MySQL · 性能优化 · MySQL常见SQL错误用法

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。

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：

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 | | ref | | | 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 | | 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 ^^。
使用云上数据库遇到难点（不局限于SQL问题），随时寻求阿里云原厂专家服务的帮助。