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;

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