12 PL/SQL Optimization and Tuning

Subprogram Inlining

One optimization that the compiler can perform is subprogram inlining. Subprogram inlining replaces a subprogram invocation with a copy of the invoked subprogram (if the invoked and invoking subprograms are in the same program unit). To allow subprogram inlining, either accept the default value of the PLSQL_OPTIMIZE_LEVEL compilation parameter (which is 2) or set it to 3.

With PLSQL_OPTIMIZE_LEVEL=2, you must specify each subprogram to be inlined with the INLINE pragma:

PRAGMA INLINE (subprogram, 'YES')

If subprogram is overloaded, then the preceding pragma applies to every subprogram with that name.

With PLSQL_OPTIMIZE_LEVEL=3, the PL/SQL compiler seeks opportunities to inline subprograms. You need not specify subprograms to be inlined. However, you can use the INLINE pragma (with the preceding syntax) to give a subprogram a high priority for inlining, and then the compiler inlines it unless other considerations or limits make the inlining undesirable.

If a particular subprogram is inlined, performance almost always improves. However, because the compiler inlines subprograms early in the optimization process, it is possible for subprogram inlining to preclude later, more powerful optimizations.

If subprogram inlining slows the performance of a particular PL/SQL program, then use the PL/SQL hierarchical profiler (explained in Oracle Database Advanced Application Developer's Guide) to identify subprograms for which you want to turn off inlining. To turn off inlining for a subprogram, use the INLINE pragma:

PRAGMA INLINE (subprogram, 'NO')

The INLINE pragma affects only the immediately following declaration or statement, and only some kinds of statements.

When the INLINE pragma immediately precedes a declaration, it affects:

• Every invocation of the specified subprogram in that declaration

• Every initialization value in that declaration except the default initialization values of records

When the INLINE pragma immediately precedes one of these statements, the pragma affects every invocation of the specified subprogram in that statement:

• Assignment

• CALL

• Conditional

• CASE

• CONTINUE WHEN

• EXECUTE IMMEDIATE

• EXIT WHEN

• LOOP

• RETURN

The INLINE pragma does not affect statements that are not in the preceding list.

In Example 12-1, if PLSQL_OPTIMIZE_LEVEL=2, the INLINE pragma affects the procedure invocations p1(1) and p1(2), but not the procedure invocations p1(3) and p1(4).

PROCEDURE p1 (x PLS_INTEGER) IS ...
...
PRAGMA INLINE (p1, 'YES');
x:= p1(1) + p1(2) + 17;    -- These 2 invocations to p1 are inlined
...
x:= p1(3) + p1(4) + 17;    -- These 2 invocations to p1 are not inlined
...

In Example 12-2, if PLSQL_OPTIMIZE_LEVEL=2, the INLINE pragma affects both functions named p2.

FUNCTION p2 (p boolean) return PLS_INTEGER IS ...
FUNCTION p2 (x PLS_INTEGER) return PLS_INTEGER IS ...
...
PRAGMA INLINE(p2, 'YES');
x := p2(true) + p2(3);
...

In Example 12-3, the INLINE pragma affects the procedure invocations p1(1) and p1(2), but not the procedure invocations p1(3) and p1(4).

PROCEDURE p1 (x PLS_INTEGER) IS ...
...
PRAGMA INLINE (p1, 'NO');
x:= p1(1) + p1(2) + 17;    -- These 2 invocations to p1 are not inlined
...
x:= p1(3) + p1(4) + 17;    -- These 2 invocations to p1 might be inlined
...

Multiple pragmas can affect the same declaration or statement. Each pragma applies its own effect to the statement. If PRAGMA INLINE(subprogram,'YES') and PRAGMA INLINE(identifier,'NO') have the same subprogram, then 'NO' overrides 'YES'. One PRAGMA INLINE(subprogram,'NO') overrides any number of occurrences of PRAGMA INLINE(subprogram,'YES'), and the order of these pragmas is not important.

In Example 12-4, the second INLINE pragma overrides both the first and third INLINE pragmas.

PROCEDURE p1 (x PLS_INTEGER) IS ...
...
PRAGMA INLINE (p1, 'YES');
PRAGMA INLINE (p1, 'NO');
PRAGMA INLINE (p1, 'YES');
x:= p1(1) + p1(2) + 17;    -- These 2 invocations to p1 are not inlined
...

Tune SQL Statements

The most common cause of slowness in PL/SQL programs is slow SQL statements. To make SQL statements in a PL/SQL program as efficient as possible:

• Use appropriate indexes.

  For details, see Oracle Database Performance Tuning Guide.

• Use query hints to avoid unnecessary full-table scans.

  For details, see Oracle Database Performance Tuning Guide.

• Collect current statistics on all tables, using the subprograms in the DBMS_STATS package.

  For details, see Oracle Database Performance Tuning Guide.

• Analyze the execution plans and performance of the SQL statements, using:

  • EXPLAIN PLAN statement

    For details, see Oracle Database Performance Tuning Guide.

  • SQL Trace facility with TKPROF utility

    For details, see Oracle Database Performance Tuning Guide.

• Use bulk SQL, a set of PL/SQL features that minimizes the performance overhead of the communication between PL/SQL and SQL.

  For details, see "Bulk SQL and Bulk Binding".

Tune Function Invocations in Queries

Functions invoked in queries might run millions of times. Do not invoke a function in a query unnecessarily, and make the invocation as efficient as possible.

Create a function-based index on the table in the query. The CREATE INDEX statement (described in Oracle Database SQL Language Reference) might take a while, but the query can run much faster because the function value for each row is cached.

If the query passes a column to a function, then the query cannot use user-created indexes on that column, so the query might invoke the function for every row of the table (which might be very large). To minimize the number of function invocations, use a nested query. Have the inner query filter the result set to a small number of rows, and have the outer query invoke the function for only those rows.

In Example 12-5, the two queries produce the same result set, but the second query is more efficient than the first. (In the example, the times and time difference are very small, because the EMPLOYEES table is very small. For a very large table, they would be significant.)

DECLARE
  starting_time  TIMESTAMP WITH TIME ZONE;
  ending_time    TIMESTAMP WITH TIME ZONE;
BEGIN
  -- Invokes SQRT for every row of employees table:
 
  SELECT SYSTIMESTAMP INTO starting_time FROM DUAL;
 
  FOR item IN (
    SELECT DISTINCT(SQRT(department_id)) col_alias
    FROM employees
    ORDER BY col_alias
  )
  LOOP
    DBMS_OUTPUT.PUT_LINE('Square root of dept. ID = ' || item.col_alias);
  END LOOP;
 
  SELECT SYSTIMESTAMP INTO ending_time FROM DUAL;
 
  DBMS_OUTPUT.PUT_LINE('Time = ' || TO_CHAR(ending_time - starting_time));
 
  -- Invokes SQRT for every distinct department_id of employees table:
 
  SELECT SYSTIMESTAMP INTO starting_time FROM DUAL;
 
  FOR item IN (
    SELECT SQRT(department_id) col_alias
    FROM (SELECT DISTINCT department_id FROM employees)
    ORDER BY col_alias
  )
  LOOP
    IF item.col_alias IS NOT NULL THEN
      DBMS_OUTPUT.PUT_LINE('Square root of dept. ID = ' || item.col_alias);
    END IF;
  END LOOP;
 
  SELECT SYSTIMESTAMP INTO ending_time FROM DUAL;
 
  DBMS_OUTPUT.PUT_LINE('Time = ' || TO_CHAR(ending_time - starting_time));
END;
/

Square root of dept. ID = 3.16227766016837933199889354443271853372
Square root of dept. ID = 4.47213595499957939281834733746255247088
Square root of dept. ID = 5.47722557505166113456969782800802133953
Square root of dept. ID = 6.32455532033675866399778708886543706744
Square root of dept. ID = 7.07106781186547524400844362104849039285
Square root of dept. ID = 7.74596669241483377035853079956479922167
Square root of dept. ID = 8.36660026534075547978172025785187489393
Square root of dept. ID = 8.94427190999915878563669467492510494176
Square root of dept. ID = 9.48683298050513799599668063329815560116
Square root of dept. ID = 10
Square root of dept. ID = 10.48808848170151546991453513679937598475
Time = +000000000 00:00:00.046000000
Square root of dept. ID = 3.16227766016837933199889354443271853372
Square root of dept. ID = 4.47213595499957939281834733746255247088
Square root of dept. ID = 5.47722557505166113456969782800802133953
Square root of dept. ID = 6.32455532033675866399778708886543706744
Square root of dept. ID = 7.07106781186547524400844362104849039285
Square root of dept. ID = 7.74596669241483377035853079956479922167
Square root of dept. ID = 8.36660026534075547978172025785187489393
Square root of dept. ID = 8.94427190999915878563669467492510494176
Square root of dept. ID = 9.48683298050513799599668063329815560116
Square root of dept. ID = 10
Square root of dept. ID = 10.48808848170151546991453513679937598475
Time = +000000000 00:00:00.000000000

Tune Subprogram Invocations

If a subprogram has OUT or IN OUT parameters, you can sometimes decrease its invocation overhead by declaring those parameters with the NOCOPY hint (described in "NOCOPY").

By default, PL/SQL passes OUT and IN OUT subprogram parameters by value. Before running the subprogram, PL/SQL copies each OUT and IN OUT parameter to a temporary variable, which holds the value of the parameter during subprogram execution. If the subprogram is exited normally, then PL/SQL copies the value of the temporary variable to the corresponding actual parameter. If the subprogram is exited with an unhandled exception, then PL/SQL does not change the value of the actual parameter.

When OUT or IN OUT parameters represent large data structures such as collections, records, and instances of ADTs, copying them slows execution and increases memory use—especially for an instance of an ADT.

For each invocation of an ADT method, PL/SQL copies every attribute of the ADT. If the method is exited normally, then PL/SQL applies any changes that the method made to the attributes. If the method is exited with an unhandled exception, then PL/SQL does not change the attributes.

