variable has NA2 bits.
Usage Notes
Understanding Variable Segments
A segment is contiguous disk space reserved for a portion of the total number of values a variable holds. For example, for a variable dimensioned by month with a SEGWIDTH of 150 and product with a SEGWIDTH of 90,000, each segment holds up to 150 x 90,000 values of the variable. The number of segments in a variable affects the performance of data loading and data accessing.
When you do not specify CHGDFN SEGWIDTH, the default behavior is to assign a segwidth of 0 (zero) on non-composite dimensions and a large value for composites that are not the slowest-varying in the dimension set. This behavior allows new dimension and composite values to be added in most situations without greatly increasing the number of segments and degrading performance.
When you specify SEGWIDTH, you must specify a number, 0 (zero), or nonzero, for every dimension and composite of the variable.
When you set the value of SEGWIDTH for a dimension to 0, Oracle OLAP grows segments in that dimension as needed, minimizing the number of segments but not changing any existing segments. You can always specify 0 (zero for the slowest-varying dimension, because the data for any values that are later added to that dimension is appended to the existing data in the variable's last segment.
The segment size that you specify is used not only for the variable you designate as varname, but also for all other variables and relations that are defined with the same combination of dimensions and composites in the same order. The DEFINE command sets the SEGWIDTH at the time it creates a variable or relation. Changing the SEGWIDTH affects any new variable or relation that you subsequently create. The changed SEGWIDTH setting does not apply to previously existing variables or relations.
The time it takes to do data loads on a variable depends on how many pages are brought into memory and then written back out. This number can be affected by how a variable is divided into segments. Too many segments (thousands to millions) can degrade performance. See "Reducing the Number of Segments".
The number of segments also affects data access. The time it takes to report a variable depends on how many values are brought into memory. You decide how many segments your variable should have based on your data loading and data accessing patterns.
DEFINE provides default segments. In most cases, you can use the default segments so that you do not have to use CHGDFN SEGWIDTH to manually control the size of segments. However, you may be able to improve performance by specifying the segment size instead of using the defaults.When you are not sure what your segment size should be, use the maximum anticipated number of values for each dimension or composite as the length arguments to SEGWIDTH. Then only one segment is created for the variable.
Reducing the Number of Segments
You can use OBJ (NUMSEGS) to find out if you have too many segments for objects that have a particular dimension set. When you find that you do, you can reduce the number of segments by following these steps:
Export the variables and relations that use this dimension set to an EIF file.
Execute a MAINTAIN DELETE ALL statement for a dimension in the dimension set.
Optimally, execute a CHGDFN statement for a variable or relation with this dimension set, and increase the value of the length arguments to the SEGWIDTH keyword.
From the EIF file, import all the values you exported in Step 1.
Changing the Index Algorithm of a Conjoint from BTREE to NOHASH
When you must change a conjoint dimension that was originally defined with the BTREE algorithm to a NOHASH conjoint, you can use the following method:
Export the conjoint dimension and all the objects dimensioned by it to an EIF file.
Delete all the objects dimensioned by the conjoint dimension, and then delete the conjoint itself.
Redefine the conjoint as a NOHASH conjoint.
Import the conjoint dimension and the objects dimensioned by it from the EIF file. The NOHASH attribute on the definition at the time of the import causes the conjoint dimension to be read in as a NOHASH conjoint.
Changing an Unnamed Composite to a Named Conjoint Dimension
When you want to change an unnamed composite into a conjoint dimension, you can use a RENAME statement to change the unnamed composite into a named composite, and then use CHGDFN to change the named composite into a conjoint dimension.
Examples
For an example of removing null tracking from a variable, see Example 9-104, "Defining a Variable with Null Tracking".
Example 9-62 Using CHGDFN SEGWIDTH
Suppose you have a variable called d.sales that is dimensioned by month and by a composite with the base dimensions market and product. The definition of d.sales looks like the following.
DEFINE d.sales VARIABLE DECIMAL <month SPARSE<market product>>
Suppose you want to have only one segment in the d.sales variable. You estimate that the month dimension eventually has 150 values and the composite has 100,000. The following statement creates one segment for the d.sales variable.
CHGDFN d.sales SEGWIDTH 150 100000
However, a better way to specify segment size for d.sales is to specify 0 for the slowest-varying dimension.
