oracle 表连接

一. nested loop 原理

nested loop 连接(循环嵌套连接)指的是两个表连接时, 通过两层嵌套循环来进行依次的匹配, 最后得到返回结果集的表连接方法.

假如下面的 sql 语句中表 T1 和 T2 的连接方式是循环嵌套连接, T1 是驱动表
select *
from T1, T2
where T1.id = T2.id and T1.name = 'David';
那么将上述 sql 语句翻译为伪码应该如下所示:

1 for each row in (select * from T1 where name = 'David') loop
2 for (select * from T2 where T2.id = outer.id) loop
3 If match then pass the row on to the next step
4 If no match then discard the row
5 end loop
6 end loop

具体来说, 如果上述 sql 语句执行循环嵌套连接的话, 那么实际的执行过程应该如下所示:

(1) 首先 oracle 会根据一定的规则(根据统计信息的成本计算或者 hint 强制)决定哪个表是驱动表, 哪个表是被驱动表 (假设 T1 是驱动表)
(2) 查询驱动表 "select * from T1 where name = 'David'" 然后得到驱动结果集 Q1
(3) 遍历驱动结果集 Q1 以及被驱动表 T2, 从驱动结果集 Q1 中取出一条记录, 接着遍历 T2 并按照连接条件 T2.id = T1.id 去判断 T2 中是否存在匹配的记录,
如果能够匹配则保留, 不能匹配则忽略此行, 然后再从 Q1 中取出下一条记录, 接着遍历 T2 进行匹配, 如此下去直到取完 Q1 中的所有记录

具体来说, 如果上述 sql 语句执行循环嵌套连接的话, 那么实际的执行过程应该如下所示:
(1) 首先 oracle 会根据一定的规则(根据统计信息的成本计算或者 hint 强制)决定哪个表是驱动表, 哪个表是被驱动表 (假设 T1 是驱动表)
(2) 查询驱动表 "select * from T1 where name = 'David'" 然后得到驱动结果集 Q1
(3) 遍历驱动结果集 Q1 以及被驱动表 T2, 从驱动结果集 Q1 中取出一条记录, 接着遍历 T2 并按照连接条件 T2.id = T1.id 去判断 T2 中是否存在匹配的记录,
如果能够匹配则保留, 不能匹配则忽略此行, 然后再从 Q1 中取出下一条记录, 接着遍历 T2 进行匹配, 如此下去直到取完 Q1 中的所有记录

二. nested loop 特性

嵌套循环连接有以下特性:

(1) 通常 sql 语句中驱动表只访问一次, 被驱动表访问多次
(2) 不必等待处理完成所有行前可以先返回部分已经处理完成的数据
(3) 在限制条件以及连接条件列上建立索引, 能够提高执行效率
(4) 支持所有类型的连接 (等值连接, 非等值连接, like 等)

构造试验数据

SQL> CREATE TABLE t1 (
2 id NUMBER NOT NULL,
3 n NUMBER,
4 pad VARCHAR2(4000),
5 CONSTRAINT t1_pk PRIMARY KEY(id)
6 );
Table created.

SQL> CREATE TABLE t2 (
2 id NUMBER NOT NULL,
3 t1_id NUMBER NOT NULL,
4 n NUMBER,
5 pad VARCHAR2(4000),
6 CONSTRAINT t2_pk PRIMARY KEY(id),
7 CONSTRAINT t2_t1_fk FOREIGN KEY (t1_id) REFERENCES t1
8 ); 
Table created.

SQL> CREATE TABLE t3 (
2 id NUMBER NOT NULL,
3 t2_id NUMBER NOT NULL,
4 n NUMBER,
5 pad VARCHAR2(4000),
6 CONSTRAINT t3_pk PRIMARY KEY(id),
7 CONSTRAINT t3_t2_fk FOREIGN KEY (t2_id) REFERENCES t2
8 ); 
Table created.

SQL> CREATE TABLE t4 (
2 id NUMBER NOT NULL,
3 t3_id NUMBER NOT NULL,
4 n NUMBER,
5 pad VARCHAR2(4000),
6 CONSTRAINT t4_pk PRIMARY KEY(id),
7 CONSTRAINT t4_t3_fk FOREIGN KEY (t3_id) REFERENCES t3
8 ); 
Table created.

SQL> execute dbms_random.seed(0) 
PL/SQL procedure successfully completed.