If your program does not require that an OUT or IN OUT parameter retain its pre-invocation value if the subprogram ends with an unhandled exception, then include the NOCOPY hint in the parameter declaration. The NOCOPY hint requests (but does not ensure) that the compiler pass the corresponding actual parameter by reference instead of value. For more information about NOCOPY, see "NOCOPY". For information about using NOCOPY with member methods of ADTs, see Oracle Database Object-Relational Developer's Guide.

In Example 12-6, if the compiler obeys the NOCOPY hint for the invocation of do_nothing2, then the invocation of do_nothing2 is faster than the invocation of do_nothing1.

DECLARE
  TYPE EmpTabTyp IS TABLE OF employees%ROWTYPE;
  emp_tab EmpTabTyp := EmpTabTyp(NULL);  -- initialize
  t1 NUMBER;
  t2 NUMBER;
  t3 NUMBER;

  PROCEDURE get_time (t OUT NUMBER) IS
  BEGIN
    t := DBMS_UTILITY.get_time;
  END;

  PROCEDURE do_nothing1 (tab IN OUT EmpTabTyp) IS
  BEGIN
    NULL;
  END;

  PROCEDURE do_nothing2 (tab IN OUT NOCOPY EmpTabTyp) IS
  BEGIN
    NULL;
  END;

BEGIN
  SELECT * INTO emp_tab(1)
  FROM employees
  WHERE employee_id = 100;

  emp_tab.EXTEND(49999, 1);  -- Copy element 1 into 2..50000
  get_time(t1);
  do_nothing1(emp_tab);  -- Pass IN OUT parameter
  get_time(t2);
  do_nothing2(emp_tab);  -- Pass IN OUT NOCOPY parameter
  get_time(t3);
  DBMS_OUTPUT.PUT_LINE ('Call Duration (secs)');
  DBMS_OUTPUT.PUT_LINE ('--------------------');
  DBMS_OUTPUT.PUT_LINE ('Just IN OUT: ' || TO_CHAR((t2 - t1)/100.0));
  DBMS_OUTPUT.PUT_LINE ('With NOCOPY: ' || TO_CHAR((t3 - t2))/100.0);
END;
/

Tune Loops

Because PL/SQL applications are often built around loops, it is important to optimize both the loops themselves and the code inside them.

If you must loop through a result set more than once, or issue other queries as you loop through a result set, you might be able to change the original query to give you exactly the results you want. Explore the SQL set operators that let you combine multiple queries, described in Oracle Database SQL Language Reference.

You can also use subqueries to do the filtering and sorting in multiple stages—see "Query Result Set Processing with Subqueries".

Tune Computation-Intensive PL/SQL Code

These recommendations apply especially (but not only) to computation-intensive PL/SQL code.

Topics

• Use Data Types that Use Hardware Arithmetic

• Avoid Constrained Subtypes in Performance-Critical Code

• Minimize Implicit Data Type Conversion

Use SQL Character Functions

SQL has many highly optimized character functions, which use low-level code that is more efficient than PL/SQL code. Use these functions instead of writing PL/SQL code to do the same things.

Put Least Expensive Conditional Tests First

PL/SQL stops evaluating a logical expression as soon as it can determine the result. Take advantage of this short-circuit evaluation by putting the conditions that are least expensive to evaluate first in logical expressions whenever possible. For example, test the values of PL/SQL variables before testing function return values, so that if the variable tests fail, PL/SQL need not invoke the functions:

IF boolean_variable OR (number > 10) OR boolean_function(parameter) THEN ...

FORALL Statement

The FORALL statement, a feature of bulk SQL, sends DML statements from PL/SQL to SQL in batches rather than one at a time. To understand the FORALL statement, first consider the FOR LOOP statement in Example 12-7. It sends these DML statements from PL/SQL to SQL one at a time:

DELETE FROM employees_temp WHERE department_id = depts(10);
DELETE FROM employees_temp WHERE department_id = depts(30);
DELETE FROM employees_temp WHERE department_id = depts(70);

DROP TABLE employees_temp;
CREATE TABLE employees_temp AS SELECT * FROM employees;

DECLARE
  TYPE NumList IS VARRAY(20) OF NUMBER;
  depts NumList := NumList(10, 30, 70);  -- department numbers
BEGIN
  FOR i IN depts.FIRST..depts.LAST LOOP
    DELETE FROM employees_temp
    WHERE department_id = depts(i);
  END LOOP;
END;
/

Now consider the FORALL statement in Example 12-8. It sends the same three DML statements from PL/SQL to SQL as a batch.

DROP TABLE employees_temp;
CREATE TABLE employees_temp AS SELECT * FROM employees;

DECLARE
  TYPE NumList IS VARRAY(20) OF NUMBER;
  depts NumList := NumList(10, 30, 70);  -- department numbers
BEGIN
  FORALL i IN depts.FIRST..depts.LAST
    DELETE FROM employees_temp
    WHERE department_id = depts(i);
END;
/

A FORALL statement is usually much faster than an equivalent FOR LOOP statement. However, a FOR LOOP statement can contain multiple DML statements, while a FORALL statement can contain only one. The batch of DML statements that a FORALL statement sends to SQL differ only in their VALUES and WHERE clauses. The values in those clauses must come from existing, populated collections.

Example 12-9 inserts the same collection elements into two database tables, using a FOR LOOP statement for the first table and a FORALL statement for the second table and showing how long each statement takes. (Times vary from run to run.)

DROP TABLE parts1;
CREATE TABLE parts1 (
  pnum INTEGER,
  pname VARCHAR2(15)
);
 
DROP TABLE parts2;
CREATE TABLE parts2 (
  pnum INTEGER,
  pname VARCHAR2(15)
);

DECLARE
  TYPE NumTab IS TABLE OF parts1.pnum%TYPE INDEX BY PLS_INTEGER;
  TYPE NameTab IS TABLE OF parts1.pname%TYPE INDEX BY PLS_INTEGER;
  pnums   NumTab;
  pnames  NameTab;
  iterations  CONSTANT PLS_INTEGER := 50000;
  t1  INTEGER;
  t2  INTEGER;
  t3  INTEGER;
BEGIN
  FOR j IN 1..iterations LOOP  -- populate collections
    pnums(j) := j;
    pnames(j) := 'Part No. ' || TO_CHAR(j);
  END LOOP;

  t1 := DBMS_UTILITY.get_time;

  FOR i IN 1..iterations LOOP
    INSERT INTO parts1 (pnum, pname)
    VALUES (pnums(i), pnames(i));
  END LOOP;

  t2 := DBMS_UTILITY.get_time;

  FORALL i IN 1..iterations
    INSERT INTO parts2 (pnum, pname)
    VALUES (pnums(i), pnames(i));

  t3 := DBMS_UTILITY.get_time;

  DBMS_OUTPUT.PUT_LINE('Execution Time (secs)');
  DBMS_OUTPUT.PUT_LINE('---------------------');
  DBMS_OUTPUT.PUT_LINE('FOR LOOP: ' || TO_CHAR((t2 - t1)/100));
  DBMS_OUTPUT.PUT_LINE('FORALL:   ' || TO_CHAR((t3 - t2)/100));
  COMMIT;
END;
/

Execution Time (secs)
---------------------
FOR LOOP: 2.16
FORALL:   .11
 
PL/SQL procedure successfully completed.

In Example 12-10, the FORALL statement applies to a subset of a collection.

DROP TABLE employees_temp;
CREATE TABLE employees_temp AS SELECT * FROM employees;

DECLARE
  TYPE NumList IS VARRAY(10) OF NUMBER;
  depts NumList := NumList(5,10,20,30,50,55,57,60,70,75);
BEGIN
  FORALL j IN 4..7
    DELETE FROM employees_temp WHERE department_id = depts(j);
END;
/

Topics

• FORALL Statements for Sparse Collections

• Unhandled Exceptions in FORALL Statements

• Handling FORALL Exceptions Immediately

• Handling FORALL Exceptions After FORALL Statement Completes

• Getting Number of Rows Affected by FORALL Statement

DROP TABLE valid_orders;
CREATE TABLE valid_orders (
  cust_name  VARCHAR2(32),
  amount     NUMBER(10,2)
);
 
DROP TABLE big_orders;
CREATE TABLE big_orders AS
  SELECT * FROM valid_orders
  WHERE 1 = 0;
 
DROP TABLE rejected_orders;
CREATE TABLE rejected_orders AS
  SELECT * FROM valid_orders
  WHERE 1 = 0;
 
DECLARE
  SUBTYPE cust_name IS valid_orders.cust_name%TYPE;
  TYPE cust_typ IS TABLE OF cust_name;
  cust_tab  cust_typ;  -- Collection of customer names
 
  SUBTYPE order_amount IS valid_orders.amount%TYPE;
  TYPE amount_typ IS TABLE OF NUMBER;
  amount_tab  amount_typ;  -- Collection of order amounts
 
  TYPE index_pointer_t IS TABLE OF PLS_INTEGER;
 
  /* Collections for pointers to elements of cust_tab collection
     (to represent two subsets of cust_tab): */
 
  big_order_tab       index_pointer_t := index_pointer_t();
  rejected_order_tab  index_pointer_t := index_pointer_t();
 
  PROCEDURE populate_data_collections IS
  BEGIN
    cust_tab := cust_typ(
      'Company1','Company2','Company3','Company4','Company5'
    );
 
    amount_tab := amount_typ(5000.01, 0, 150.25, 4000.00, NULL);
  END;
 
BEGIN
  populate_data_collections;
 
  DBMS_OUTPUT.PUT_LINE ('--- Original order data ---');
 
  FOR i IN 1..cust_tab.LAST LOOP
    DBMS_OUTPUT.PUT_LINE (
      'Customer #' || i || ', ' || cust_tab(i) || ': $' || amount_tab(i)
    );
  END LOOP;
 
  -- Delete invalid orders:
 
  FOR i IN 1..cust_tab.LAST LOOP
    IF amount_tab(i) IS NULL OR amount_tab(i) = 0 THEN
      cust_tab.delete(i);
      amount_tab.delete(i);
    END IF;
  END LOOP;
 
  -- cust_tab is now a sparse collection.
 
