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nested loops join 嵌套循环
merge sort join 排序合并
hash join 哈希连接
nested loops join（嵌套循环）
驱动表返回几条结果集，被驱动表访问多少次，有驱动顺序，无须排序，无任何限制。
驱动表限制条件有索引，被驱动表连接条件有索引。
hints：use_nl()
merge sort join（排序合并）
驱动表和被驱动表都是最多访问1次，无驱动顺序，需要排序（SORT_AREA_SIZE），连接条件是<>或like导致无法使用。
在连接条件上建立索引可以消除一张表的排序。
hints：use_merge()
hash join（哈希连接）
驱动表和被驱动表都是最多访问1次，有驱动顺序，无须排序（HASH_AREA_SIZE但是会消耗内存用于建HASH表），连接条件是<> > < 或like导致无法使用。
索引列在表连接中无特殊要求，与单表情况相同。
hints：use_hash()
实验验证：
首先，准备两张表t1,t2,分别初始化随机插入100条和100,000条数据：
drop table t1 cascade constraints purge; drop table t2 cascade constraints purge; create table t1( id number not null, n number, contents varchar2(4000) ); create table t2( id number not null, t1_id number not null, n number, contents varchar2(4000) ); execute dbms_random.seed(0); insert into t1 select rownum, rownum, dbms_random.string(‘a‘,50) from dual connect by level <= 100 order by dbms_random.random; commit; insert into t2 select rownum, rownum, rownum, dbms_random.string(‘b‘,50) from dual connect by level <= 100000 order by dbms_random.random; commit; select count(1) from t1; select count(1) from t2;
1.不同表连接的表访问次数验证：
set linesize 1000 alter session set statistics_level = all;
select * from table(dbms_xplan.display_cursor(null,null,‘allstats last‘));
1.1 nested loops join:
select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id; select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n in(17,19); select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 99999999;
1.2 hash join:
select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n in(17,19); select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 99999999; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and 1 = 2;
1.3 merge sort join
select /*+ ordered use_merge(t2) */ * from t1, t2 where t1.id = t2.t1_id;
2.不同表连接的驱动顺序区别：
2.1 nested loops join
select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t2)use_nl(t1) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
2.2 hash join
select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t2)use_hash(t1) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
2.3 merge sort join
select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t2)use_merge(t1) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
说到不同表连接表的驱动顺序，网上也有一个普遍流行的观点，就是小表作为驱动表。其实通过上面的实验可以发现这样的描述是不准确的。
正确地描述应该是：对于nested loops join和hash join来说，小的结果集先访问,大的结果集后访问（即与表的大小没有关系，与具体sql返回的结果集大小有关）；而对于merge sort join 来说，先访问谁效率都是一样的。
3.不同表连接的排序情况分析：
嵌套循环，不排序；
hash连接，消耗内存建立hash表；
排序合并，需要排序。
开发人员需要注意不要取多余的字段参与排序：
select /*+ leading(t2)use_merge(t1) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t2)use_merge(t1) */ t1.id from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
select * from table(dbms_xplan.display_cursor(null,null,‘allstats last‘));
4.不同表连接的限制场景对比：
4.1 hash join不支持<> > < like连接条件
select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id <> t2.t1_id and t1.n = 19; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id > t2.t1_id and t1.n = 19; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id < t2.t1_id and t1.n = 19; select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id like t2.t1_id and t1.n = 19;
select * from table(dbms_xplan.display_cursor(null,null,‘allstats last‘));
4.2 merge sort join不支持<> like 连接方式
select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id <> t2.t1_id and t1.n = 19; select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id > t2.t1_id and t1.n = 19; select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id < t2.t1_id and t1.n = 19; select /*+ leading(t1)use_merge(t2) */ * from t1, t2 where t1.id like t2.t1_id and t1.n = 19;
select * from table(dbms_xplan.display_cursor(null,null,‘allstats last‘));
4.3 nested loops join 所有都支持
从上面实验结果来看，不能走hash和merge的表连接条件，都会走nested loops join。
5.不同表连接和索引的关系：
5.1 nested loops join
驱动表的限制条件建立索引，被驱动表的连接条件建立索引。
create index idx_t1_n on t1(n); create index idx_t2_t1_id on t2(t1_id); select /*+ leading(t1)use_nl(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select * from table(dbms_xplan.display_cursor(null,null,‘allstats last‘));
5.2 hash join
select /*+ leading(t1)use_hash(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19; select * from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
一般查询没有合适索引，Oracle都会选择用hash join的表连接。
5.3 merge sort join
create index idx_t1_id on t1(id);
select /*+ ordered use_merge(t2) */ * from t1, t2 where t1.id = t2.t1_id and t1.n = 19;
Oracle 10g版本，在连接条件建立索引可以消除merge sort join表连接的一张表的排序操作。(虽然在两张表的连接条件都建立了索引，却只能消除一张表的排序操作)
注：本文为《收获，不止Oracle》表连接一章的总结笔记。
SQL Tuning 基础概述06 - 表的连接方式：Nested Loops Join，Merge Sort Join & Hash Join
标签：style blog io ar color 使用 sp strong on
原文地址：http://www.cnblogs.com/jyzhao/p/3930550.html
