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简介

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。

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) tON 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.uidLEFT 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 ^^。

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。

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