  DBMS_OUTPUT.PUT_LINE ('--- Order data with invalid orders deleted ---');
 
  FOR i IN 1..cust_tab.LAST LOOP
    IF cust_tab.EXISTS(i) THEN
      DBMS_OUTPUT.PUT_LINE (
        'Customer #' || i || ', ' || cust_tab(i) || ': $' || amount_tab(i)
      );
    END IF;
  END LOOP;
 
  -- Using sparse collection, populate valid_orders table:
 
  FORALL i IN INDICES OF cust_tab
    INSERT INTO valid_orders (cust_name, amount)
    VALUES (cust_tab(i), amount_tab(i));
 
  populate_data_collections;  -- Restore original order data
 
  -- cust_tab is a dense collection again.
 
  /* Populate collections of pointers to elements of cust_tab collection
     (which represent two subsets of cust_tab): */
 
  FOR i IN cust_tab.FIRST .. cust_tab.LAST LOOP
    IF amount_tab(i) IS NULL OR amount_tab(i) = 0 THEN
      rejected_order_tab.EXTEND;
      rejected_order_tab(rejected_order_tab.LAST) := i; 
    END IF;
 
    IF amount_tab(i) > 2000 THEN
      big_order_tab.EXTEND;
      big_order_tab(big_order_tab.LAST) := i;
    END IF;
  END LOOP;
 
  /* Using each subset in a different FORALL statement,
     populate rejected_orders and big_orders tables: */
 
  FORALL i IN VALUES OF rejected_order_tab
    INSERT INTO rejected_orders (cust_name, amount)
    VALUES (cust_tab(i), amount_tab(i));
 
  FORALL i IN VALUES OF big_order_tab
    INSERT INTO big_orders (cust_name, amount)
    VALUES (cust_tab(i), amount_tab(i));
END;
/

--- Original order data ---
Customer #1, Company1: $5000.01
Customer #2, Company2: $0
Customer #3, Company3: $150.25
Customer #4, Company4: $4000
Customer #5, Company5: $
--- Data with invalid orders deleted ---
Customer #1, Company1: $5000.01
Customer #3, Company3: $150.25
Customer #4, Company4: $4000

SELECT cust_name "Customer", amount "Valid order amount"
FROM valid_orders
ORDER BY cust_name;

Customer                         Valid order amount
-------------------------------- ------------------
Company1                                    5000.01
Company3                                     150.25
Company4                                       4000
 
3 rows selected.

SELECT cust_name "Customer", amount "Big order amount"
FROM big_orders
ORDER BY cust_name;

Customer                         Big order amount
-------------------------------- ----------------
Company1                                  5000.01
Company4                                     4000
 
2 rows selected.

SELECT cust_name "Customer", amount "Rejected order amount"
FROM rejected_orders
ORDER BY cust_name;

Customer                         Rejected order amount
-------------------------------- ---------------------
Company2                                             0
Company5
 
2 rows selected.

DELETE FROM employees_temp WHERE department_id = depts(10);
DELETE FROM employees_temp WHERE department_id = depts(30);
DELETE FROM employees_temp WHERE department_id = depts(70);

DROP TABLE emp_temp;
CREATE TABLE emp_temp (
  deptno NUMBER(2),
  job VARCHAR2(18)
);
 
CREATE OR REPLACE PROCEDURE p AUTHID DEFINER AS
  TYPE NumList IS TABLE OF NUMBER;
 
  depts          NumList := NumList(10, 20, 30);
  error_message  VARCHAR2(100);
 
BEGIN
  -- Populate table:
 
  INSERT INTO emp_temp (deptno, job) VALUES (10, 'Clerk');
  INSERT INTO emp_temp (deptno, job) VALUES (20, 'Bookkeeper');
  INSERT INTO emp_temp (deptno, job) VALUES (30, 'Analyst');
  COMMIT;
 
  -- Append 9-character string to each job:
 
  FORALL j IN depts.FIRST..depts.LAST
    UPDATE emp_temp SET job = job || ' (Senior)'
    WHERE deptno = depts(j);
 
EXCEPTION
  WHEN OTHERS THEN
    error_message := SQLERRM;
    DBMS_OUTPUT.PUT_LINE (error_message);
 
    COMMIT;  -- Commit results of successful updates
    RAISE;
END;
/

Procedure created.

BEGIN
  p;
END;
/

ORA-12899: value too large for column "HR"."EMP_TEMP"."JOB" (actual: 19,
maximum: 18)
ORA-06512: at "HR.P", line 27
ORA-06512: at line 2
 
PL/SQL procedure successfully completed.

SELECT * FROM emp_temp;

DEPTNO JOB
---------- ------------------
        10 Clerk (Senior)
        20 Bookkeeper
        30 Analyst
 
3 rows selected.

SQLERRM(-(SQL%BULK_EXCEPTIONS(i).ERROR_CODE))

CREATE OR REPLACE PROCEDURE p AUTHID DEFINER AS
  TYPE NumList IS TABLE OF NUMBER;
  depts        NumList := NumList(10, 20, 30);
 
  error_message  VARCHAR2(100);
  bad_stmt_no    PLS_INTEGER;
  bad_deptno     emp_temp.deptno%TYPE;
  bad_job        emp_temp.job%TYPE;
 
  dml_errors  EXCEPTION;
  PRAGMA EXCEPTION_INIT(dml_errors, -24381);
BEGIN
  -- Populate table:
 
  INSERT INTO emp_temp (deptno, job) VALUES (10, 'Clerk');
  INSERT INTO emp_temp (deptno, job) VALUES (20, 'Bookkeeper');
  INSERT INTO emp_temp (deptno, job) VALUES (30, 'Analyst');
  COMMIT;
 
  -- Append 9-character string to each job:
 
  FORALL j IN depts.FIRST..depts.LAST SAVE EXCEPTIONS
    UPDATE emp_temp SET job = job || ' (Senior)'
    WHERE deptno = depts(j); 
 
EXCEPTION
  WHEN dml_errors THEN
    FOR i IN 1..SQL%BULK_EXCEPTIONS.COUNT LOOP
      error_message := SQLERRM(-(SQL%BULK_EXCEPTIONS(i).ERROR_CODE));
      DBMS_OUTPUT.PUT_LINE (error_message);
 
      bad_stmt_no := SQL%BULK_EXCEPTIONS(i).ERROR_INDEX;
      DBMS_OUTPUT.PUT_LINE('Bad statement #: ' || bad_stmt_no);
 
      bad_deptno := depts(bad_stmt_no);
      DBMS_OUTPUT.PUT_LINE('Bad department #: ' || bad_deptno);
 
      SELECT job INTO bad_job FROM emp_temp WHERE deptno = bad_deptno;
 
      DBMS_OUTPUT.PUT_LINE('Bad job: ' || bad_job);
    END LOOP;
 
    COMMIT;  -- Commit results of successful updates

    WHEN OTHERS THEN
      DBMS_OUTPUT.PUT_LINE('Unrecognized error.');
      RAISE;
END;
/
 

Procedure created.

BEGIN
  p;
END;
/

ORA-12899: value too large for column  (actual: , maximum: )
Bad statement #: 2
Bad department #: 20
Bad job: Bookkeeper
 
PL/SQL procedure successfully completed.

SELECT * FROM emp_temp;

DEPTNO JOB
---------- ------------------
        10 Clerk (Senior)
        20 Bookkeeper
        30 Analyst (Senior)
 
3 rows selected.

DROP TABLE emp_temp;
CREATE TABLE emp_temp AS SELECT * FROM employees;

DECLARE
  TYPE NumList IS TABLE OF NUMBER;
  depts NumList := NumList(30, 50, 60);
BEGIN
  FORALL j IN depts.FIRST..depts.LAST
    DELETE FROM emp_temp WHERE department_id = depts(j);

  FOR i IN depts.FIRST..depts.LAST LOOP
    DBMS_OUTPUT.PUT_LINE (
      'Statement #' || i || ' deleted ' ||
      SQL%BULK_ROWCOUNT(i) || ' rows.'
    );
  END LOOP;

  DBMS_OUTPUT.PUT_LINE('Total rows deleted: ' || SQL%ROWCOUNT);
END;
/

Statement #1 deleted 6 rows.
Statement #2 deleted 45 rows.
Statement #3 deleted 5 rows.
Total rows deleted: 56

DROP TABLE emp_by_dept;
CREATE TABLE emp_by_dept AS
  SELECT employee_id, department_id
  FROM employees
  WHERE 1 = 0;

DECLARE
  TYPE dept_tab IS TABLE OF departments.department_id%TYPE;
  deptnums  dept_tab;
BEGIN
  SELECT department_id BULK COLLECT INTO deptnums FROM departments;

  FORALL i IN 1..deptnums.COUNT
    INSERT INTO emp_by_dept (employee_id, department_id)
      SELECT employee_id, department_id
      FROM employees
      WHERE department_id = deptnums(i)
      ORDER BY department_id, employee_id;

  FOR i IN 1..deptnums.COUNT LOOP
    -- Count how many rows were inserted for each department; that is,
    -- how many employees are in each department.
    DBMS_OUTPUT.PUT_LINE (
      'Dept '||deptnums(i)||': inserted '||
      SQL%BULK_ROWCOUNT(i)||' records'
    );
  END LOOP;
  DBMS_OUTPUT.PUT_LINE('Total records inserted: ' || SQL%ROWCOUNT);
END;
/

Dept 10: inserted 1 records
Dept 20: inserted 2 records
Dept 30: inserted 6 records
Dept 40: inserted 1 records
Dept 50: inserted 45 records
Dept 60: inserted 5 records
Dept 70: inserted 1 records
Dept 80: inserted 34 records
Dept 90: inserted 3 records
Dept 100: inserted 6 records
Dept 110: inserted 2 records
Dept 120: inserted 0 records
Dept 130: inserted 0 records
Dept 140: inserted 0 records
Dept 150: inserted 0 records
Dept 160: inserted 0 records
Dept 170: inserted 0 records
Dept 180: inserted 0 records
Dept 190: inserted 0 records
Dept 200: inserted 0 records
Dept 210: inserted 0 records
Dept 220: inserted 0 records
Dept 230: inserted 0 records
Dept 240: inserted 0 records
Dept 250: inserted 0 records
Dept 260: inserted 0 records
Dept 270: inserted 0 records
Dept 280: inserted 0 records
Total records inserted: 106

BULK COLLECT Clause

The BULK COLLECT clause, a feature of bulk SQL, returns results from SQL to PL/SQL in batches rather than one at a time. The BULK COLLECT clause can appear in:

• SELECT INTO statement

• FETCH statement

• RETURNING INTO clause of:

  • DELETE statement

  • INSERT statement

  • UPDATE statement

  • EXECUTE IMMEDIATE statement

With the BULK COLLECT clause, each of the preceding statements retrieves an entire result set and stores it in one or more collection variables in a single operation (which is more efficient than using a loop statement to retrieve one result row at a time).

