“NOT IN” and “NOT EXISTS” clauses are not the same functionally or performance wise and, therefore, should be used appropriately. This blog post outlines how these commands are executed and discusses when it is appropriate to use them.
CREATE TABLE EMP_MASTER
(
EMP_NBR NUMBER(10) NOT NULL PRIMARY KEY,
EMP_NAME VARCHAR2(20 CHAR),
MGR_NBR NUMBER(10) NULL
)
INSERT INTO EMP_MASTER VALUES (1, ‘DON’, 5);
INSERT INTO EMP_MASTER VALUES (2, ‘HARI’, 5);
INSERT INTO EMP_MASTER VALUES (3, ‘RAMESH’, 5);
INSERT INTO EMP_MASTER VALUES (4, ‘JOE’, 5);
INSERT INTO EMP_MASTER VALUES (5, ‘DENNIS’, NULL);
INSERT INTO EMP_MASTER VALUES (6, ‘NIMISH’, 5);
INSERT INTO EMP_MASTER VALUES (7, ‘JESSIE’, 5);
INSERT INTO EMP_MASTER VALUES (8, ‘KEN’, 5);
INSERT INTO EMP_MASTER VALUES (9, ‘AMBER’, 5);
INSERT INTO EMP_MASTER VALUES (10, ‘JIM’, 5);
Now, the aim is to find all those employees who are not managers. Let’s see how we can achieve that by using the “NOT IN” vs the “NOT EXISTS” clause.
NOT IN
SQL> select count(*) from emp_master where emp_nbr not in ( select mgr_nbr from emp_master );
COUNT(*)
———-
0
NOT EXISTS
SQL> select count(*) from emp_master T1 where not exists ( select 1 from emp_master T2 where t2.mgr_nbr = t1.emp_nbr );
COUNT(*)
———-
9
Now there are 9 people who are not managers. So, you can clearly see the difference that NULL values make and since NULL != NULL in SQL, the NOT IN clause does not return any records back. (in MS SQL Server, depending upon the ANSI NULLS setting, the behavior can be altered but this post only talks about the behavior that is same in Oracle, DB2 LUW and MS SQL Server).
Performance implications:
When using “NOT IN”, the query performs nested full table scans, whereas for “NOT EXISTS”, query can use an index within the sub-query.
