8 种经常被忽视的 SQL 错误用法，你有没有踩过坑？

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_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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

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

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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