Topics

• SELECT INTO Statement with BULK COLLECT Clause

• FETCH Statement with BULK COLLECT Clause

• RETURNING INTO Clause with BULK COLLECT Clause

DECLARE
  TYPE NumTab IS TABLE OF employees.employee_id%TYPE;
  TYPE NameTab IS TABLE OF employees.last_name%TYPE;
 
  enums NumTab;
  names NameTab;
 
  PROCEDURE print_first_n (n POSITIVE) IS
  BEGIN
    IF enums.COUNT = 0 THEN
      DBMS_OUTPUT.PUT_LINE ('Collections are empty.');
    ELSE
      DBMS_OUTPUT.PUT_LINE ('First ' || n || ' employees:');
 
      FOR i IN 1 .. n LOOP
        DBMS_OUTPUT.PUT_LINE (
          '  Employee #' || enums(i) || ': ' || names(i));
      END LOOP;
    END IF;
  END;
 
BEGIN
  SELECT employee_id, last_name
  BULK COLLECT INTO enums, names
  FROM employees
  ORDER BY employee_id;
 
  print_first_n(3);
  print_first_n(6);
END;
/

First 3 employees:
Employee #100: King
Employee #101: Kochhar
Employee #102: De Haan
First 6 employees:
Employee #100: King
Employee #101: Kochhar
Employee #102: De Haan
Employee #103: Hunold
Employee #104: Ernst
Employee #105: Austin

DECLARE
  CURSOR c1 IS
    SELECT first_name, last_name, hire_date
    FROM employees;
  
  TYPE NameSet IS TABLE OF c1%ROWTYPE;
 
  stock_managers  NameSet;  -- nested table of records
 
BEGIN 
  -- Assign values to nested table of records:
 
  SELECT first_name, last_name, hire_date
    BULK COLLECT INTO stock_managers
    FROM employees
    WHERE job_id = 'ST_MAN'
    ORDER BY hire_date;
 
  -- Print nested table of records:
 
    FOR i IN stock_managers.FIRST .. stock_managers.LAST LOOP
      DBMS_OUTPUT.PUT_LINE (
        stock_managers(i).hire_date || ' ' ||
        stock_managers(i).last_name  || ', ' ||
        stock_managers(i).first_name
      );
    END LOOP;END;
/

01-MAY-03 Kaufling, Payam
18-JUL-04 Weiss, Matthew
10-APR-05 Fripp, Adam
10-OCT-05 Vollman, Shanta
16-NOV-07 Mourgos, Kevin

SELECT column BULK COLLECT INTO collection FROM table ...

CREATE OR REPLACE TYPE numbers_type IS
  TABLE OF INTEGER
/
CREATE OR REPLACE PROCEDURE p (i IN INTEGER) IS
  numbers1  numbers_type := numbers_type(1,2,3,4,5);
BEGIN
  DBMS_OUTPUT.PUT_LINE('Before SELECT statement');
  DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
  
  FOR j IN 1..numbers1.COUNT() LOOP
    DBMS_OUTPUT.PUT_LINE('numbers1(' || j || ') = ' || numbers1(j));
  END LOOP;
 
  --Self-selecting BULK COLLECT INTO clause:
 
  SELECT a.COLUMN_VALUE
  BULK COLLECT INTO numbers1
  FROM TABLE(numbers1) a
  WHERE a.COLUMN_VALUE > p.i
  ORDER BY a.COLUMN_VALUE;
 
  DBMS_OUTPUT.PUT_LINE('After SELECT statement');
  DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
END p;
/

BEGIN
  p(2);
END;
/

Before SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
After SELECT statement
numbers1.COUNT() = 0
 
PL/SQL procedure successfully completed.

BEGIN
  p(10);
END;
/

Before SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
After SELECT statement
numbers1.COUNT() = 0

CREATE OR REPLACE TYPE numbers_type IS
  TABLE OF INTEGER
/
CREATE OR REPLACE PROCEDURE p (i IN INTEGER) IS
  numbers1  numbers_type := numbers_type(1,2,3,4,5);
  
  CURSOR c IS
    SELECT a.COLUMN_VALUE
    FROM TABLE(numbers1) a
    WHERE a.COLUMN_VALUE > p.i
    ORDER BY a.COLUMN_VALUE;
  BEGIN
    DBMS_OUTPUT.PUT_LINE('Before FETCH statement');
    DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
 
    FOR j IN 1..numbers1.COUNT() LOOP
      DBMS_OUTPUT.PUT_LINE('numbers1(' || j || ') = ' || numbers1(j));
    END LOOP;
 
  OPEN c;
  FETCH c BULK COLLECT INTO numbers1;
  CLOSE c;
 
  DBMS_OUTPUT.PUT_LINE('After FETCH statement');
  DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
 
  IF numbers1.COUNT() > 0 THEN
    FOR j IN 1..numbers1.COUNT() LOOP
      DBMS_OUTPUT.PUT_LINE('numbers1(' || j || ') = ' || numbers1(j));
    END LOOP;
  END IF;
END p;
/

BEGIN
  p(2);
END;
/

Before FETCH statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
After FETCH statement
numbers1.COUNT() = 3
numbers1(1) = 3
numbers1(2) = 4
numbers1(3) = 5

BEGIN
  p(10);
END;
/

Before FETCH statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
After FETCH statement
numbers1.COUNT() = 0

CREATE OR REPLACE TYPE numbers_type IS
  TABLE OF INTEGER
/
CREATE OR REPLACE PROCEDURE p (i IN INTEGER) IS
  numbers1  numbers_type := numbers_type(1,2,3,4,5);
 numbers2  numbers_type := numbers_type(0,0,0,0,0);
  
BEGIN
  DBMS_OUTPUT.PUT_LINE('Before SELECT statement');
  
  DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
  
  FOR j IN 1..numbers1.COUNT() LOOP
    DBMS_OUTPUT.PUT_LINE('numbers1(' || j || ') = ' || numbers1(j));
  END LOOP;
 
  DBMS_OUTPUT.PUT_LINE('numbers2.COUNT() = ' || numbers2.COUNT());
 
  FOR j IN 1..numbers2.COUNT() LOOP
    DBMS_OUTPUT.PUT_LINE('numbers2(' || j || ') = ' || numbers2(j));
  END LOOP;
 
  SELECT a.COLUMN_VALUE
  BULK COLLECT INTO numbers2      -- numbers2 appears here
  FROM TABLE(numbers1) a        -- numbers1 appears here
  WHERE a.COLUMN_VALUE > p.i
  ORDER BY a.COLUMN_VALUE;
 
  DBMS_OUTPUT.PUT_LINE('After SELECT statement');
  DBMS_OUTPUT.PUT_LINE('numbers1.COUNT() = ' || numbers1.COUNT());
 
  IF numbers1.COUNT() > 0 THEN
    FOR j IN 1..numbers1.COUNT() LOOP
      DBMS_OUTPUT.PUT_LINE('numbers1(' || j || ') = ' || numbers1(j));
    END LOOP;
  END IF;
 
  DBMS_OUTPUT.PUT_LINE('numbers2.COUNT() = ' || numbers2.COUNT());
 
  IF numbers2.COUNT() > 0 THEN
    FOR j IN 1..numbers2.COUNT() LOOP
      DBMS_OUTPUT.PUT_LINE('numbers2(' || j || ') = ' || numbers2(j));
    END LOOP;
  END IF;
END p;
/

BEGIN
  p(2);
 END;
/

Before SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
numbers2.COUNT() = 5
numbers2(1) = 0
numbers2(2) = 0
numbers2(3) = 0
numbers2(4) = 0
numbers2(5) = 0
After SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
numbers2.COUNT() = 3
numbers2(1) = 3
numbers2(2) = 4
numbers2(3) = 5
 
PL/SQL procedure successfully completed.

