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 > "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：

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：

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

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。