这8种常见的SQL错误用法，你还在用吗？（二）-阿里云开发者社区

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

AliSQL即将推出WITH语法，敬请期待。

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。

这8种常见的SQL错误用法，你还在用吗？（二）

5. EXISTS语句

6. 条件下推

7. 提前缩小范围

8. 中间结果集下推

总结

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