BEGIN
  p(10);
END;
/

Before SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
numbers2.COUNT() = 5
numbers2(1) = 0
numbers2(2) = 0
numbers2(3) = 0
numbers2(4) = 0
numbers2(5) = 0
After SELECT statement
numbers1.COUNT() = 5
numbers1(1) = 1
numbers1(2) = 2
numbers1(3) = 3
numbers1(4) = 4
numbers1(5) = 5
numbers2.COUNT() = 0

DECLARE
  TYPE SalList IS TABLE OF employees.salary%TYPE;
  sals SalList;
BEGIN
  SELECT salary BULK COLLECT INTO sals
  FROM employees
  WHERE ROWNUM <= 50;

  SELECT salary BULK COLLECT INTO sals FROM employees SAMPLE (10);
END;
/

DECLARE
  TYPE NameList IS TABLE OF employees.last_name%TYPE;
  TYPE SalList IS TABLE OF employees.salary%TYPE;

  CURSOR c1 IS
    SELECT last_name, salary
    FROM employees
    WHERE salary > 10000
    ORDER BY last_name;

  names  NameList;
  sals   SalList;

  TYPE RecList IS TABLE OF c1%ROWTYPE;
  recs RecList;

  v_limit PLS_INTEGER := 10;

  PROCEDURE print_results IS
  BEGIN
    -- Check if collections are empty:

    IF names IS NULL OR names.COUNT = 0 THEN
      DBMS_OUTPUT.PUT_LINE('No results!');
    ELSE
      DBMS_OUTPUT.PUT_LINE('Result: ');
      FOR i IN names.FIRST .. names.LAST
      LOOP
        DBMS_OUTPUT.PUT_LINE('  Employee ' || names(i) || ': $' || sals(i));
      END LOOP;
    END IF;
  END;

BEGIN
  DBMS_OUTPUT.PUT_LINE ('--- Processing all results simultaneously ---');
  OPEN c1;
  FETCH c1 BULK COLLECT INTO names, sals;
  CLOSE c1;
  print_results();
  DBMS_OUTPUT.PUT_LINE ('--- Processing ' || v_limit || ' rows at a time ---');
  OPEN c1;
  LOOP
    FETCH c1 BULK COLLECT INTO names, sals LIMIT v_limit;
    EXIT WHEN names.COUNT = 0;
    print_results();
  END LOOP;
  CLOSE c1;
  DBMS_OUTPUT.PUT_LINE ('--- Fetching records rather than columns ---');
  OPEN c1;
  FETCH c1 BULK COLLECT INTO recs;
  FOR i IN recs.FIRST .. recs.LAST
  LOOP
    -- Now all columns from result set come from one record
    DBMS_OUTPUT.PUT_LINE (
      '  Employee ' || recs(i).last_name || ': $' || recs(i).salary
    );
  END LOOP;
END;
/

--- Processing all results simultaneously ---
Result:
Employee Abel: $11000
Employee Cambrault: $11000
Employee De Haan: $17000
Employee Errazuriz: $12000
Employee Fripp: $18540.29
Employee Greenberg: $12008
Employee Hartstein: $13000
Employee Higgins: $12008
Employee Kaufling: $17862
Employee King: $24000
Employee Kochhar: $17000
Employee Mourgos: $13113.87
Employee Ozer: $11500
Employee Partners: $13500
Employee Raphaely: $11000
Employee Russell: $14000
Employee Vishney: $10500
Employee Vollman: $14696.58
Employee Weiss: $22907.66
Employee Zlotkey: $10500
--- Processing 10 rows at a time ---
Result:
Employee Abel: $11000
Employee Cambrault: $11000
Employee De Haan: $17000
Employee Errazuriz: $12000
Employee Fripp: $18540.29
Employee Greenberg: $12008
Employee Hartstein: $13000
Employee Higgins: $12008
Employee Kaufling: $17862
Employee King: $24000
Result:
Employee Kochhar: $17000
Employee Mourgos: $13113.87
Employee Ozer: $11500
Employee Partners: $13500
Employee Raphaely: $11000
Employee Russell: $14000
Employee Vishney: $10500
Employee Vollman: $14696.58
Employee Weiss: $22907.66
Employee Zlotkey: $10500
--- Fetching records rather than columns ---
Employee Abel: $11000
Employee Cambrault: $11000
Employee De Haan: $17000
Employee Errazuriz: $12000
Employee Fripp: $18540.29
Employee Greenberg: $12008
Employee Hartstein: $13000
Employee Higgins: $12008
Employee Kaufling: $17862
Employee King: $24000
Employee Kochhar: $17000
Employee Mourgos: $13113.87
Employee Ozer: $11500
Employee Partners: $13500
Employee Raphaely: $11000
Employee Russell: $14000
Employee Vishney: $10500
Employee Vollman: $14696.58
Employee Weiss: $22907.66
Employee Zlotkey: $10500

DECLARE
  CURSOR c1 IS
    SELECT first_name, last_name, hire_date
    FROM employees;
  
  TYPE NameSet IS TABLE OF c1%ROWTYPE;
  stock_managers  NameSet;  -- nested table of records
 
  TYPE cursor_var_type is REF CURSOR;
  cv cursor_var_type;
 
BEGIN 
  -- Assign values to nested table of records:
 
  OPEN cv FOR
    SELECT first_name, last_name, hire_date
    FROM employees
    WHERE job_id = 'ST_MAN'
    ORDER BY hire_date;
 
  FETCH cv BULK COLLECT INTO stock_managers;
  CLOSE cv;
 
  -- Print nested table of records:
 
    FOR i IN stock_managers.FIRST .. stock_managers.LAST LOOP
      DBMS_OUTPUT.PUT_LINE (
        stock_managers(i).hire_date || ' ' ||
        stock_managers(i).last_name  || ', ' ||
        stock_managers(i).first_name
      );
    END LOOP;END;
/

01-MAY-03 Kaufling, Payam
18-JUL-04 Weiss, Matthew
10-APR-05 Fripp, Adam
10-OCT-05 Vollman, Shanta
16-NOV-07 Mourgos, Kevin

DECLARE
  TYPE numtab IS TABLE OF NUMBER INDEX BY PLS_INTEGER;

  CURSOR c1 IS
    SELECT employee_id
    FROM employees
    WHERE department_id = 80
    ORDER BY employee_id;

  empids  numtab;
BEGIN
  OPEN c1;
  LOOP  -- Fetch 10 rows or fewer in each iteration
    FETCH c1 BULK COLLECT INTO empids LIMIT 10;
    DBMS_OUTPUT.PUT_LINE ('------- Results from One Bulk Fetch --------');
    FOR i IN 1..empids.COUNT LOOP
      DBMS_OUTPUT.PUT_LINE ('Employee Id: ' || empids(i));
    END LOOP;
    EXIT WHEN c1%NOTFOUND;
  END LOOP;
  CLOSE c1;
END;
/

------- Results from One Bulk Fetch --------
Employee Id: 145
Employee Id: 146
Employee Id: 147
Employee Id: 148
Employee Id: 149
Employee Id: 150
Employee Id: 151
Employee Id: 152
Employee Id: 153
Employee Id: 154
------- Results from One Bulk Fetch --------
Employee Id: 155
Employee Id: 156
Employee Id: 157
Employee Id: 158
Employee Id: 159
Employee Id: 160
Employee Id: 161
Employee Id: 162
Employee Id: 163
Employee Id: 164
------- Results from One Bulk Fetch --------
Employee Id: 165
Employee Id: 166
Employee Id: 167
Employee Id: 168
Employee Id: 169
Employee Id: 170
Employee Id: 171
Employee Id: 172
Employee Id: 173
Employee Id: 174
------- Results from One Bulk Fetch --------
Employee Id: 175
Employee Id: 176
Employee Id: 177
Employee Id: 179

DROP TABLE emp_temp;
CREATE TABLE emp_temp AS
SELECT * FROM employees
ORDER BY employee_id;

DECLARE
  TYPE NumList IS TABLE OF employees.employee_id%TYPE;
  enums  NumList;
  TYPE NameList IS TABLE OF employees.last_name%TYPE;
  names  NameList;
BEGIN
  DELETE FROM emp_temp
  WHERE department_id = 30
  RETURNING employee_id, last_name
  BULK COLLECT INTO enums, names;

  DBMS_OUTPUT.PUT_LINE ('Deleted ' || SQL%ROWCOUNT || ' rows:');
  FOR i IN enums.FIRST .. enums.LAST
  LOOP
    DBMS_OUTPUT.PUT_LINE ('Employee #' || enums(i) || ': ' || names(i));
  END LOOP;
END;
/

Deleted 6 rows:
Employee #114: Raphaely
Employee #115: Khoo
Employee #116: Baida
Employee #117: Tobias
Employee #118: Himuro
Employee #119: Colmenares

Using FORALL Statement and BULK COLLECT Clause Together

In a FORALL statement, the DML statement can have a RETURNING BULK COLLECT INTO clause. For each iteration of the FORALL statement, the DML statement stores the specified values in the specified collections—without overwriting the previous values, as the same DML statement would do in a FOR LOOP statement.

In Example 12-26, the FORALL statement runs a DELETE statement that has a RETURNING BULK COLLECT INTO clause. For each iteration of the FORALL statement, the DELETE statement stores the employee_id and department_id values of the deleted row in the collections e_ids and d_ids, respectively.

DROP TABLE emp_temp;
CREATE TABLE emp_temp AS
SELECT * FROM employees
ORDER BY employee_id, department_id;

DECLARE
  TYPE NumList IS TABLE OF NUMBER;
  depts  NumList := NumList(10,20,30);

  TYPE enum_t IS TABLE OF employees.employee_id%TYPE;
  e_ids  enum_t;

  TYPE dept_t IS TABLE OF employees.department_id%TYPE;
  d_ids  dept_t;

BEGIN
  FORALL j IN depts.FIRST..depts.LAST
    DELETE FROM emp_temp
    WHERE department_id = depts(j)
    RETURNING employee_id, department_id
    BULK COLLECT INTO e_ids, d_ids;

  DBMS_OUTPUT.PUT_LINE ('Deleted ' || SQL%ROWCOUNT || ' rows:');

  FOR i IN e_ids.FIRST .. e_ids.LAST
  LOOP
    DBMS_OUTPUT.PUT_LINE (
      'Employee #' || e_ids(i) || ' from dept #' || d_ids(i)
    );
  END LOOP;
END;
/

Deleted 9 rows:
Employee #200 from dept #10
Employee #201 from dept #20
Employee #202 from dept #20
Employee #114 from dept #30
Employee #115 from dept #30
Employee #116 from dept #30
Employee #117 from dept #30
Employee #118 from dept #30
Employee #119 from dept #30

Example 12-27 is like Example 12-26 except that it uses a FOR LOOP statement instead of a FORALL statement.

