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。欢迎大家关注我的公种浩【程序员追风】,整理了2019年多家公司java面试题资料100多页pdf文档,文章都会在里面更新,整理的资料也会放在里面。
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 | <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 |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
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
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 。

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