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。
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:
SELECT *
FROM operation
WHERE type = 'SQLStats'
AND name = 'SlowLog'
AND create_time > '2017-03-16 14:00:00'
ORDER BY create_time limit 10;
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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
- 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 |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
写在最后
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