DECLARE
  TYPE NumList IS TABLE OF NUMBER;
  depts  NumList := NumList(10,20,30);
 
  TYPE enum_t IS TABLE OF employees.employee_id%TYPE;
  e_ids  enum_t;
 
  TYPE dept_t IS TABLE OF employees.department_id%TYPE;
  d_ids  dept_t;
 
BEGIN
  FOR j IN depts.FIRST..depts.LAST LOOP
    DELETE FROM emp_temp
    WHERE department_id = depts(j)
    RETURNING employee_id, department_id
    BULK COLLECT INTO e_ids, d_ids;
  END LOOP;
 
  DBMS_OUTPUT.PUT_LINE ('Deleted ' || SQL%ROWCOUNT || ' rows:');
 
  FOR i IN e_ids.FIRST .. e_ids.LAST
  LOOP
    DBMS_OUTPUT.PUT_LINE (
      'Employee #' || e_ids(i) || ' from dept #' || d_ids(i)
    );
  END LOOP;
END;
/

Deleted 6 rows:
Employee #114 from dept #30
Employee #115 from dept #30
Employee #116 from dept #30
Employee #117 from dept #30
Employee #118 from dept #30
Employee #119 from dept #30

Client Bulk-Binding of Host Arrays

Client programs (such as OCI and Pro*C programs) can use PL/SQL anonymous blocks to bulk-bind input and output host arrays. This is the most efficient way to pass collections to and from the database server.

In the client program, declare and assign values to the host variables to be referenced in the anonymous block. In the anonymous block, prefix each host variable name with a colon (:) to distinguish it from a PL/SQL collection variable name. When the client program runs, the database server runs the PL/SQL anonymous block.

In Example 12-28, the anonymous block uses a FORALL statement to bulk-bind a host input array. In the FORALL statement, the DELETE statement refers to four host variables: scalars lower, upper, and emp_id and array depts.

BEGIN
  FORALL i IN :lower..:upper
    DELETE FROM employees
    WHERE department_id = :depts(i);
END;
/

Overview of Table Functions

A table function is a user-defined PL/SQL function that returns a collection of rows (a nested table or varray). You can select from this collection as if it were a database table by invoking the table function inside the TABLE clause in a SELECT statement. For example:

SELECT * FROM TABLE(table_function_name(parameter_list))

(For more information about the TABLE clause of the SELECT statement, see Oracle Database SQL Language Reference.)

A table function can take a collection of rows as input (that is, it can have an input parameter that is a nested table, varray, or cursor variable). Therefore, output from table function tf1 can be input to table function tf2, and output from tf2 can be input to table function tf3, and so on. For more information, see "Chaining Pipelined Table Functions".

To improve the performance of a table function, you can:

• Enable the function for parallel execution, with the PARALLEL_ENABLE option.

  Functions enabled for parallel execution can run concurrently.

• Stream the function results directly to the next process, with Oracle Streams.

  Streaming eliminates intermediate staging between processes. For information about Oracle Streams, see Oracle Streams Concepts and Administration.

• Pipeline the function results, with the PIPELINED option.

  A pipelined table function returns a row to its invoker immediately after processing that row and continues to process rows. Response time improves because the entire collection need not be constructed and returned to the server before the query can return a single result row. (Also, the function needs less memory, because the object cache need not materialize the entire collection.)

  Caution:

  A pipelined table function always references the current state of the data. If the data in the collection changes after the cursor opens for the collection, then the cursor reflects the changes. PL/SQL variables are private to a session and are not transactional. Therefore, read consistency, well known for its applicability to table data, does not apply to PL/SQL collection variables.

Creating Pipelined Table Functions

A pipelined table function must be either a standalone function or a package function.

PIPELINED Option (Required)

For a standalone function, specify the PIPELINED option in the CREATE FUNCTION statement (for syntax, see "CREATE FUNCTION Statement"). For a package function, specify the PIPELINED option in both the function declaration and function definition (for syntax, see "Function Declaration and Definition").

PARALLEL_ENABLE Option (Recommended)

To improve its performance, enable the pipelined table function for parallel execution by specifying the PARALLEL_ENABLE option.

AUTONOMOUS_TRANSACTION Pragma

If the pipelined table function runs DML statements, then make it autonomous, with the AUTONOMOUS_TRANSACTION pragma (described in "AUTONOMOUS_TRANSACTION Pragma"). Then, during parallel execution, each instance of the function creates an independent transaction.

DETERMINISTIC Option (Recommended)

Multiple invocations of a pipelined table function, in either the same query or separate queries, cause multiple executions of the underlying implementation. If the function is deterministic, specify the DETERMINISTIC option, described in "DETERMINISTIC".

Parameters

Typically, a pipelined table function has one or more cursor variable parameters. For information about cursor variables as function parameters, see "Cursor Variables as Subprogram Parameters".

RETURN Data Type

The data type of the value that a pipelined table function returns must be a collection type defined either at schema level or inside a package (therefore, it cannot be an associative array type). The elements of the collection type must be SQL data types, not data types supported only by PL/SQL (such as PLS_INTEGER and BOOLEAN). For information about collection types, see "Collection Types". For information about SQL data types, see Oracle Database SQL Language Reference.

You can use SQL data types ANYTYPE, ANYDATA, and ANYDATASET to dynamically encapsulate and access type descriptions, data instances, and sets of data instances of any other SQL type, including object and collection types. You can also use these types to create unnamed types, including anonymous collection types. For information about these types, see Oracle Database PL/SQL Packages and Types Reference.

PIPE ROW Statement

Inside a pipelined table function, use the PIPE ROW statement to return a collection element to the invoker without returning control to the invoker. See "PIPE ROW Statement" for its syntax and semantics.

RETURN Statement

As in every function, every execution path in a pipelined table function must lead to a RETURN statement, which returns control to the invoker. However, in a pipelined table function, a RETURN statement need not return a value to the invoker. See "RETURN Statement" for its syntax and semantics.

Example

Example 12-29 creates a package that includes a pipelined table function, f1, and then selects from the collection of rows that f1 returns.

CREATE OR REPLACE PACKAGE pkg1 AS
  TYPE numset_t IS TABLE OF NUMBER;
  FUNCTION f1(x NUMBER) RETURN numset_t PIPELINED;
END pkg1;
/

CREATE PACKAGE BODY pkg1 AS
  -- FUNCTION f1 returns a collection of elements (1,2,3,... x)
  FUNCTION f1(x NUMBER) RETURN numset_t PIPELINED IS
  BEGIN
    FOR i IN 1..x LOOP
      PIPE ROW(i);
    END LOOP;
    RETURN;
  END f1;
END pkg1;
/

SELECT * FROM TABLE(pkg1.f1(5));

COLUMN_VALUE
------------
           1
           2
           3
           4
           5
 
5 rows selected.

Pipelined Table Functions as Transformation Functions

A pipelined table function with a cursor variable parameter can serve as a transformation function. Using the cursor variable, the function fetches an input row. Using the PIPE ROW statement, the function pipes the transformed row or rows to the invoker. If the FETCH and PIPE ROW statements are inside a LOOP statement, the function can transform multiple input rows.

In Example 12-30, the pipelined table function transforms each selected row of the employees table to two nested table rows, which it pipes to the SELECT statement that invokes it. The actual parameter that corresponds to the formal cursor variable parameter is a CURSOR expression; for information about these, see "Passing CURSOR Expressions to Pipelined Table Functions".

CREATE OR REPLACE PACKAGE refcur_pkg IS
  TYPE refcur_t IS REF CURSOR RETURN employees%ROWTYPE;
  TYPE outrec_typ IS RECORD (
    var_num    NUMBER(6),
    var_char1  VARCHAR2(30),
    var_char2  VARCHAR2(30)
  );
  TYPE outrecset IS TABLE OF outrec_typ;
  FUNCTION f_trans (p refcur_t) RETURN outrecset PIPELINED;
END refcur_pkg;
/

CREATE OR REPLACE PACKAGE BODY refcur_pkg IS
  FUNCTION f_trans (p refcur_t) RETURN outrecset PIPELINED IS
    out_rec outrec_typ;
    in_rec  p%ROWTYPE;
  BEGIN
    LOOP
      FETCH p INTO in_rec;  -- input row
      EXIT WHEN p%NOTFOUND;

      out_rec.var_num := in_rec.employee_id;
      out_rec.var_char1 := in_rec.first_name;
      out_rec.var_char2 := in_rec.last_name;
      PIPE ROW(out_rec);  -- first transformed output row

      out_rec.var_char1 := in_rec.email;
      out_rec.var_char2 := in_rec.phone_number;
      PIPE ROW(out_rec);  -- second transformed output row
    END LOOP;
    CLOSE p;
    RETURN;
  END f_trans;
END refcur_pkg;
/

SELECT * FROM TABLE (
  refcur_pkg.f_trans (
    CURSOR (SELECT * FROM employees WHERE department_id = 60)
  )
);

VAR_NUM VAR_CHAR1                      VAR_CHAR2
---------- ------------------------------ ------------------------------
       103 Alexander                      Hunold
       103 AHUNOLD                        590.423.4567
       104 Bruce                          Ernst
       104 BERNST                         590.423.4568
       105 David                          Austin
       105 DAUSTIN                        590.423.4569
       106 Valli                          Pataballa
       106 VPATABAL                       590.423.4560
       107 Diana                          Lorentz
       107 DLORENTZ                       590.423.5567

10 rows selected.

Chaining Pipelined Table Functions

To chain pipelined table functions tf1 and tf2 is to make the output of tf1 the input of tf2. For example:

SELECT * FROM TABLE(tf2(CURSOR(SELECT * FROM TABLE(tf1()))));

The rows that tf1 pipes out must be compatible actual parameters for the formal input parameters of tf2.

If chained pipelined table functions are enabled for parallel execution, then each function runs in a different process (or set of processes).

