oracle 表连接 - nested loop 嵌套循环连接
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
