声明：感谢laserhe, denniswwh，ACMAIN_CHM，vinsonshen 的热心帮助
首先说明该条sql的功能是查询集合a不在集合b的数据。
not in的写法
select add_tb.RUID
from (select distinct RUID
from UserMsg
where SubjectID =12
and CreateTime>'2009-8-14 15:30:00'
and CreateTime<='2009-8-17 16:00:00'
) add_tb
where add_tb.RUID
not in (select distinct RUID
from UserMsg
where SubjectID =12
and CreateTime<'2009-8-14 15:30:00'
)
返回444行记录用时 0.07sec
explain 结果
+----+--------------------+------------+----------------+---------------------------+------------+---------+------+------+--
----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows |
Extra |
+----+--------------------+------------+----------------+---------------------------+------------+---------+------+------+--
----------------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 452 |
Using where |
| 3 | DEPENDENT SUBQUERY | UserMsg | index_subquery | RUID,SubjectID,CreateTime | RUID | 96 | func | 2 |
Using index; Using where |
| 2 | DERIVED | UserMsg | range | SubjectID,CreateTime | CreateTime | 9 | NULL | 1857 |
Using where; Using temporary |
+----+--------------------+------------+----------------+---------------------------+------------+---------+------+------+--
----------------------------+
分析:该条查询速度快原因为id=2的sql查询出来的结果比较少，所以id=1sql所以运行速度比较快，id=2的使用了临时表，不知道这个时候是否使用索引？
其中一种left join
select a.ruid,b.ruid
from(select distinct RUID
from UserMsg
where SubjectID =12
and CreateTime >= '2009-8-14 15:30:00'
and CreateTime<='2009-8-17 16:00:00'
) a left join (
select distinct RUID
from UserMsg
where SubjectID =12 and CreateTime< '2009-8-14 15:30:00'
) b on a.ruid = b.ruid
where b.ruid is null
返回444行记录用时 0.39sec
explain 结果
+----+-------------+------------+-------+----------------------+------------+---------+------+------+-----------------------
-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+-------------+------------+-------+----------------------+------------+---------+------+------+-----------------------
-------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 452 |
|
| 1 | PRIMARY | <derived3> | ALL | NULL | NULL | NULL | NULL | 1112 | Using where; Not exists
|
| 3 | DERIVED | UserMsg | ref | SubjectID,CreateTime | SubjectID | 5 | | 6667 | Using where; Using
temporary |
| 2 | DERIVED | UserMsg | range | SubjectID,CreateTime | CreateTime | 9 | NULL | 1838 | Using where; Using
temporary |
+----+-------------+------------+-------+----------------------+------------+---------+------+------+-----------------------
-------+
分析:使用了两个临时表，并且两个临时表做了笛卡尔积，导致不能使用索引并且数据量很大
另外一种left join
select distinct a.RUID
from UserMsg a
left join UserMsg b
on a.ruid = b.ruid
and b.subjectID =12 and b.createTime < '2009-8-14 15:30:00'
where a.subjectID =12
and a.createTime >= '2009-8-14 15:30:00'
and a.createtime <='2009-8-17 16:00:00'
and b.ruid is null;
返回444行记录用时 0.07sec
explain 结果
+----+-------------+-------+-------+---------------------------+------------+---------+--------------+------+---------------
--------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+-------------+-------+-------+---------------------------+------------+---------+--------------+------+---------------
--------------------+
| 1 | SIMPLE | a | range | SubjectID,CreateTime | CreateTime | 9 | NULL | 1839 | Using where;
Using temporary |
| 1 | SIMPLE | b | ref | RUID,SubjectID,CreateTime | RUID | 96 | dream.a.RUID | 2 | Using where;
Not exists; Distinct |
+----+-------------+-------+-------+---------------------------+------------+---------+--------------+------+---------------
--------------------+
分析：两次查询都是用上了索引，并且查询时同时进行的，所以查询效率应该很高
使用not exists的sql
select distinct a.ruid
from UserMsg a
where a.subjectID =12
and a.createTime >= '2009-8-14 15:30:00'
and a.createTime <='2009-8-17 16:00:00'
and not exists (
select distinct RUID
from UserMsg
where subjectID =12 and createTime < '2009-8-14 15:30:00'
and ruid=a.ruid
)
返回444行记录用时 0.08sec
explain 结果
+----+--------------------+---------+-------+---------------------------+------------+---------+--------------+------+------
------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+--------------------+---------+-------+---------------------------+------------+---------+--------------+------+------
------------------------+
| 1 | PRIMARY | a | range | SubjectID,CreateTime | CreateTime | 9 | NULL | 1839 | Using
where; Using temporary |
| 2 | DEPENDENT SUBQUERY | UserMsg | ref | RUID,SubjectID,CreateTime | RUID | 96 | dream.a.RUID | 2 | Using
where |