Fetching from Results of Pipelined Table Functions

You can associate a named cursor with a query that invokes a pipelined table function. Such a cursor has no special fetch semantics, and such a cursor variable has no special assignment semantics.

However, the SQL optimizer does not optimize across PL/SQL statements. Therefore, in Example 12-31, the first PL/SQL statement is slower than the second—despite the overhead of running two SQL statements in the second PL/SQL statement, and even if function results are piped between the two SQL statements in the first PL/SQL statement.

In Example 12-31, assume that f and g are pipelined table functions, and that each function accepts a cursor variable parameter. The first PL/SQL statement associates cursor variable r with a query that invokes f, and then passes r to g. The second PL/SQL statement passes CURSOR expressions to both f and g.

DECLARE
  r SYS_REFCURSOR;
  ...
  -- First PL/SQL statement (slower):
BEGIN
  OPEN r FOR SELECT * FROM TABLE(f(CURSOR(SELECT * FROM tab)));
  SELECT * BULK COLLECT INTO rec_tab FROM TABLE(g(r));

  -- NOTE: When g completes, it closes r.
END;

-- Second PL/SQL statement (faster):

SELECT * FROM TABLE(g(CURSOR(SELECT * FROM
  TABLE(f(CURSOR(SELECT * FROM tab))))));
/

Passing CURSOR Expressions to Pipelined Table Functions

As Example 12-31 shows, the actual parameter for the cursor variable parameter of a pipelined table function can be either a cursor variable or a CURSOR expression, and the latter is more efficient.

Example 12-32 creates a package that includes a pipelined table function with two cursor variable parameters and then invokes the function in a SELECT statement, using CURSOR expressions for actual parameters.

CREATE OR REPLACE PACKAGE refcur_pkg IS
  TYPE refcur_t1 IS REF CURSOR RETURN employees%ROWTYPE;
  TYPE refcur_t2 IS REF CURSOR RETURN departments%ROWTYPE;
  TYPE outrec_typ IS RECORD (
    var_num    NUMBER(6),
    var_char1  VARCHAR2(30),
    var_char2  VARCHAR2(30)
  );
  TYPE outrecset IS TABLE OF outrec_typ;
  FUNCTION g_trans (p1 refcur_t1, p2 refcur_t2) RETURN outrecset PIPELINED;
END refcur_pkg;
/

CREATE PACKAGE BODY refcur_pkg IS
  FUNCTION g_trans (
    p1 refcur_t1,
    p2 refcur_t2
  ) RETURN outrecset PIPELINED
  IS
    out_rec outrec_typ;
    in_rec1 p1%ROWTYPE;
    in_rec2 p2%ROWTYPE;
  BEGIN
    LOOP
      FETCH p2 INTO in_rec2;
      EXIT WHEN p2%NOTFOUND;
    END LOOP;
    CLOSE p2;
    LOOP
      FETCH p1 INTO in_rec1;
      EXIT WHEN p1%NOTFOUND;
      -- first row
      out_rec.var_num := in_rec1.employee_id;
      out_rec.var_char1 := in_rec1.first_name;
      out_rec.var_char2 := in_rec1.last_name;
      PIPE ROW(out_rec);
      -- second row
      out_rec.var_num := in_rec2.department_id;
      out_rec.var_char1 := in_rec2.department_name;
      out_rec.var_char2 := TO_CHAR(in_rec2.location_id);
      PIPE ROW(out_rec);
    END LOOP;
    CLOSE p1;
    RETURN;
  END g_trans;
END refcur_pkg;
/

SELECT * FROM TABLE (
  refcur_pkg.g_trans (
    CURSOR (SELECT * FROM employees WHERE department_id = 60),
    CURSOR (SELECT * FROM departments WHERE department_id = 60)
  )
);

VAR_NUM VAR_CHAR1                      VAR_CHAR2
---------- ------------------------------ ------------------------------
       103 Alexander                      Hunold
        60 IT                             1400
       104 Bruce                          Ernst
        60 IT                             1400
       105 David                          Austin
        60 IT                             1400
       106 Valli                          Pataballa
        60 IT                             1400
       107 Diana                          Lorentz
        60 IT                             1400
 
10 rows selected.

Example 12-33 uses a pipelined table function as an aggregate function, which takes a set of input rows and returns a single result. The SELECT statement selects the function result. (For information about the pseudocolumn COLUMN_VALUE, see Oracle Database SQL Language Reference.)

DROP TABLE gradereport;
CREATE TABLE gradereport (
  student VARCHAR2(30),
  subject VARCHAR2(30),
  weight NUMBER,
  grade NUMBER
);

INSERT INTO gradereport (student, subject, weight, grade)
VALUES ('Mark', 'Physics', 4, 4);
 
INSERT INTO gradereport (student, subject, weight, grade) 
VALUES ('Mark','Chemistry', 4, 3);
 
INSERT INTO gradereport (student, subject, weight, grade) 
VALUES ('Mark','Maths', 3, 3);
 
INSERT INTO gradereport (student, subject, weight, grade) 
VALUES ('Mark','Economics', 3, 4);

CREATE PACKAGE pkg_gpa IS
  TYPE gpa IS TABLE OF NUMBER;
  FUNCTION weighted_average(input_values SYS_REFCURSOR)
    RETURN gpa PIPELINED;
END pkg_gpa;
/

CREATE PACKAGE BODY pkg_gpa IS
  FUNCTION weighted_average (input_values SYS_REFCURSOR)
    RETURN gpa PIPELINED
  IS
    grade         NUMBER;
    total         NUMBER := 0;
    total_weight  NUMBER := 0;
    weight        NUMBER := 0;
  BEGIN
    LOOP
      FETCH input_values INTO weight, grade;
      EXIT WHEN input_values%NOTFOUND;
      total_weight := total_weight + weight;  -- Accumulate weighted average
      total := total + grade*weight;
    END LOOP;
    PIPE ROW (total / total_weight);
    RETURN; -- returns single result
  END weighted_average;
END pkg_gpa;
/

SELECT w.column_value "weighted result" FROM TABLE (
  pkg_gpa.weighted_average (
    CURSOR (SELECT weight, grade FROM gradereport)
  )
) w;

weighted result
---------------
            3.5
 
1 row selected.

DML Statements on Pipelined Table Function Results

The "table" that a pipelined table function returns cannot be the target table of a DELETE, INSERT, or UPDATE statement. However, you can create a view of such a table and create INSTEAD OF triggers on the view. For information about INSTEAD OF triggers, see "INSTEAD OF Triggers".

NO_DATA_NEEDED Exception

You must understand the predefined exception NO_DATA_NEEDED in two cases:

• You include an OTHERS exception handler in a block that includes a PIPE ROW statement

• Your code that feeds a PIPE ROW statement must be followed by a clean-up procedure

  Typically, the clean-up procedure releases resources that the code no longer needs.

When the invoker of a pipelined table function needs no more rows from the function, the PIPE ROW statement raises NO_DATA_NEEDED. If the pipelined table function does not handle NO_DATA_NEEDED, as in Example 12-34, then the function invocation terminates but the invoking statement does not terminate. If the pipelined table function handles NO_DATA_NEEDED, its exception handler can release the resources that it no longer needs, as in Example 12-35.

In Example 12-34, the pipelined table function pipe_rows does not handle the NO_DATA_NEEDED exception. The SELECT statement that invokes pipe_rows needs only four rows. Therefore, during the fifth invocation of pipe_rows, the PIPE ROW statement raises the exception NO_DATA_NEEDED. The fifth invocation of pipe_rows terminates, but the SELECT statement does not terminate.

CREATE TYPE t IS TABLE OF NUMBER
/
CREATE OR REPLACE FUNCTION pipe_rows RETURN t PIPELINED IS
  n NUMBER := 0;
BEGIN
  LOOP
    n := n + 1;
    PIPE ROW (n);
  END LOOP;
END pipe_rows;
/
SELECT COLUMN_VALUE
  FROM TABLE(pipe_rows())
  WHERE ROWNUM < 5
/

COLUMN_VALUE
------------
           1
           2
           3
           4

4 rows selected.

If the exception-handling part of a block that includes a PIPE ROW statement includes an OTHERS exception handler to handle unexpected exceptions, then it must also include an exception handler for the expected NO_DATA_NEEDED exception. Otherwise, the OTHERS exception handler handles the NO_DATA_NEEDED exception, treating it as an unexpected error. The following exception handler reraises the NO_DATA_NEEDED exception, instead of treating it as a irrecoverable error:

EXCEPTION
  WHEN NO_DATA_NEEDED THEN
    RAISE;
  WHEN OTHERS THEN
    -- (Put error-logging code here)
    RAISE_APPLICATION_ERROR(-20000, 'Fatal error.');
END;

In Example 12-35, assume that the package External_Source contains these public items:

• Procedure Init, which allocates and initializes the resources that Next_Row needs

• Function Next_Row, which returns some data from a specific external source and raises the user-defined exception Done (which is also a public item in the package) when the external source has no more data

• Procedure Clean_Up, which releases the resources that Init allocated

The pipelined table function get_external_source_data pipes rows from the external source by invoking External_Source.Next_Row until either:

• The external source has no more rows.

  In this case, the External_Source.Next_Row function raises the user-defined exception External_Source.Done.

• get_external_source_data needs no more rows.

  In this case, the PIPE ROW statement in get_external_source_data raises the NO_DATA_NEEDED exception.

In either case, an exception handler in block b in get_external_source_data invokes External_Source.Clean_Up, which releases the resources that Next_Row was using.

CREATE OR REPLACE FUNCTION get_external_source_data
  RETURN t AUTHID DEFINER PIPELINED IS
BEGIN
  External_Source.Init();           -- Initialize.
  <<b>> BEGIN
    LOOP                            -- Pipe rows from external source.
      PIPE ROW (External_Source.Next_Row());
    END LOOP;
  EXCEPTION
    WHEN External_Source.Done THEN  -- When no more rows are available,
      External_Source.Clean_Up();   --  clean up.
    WHEN NO_DATA_NEEDED THEN        -- When no more rows are needed,
      External_Source.Clean_Up();   --  clean up.
      RAISE NO_DATA_NEEDED;           -- Optional, equivalent to RETURN.
  END b;
END get_external_source_data;
/

Profiler API: Package DBMS_PROFILER

The Profiler API ("Profiler") is implemented as PL/SQL package DBMS_PROFILER, whose services compute the time that your PL/SQL program spends at each line and in each subprogram and save these statistics in database tables, which you can query.