CHGDFN d.sales SEGWIDTH 150 0
Suppose you want one segment for a variable defined with a composite and two dimensions. For example, suppose you have a variable called f.costs with the following definition.
DEFINE f.costs VARIABLE DECIMAL <geog SPARSE<product channel> time>
You estimate the geog dimension has 100 values and the composite has 300,000. You do not have to estimate the number of values for the time dimension, because it is the slowest-varying dimension. The following statement creates one segment for the f.costs variable.
CHGDFN f.costs SEGWIDTH 100 300000 0
Example 9-63 Changing the Phase of a YEAR Dimension
The following statements first create a dimension of type YEAR for a fiscal year, then use CHGDFN to switch to a new time phase for the fiscal year.
DEFINE fiscal DIMENSION year BEGINNING '06 01 96' CHGDFN fiscal BEGINNING '01 01 97'
Example 9-64 Adding a Base Dimension to a Concat Dimension
The following statements create a nonunique concat dimension named reg.dist.ccdim that has the region and district dimensions as its base dimensions and report the values of the concat.
DEFINE reg.dist.ccdim DIMENSION CONCAT(region district) REPORT W 22 reg.dist.ccdim
The preceding statement produces the following output.
REG.DIST.CCDIM -------------------- <region: East> <region: Central> <region: West> <district: Boston> <district: Atlanta> <district: Chicago> <district: Dallas> <district: Denver> <district: Seattle>
The following statements add the store_id dimension as a base to the concat dimension and then report the values of the concat again.
CHGDFN reg.dist.ccd BASE ADD store_id REPORT W 22 reg.dist.ccd
The preceding statement produces the following output.
REG.DIST.CCD ---------------------- <region: East> <region: Central> <region: West> <district: Boston> ... <district: Seattle> <store_id: 10> <store_id: 20> <store_id: 30> <store_id: 100> ... <store_id: 500> <store_id: 510>
The DELETE command deletes one or more objects from an analytic workspace. The deletion becomes permanent when you execute UPDATE and COMMIT statements.
Before you delete an object, you must first delete all of its associated objects. For example, before you can delete a dimension, you must first delete any variables dimensioned by it. Also, you cannot delete an object when a PERMIT statement denies you the right to change its permission.
|
Tip: When you see an error message when you try to delete an object, then the name of that object might be a reserved word. (Use RESERVED to identify reserved words.) When this is the case, use a RENAME statement to give the object a new name, and then delete it. |
Syntax
DELETE name... [AW workspace]
Parameters
The names of one or more objects, separated by spaces or commas. DELETE removes the definitions of these objects from the appropriate workspace.
You can specify a qualified object name or use the AW argument to indicate the attached workspace in which each object can be found. Do not use both qualified object names and the AW argument in the same DELETE command.
|
Note: Oracle OLAP does not warn you when you delete an object that has the same name as an existing object in another attached workspace. Also, when the NAME dimension is limited to less than all its values, DELETE automatically sets the status of NAME to ALL |
The name of an attached workspace in which you want to delete all the specified objects. When you do not use a qualified object name or the AW argument to specify an analytic workspace, objects are deleted in the current workspace.
Examples
Example 9-107 Deleting a Dimension
Suppose you have a dimension named city and a variable named population that you want to delete. The variable population is the only object that is dimensioned by or makes use of city, so you can delete them both in a single DELETE command when you place the variable before the dimension.
DELETE population city
Placing city before population in the preceding statement would produce an error.
The PARTITIONCHECK function identifies whether an aggmap object is compatible with the partitioning specified by a partition template object.
Aggregation can cross partitions; however, the data flow must always be in one direction. The data cannot go both in and out of the same partition; this processing causes Oracle OLAP to produce an error during the aggregation.
Return Value
BOOLEAN.
YES when Oracle OLAP would not issue an error when aggregating a variable partitioned using the specified partition template using the specified aggmap; or NO when an error would occur.
Syntax
PARITITONCHECK (aggmap parttition-template)
Parameters
The NVL function replaces a NA value or an empty string with a string.
To evaluate a specified expression and replace a non-NA value or empty string with one value and a NA value with another, use NVL2.
