sql优化使用技巧

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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
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 http://mysql.taobao.org/monthly/2016/07/08

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

转自：https://www.toutiao.com/a6665531540069417475/?tt_from=weixin&utm_campaign=client_share&wxshare_count=1&timestamp=1552002686&app=news_article&utm_source=weixin&iid=65340322632&utm_medium=toutiao_android&group_id=6665531540069417475