Mysql exists 与 in

今天公司同事反馈一个SQL语句删除数据删除了一个小时,还没有删除完,强制中断。 第一眼看到 exists 的时候,脑子里要有这么个概念:

Oracle exists 的效率比in 高。而Mysql 则不一定。 Mysql 使用eixsts 与使用in的规则为:

子查询的表大的时候,使用EXISTS可以有效减少总的循环次数来提升速度;
外查询的表大的时候,使用IN可以有效减少对外查询表循环遍历来提升速度。
从本质上讲,exists 是以外查询为驱动表,而in 是以子查询为驱动表(驱动表决定了以 哪个结果集作为nestloop的对比依据)。

3.1.1 SQL

DELETE t FROM   o.`AI_AD_U_L` t   WHERE EXISTS (SELECT     1   FROM     o.`AI_AD_U_L_TEMP`  AS a   WHERE a.`ca_id`=t.`ca_id`);

3.1.2 分析过程

  1. 查看表上的索引

    mysql> show index from AI_AD_U_L;
    +-----------+------------+---------------------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    | Table     | Non_unique | Key_name                        | Seq_in_index | Column_name  | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
    +-----------+------------+---------------------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    | AI_AD_U_L |          0 | PRIMARY                         |            1 | prod_inst_id | A         |    21162012 |     NULL | NULL   |      | BTREE      |         |               |
    | AI_AD_U_L |          1 | ai_sync_prod_level_cust_addr_id |            1 | cust_addr_id | A         |     8266746 |     NULL | NULL   | YES  | BTREE      |         |               |
    | AI_AD_U_L |          1 | ai_sync_prod_level_mac          |            1 | mac          | A         |    12227460 |     NULL | NULL   | YES  | BTREE      |         |               |
    +-----------+------------+---------------------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    3 rows in set (0.00 sec)
    mysql> show index from AI_AD_U_L_TEMP;
    +----------------+------------+-------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    | Table          | Non_unique | Key_name          | Seq_in_index | Column_name  | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
    +----------------+------------+-------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    | AI_AD_U_L_TEMP |          1 | idx_cust_addr_id2 |            1 | cust_addr_id | A         |        2366 |     NULL | NULL   | YES  | BTREE      |         |               |
    | AI_AD_U_L_TEMP |          1 | idx_prod_inst_id  |            1 | prod_inst_id | A         |        3791 |     NULL | NULL   |      | BTREE      |         |               |
    +----------------+------------+-------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
    2 rows in set (0.00 sec)
    

    此时表上是有对应字段的索引的,如果索引不存在,需要创建索引。

  2. 查看执行计划

    mysql> explain DELETE   t FROM   o.`AI_AD_U_L` t WHERE EXISTS   (SELECT     1   FROM     o.`AI_AD_U_L_TEMP` AS a   WHERE a.prod_inst_id = t.prod_inst_id);
    +----+--------------------+-------+------------+------+------------------+------------------+---------+-----------------------+----------+----------+-------------+
    | id | select_type        | table | partitions | type | possible_keys    | key              | key_len | ref                   | rows     | filtered | Extra       |
    +----+--------------------+-------+------------+------+------------------+------------------+---------+-----------------------+----------+----------+-------------+
    |  1 | DELETE             | t     | NULL       | ALL  | NULL             | NULL             | NULL    | NULL                  | 21162122 |   100.00 | Using where |
    |  2 | DEPENDENT SUBQUERY | a     | NULL       | ref  | idx_prod_inst_id | idx_prod_inst_id | 8       | o.t.prod_inst_id      |        1 |   100.00 | Using index |
    +----+--------------------+-------+------------+------+------------------+------------------+---------+-----------------------+----------+----------+-------------+
    2 rows in set, 1 warning (0.01 sec)
    

    通过执行计划发现两点问题:

    1. 外查询表数据量大,21162122,也就是访问了21162122次,而子查询通过索引只访问了一次。
    2. 发现子查询使用了索引,而外查询表上没有使用索引。

    从以上两点发现,说明外查询作为了驱动表。

  3. 查看子查询中表的数据量

    mysql> select count(*) from AI_AD_U_L_TEMP;
    +----------+
    | count(*) |
    +----------+
    |     3791 |
    +----------+
    1 row in set (0.00 sec)
    

    子查询中数据量小,应以子查询为驱动表。应该用exists 应换成in。

  4. 调整SQL语句并查看执行计划 将exists 改为in 的用法 。

    mysql> explain DELETE   t FROM   o.`AI_AD_U_L` t WHERE t.prod_inst_id in  (SELECT prod_inst_id FROM     o.`AI_AD_U_L_TEMP` AS a   );
    +----+-------------+-------+------------+--------+------------------+------------------+---------+-----------------------+------+----------+------------------------+
    | id | select_type | table | partitions | type   | possible_keys    | key              | key_len | ref                   | rows | filtered | Extra                  |
    +----+-------------+-------+------------+--------+------------------+------------------+---------+-----------------------+------+----------+------------------------+
    |  1 | SIMPLE      | a     | NULL       | index  | idx_prod_inst_id | idx_prod_inst_id | 8       | NULL                  | 3791 |   100.00 | Using index; LooseScan |
    |  1 | DELETE      | t     | NULL       | eq_ref | PRIMARY          | PRIMARY          | 8       | o.a.prod_inst_id |    1 |   100.00 | NULL                   |
    +----+-------------+-------+------------+--------+------------------+------------------+---------+-----------------------+------+----------+------------------------+
    2 rows in set (0.00 sec)
    

    从执行计划中可以看到,两张表都在使用索引。而外表的访问次数也明显下降为子查询表中的行数。大量减少了循环访问外表的次数。

  5. 执行SQL语句

    mysql> DELETE   t FROM   o.`AI_AD_U_L` t WHERE t.prod_inst_id in  (SELECT prod_inst_id FROM     o.`AI_AD_U_L_TEMP` AS a   );
    Query OK, 3525 rows affected (0.44 sec)
    

    我们看到效果明显, 原来1小时都无法执行完成的SQL,现在只需要0.44秒。

原文地址:https://www.cnblogs.com/halberd-lee/p/10643431.html