SQL> INSERT INTO t1 SELECT rownum, rownum, dbms_random.string('a',50) FROM dual CONNECT BY level <= 10 ORDER BY dbms_random.random;
10 rows created.

SQL> INSERT INTO t2 SELECT 100+rownum, t1.id, 100+rownum, t1.pad FROM t1, t1 dummy ORDER BY dbms_random.random; 
100 rows created.

SQL> INSERT INTO t3 SELECT 1000+rownum, t2.id, 1000+rownum, t2.pad FROM t2, t1 dummy ORDER BY dbms_random.random; 
1000 rows created.

SQL> INSERT INTO t4 SELECT 10000+rownum, t3.id, 10000+rownum, t3.pad FROM t3, t1 dummy ORDER BY dbms_random.random; 
10000 rows created.

SQL> COMMIT; 
Commit complete.

使用 hint 让 sql 语句通过 nested loop 连接, 并且指定 t3 为驱动表

 1 SQL> select /*+ leading(t3) use_nl(t4) */ * from t3, t4
 2 2 where t3.id = t4.t3_id and t3.n = 1100;
 3 
 4 10 rows selected.
 5 
 6 SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));
 7 
 8 PLAN_TABLE_OUTPUT
 9 ---------------------------------------------------------------------------------------------
10 SQL_ID 89hnfwqakjghg, child number 0
11 -------------------------------------
12 select /*+ leading(t3) use_nl(t4) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100
13 
14 Plan hash value: 1907878852
15 
16 -------------------------------------------------------------------------------------
17 | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
18 -------------------------------------------------------------------------------------
19 | 0 | SELECT STATEMENT | | 1 | | 10 |00:00:00.01 | 121 |
20 | 1 | NESTED LOOPS | | 1 | 10 | 10 |00:00:00.01 | 121 |
21 |* 2 | TABLE ACCESS FULL| T3 | 1 | 1 | 1 |00:00:00.01 | 16 |
22 |* 3 | TABLE ACCESS FULL| T4 | 1 | 10 | 10 |00:00:00.01 | 105 |
23 -------------------------------------------------------------------------------------
24 
25 Predicate Information (identified by operation id):
26 ---------------------------------------------------
27 
28 2 - filter("T3"."N"=1100)
29 3 - filter("T3"."ID"="T4"."T3_ID")

在执行计划中我们可以看到驱动表 T3 访问一次, 因为驱动表上有谓词条件 t3.n = 1100, 通过执行谓词条件后驱动结果集的记录数为 1, 所以 T4 也只访问一次(starts 列)

使用 hint 让 sql 语句通过 nested loop 连接, 并且指定 t4 为驱动表

 1 SQL> select /*+ leading(t4) use_nl(t3) full(t4) full(t3) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100;
 2 
 3 SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));
 4 
 5 PLAN_TABLE_OUTPUT
 6 ----------------------------------------------------------------------------------------------------------
 7 SQL_ID 0yxm1muqwrfq2, child number 0
 8 -------------------------------------
 9 select /*+ leading(t4) use_nl(t3) full(t4) full(t3) */ * from t3, t4
10 where t3.id = t4.t3_id and t3.n = 1100
11 
12 Plan hash value: 3886808168
13 
14 -------------------------------------------------------------------------------------
15 | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
16 -------------------------------------------------------------------------------------
17 | 0 | SELECT STATEMENT | | 1 | | 10 |00:00:00.25 | 150K|
18 | 1 | NESTED LOOPS | | 1 | 10 | 10 |00:00:00.25 | 150K|
19 | 2 | TABLE ACCESS FULL| T4 | 1 | 10000 | 10000 |00:00:00.01 | 105 |
20 |* 3 | TABLE ACCESS FULL| T3 | 10000 | 1 | 10 |00:00:00.21 | 150K|
21 -------------------------------------------------------------------------------------
22 
23 Predicate Information (identified by operation id):
24 ---------------------------------------------------
25 
26 3 - filter(("T3"."N"=1100 AND "T3"."ID"="T4"."T3_ID"))

在执行计划中我们可以看到驱动表 T4 访问一次, 因为驱动表上 T4 结果集的记录数为 10000, 所以 T4 访问了 10000 次, buffers 和 A-time(实际执行时间) 都比较高.

