前言

MySQL在2016年仍然保持强劲的数据库流行度增长趋势。越来越多的客户将自己的应用建立在MySQL数据库之上，甚至是从Oracle迁移到MySQL上来。但也存在部分客户在使用MySQL数据库的过程中遇到一些比如响应时间慢，CPU打满等情况。阿里云RDS专家服务团队帮助云上客户解决过很多紧急问题。现将《ApsaraDB专家诊断报告》中出现的部分常见SQL问题总结如下，供大家参考。

常见SQL错误用法

1. LIMIT 语句

分页查询是最常用的场景之一，但也通常也是最容易出问题的地方。比如对于下面简单的语句，一般DBA想到的办法是在type, name, create_time字段上加组合索引。这样条件排序都能有效的利用到索引，性能迅速提升。

  1. SELECT * 
  2. FROM   operation 
  3. WHERE  type = 'SQLStats' 
  4.        AND name = 'SlowLog' 
  5. ORDER  BY create_time 
  6. 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：

  1. SELECT   * 
  2. FROM     operation 
  3. WHERE    type = 'SQLStats' 
  4. AND      name = 'SlowLog' 
  5. AND      create_time > '2017-03-16 14:00:00' 
  6. 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：

  1. mysql> explain extended SELECT * 
  2.      > FROM   my_balance b 
  3.      > WHERE  b.bpn = 14000000123 
  4.      >       AND b.isverified IS NULL ;
  5. mysql> show warnings;
  6. | 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。

  1. UPDATE operation o 
  2. SET    status = 'applying' 
  3. WHERE  o.id IN (SELECT id 
  4.                 FROM   (SELECT o.id, 
  5.                                o.status 
  6.                         FROM   operation o 
  7.                         WHERE  o.group = 123 
  8.                                AND o.status NOT IN ( 'done' ) 
  9.                         ORDER  BY o.parent, 
  10.                                   o.id 
  11.                         LIMIT  1) t);

执行计划：

  1. +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
  2. | id | select_type        | table | type  | possible_keys | key     | key_len | ref   | rows | Extra                                               |
  3. +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
  4. | 1  | PRIMARY            | o     | index |               | PRIMARY | 8       |       | 24   | Using where; Using temporary                        |
  5. | 2  | DEPENDENT SUBQUERY |       |       |               |         |         |       |      | Impossible WHERE noticed after reading const tables |
  6. | 3  | DERIVED            | o     | ref   | idx_2,idx_5   | idx_5   | 8       | const | 1    | Using where; Using filesort                         |
  7. +----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+

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。

  1. UPDATE operation o 
  2.        JOIN  (SELECT o.id, 
  3.                             o.status 
  4.                      FROM   operation o 
  5.                      WHERE  o.group = 123 
  6.                             AND o.status NOT IN ( 'done' ) 
  7.                      ORDER  BY o.parent, 
  8.                                o.id 
  9.                      LIMIT  1) t
  10.          ON o.id = t.id 
  11. SET    status = 'applying'

执行计划简化为：

  1. +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
  2. | id | select_type | table | type | possible_keys | key   | key_len | ref   | rows | Extra                                               |
  3. +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
  4. | 1  | PRIMARY     |       |      |               |       |         |       |      | Impossible WHERE noticed after reading const tables |
  5. | 2  | DERIVED     | o     | ref  | idx_2,idx_5   | idx_5 | 8       | const | 1    | Using where; Using filesort                         |
  6. +----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

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。

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

执行计划显示为全表扫描：

  1. +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+
  2. | id | select_type | table | type   | possible_keys     | key     | key_len | ref      | rows    | Extra    
  3. +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+
  4. |  1 | SIMPLE      | a     | ALL    | idx_orderid | NULL    | NULL    | NULL    | 1967647 | Using filesort |
  5. |  1 | SIMPLE      | o     | eq_ref | PRIMARY     | PRIMARY | 122     | a.orderid |       1 | NULL           |
  6. +----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+

