1.LIMIT语句
分页场景下
SELECT *
FROM operation
WHERE type = 'SQLStats'
AND name = 'SlowLog'
ORDER BY create_time
LIMIT 1000, 10;
当 LIMIT 子句变成 “LIMIT 1000000,10” 时，只取10条记录为什么还是慢？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。
SELECT *
FROM operation
WHERE type = 'SQLStats'
AND name = 'SlowLog'
AND create_time > '2017-03-16 14:00:00'
ORDER BY create_time limit 10;
2.隐式转换
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'
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。
3.关联更新、删除
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);
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'
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
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。
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
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
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：
- 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
SELECT *
FROM (SELECT target,
Count(*)
FROM operation
GROUP BY target) t
WHERE target = 'rm-xxxx'
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
7.提前缩小范围
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。
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
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