三. nested loop 优化

在 nested loop 被驱动表上的连接列上 (T4 表的 t3_id 列) 建立索引

 1 SQL> CREATE INDEX t4_t3_id ON t4(t3_id);
 2 
 3 Index created.
 4 
 5 SQL> select /*+ leading(t3) use_nl(t4) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100;
 6 
 7 10 rows selected.
 8 
 9 SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));
10 
11 PLAN_TABLE_OUTPUT
12 ------------------------------------------------------------------------------------------------------------------------------------
13 SQL_ID 89hnfwqakjghg, child number 0
14 -------------------------------------
15 select /*+ leading(t3) use_nl(t4) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100
16 
17 Plan hash value: 2039660043
18 
19 ------------------------------------------------------------------------------------------------------------
20 | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads |
21 ------------------------------------------------------------------------------------------------------------
22 | 0 | SELECT STATEMENT | | 1 | | 10 |00:00:00.01 | 29 | 1 |
23 | 1 | NESTED LOOPS | | 1 | | 10 |00:00:00.01 | 29 | 1 |
24 | 2 | NESTED LOOPS | | 1 | 10 | 10 |00:00:00.01 | 19 | 1 |
25 |* 3 | TABLE ACCESS FULL | T3 | 1 | 1 | 1 |00:00:00.01 | 16 | 0 |
26 |* 4 | INDEX RANGE SCAN | T4_T3_ID | 1 | 10 | 10 |00:00:00.01 | 3 | 1 |
27 | 5 | TABLE ACCESS BY INDEX ROWID| T4 | 10 | 10 | 10 |00:00:00.01 | 10 | 0 |
28 ------------------------------------------------------------------------------------------------------------
29 Predicate Information (identified by operation id):
30 ---------------------------------------------------
31 3 - filter("T3"."N"=1100)
32 4 - access("T3"."ID"="T4"."T3_ID")

 在执行计划中可以看到在被驱动表上的连接列上加上索引后, buffer 从 121 下降到了 29

在驱动表的谓词条件列上 (T3 表的 n 列) 加上索引

SQL> create index t3_n on t3(n);

Index created.

SQL> select /*+ leading(t3) use_nl(t4) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100;

10 rows selected.

SQL> select * from table(dbms_xplan.display_cursor(null,null,'allstats last'));

PLAN_TABLE_OUTPUT
-------------------------------------------------------------------------------------------------------------------------------------
SQL_ID 89hnfwqakjghg, child number 0
-------------------------------------
select /*+ leading(t3) use_nl(t4) */ * from t3, t4 where t3.id = t4.t3_id and t3.n = 1100

Plan hash value: 2304842513

-------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads |
-------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 10 |00:00:00.01 | 17 | 1 |
| 1 | NESTED LOOPS | | 1 | | 10 |00:00:00.01 | 17 | 1 |
| 2 | NESTED LOOPS | | 1 | 10 | 10 |00:00:00.01 | 7 | 1 |
| 3 | TABLE ACCESS BY INDEX ROWID| T3 | 1 | 1 | 1 |00:00:00.01 | 4 | 1 |
|* 4 | INDEX RANGE SCAN | T3_N | 1 | 1 | 1 |00:00:00.01 | 3 | 1 |
|* 5 | INDEX RANGE SCAN | T4_T3_ID | 1 | 10 | 10 |00:00:00.01 | 3 | 0 |
| 6 | TABLE ACCESS BY INDEX ROWID | T4 | 10 | 10 | 10 |00:00:00.01 | 10 | 0 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

4 - access("T3"."N"=1100)
5 - access("T3"."ID"="T4"."T3_ID")

　　在执行计划中可以看到在驱动表上的谓词条件列上加上索引后, buffer 从 29 继续下降到了 17

四. 小结

由此可见, 在 sql 调优时如果遇到表的连接方式是 nested loop：

首先，要确保结果集小的表为驱动表，结果集多的表为被驱动表。这不意味着记录多的表不能作为驱动表, 只要通过谓词条件过滤后得到的结果集比较小，也可以作为驱动表。

其次，在驱动表的谓词条件列以及被驱动表的连接列上加上索引，能够显著的提高执行性能。

最后，如果要查询的列都在索引中，避免回表查询列信息时，又将进一步提高执行性能。

https://blog.csdn.net/dataminer_2007/article/details/41826915

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原文地址：https://www.cnblogs.com/elontian/p/9483072.html