MySQL中常见的八种SQL错误用法示例

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。

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。

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_key
0
>
| <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 DESC
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。

+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
| 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 。

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