Return Value
The specified replacement value when the value of the base expression is NA, or the base expression when the value of the base expression is not NA. The data type of the return value is always the same as the data type of the base expression.
Syntax
NVL (exp , replacement-exp)
Parameters
The expression to replace when it has a NA value or an empty string.
The value with which you want to replace a NA value.
Examples
The PROGRAM command enters completely new contents into a new or existing program. When the program already has lines of code, Oracle OLAP overwrites them.
To use PROGRAM to enter the contents of a program object, the program object definition must be the one most recently defined or considered during the current session. When it is not, you must first use a CONSIDER statement to make it the current definition.
An alternative to a PROGRAM statement is an EDIT PROGRAM statement, which is available only in OLAP Worksheet. An EDIT PROGRAM statement opens an Edit window in which you can add, delete, or change the specification for a program object.
|
See also: For a discussion of writing, compiling, and debugging OLAP DML programs, see Chapter 6, "OLAP DML Programs". |
Syntax
PROGRAM [contents]
Parameters
A text expression that is the OLAP DML statements that are the lines of the program. You can use most OLAP DML statements within a program. For a discussion of writing, compiling, and debugging OLAP DML programs, see Chapter 6, "OLAP DML Programs".
The maximum number of lines you can have in a program is 4,000.When coding a PROGRAM statement at the command line level, separate program lines with newline delimiters (\n), or use the JOINLINES function as shown in "Program On the Fly".
Examples
Example 10-79 User-Defined Function with Arguments
Suppose your analytic workspace contains a variable called units.plan, which is dimensioned by the product, district, and month dimensions. The variable holds INTEGER data that indicates the number of product units that are expected to be sold.
Suppose also that you define a program namedunits_goals_met. This program is a user-defined function. It accepts three dimension-value arguments that specify a given cell of the units.plan variable, and it accepts a fourth argument that specifies the number of units that were actually sold for that cell. The program returns a Boolean value to the calling program. It returns YES when the actual figure comes up to within 10 percent of the planned figure; it returns NO when the actual figure does not.
The definition of the units_goals_met program is follows.
DEFINE units_goal_met PROGRAM BOOLEAN LD Tests whether actual units met the planned estimate "Program Initialization ARGUMENT userprod TEXT ARGUMENT userdist TEXT ARGUMENT usermonth TEXT ARGUMENT userunits INTEGER VARIABLE answer boolean TRAP ON errorlabel PUSH product district month "Program Body LIMIT product TO userprod LIMIT district TO userdist LIMIT month TO usermonth IF (units.plan - userunits) / units.plan GT .10 THEN answer = NO ELSE answer = YES "Normal Exit POP product district month RETURN answer "Abnormal Exit errorlabel: POP product district month SIGNAL ERRORNAME ERRORTEXT END
To execute the units_goal_met program and store the return value in a variable called success, you can use an assignment statement (SET).
success = units_goal_met('TENTS' 'BOSTON' 'JUN96' 2000)
Example 10-80 Program On the Fly
This example creates a flexible report program "on the fly" to avoid the inefficiencies of a more conventional program using ampersand substitution. The conventional program would contain the following loop.
FOR &dimname ROW &dimname &varname
To avoid ampersand substitution, define a program, for example, STANDARDREP, and leave it without any code in it, or with code that can be discarded. Then in your report program, insert lines such as the following.
DEFINE myreport PROGRAM
LD Program to produce my report
PROGRAM
ARGUMENT dimname TEXT
ARGUMENT varname TEXT
...
CONSIDER standardrep
PROGRAM JOINLINES(JOINCHARS('FOR ', dimname) -
JOINCHARS(' ROW ', dimname, ' ', varname) )
COMPILE standardrep
standardrep
...
Example 10-81 Program from an Input File
This example presents the text of a simple program that is in an ASCII disk file called salesrep.inf. The first line in the file defines the program, the second line contains a PROGRAM statement, and the subsequent lines provide the lines of the program.
DEFINE salesrep PROGRAM PROGRAM PUSH month product district TRAP ON haderror LIMIT month TO FIRST 3 LIMIT product TO FIRST 3 LIMIT district TO ALL REPORT grandtotals sales haderror: POP month product district END
To include the salesrep program in your analytic workspace, you can execute the following statement.
