MySQL 性能优化：8 种常见 SQL 错误用法！

SELECT * FROM   operation WHERE  type = 'SQLStats'        AND name = 'SlowLog' ORDER  BY create_time LIMIT  1000, 10;

好吧，可能90%以上的 DBA 解决该问题就到此为止。但当 LIMIT 子句变成 “LIMIT 1000000,10” 时，程序员仍然会抱怨：我只取10条记录为什么还是慢？

要知道数据库也并不知道第1000000条记录从什么地方开始，即使有索引也需要从头计算一次。出现这种性能问题，多数情形下是程序员偷懒了。

在前端数据浏览翻页，或者大数据分批导出等场景下，是可以将上一页的最大值当成参数作为查询条件的。SQL 重新设计如下：

SELECT   * FROM     operation WHERE    type = 'SQLStats' AND      name = 'SlowLog' AND      create_time > '2017-03-16 14:00:00' ORDER BY create_time limit 10;

在新设计下查询时间基本固定，不会随着数据量的增长而发生变化。

2、隐式转换

SQL语句中查询变量和字段定义类型不匹配是另一个常见的错误。比如下面的语句：

mysql> explain extended SELECT *      > FROM my_balance b      > WHERE b.bpn = 14000000123      > AND b.isverified IS NULL ;mysql> show warnings;| Warning | 1739 | Cannot use ref access on index 'bpn' due to type or collation conversion on field 'bpn'

其中字段 bpn 的定义为 varchar(20)，MySQL 的策略是将字符串转换为数字之后再比较。函数作用于表字段，索引失效。

上述情况可能是应用程序框架自动填入的参数，而不是程序员的原意。现在应用框架很多很繁杂，使用方便的同时也小心它可能给自己挖坑。

3、关联更新、删除

虽然 MySQL5.6 引入了物化特性，但需要特别注意它目前仅仅针对查询语句的优化。对于更新或删除需要手工重写成 JOIN。

比如下面 UPDATE 语句，MySQL 实际执行的是循环/嵌套子查询（DEPENDENT SUBQUERY)，其执行时间可想而知。

UPDATE operation o SET    status = 'applying' WHERE  o.id IN (SELECT id                 FROM   (SELECT o.id,                                o.status                         FROM   operation o                         WHERE  o.group = 123                                AND o.status NOT IN ( 'done' )                         ORDER  BY o.parent,                                   o.id                         LIMIT  1) t);

执行计划：

+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+| 1  | PRIMARY | o | index |               | PRIMARY | 8       | | 24   | Using where; Using temporary || 2 | DEPENDENT SUBQUERY | |       | |         | |       | | Impossible WHERE noticed after reading const tables || 3  | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8       | const | 1    | Using where; Using filesort |+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+

重写为 JOIN 之后，子查询的选择模式从 DEPENDENT SUBQUERY 变成 DERIVED，执行速度大大加快，从7秒降低到2毫秒。

UPDATE operation o        JOIN  (SELECT o.id,                             o.status                      FROM   operation o                      WHERE  o.group = 123                             AND o.status NOT IN ( 'done' )                      ORDER  BY o.parent,                                o.id                      LIMIT  1) t         ON o.id = t.id SET    status = 'applying'

执行计划简化为：

+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+| 1  | PRIMARY |       | |               | |         | |      | Impossible WHERE noticed after reading const tables || 2 | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8 | const | 1 | Using where; Using filesort |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

4、混合排序

MySQL 不能利用索引进行混合排序。但在某些场景，还是有机会使用特殊方法提升性能的。

SELECT * FROM   my_order o        INNER JOIN my_appraise a ON a.orderid = o.id ORDER  BY a.is_reply ASC,           a.appraise_time DESC LIMIT  0, 20

执行计划显示为全表扫描：

+----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+| 1 | SIMPLE | a | ALL | idx_orderid | NULL | NULL | NULL | 1967647 | Using filesort ||  1 | SIMPLE | o | eq_ref | PRIMARY | PRIMARY | 122     | a.orderid |       1 | NULL |+----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+

