新同事不讲“码”德,这SQL写得太野了,请耗子尾汁~

今天来分享几个MySQL常见的SQL错误(不当)用法。我们在作为一个初学者时,很有可能自己在写SQL时也没有注意到这些问题,导致写出来的SQL语句效率低下,所以我们也可以自省自检一下。

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 |

+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

 

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 |

+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

看完这篇文章,你有什么收获?欢迎在留言区与30w+Java开发者一起讨论~

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原文地址:https://www.cnblogs.com/bainannan/p/14025009.html