INFILE 'salesrep.inf'
You can create an input file from an existing program using an OUTFILE statement
Example 10-82 Using OLAP Worksheet Instead of a PROGRAM Statement
When you use OLAP Worksheet to create a program, you can use an EDIT statement to display an Edit window where you can enter the contents. For example, use the following statements to define a new program named salesrep and display it in an Edit window.
DEFINE salesrep PROGRAM EDIT salesrep
The POUTFILEUNIT option identifies a destination for status information about the execution of many OLAP DML statements, including:
When an OLAP DML statement is executed through SQL, using the POUTFILEUNIT option enables you to see the work that the statement is doing as it progresses instead of waiting until the execution of the SQL call is complete.
Syntax
POUTFILEUNIT = -1 |fileunit
Parameters
(Default) Specifies that Oracle OLAP is currently not logging data.
Specifies a destination, such as an open disk file, to which Oracle OLAP sends information on the progress of an operation. The fileunit can be the value of the OUTFILEUNIT option or the results of the FILEOPEN function.
Usage Notes
Changing the Setting of POUTFILEUNIT From Fileunit to -1
When you change the value of POUTFILEUNIT from fileunit to -1, Oracle OLAP disassociates the file identified by fileunit from POUTFILEUNIT and suspends logging to that file; however, but Oracle OLAP does not close that file. You can resume logging to that file by issuing another POUTFILEUNIT.
To close the file before suspending logging, issue a FILECLOSEPOUTFILEUNIT before you change the value of POUTFILEUNIT from fileunit to -1.
Information Sent by ALLOCATE and AGGREGATE
ALLOCATE, the AGGREGATE command, and AGGREGATE function send the following types of information:
Progress of the verification of the hierarchy of a dimension
Progress of the building of intermediate computation structures
The execution of the allocation or aggregation
Errors or anomalous behavior that Oracle OLAP encounters in allocating or aggregating the source data to the target variable cells, such as skipped deadlocks in an allocation.
Examples
Example 5-91 Using FILEOPEN to Open a File
In this example, a FILEOPEN statement opens a file named progress.txt in the userfiles directory object and returns the file handle to the POUTFILEUNIT option. The file receives status messages from the AGGREGATE command. When the aggregation is complete, a FILECLOSE statement closes the file.
POUTFILEUNIT=FILEOPEN('userfiles/progress.txt' WRITE)
AGGREGATE sales units USING gpct.aggmap
FILECLOSE POUTFILEUNIT
Example 5-92 Viewing Progress in OLAP Worksheet
The following statement sets POUTFILEUNIT to the current outfile destination. When the current outfile destination is the OLAP Worksheet window, remember that you cannot do other work in your session until the operation completes.
POUTFILEUNIT=OUTFILEUNIT
The SPARSITY_ADVICE_TABLE procedure creates a table for storing the advice generated by the ADVISE_SPARSITY procedure.
|
Note: You cannot execute this procedure from within the OLAP Worksheet. You must execute if in a SQL tool such as SQL*Plus. |
Syntax
SPARSITY_ADVICE_TABLE (
tblname IN VARCHAR2 DEFAULT);
Parameters
Table B-30 SPARSITY_ADVICE_TABLE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of the table. The default name is |
Example
The following example creates a table named GLOBAL_SPARSITY_ADVICE.
EXECUTE dbms_aw.sparsity_advice_table('global_sparsity_advice');
The FILEQUERY function returns information about a file. The attribute argument you specify in your FILEQUERY function call determines the type of information that is returned.
Return Value
The data type of the return value depends on the attribute you specify. See Table 7-10, "File Attributes Returned by FILEQUERY" for more information.
Syntax
FILEQUERY(file-id attrib-arg)
Parameters
A fileunit number or a file name.
A fileunit number is a number that Oracle OLAP assigned to a file you opened through a previous call to the FILEOPEN function or through the OUTFILE command. You can use the return value of the FILEOPEN function or the value of the OUTFILEUNIT option.
A file name is a text expression specifying the name of the file you want to move or rename. Unless the file is in the current directory, you must include the name of the directory object in the name of the file.
