We usually use cursor for loops to process data.(i.e declare a cursor, open it, fetch from it row by row in a loop and process the row they fetch) statements in plsql programs causes a context switch between the plsql engine and the sql engine.Too many context switches may degrade performance dramatically.
In order to reduce the number of these context switches we can use bulk collecting feature
Bulk collecting lets us to transfer rows between the sql engine and the plsql engine as collections.
Bulk collecting is available for select, insert, delete and update statements.
Below are some examples:
create table BULK_COLLECT_TEST as select * from PER_ALL_PEOPLE_F;
Table created.
insert into BULK_COLLECT_TEST
select * from BULK_COLLECT_TEST;
20000 rows created.
--BLOCK1:Using Loops
declare
cursor c1
is select object_name from BULK_COLLECT_TEST;
rec1 c1%rowtype;
begin
open c1;
loop
fetch c1 into rec1;
exit when c1%notfound;
null;
end loop;
end;
total Elapsed Time is : 45 Secs
--BLOCK2: Using Bulk Collecting
declare
cursor c1 is select object_name from BULK_COLLECT_TEST;
type c1_type is table of c1%rowtype;
rec1 c1_type;
begin
open c1;
fetch c1 bulk collect into rec1;
end;
total Elapsed Time is : 5 Sec
So bulk collecting the rows shows a huge performance improvement over fetching row by row.
Some cases there are many rows to process, we can limit the number of rows to bulk collect, process those rows and fetch again.
Otherwise process memory gets bigger and bigger as you fetch the rows.
--Bulk Collect Example using LIMIT :
declare
cursor c1 is select object_name from BULK_COLLECT_TEST;
type c1_type is table of c1%rowtype;
rec1 c1_type;
begin
open c1;
loop
fetch c1 bulk collect into rec1 limit 200;
for i in 1..rec1.count loop
null;
end loop;
exit when c1%notfound;
end loop;
end;
In order to reduce the number of these context switches we can use bulk collecting feature
Bulk collecting lets us to transfer rows between the sql engine and the plsql engine as collections.
Bulk collecting is available for select, insert, delete and update statements.
Below are some examples:
create table BULK_COLLECT_TEST as select * from PER_ALL_PEOPLE_F;
Table created.
insert into BULK_COLLECT_TEST
select * from BULK_COLLECT_TEST;
20000 rows created.
--BLOCK1:Using Loops
declare
cursor c1
is select object_name from BULK_COLLECT_TEST;
rec1 c1%rowtype;
begin
open c1;
loop
fetch c1 into rec1;
exit when c1%notfound;
null;
end loop;
end;
total Elapsed Time is : 45 Secs
--BLOCK2: Using Bulk Collecting
declare
cursor c1 is select object_name from BULK_COLLECT_TEST;
type c1_type is table of c1%rowtype;
rec1 c1_type;
begin
open c1;
fetch c1 bulk collect into rec1;
end;
total Elapsed Time is : 5 Sec
So bulk collecting the rows shows a huge performance improvement over fetching row by row.
Some cases there are many rows to process, we can limit the number of rows to bulk collect, process those rows and fetch again.
Otherwise process memory gets bigger and bigger as you fetch the rows.
--Bulk Collect Example using LIMIT :
declare
cursor c1 is select object_name from BULK_COLLECT_TEST;
type c1_type is table of c1%rowtype;
rec1 c1_type;
begin
open c1;
loop
fetch c1 bulk collect into rec1 limit 200;
for i in 1..rec1.count loop
null;
end loop;
exit when c1%notfound;
end loop;
end;
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