【sql调优之执行计划】nested loops join and nested loop join outer
Nested loops（嵌套循环）看一个例子：
SQL> select b.* from scott.emp a,scott.dept b
2 where a.deptno = b.deptno
3 and a.empno = 7369
4 ;
DEPTNO DNAME LOC
---------- -------------- -------------
20 RESEARCH DALLAS
Execution Plan
----------------------------------------------------------
Plan hash value: 2385808155
--------------------------------------------------------------------------------
--------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Ti
me |
--------------------------------------------------------------------------------
--------
| 0 | SELECT STATEMENT | | 1 | 27 | 2 (0)| 00
:00:01 |
| 1 | NESTED LOOPS | | 1 | 27 | 2 (0)| 00
:00:01 |
| 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 7 | 1 (0)| 00
:00:01 |
|* 3 | INDEX UNIQUE SCAN | PK_EMP | 1 | | 0 (0)| 00
:00:01 |
| 4 | TABLE ACCESS BY INDEX ROWID| DEPT | 4 | 80 | 1 (0)| 00
:00:01 |
|* 5 | INDEX UNIQUE SCAN | PK_DEPT | 1 | | 0 (0)| 00
:00:01 |
--------------------------------------------------------------------------------
--------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - access("A"."EMPNO"=7369)
5 - access("A"."DEPTNO"="B"."DEPTNO")
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
4 consistent gets
0 physical reads
0 redo size
533 bytes sent via SQL*Net to client
400 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
SQL>
简单的讲就是在表1中每取一行数据，然后从表2中查找匹配的行，然后再回到表1取下一行，如此循环取下去。那么表1中取得的行越少，表2中查找行越容易则嵌套循环的效率越高。
第一个表也通常称为驱动表（或者外部表），第二个表通常称为内部表。
对nested loops join 的选择或者优化，应该考虑驱动表行的选择性和绝对数量大小，并且内部表要能方便的访问到，例如唯一索引，这种结构很多时候用于一个主数据表和一个关联表（或者字典表等）的关联，而关联表很容易使用与主表关联的字段上的索引访问。
上述的执行计划可以看出，先访问表emp，emp作为了驱动表，当然也可以使用dept作为驱动表：
SQL> select /*+ leading(b) use_nl(a,b)*/b.* from scott.dept b,scott.emp a
2 where a.deptno = b.deptno
3 and a.empno = 7369;
DEPTNO DNAME LOC
---------- -------------- -------------
20 RESEARCH DALLAS
Execution Plan
----------------------------------------------------------
Plan hash value: 3431005640
--------------------------------------------------------------------------------
-------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Tim
e |
--------------------------------------------------------------------------------
-------
| 0 | SELECT STATEMENT | | 1 | 27 | 7 (0)| 00:
00:01 |
| 1 | NESTED LOOPS | | 1 | 27 | 7 (0)| 00:
00:01 |
| 2 | TABLE ACCESS FULL | DEPT | 4 | 80 | 3 (0)| 00:
00:01 |
|* 3 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 7 | 1 (0)| 00:
00:01 |
|* 4 | INDEX UNIQUE SCAN | PK_EMP | 1 | | 0 (0)| 00:
00:01 |
--------------------------------------------------------------------------------
-------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - filter("A"."DEPTNO"="B"."DEPTNO")
4 - access("A"."EMPNO"=7369)
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
15 consistent gets
5 physical reads
0 redo size
533 bytes sent via SQL*Net to client
400 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
SQL>
上述执行计划先访问dept表（全表扫描），然后通过index访问emp表，可以看到后者的nested loops的cost为7，大于前者的cost2，可以初步判断后者的效率不如前者，或者也可以简单的看看2者的逻辑读数量来判断一下优劣。具体的性能优化结合实例再述。
扩展一下，两个数据集做nested loops join和两个表相似。
Nested loops join outer 则是由于做了外连接而产生的，例如：
SQL> select b.* from scott.emp a,scott.dept b
2 where a.deptno = b.deptno(+)
3 and a.empno = 7369;
DEPTNO DNAME LOC
---------- -------------- -------------
20 RESEARCH DALLAS
Execution Plan
----------------------------------------------------------
Plan hash value: 1858280091
--------------------------------------------------------------------------------
--------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Ti
me |
--------------------------------------------------------------------------------
--------
| 0 | SELECT STATEMENT | | 1 | 27 | 2 (0)| 00
:00:01 |
| 1 | NESTED LOOPS OUTER | | 1 | 27 | 2 (0)| 00
:00:01 |
| 2 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 7 | 1 (0)| 00
:00:01 |
|* 3 | INDEX UNIQUE SCAN | PK_EMP | 1 | | 0 (0)| 00
:00:01 |
| 4 | TABLE ACCESS BY INDEX ROWID| DEPT | 4 | 80 | 1 (0)| 00
:00:01 |
|* 5 | INDEX UNIQUE SCAN | PK_DEPT | 1 | | 0 (0)| 00
:00:01 |
--------------------------------------------------------------------------------
--------
Predicate Information (identified by operation id):
---------------------------------------------------
3 - access("A"."EMPNO"=7369)
5 - access("A"."DEPTNO"="B"."DEPTNO"(+))
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
4 consistent gets
0 physical reads
0 redo size
533 bytes sent via SQL*Net to client
400 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
SQL>