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Note: Directory objects are defined in the Database, and they control access to directories and file in those directories. You can use a CDA statement to identify and specify a current directory object. Contact your Oracle DBA for access rights to a directory object where your database user name can read and write files. |
Some attributes require that you specify a fileunit number; others require the file name. In many cases, you can specify either. See Table 7-10, "File Attributes Returned by FILEQUERY" for more information.
Specifies the type of information you want to retrieve about the file. The data type of FILEQUERY's return value depends on the attribute you specify. The attribute you specify must be appropriate for the file; otherwise, an error occurs. Table 7-10, "File Attributes Returned by FILEQUERY" lists the valid keywords for attrib-arg and, for each keyword, provides a description and indicates whether you specify a file-unit-number of a file-name for the file-id argument.
Table 7-10 File Attributes Returned by FILEQUERY
| Keyword | Return Values | Return Data Type | file-id Parameter |
|---|---|---|---|
|
APPEND |
|
|
Fileunit number |
|
BMARGIN |
The number of blank lines that form the bottom margin. |
|
Fileunit number |
|
CHANGED |
|
|
Fileunit number or file name |
|
EOF |
|
|
Fileunit number |
|
EXISTS |
|
|
Fileunit number or file name |
|
FILENAME |
The file name associated with the fileunit. |
|
Fileunit number |
|
LINENUM |
The current line number. Resets after each page break when PAGING is on; keeps incrementing when PAGING is off. When file is currently open in READ mode, returns the current record number. |
|
Fileunit number |
|
LINESLEFT |
The number of lines left on the page. |
|
Fileunit number |
|
LSIZE |
For a file that is open for writing, the line length for the standard Oracle OLAP page heading. (See the STDHDR program.) For a fileunit that is open for reading, specifies the record length for binary input files. |
|
Fileunit number |
|
NLS_CHARSET |
The character set being used for this fileunit. See the FILEOPEN function for more information. |
|
Fileunit number |
|
NUMBYTES |
The size of the file in bytes. |
|
Fileunit number or file name |
|
ORIGIN |
The type of computer on which the file was created. The ORIGIN attribute, which is relevant only for files that are open for reading, is set when you issue a FILESET statement. |
|
Fileunit number |
|
PAGENUM |
The current page number. See "Paging Attributes". |
|
Fileunit number |
|
PAGEPRG |
The Oracle OLAP program or statement that produces headings when output is paged. See "Paging Attributes". |
|
Fileunit number |
|
PAGESIZE |
The number of lines on each page. See "Paging Attributes". |
|
Fileunit number |
|
PAGING |
|
|
Fileunit number |
|
PAUSEATPAGEEND |
|
|
Fileunit number |
|
R[EAD] |
|
|
Fileunit number |
|
RO |
|
|
Fileunit number or file name |
|
TABEXPAND |
|
|
Fileunit number or file name |
|
TMARGIN |
The number of blank lines that form the top margin. |
|
Fileunit number |
|
UNIT |
The file unit for the specified file name. |
|
File name |
|
W[RITE] |
|
|
Fileunit number |
Usage Notes
Tab Treatment
When you want tab characters in the source file to be expanded when read by FILEGET or FILEREAD, you can specify the TABEXPAND attribute with the FILESET command. When TABEXPAND is zero, tab characters are not expanded. A value greater than 0 indicates the distance, in bytes, between tab stops. The default value of TABEXPAND is 8.
Paging Attributes
The paging attributes apply only to files that currently, unless otherwise noted, have PAGING set to YES and are open in WRITE mode -- such as files opened with FILEOPEN(...WRITE) or FILEOPEN(...APPEND). You can set any of the paging attributes with the FILESET command.
Wildcard Characters
(UNIX only) When querying for UNIX file names, wildcard characters (that is, * ?) are allowed when searching with the EXISTS attribute argument.
Examples
Example 7-93 Setting Paging Options for a File Opened for Writing
The following statements show how the paging options are set for a file opened for writing.
DEFINE fil.unit INTEGER
fil.unit = FILEOPEN('REPORT' WRITE)
The statement
SHOW FILEQUERY(fil.unit PAGING)
produces the following output.
YES
The statement
SHOW FILEQUERY(fil.unit PAGESIZE)
produces the following output.
66
The statement
SHOW FILEQUERY(fil.unit TMARGIN)
produces the following output.
5
The following statement closes the file.
FILECLOSE fil.unit