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。

  1. SELECT * 
  2. FROM   ((SELECT *
  3.          FROM   my_order o 
  4.                 INNER JOIN my_appraise a 
  5.                         ON a.orderid = o.id 
  6.                            AND is_reply = 0 
  7.          ORDER  BY appraise_time DESC 
  8.          LIMIT  0, 20) 
  9.         UNION ALL 
  10.         (SELECT *
  11.          FROM   my_order o 
  12.                 INNER JOIN my_appraise a 
  13.                         ON a.orderid = o.id 
  14.                            AND is_reply = 1 
  15.          ORDER  BY appraise_time DESC 
  16.          LIMIT  0, 20)) t 
  17. ORDER  BY  is_reply ASC, 
  18.           appraisetime DESC 
  19. 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：

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

执行计划为：

  1. +----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+
  2. | id | select_type        | table | type | possible_keys     | key   | key_len | ref   | rows    | Extra   |
  3. +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+
  4. |  1 | PRIMARY            | n     | ALL  |  | NULL     | NULL    | NULL  | 1086041 | Using where                   |
  5. |  1 | PRIMARY            | sra   | ref  |  | idx_user_id | 123     | const |       1 | Using where          |
  6. |  2 | DEPENDENT SUBQUERY | m     | ref  |  | idx_message_info   | 122     | const |       1 | Using index condition; Using where |
  7. +----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+

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。

  1. SELECT *
  2. FROM   my_neighbor n 
  3.        INNER JOIN message_info m 
  4.                ON n.id = m.neighbor_id 
  5.                   AND m.inuser = 'xxx' 
  6.        LEFT JOIN my_neighbor_apply sra 
  7.               ON n.id = sra.neighbor_id 
  8.                  AND sra.user_id = 'xxx' 
  9. WHERE  n.topic_status < 4 
  10.        AND n.topic_type <> 5

新的执行计划：

  1. +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
  2. | id | select_type | table | type   | possible_keys     | key       | key_len | ref   | rows | Extra                 |
  3. +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
  4. |  1 | SIMPLE      | m     | ref    | | idx_message_info   | 122     | const    |    1 | Using index condition |
  5. |  1 | SIMPLE      | n     | eq_ref | | PRIMARY   | 122     | ighbor_id |    1 | Using where      |
  6. |  1 | SIMPLE      | sra   | ref    | | idx_user_id | 123     | const     |    1 | Using where           |
  7. +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

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：

  1. 聚合子查询；
  2. 含有LIMIT的子查询；
  3. UNION 或UNION ALL子查询；
  4. 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：

  1. SELECT * 
  2. FROM   (SELECT target, 
  3.                Count(*) 
  4.         FROM   operation 
  5.         GROUP  BY target) t 
  6. WHERE  target = 'rm-xxxx'
  1. +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
  2. | id | select_type | table      | type  | possible_keys | key         | key_len | ref   | rows | Extra       |
  3. +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
  4. |  1 | PRIMARY     | <derived2> | ref   | <auto_key0>   | <auto_key0> | 514     | const |    2 | Using where |
  5. |  2 | DERIVED     | operation  | index | idx_4         | idx_4       | 519     | NULL  |   20 | Using index |
  6. +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+

确定从语义上查询条件可以直接下推后，重写如下：

  1. SELECT target, 
  2.        Count(*) 
  3. FROM   operation 
  4. WHERE  target = 'rm-xxxx' 
  5. GROUP  BY target

执行计划变为：

  1. +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
  2. | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
  3. +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
  4. | 1 | SIMPLE | operation | ref | idx_4 | idx_4 | 514 | const | 1 | Using where; Using index |
  5. +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

关于MySQL外部条件不能下推的详细解释说明请参考以前文章：MySQL · 性能优化 · 条件下推到物化表

7. 提前缩小范围

先上初始SQL语句：

  1. SELECT * 
  2. FROM   my_order o 
  3.        LEFT JOIN my_userinfo u 
  4.               ON o.uid = u.uid
  5.        LEFT JOIN my_productinfo p 
  6.               ON o.pid = p.pid 
  7. WHERE  ( o.display = 0 ) 
  8.        AND ( o.ostaus = 1 ) 
  9. ORDER  BY o.selltime DESC 
  10. 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。

