Oracle uses two engines to process PL/SQL code. All procedural
code is handled by the PL/SQL engine while all SQL is handled by the SQL
statement executor, or SQL engine.
There is an overhead associated with each context switch between
the two engines. If PL/SQL code loops through a collection performing the same
DML operation for each item in the collection it is possible to reduce context
switches by bulk binding the whole collection to the DML statement in one
operation.
BULK COLLECT
Bulk binds can improve the performance when loading collections
from queries. The BULK COLLECT INTO construct binds the output of the query to
the collection. To test this, create the following table.
CREATE TABLE bulk_collect_test AS
SELECT owner,
object_name,
object_id
FROM all_objects;
The following code compares the time taken to populate a
collection manually and using a bulk bind.
SET SERVEROUTPUT ON
DECLARE
TYPE t_bulk_collect_test_tab IS TABLE OF bulk_collect_test%ROWTYPE;
l_tab t_bulk_collect_test_tab := t_bulk_collect_test_tab();
l_start NUMBER;
BEGIN
-- Time a regular population.
l_start := DBMS_UTILITY.get_time;
FOR cur_rec IN (SELECT * FROM
bulk_collect_test)
LOOP
l_tab.extend;
l_tab(l_tab.last) := cur_rec;
END LOOP;
DBMS_OUTPUT.put_line('Regular (' || l_tab.count || ' rows): ' || (DBMS_UTILITY.get_time - l_start));
-- Time bulk population.
l_start
:= DBMS_UTILITY.get_time;
SELECT * BULK COLLECT INTO l_tab FROM
bulk_collect_test;
DBMS_OUTPUT.put_line('Bulk (' || l_tab.count || ' rows): ' || (DBMS_UTILITY.get_time - l_start));
END;
/
Regular (42578 rows): 66
Bulk (42578 rows): 4
PL/SQL procedure successfully completed.
SQL>We can see the improvement associated with bulk
operations to reduce context switches.
Note. The select list must match the collections record
definition exactly for this to be successful.
Remember that collections are held in memory, so doing a bulk
collect from a large query could cause a considerable performance problem. In
actual fact you would rarely do a straight bulk collect in this manner. Instead
you would limit the rows returned using the LIMIT clause and move through the
data processing smaller chunks.
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