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 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.

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.

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
...

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);

...

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
...

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
...

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.

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

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

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;
/

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 13-7. 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);

Now consider the FORALL statement in Example 13-8. It sends the same three DML statements from PL/SQL to SQL as a batch.

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 13-9 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.)

In Example 13-10, 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(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;
/

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;
/

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: 5.97
FORALL:   .07
 
PL/SQL procedure successfully completed.

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;
/

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).

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.

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

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 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 13-28, 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;
/

A table function is a user-defined PL/SQL function that returns a collection of rows (an associative array, 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. The TABLE operator is optional.

For example:

SELECT * FROM TABLE(table_function_name(parameter_list))

Alternatively, the same query can be written without the TABLE operator as follow:

SELECT * FROM table_function_name(parameter_list)

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.

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.

• 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.

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

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

CREATE OR REPLACE PACKAGE BODY pkg1 AS
  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.

SELECT * FROM pkg1.f1(2);

COLUMN_VALUE
------------
           1
           2

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 13-30, 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 AUTHID DEFINER 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.

The "table" that a pipelined table function returns cannot be the target table of a DELETE, INSERT, UPDATE, or MERGE 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 DML Triggers".

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 13-34, 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 13-35.

In Example 13-34, 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.

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 13-35, 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 TYPE t IS TABLE OF NUMBER
/
CREATE OR REPLACE FUNCTION pipe_rows RETURN t PIPELINED AUTHID DEFINER 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.

CREATE OR REPLACE FUNCTION get_external_source_data
  RETURN t PIPELINED AUTHID DEFINER 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;
/

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".

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".

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. Re-execute 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;