  1. +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
  2. | id | select_type | table | type   | possible_keys | key     | key_len | ref             | rows   | Extra                                              |
  3. +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
  4. |  1 | SIMPLE      | o     | ALL    | NULL          | NULL    | NULL    | NULL            | 909119 | Using where; Using temporary; Using filesort       |
  5. |  1 | SIMPLE      | u     | eq_ref | PRIMARY       | PRIMARY | 4       | o.uid |      1 | NULL                                               |
  6. |  1 | SIMPLE      | p     | ALL    | PRIMARY       | NULL    | NULL    | NULL            |      6 | Using where; Using join buffer (Block Nested Loop) |
  7. +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+

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。

  1. SELECT * 
  2. FROM (
  3. SELECT * 
  4. FROM   my_order o 
  5. WHERE  ( o.display = 0 ) 
  6.        AND ( o.ostaus = 1 ) 
  7. ORDER  BY o.selltime DESC 
  8. LIMIT  0, 15
  9. ) o 
  10.      LEFT JOIN my_userinfo u 
  11.               ON o.uid = u.uid 
  12.      LEFT JOIN my_productinfo p 
  13.               ON o.pid = p.pid 
  14. ORDER BY  o.selltime DESC
  15. limit 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。

  2. +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
  3. | id | select_type | table      | type   | possible_keys | key     | key_len | ref   | rows   | Extra                                              |
  4. +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
  5. |  1 | PRIMARY     | <derived2> | ALL    | NULL          | NULL    | NULL    | NULL  |     15 | Using temporary; Using filesort                    |
  6. |  1 | PRIMARY     | u          | eq_ref | PRIMARY       | PRIMARY | 4       | o.uid |      1 | NULL                                               |
  7. |  1 | PRIMARY     | p          | ALL    | PRIMARY       | NULL    | NULL    | NULL  |      6 | Using where; Using join buffer (Block Nested Loop) |
  8. |  2 | DERIVED     | o          | index  | NULL          | idx_1   | 5       | NULL  | 909112 | Using where                                        |
  9. +----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

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)：

  1. SELECT    a.*, 
  2.           c.allocated 
  3. FROM      ( 
  4.               SELECT   resourceid 
  5.               FROM     my_distribute d 
  6.                    WHERE    isdelete = 0 
  7.                    AND      cusmanagercode = '1234567' 
  8.                    ORDER BY salecode limit 20) a 
  9. LEFT JOIN 
  10.           ( 
  11.               SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated 
  12.               FROM     my_resources 
  13.                    GROUP BY resourcesid) c 
  14. 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。

  1. SELECT    a.*, 
  2.           c.allocated 
  3. FROM      ( 
  4.                    SELECT   resourceid 
  5.                    FROM     my_distribute d 
  6.                    WHERE    isdelete = 0 
  7.                    AND      cusmanagercode = '1234567' 
  8.                    ORDER BY salecode limit 20) a 
  9. LEFT JOIN 
  10.           ( 
  11.                    SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated 
  12.                    FROM     my_resources r, 
  13.                             ( 
  14.                                      SELECT   resourceid 
  15.                                      FROM     my_distribute d 
  16.                                      WHERE    isdelete = 0 
  17.                                      AND      cusmanagercode = '1234567' 
  18.                                      ORDER BY salecode limit 20) a 
  19.                    WHERE    r.resourcesid = a.resourcesid 
  20.                    GROUP BY resourcesid) c 
  21. 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：

  1. WITH a AS 
  2. ( 
  3.          SELECT   resourceid 
  4.          FROM     my_distribute d 
  5.          WHERE    isdelete = 0 
  6.          AND      cusmanagercode = '1234567' 
  7.          ORDER BY salecode limit 20)
  8. SELECT    a.*, 
  9.           c.allocated 
  10. FROM      a 
  11. LEFT JOIN 
  12.           ( 
  13.                    SELECT   resourcesid， sum(ifnull(allocation, 0) * 12345) allocated 
  14.                    FROM     my_resources r, 
  15.                             a 
  16.                    WHERE    r.resourcesid = a.resourcesid 
  17.                    GROUP BY resourcesid) c 
  18. ON        a.resourceid = c.resourcesid

AliSQL即将推出WITH语法，敬请期待。

总结

  1. 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。
  2. 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。
  3. 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 ^^。
  4. 使用云上数据库遇到难点（不局限于SQL问题），随时寻求阿里云原厂专家服务的帮助。