由于 is_reply 只有0和1两种状态，我们按照下面的方法重写后，执行时间从1.58秒降低到2毫秒。

SELECT * FROM   ((SELECT *         FROM   my_order o                 INNER JOIN my_appraise a                         ON a.orderid = o.id                            AND is_reply = 0          ORDER  BY appraise_time DESC          LIMIT  0, 20)         UNION ALL         (SELECT *         FROM   my_order o                 INNER JOIN my_appraise a                         ON a.orderid = o.id                            AND is_reply = 1          ORDER  BY appraise_time DESC          LIMIT  0, 20)) t ORDER  BY  is_reply ASC,           appraisetime DESC LIMIT  20;

5、EXISTS语句

MySQL 对待 EXISTS 子句时，仍然采用嵌套子查询的执行方式。如下面的 SQL 语句：

SELECT *FROM   my_neighbor n        LEFT JOIN my_neighbor_apply sra               ON n.id = sra.neighbor_id                  AND sra.user_id = 'xxx' WHERE  n.topic_status < 4        AND EXISTS(SELECT 1                   FROM   message_info m                   WHERE  n.id = m.neighbor_id                          AND m.inuser = 'xxx')        AND n.topic_type <> 5

执行计划为：

+----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+|  1 | PRIMARY | n | ALL |  | NULL | NULL | NULL | 1086041 | Using where || 1 | PRIMARY | sra | ref | | idx_user_id | 123 | const | 1 | Using where ||  2 | DEPENDENT SUBQUERY | m | ref |  | idx_message_info | 122     | const |       1 | Using index condition; Using where |+----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+

去掉 exists 更改为 join，能够避免嵌套子查询，将执行时间从1.93秒降低为1毫秒。

SELECT *FROM   my_neighbor n        INNER JOIN message_info m                ON n.id = m.neighbor_id                   AND m.inuser = 'xxx'        LEFT JOIN my_neighbor_apply sra               ON n.id = sra.neighbor_id                  AND sra.user_id = 'xxx' WHERE  n.topic_status < 4        AND n.topic_type <> 5

新的执行计划：

+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+|  1 | SIMPLE | m | ref | | idx_message_info | 122     | const |    1 | Using index condition || 1 | SIMPLE | n | eq_ref | | PRIMARY | 122 | ighbor_id | 1 | Using where ||  1 | SIMPLE | sra | ref | | idx_user_id | 123     | const |    1 | Using where |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

6、条件下推

外部查询条件不能够下推到复杂的视图或子查询的情况有：

聚合子查询；
含有 LIMIT 的子查询；
UNION 或 UNION ALL 子查询；
输出字段中的子查询；

如下面的语句，从执行计划可以看出其条件作用于聚合子查询之后：

SELECT * FROM   (SELECT target,                Count(*)         FROM   operation         GROUP  BY target) t WHERE  target = 'rm-xxxx'

+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+|  1 | PRIMARY | <derived2> | ref | <auto_key0> | <auto_key0> | 514     | const |    2 | Using where || 2 | DERIVED | operation | index | idx_4 | idx_4 | 519 | NULL | 20 | Using index |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+

确定从语义上查询条件可以直接下推后，重写如下：

SELECT target,        Count(*) FROM   operation WHERE  target = 'rm-xxxx' GROUP  BY target

执行计划变为：

+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+| 1 | SIMPLE | operation | ref | idx_4 | idx_4 | 514 | const | 1 | Using where; Using index |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

关于 MySQL 外部条件不能下推的详细解释说明请参考文章：

http://mysql.taobao.org/monthly/2016/07/08

7、提前缩小范围

先上初始 SQL 语句：

SELECT * FROM   my_order o        LEFT JOIN my_userinfo u               ON o.uid = u.uid       LEFT JOIN my_productinfo p               ON o.pid = p.pid WHERE  ( o.display = 0 )        AND ( o.ostaus = 1 ) ORDER  BY o.selltime DESC LIMIT  0, 15