To use Profiler:

1. Start the profiling session.

2. Run your PL/SQL program long enough to get adequate code coverage.

3. Flush the collected data to the database.

4. Stop the profiling session.

After you have collected data with Profiler, you can:

1. Query the database tables that contain the performance data.

2. Identify the subprograms and packages that use the most execution time.

3. Determine why your program spent more time accessing certain data structures and running certain code segments.

   Inspect possible performance bottlenecks such as SQL statements, loops, and recursive functions.

4. Use the results of your analysis to replace inappropriate data structures and rework slow algorithms.

   For example, with an exponential growth in data, you might need to replace a linear search with a binary search.

For detailed information about the DBMS_PROFILER subprograms, see Oracle Database PL/SQL Packages and Types Reference.

Trace API: Package DBMS_TRACE

The Trace API ("Trace") is implemented as PL/SQL package DBMS_TRACE, whose services trace execution by subprogram or exception and save these statistics in database tables, which you can query.

To use Trace:

1. (Optional) Limit tracing to specific subprograms and choose a tracing level.

   Tracing all subprograms and exceptions in a large program can produce huge amounts of data that are difficult to manage.

2. Start the tracing session.

3. Run your PL/SQL program.

4. Stop the tracing session.

After you have collected data with Trace, you can query the database tables that contain the performance data and analyze it in the same way that you analyze the performance data from Profiler (see "Profiler API: Package DBMS_PROFILER").

For detailed information about the DBMS_TRACE subprograms, see Oracle Database PL/SQL Packages and Types Reference.

Determining Whether to Use PL/SQL Native Compilation

Whether to compile a PL/SQL unit for native or interpreted mode depends on where you are in the development cycle and on what the program unit does.

While you are debugging program units and recompiling them frequently, interpreted mode has these advantages:

• You can use PL/SQL debugging tools on program units compiled for interpreted mode (but not for those compiled for native mode).

• Compiling for interpreted mode is faster than compiling for native mode.

After the debugging phase of development, in determining whether to compile a PL/SQL unit for native mode, consider:

• PL/SQL native compilation provides the greatest performance gains for computation-intensive procedural operations. Examples are data warehouse applications and applications with extensive server-side transformations of data for display.

• PL/SQL native compilation provides the least performance gains for PL/SQL subprograms that spend most of their time running SQL.

• When many program units (typically over 15,000) are compiled for native execution, and are simultaneously active, the large amount of shared memory required might affect system performance.

How PL/SQL Native Compilation Works

Without native compilation, the PL/SQL statements in a PL/SQL unit are compiled into an intermediate form, system code, which is stored in the catalog and interpreted at run time.

With PL/SQL native compilation, the PL/SQL statements in a PL/SQL unit are compiled into native code and stored in the catalog. The native code need not be interpreted at run time, so it runs faster.

Because native compilation applies only to PL/SQL statements, a PL/SQL unit that uses only SQL statements might not run faster when natively compiled, but it does run at least as fast as the corresponding interpreted code. The compiled code and the interpreted code make the same library calls, so their action is the same.

The first time a natively compiled PL/SQL unit runs, it is fetched from the SYSTEM tablespace into shared memory. Regardless of how many sessions invoke the program unit, shared memory has only one copy it. If a program unit is not being used, the shared memory it is using might be freed, to reduce memory load.

Natively compiled subprograms and interpreted subprograms can invoke each other.

PL/SQL native compilation works transparently in an Oracle Real Application Clusters (Oracle RAC) environment.

The PLSQL_CODE_TYPE compilation parameter determines whether PL/SQL code is natively compiled or interpreted. For information about this compilation parameters, see "PL/SQL Units and Compilation Parameters".

Dependencies, Invalidation, and Revalidation

Recompilation is automatic with invalidated PL/SQL modules. For example, if an object on which a natively compiled PL/SQL subprogram depends changes, the subprogram is invalidated. The next time the same subprogram is called, the database recompiles the subprogram automatically. Because the PLSQL_CODE_TYPE setting is stored inside the library unit for each subprogram, the automatic recompilation uses this stored setting for code type.

Explicit recompilation does not necessarily use the stored PLSQL_CODE_TYPE setting. For the conditions under which explicit recompilation uses stored settings, see "PL/SQL Units and Compilation Parameters".

Setting Up a New Database for PL/SQL Native Compilation

If you have DBA privileges, you can set up a new database for PL/SQL native compilation by setting the compilation parameter PLSQL_CODE_TYPE to NATIVE. The performance benefits apply to the PL/SQL packages that Oracle Database supplies, which are used for many database operations.

Compiling the Entire Database for PL/SQL Native or Interpreted Compilation

If you have DBA privileges, you can recompile all PL/SQL modules in an existing database to NATIVE or INTERPRETED, using the dbmsupgnv.sql and dbmsupgin.sql scripts respectively during the process explained in this section. Before making the conversion, review "Determining Whether to Use PL/SQL Native Compilation".

During the conversion to native compilation, TYPE specifications are not recompiled by dbmsupgnv.sql to NATIVE because these specifications do not contain executable code.

Package specifications seldom contain executable code so the runtime benefits of compiling to NATIVE are not measurable. You can use the TRUE command-line parameter with the dbmsupgnv.sql script to exclude package specs from recompilation to NATIVE, saving time in the conversion process.

When converting to interpreted compilation, the dbmsupgin.sql script does not accept any parameters and does not exclude any PL/SQL units.

1. Ensure that a test PL/SQL unit can be compiled. For example:

   ALTER PROCEDURE my_proc COMPILE PLSQL_CODE_TYPE=NATIVE REUSE SETTINGS;
   

2. Shut down application services, the listener, and the database.

   • Shut down all of the Application services including the Forms Processes, Web Servers, Reports Servers, and Concurrent Manager Servers. After shutting down all of the Application services, ensure that all of the connections to the database were terminated.

   • Shut down the TNS listener of the database to ensure that no new connections are made.

   • Shut down the database in normal or immediate mode as the user SYS. See Oracle Database Administrator's Guide.

3. Set PLSQL_CODE_TYPE to NATIVE in the compilation parameter file. If the database is using a server parameter file, then set this after the database has started.

   The value of PLSQL_CODE_TYPE does not affect the conversion of the PL/SQL units in these steps. However, it does affect all subsequently compiled units, so explicitly set it to the desired compilation type.

4. Start up the database in upgrade mode, using the UPGRADE option. For information about SQL*Plus STARTUP, see SQL*Plus User's Guide and Reference.

5. Run this code to list the invalid PL/SQL units. You can save the output of the query for future reference with the SQL SPOOL statement:

   -- To save the output of the query to a file:
     SPOOL pre_update_invalid.log
   SELECT o.OWNER, o.OBJECT_NAME, o.OBJECT_TYPE 
   FROM DBA_OBJECTS o, DBA_PLSQL_OBJECT_SETTINGS s 
   WHERE o.OBJECT_NAME = s.NAME AND o.STATUS='INVALID';
   -- To stop spooling the output: SPOOL OFF
   

   If any Oracle supplied units are invalid, try to validate them by recompiling them. For example:

   ALTER PACKAGE SYS.DBMS_OUTPUT COMPILE BODY REUSE SETTINGS;
   

   If the units cannot be validated, save the spooled log for future resolution and continue.

6. Run this query to determine how many objects are compiled NATIVE and INTERPRETED (to save the output, use the SQL SPOOL statement):

   SELECT TYPE, PLSQL_CODE_TYPE, COUNT(*)
   FROM DBA_PLSQL_OBJECT_SETTINGS
   WHERE PLSQL_CODE_TYPE IS NOT NULL
   GROUP BY TYPE, PLSQL_CODE_TYPE
   ORDER BY TYPE, PLSQL_CODE_TYPE;
   

   Any objects with a NULL plsql_code_type are special internal objects and can be ignored.

7. Run the $ORACLE_HOME/rdbms/admin/dbmsupgnv.sql script as the user SYS to update the plsql_code_type setting to NATIVE in the dictionary tables for all PL/SQL units. This process also invalidates the units. Use TRUE with the script to exclude package specifications; FALSE to include the package specifications.

   This update must be done when the database is in UPGRADE mode. The script is guaranteed to complete successfully or rollback all the changes.

8. Shut down the database and restart in NORMAL mode.

9. Before you run the utlrp.sql script, Oracle recommends that no other sessions are connected to avoid possible problems. You can ensure this with this statement:

   ALTER SYSTEM ENABLE RESTRICTED SESSION;
   

10. Run the $ORACLE_HOME/rdbms/admin/utlrp.sql script as the user SYS. This script recompiles all the PL/SQL modules using a default degree of parallelism. See the comments in the script for information about setting the degree explicitly.

    If for any reason the script is abnormally terminated, rerun the utlrp.sql script to recompile any remaining invalid PL/SQL modules.

11. After the compilation completes successfully, verify that there are no invalid PL/SQL units using the query in step 5. You can spool the output of the query to the post_upgrade_invalid.log file and compare the contents with the pre_upgrade_invalid.log file, if it was created previously.

12. Reexecute the query in step 6. If recompiling with dbmsupgnv.sql, confirm that all PL/SQL units, except TYPE specifications and package specifications if excluded, are NATIVE. If recompiling with dbmsupgin.sql, confirm that all PL/SQL units are INTERPRETED.

13. Disable the restricted session mode for the database, then start the services that you previously shut down. To disable restricted session mode, use this statement:

    ALTER SYSTEM DISABLE RESTRICTED SESSION;