8种常见的SQL错误用法

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。

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 > '2019-10-19 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：

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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