+----+--------------------+---------+-------+---------------------------+------------+---------+--------------+------+------
------------------------+
分析：同上基本上是一样的，只是分解了2个查询顺序执行，查询效率低于第3个
为了验证数据查询效率，将上述查询中的subjectID =12的限制条件去掉，结果统计查询时间如下
0.20s
21.31s
0.25s
0.43s
laserhe帮忙分析问题总结
select a.ruid,b.ruid
from( select distinct RUID
from UserMsg
where CreateTime >= '2009-8-14 15:30:00'
and CreateTime<='2009-8-17 16:00:00'
) a left join UserMsg b
on a.ruid = b.ruid
and b.createTime < '2009-8-14 15:30:00'
where b.ruid is null;
执行时间0.13s
+----+-------------+------------+-------+-----------------+------------+---------+--------+------+--------------------------
----+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+-------------+------------+-------+-----------------+------------+---------+--------+------+--------------------------
----+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 1248 |
|
| 1 | PRIMARY | b | ref | RUID,CreateTime | RUID | 96 | a.RUID | 2 | Using where; Not exists
|
| 2 | DERIVED | UserMsg | range | CreateTime | CreateTime | 9 | NULL | 3553 | Using where; Using
temporary |
+----+-------------+------------+-------+-----------------+------------+---------+--------+------+--------------------------
----+
执行效率类似与not in的效率
数据库优化的基本原则：让笛卡尔积发生在尽可能小的集合之间，mysql在join的时候可以直接通过索引来扫描，而嵌入到子查询里头，查询规
划器就不晓得用合适的索引了。
一个SQL在数据库里是这么优化的：首先SQL会分析成一堆分析树，一个树状数据结构，然后在这个数据结构里，查询规划器会查找有没有合适
的索引，然后根据具体情况做一个排列组合，然后计算这个排列组合中的每一种的开销（类似explain的输出的计算机可读版本），然后比较里
面开销最小的，选取并执行之。那么：
explain select a.ruid,b.ruid from(select distinct RUID from UserMsg where CreateTime >= '2009-8-14 15:30:00'
and CreateTime<='2009-8-17 16:00:00' ) a left join UserMsg b on a.ruid = b.ruid and b.createTime < '2009-8-14 15:30:00'
where b.ruid is null;
和
explain select add_tb.RUID
-> from (select distinct RUID
-> from UserMsg
-> where CreateTime>'2009-8-14 15:30:00'
-> and CreateTime<='2009-8-17 16:00:00'
-> ) add_tb
-> where add_tb.RUID
-> not in (select distinct RUID
-> from UserMsg
-> where CreateTime<'2009-8-14 15:30:00'
-> );
explain
+----+--------------------+------------+----------------+-----------------+------------+---------+------+------+------------
------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+--------------------+------------+----------------+-----------------+------------+---------+------+------+------------
------------------+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 1248 | Using where
|
| 3 | DEPENDENT SUBQUERY | UserMsg | index_subquery | RUID,CreateTime | RUID | 96 | func | 2 | Using index;
Using where |
| 2 | DERIVED | UserMsg | range | CreateTime | CreateTime | 9 | NULL | 3509 | Using where;
Using temporary |
+----+--------------------+------------+----------------+-----------------+------------+---------+------+------+------------
------------------+
开销是完全一样的，开销可以从 rows 那个字段得出（基本上是rows那个字段各个行的数值的乘积，也就是笛卡尔积）
但是呢：下面这个：
explain select a.ruid,b.ruid from(select distinct RUID from UserMsg where CreateTime >= '2009-8-14 15:30:00'
and CreateTime<='2009-8-17 16:00:00' ) a left join ( select distinct RUID from UserMsg where createTime < '2009-8-14
15:30:00' ) b on a.ruid = b.ruid where b.ruid is null;
执行时间21.31s
+----+-------------+------------+-------+---------------+------------+---------+------+-------+-----------------------------
-+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra
|
+----+-------------+------------+-------+---------------+------------+---------+------+-------+-----------------------------
-+
| 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 1248 |
|
| 1 | PRIMARY | <derived3> | ALL | NULL | NULL | NULL | NULL | 30308 | Using where; Not exists
|
| 3 | DERIVED | UserMsg | ALL | CreateTime | NULL | NULL | NULL | 69366 | Using where; Using temporary
|
| 2 | DERIVED | UserMsg | range | CreateTime | CreateTime | 9 | NULL | 3510 | Using where; Using temporary
|
+----+-------------+------------+-------+---------------+------------+---------+------+-------+-----------------------------
-+
我就有些不明白
为何是四行
并且中间两行巨大无比
按理说
查询规划器应该能把这个查询优化得跟前面的两个一样的
（至少在我熟悉的pgsql数据库里我有信心是一样的）
但mysql里头不是
所以我感觉查询规划器里头可能还是糙了点
我前面说过优化的基本原则就是，让笛卡尔积发生在尽可能小的集合之间
那么上面最后一种写法至少没有违反这个原则
虽然b 表因为符合条件的非常多，基本上不会用索引
但是并不应该妨碍查询优化器看到外面的join on条件，从而和前面两个SQL一样，选取主键进行join
不过我前面说过查询规划器的作用
理论上来讲
遍历一遍所有可能，计算一下开销
是合理的
我感觉这里最后一种写法没有遍历完整所有可能
可能的原因是子查询的实现还是比较简单？
子查询对数据库的确是个挑战
因为基本都是递归的东西
所以在这个环节有点毛病并不奇怪
其实你仔细想想，最后一种写法无非是我们第一种写法的一个变种，关键在表b的where 条件放在哪里
放在里面，就不会用索引去join
放在外面就会
这个本身就是排列组合的一个可能