该SQL语句原意是：先做一系列的左连接，然后排序取前15条记录。从执行计划也可以看出，最后一步估算排序记录数为90万，时间消耗为12秒。

+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+|  1 | SIMPLE | o | ALL | NULL | NULL | NULL | NULL | 909119 | Using where; Using temporary; Using filesort || 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL ||  1 | SIMPLE | p | ALL | PRIMARY | NULL | NULL | NULL |      6 | Using where; Using join buffer (Block Nested Loop) |+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+

由于最后 WHERE 条件以及排序均针对最左主表，因此可以先对 my_order 排序提前缩小数据量再做左连接。SQL 重写后如下，执行时间缩小为1毫秒左右。

SELECT * FROM (SELECT * FROM   my_order o WHERE  ( o.display = 0 )        AND ( o.ostaus = 1 ) ORDER  BY o.selltime DESC LIMIT  0, 15) o      LEFT JOIN my_userinfo u               ON o.uid = u.uid      LEFT JOIN my_productinfo p               ON o.pid = p.pid ORDER BY  o.selltime DESClimit 0, 15

再检查执行计划：子查询物化后（select_type=DERIVED)参与 JOIN。虽然估算行扫描仍然为90万，但是利用了索引以及 LIMIT 子句后，实际执行时间变得很小。

+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+|  1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL |     15 | Using temporary; Using filesort || 1 | PRIMARY | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL ||  1 | PRIMARY | p | ALL | PRIMARY | NULL | NULL | NULL |      6 | Using where; Using join buffer (Block Nested Loop) || 2 | DERIVED | o | index | NULL | idx_1 | 5 | NULL | 909112 | Using where |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

8、中间结果集下推

再来看下面这个已经初步优化过的例子(左连接中的主表优先作用查询条件)：

SELECT    a.*,           c.allocated FROM      (               SELECT   resourceid               FROM     my_distribute d                    WHERE    isdelete = 0                    AND      cusmanagercode = '1234567'                    ORDER BY salecode limit 20) a LEFT JOIN           (               SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated               FROM     my_resources                    GROUP BY resourcesid) c ON        a.resourceid = c.resourcesid

那么该语句还存在其它问题吗？不难看出子查询 c 是全表聚合查询，在表数量特别大的情况下会导致整个语句的性能下降。

其实对于子查询 c，左连接最后结果集只关心能和主表 resourceid 能匹配的数据。因此我们可以重写语句如下，执行时间从原来的2秒下降到2毫秒。

SELECT    a.*,           c.allocated FROM      (                    SELECT   resourceid                    FROM     my_distribute d                    WHERE    isdelete = 0                    AND      cusmanagercode = '1234567'                    ORDER BY salecode limit 20) a LEFT JOIN           (                    SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated                    FROM     my_resources r,                             (                                      SELECT   resourceid                                      FROM     my_distribute d                                      WHERE    isdelete = 0                                      AND      cusmanagercode = '1234567'                                      ORDER BY salecode limit 20) a                    WHERE    r.resourcesid = a.resourcesid                    GROUP BY resourcesid) c ON        a.resourceid = c.resourcesid

但是子查询 a 在我们的SQL语句中出现了多次。这种写法不仅存在额外的开销，还使得整个语句显的繁杂。使用 WITH 语句再次重写：

WITH a AS (          SELECT   resourceid          FROM     my_distribute d          WHERE    isdelete = 0          AND      cusmanagercode = '1234567'          ORDER BY salecode limit 20)SELECT    a.*,           c.allocated FROM      a LEFT JOIN           (                    SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated                    FROM     my_resources r,                             a                    WHERE    r.resourcesid = a.resourcesid                    GROUP BY resourcesid) c ON        a.resourceid = c.resourcesid

总结

数据库编译器产生执行计划，决定着SQL的实际执行方式。但是编译器只是尽力服务，所有数据库的编译器都不是尽善尽美的。

上述提到的多数场景，在其它数据库中也存在性能问题。了解数据库编译器的特性，才能避规其短处，写出高性能的SQL语句。

程序员在设计数据模型以及编写SQL语句时，要把算法的思想或意识带进来。

编写复杂SQL语句要养成使用 WITH 语句的习惯。简洁且思路清晰的SQL语句也能减小数据库的负担。