Nested Loop, Hash Join, Sort Merge Join, Cartesian join difference

This article is written in oracle 9.2.0.8.

Nested loop Joins The optimizer uses nested loop joins when joining small number of rows, with a good driving condition between the two tables. It drives from the outer loop to the inner loop. The inner loop is iterated for every row returned from the outer loop, ideally by an index scan. It is inefficient when join returns large number of rows (typically, more than 10,000 rows is considered large), and the optimizer might choose not to use it.

The cost is calculated as below.
cost = access cost of A + (access cost of B * no_of_rows from A)

A nested loop join involves the following steps:

1. The optimizer determines the driving table and designates it as the outer table.
2. The other table is designated as the inner table.
3. For every row in the outer table, Oracle accesses all the rows in the inner table.

For instance,
scott@DB1.US.ORACLE.COM> SELECT emp.empno, dept.dname
2 FROM EMP , DEPT
3 WHERE dept.deptno = 10
4 AND emp.deptno = dept.deptno
5 /

EMPNO DNAME
---------- --------------
7782 ACCOUNTING
7839 ACCOUNTING
7934 ACCOUNTING

Execution Plan
----------------------------------------------------------
0 SELECT STATEMENT Optimizer=CHOOSE (Cost=3 Card=5 Bytes=85)
1 0 NESTED LOOPS (Cost=3 Card=5 Bytes=85)
2 1 TABLE ACCESS (BY INDEX ROWID) OF 'DEPT' (Cost=1 Card=1 Bytes=10)
3 2 INDEX (UNIQUE SCAN) OF 'PK_DEPT' (UNIQUE)
4 1 TABLE ACCESS (FULL) OF 'EMP' (Cost=2 Card=5 Bytes=35)

We can also force the Nested loop join hint as below.

SELECT /*+ USE_NL(emp dept) */ emp.empno, dept.dname
FROM EMP , DEPT WHERE dept.deptno = 10
AND emp.deptno = dept.deptno

Hash Join Hash joins are used for joining large data sets. The optimizer uses the smaller of two tables or data sources to build a hash table on the join key in memory. It then scans the larger table, probing the hash table to find the joined rows. This method is best used when the smaller table fits in available memory. The optimizer uses a hash join to join two tables if they are joined using an equijoin(joins with equals predicates) and large amount of data needs to be joined.

The cost of a Hash loop join is calculated by the following formula:
cost=(access cost of A*no_of_hash partitions of B) + access cost of B

For instance,
scott@DB1.US.ORACLE.COM> ;
1 SELECT emp.empno, dept.dname
2 FROM EMP , DEPT
3* WHERE emp.deptno = dept.deptno
scott@DB1.US.ORACLE.COM>
/
Execution Plan
----------------------------------------------------------
0 SELECT STATEMENT Optimizer=CHOOSE (Cost=5 Card=14 Bytes=238)
1 0 HASH JOIN (Cost=5 Card=14 Bytes=238)
2 1 TABLE ACCESS (FULL) OF 'DEPT' (Cost=2 Card=7 Bytes=70)
3 1 TABLE ACCESS (FULL) OF 'EMP' (Cost=2 Card=14 Bytes=98)

We can also force the Hash join hint as below.
SELECT /*+USE_HASH(emp dept) */ emp.empno, dept.dname
FROM EMP , DEPT
WHERE emp.deptno = dept.deptno

Sort-Merge Join Sort merge joins can be used to join rows from two independent sources. Hash joins generally perform better than sort merge joins. On the other hand, sort merge joins can perform better than hash joins if both of the following conditions exist:

1. The row sources are sorted already.
2. A sort operation does not have to be done.

Sort merge joins are almost exclusively used for non-equi joins (>, <, BETWEEN). Sort merge joins perform better than nested loop joins for large data sets. (You cannot use hash joins unless there is an equality condition). In a merge join, there is no concept of a driving table.
The join consists of two steps:
Sort join operation: Both the inputs are sorted on the join key.
Merge join operation: The sorted lists are merged together.

The optimizer can choose a sort merge join over a hash join for joining large amounts of data if any of the following conditions are true:

1. The join condition between two tables is not an equi-join.
2. OPTIMIZER_MODE is set to RULE.
3. HASH_JOIN_ENABLED is false.
4. Because of sorts already required by other operations, the optimizer finds it is cheaper to use a sort merge than a hash join.
5. The optimizer thinks that the cost of a hash join is higher, based on the settings of HASH_AREA_SIZE and SORT_AREA_SIZE.

The cost of a sort merge join is calculated by the following formula:
cost = access cost of A + access cost of B + (sort cost of A + sort cost of B)

For instance, scott@DB1.US.ORACLE.COM> SELECT emp.empno, dept.dname
2 FROM EMP , DEPT
3 WHERE emp.deptno < dept.deptno

Execution Plan
----------------------------------------------------------
0 SELECT STATEMENT Optimizer=CHOOSE (Cost=6 Card=5 Bytes=85)
1 0 MERGE JOIN (Cost=6 Card=5 Bytes=85)
2 1 SORT (JOIN) (Cost=2 Card=7 Bytes=70)
3 2 TABLE ACCESS (BY INDEX ROWID) OF 'DEPT' (Cost=2 Card=7 Bytes=70)
4 3 INDEX (FULL SCAN) OF 'PK_DEPT' (UNIQUE) (Cost=1 Card =7)
5 1 SORT (JOIN) (Cost=4 Card=14 Bytes=98)
6 5 TABLE ACCESS (FULL) OF 'EMP' (Cost=2 Card=14 Bytes=98)

We can also force the Hash join hint as below.

scott@DB1.US.ORACLE.COM> SELECT /*+USE_MERGE(emp dept) */
emp.empno, dept.dname
2 FROM EMP , DEPT
3 WHERE emp.deptno < dept.deptno

Cartesian join A Cartesian join is used when one or more of the tables does not have any join conditions to any other tables in the statement. The optimizer joins every row from one data source with all the row from the other data source, creating the Cartesian product of the two sets.

For instance,
scott@DB1.US.ORACLE.COM> select * from emp,dept;
Execution Plan
----------------------------------------------------------
0 SELECT STATEMENT Optimizer=CHOOSE (Cost=16 Card=98 Bytes=5194)
1 0 MERGE JOIN (CARTESIAN) (Cost=16 Card=98 Bytes=5194)
2 1 TABLE ACCESS (FULL) OF 'DEPT' (Cost=2 Card=7 Bytes=112)
3 1 BUFFER (SORT) (Cost=14 Card=14 Bytes=518)
4 3 TABLE ACCESS (FULL) OF 'EMP' (Cost=2 Card=14 Bytes=518)