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。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***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:
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,***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***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***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
当前标题:性能优化|MySQL常见SQL错误用法
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