[MySQL优化案例]系列 — RAND()优化

众所周知,在MySQL中,如果直接 ORDER BY RAND() 的话,效率非常差,因为会多次执行。事实上,如果等值查询也是用 RAND() 的话也如此,我们先来看看下面这几个SQL的不同执行计划和执行耗时。
首先,看下建表DDL,这是一个没有显式自增主键的InnoDB表:

[yejr@imysql]> show create table t_innodb_random\G
*************************** 1. row ***************************
Table: t_innodb_random
Create Table: CREATE TABLE `t_innodb_random` (
`id` int(10) unsigned NOT NULL,
`user` varchar(64) NOT NULL DEFAULT '',
KEY `idx_id` (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1

往这个表里灌入一些测试数据,至少10万以上, id 字段也是乱序的。

[yejr@imysql]> select count(*) from t_innodb_random\G
*************************** 1. row ***************************
count(*): 393216

1、常量等值检索:

[yejr@imysql]> explain select id from t_innodb_random where id = 13412\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t_innodb_random
type: ref
possible_keys: idx_id
key: idx_id
key_len: 4
ref: const
rows: 1
Extra: Using index

[yejr@imysql]> select id from t_innodb_random where id = 13412;
1 row in set (0.00 sec)

可以看到执行计划很不错,是常量等值查询,速度非常快。

2、使用RAND()函数乘以常量,求得随机数后检索:

[yejr@imysql]> explain select id from t_innodb_random where id = round(rand()*13241324)\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using where; Using index

[yejr@imysql]> select id from t_innodb_random where id = round(rand()*13241324)\G
Empty set (0.26 sec)

可以看到执行计划很糟糕,虽然是只扫描索引,但是做了全索引扫描,效率非常差。因为WHERE条件中包含了RAND(),使得MySQL把它当做变量来处理,无法用常量等值的方式查询,效率很低。

我们把常量改成取t_innodb_random表的最大id值,再乘以RAND()求得随机数后检索看看什么情况:

[yejr@imysql]> explain select id from t_innodb_random where id = round(rand()*(select max(id) from t_innodb_random))\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using where; Using index
*************************** 2. row ***************************
id: 2
select_type: SUBQUERY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away

[yejr@imysql]> select id from t_innodb_random where id = round(rand()*(select max(id) from t_innodb_random))\G
Empty set (0.27 sec)

可以看到,执行计划依然是全索引扫描,执行耗时也基本相当。

3、改造成普通子查询模式 ,这里有两次子查询

[yejr@imysql]> explain select id from t_innodb_random where id = (select round(rand()*(select max(id) from t_innodb_random)) as nid)\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using where; Using index
*************************** 2. row ***************************
id: 3
select_type: SUBQUERY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away

[yejr@imysql]> select id from t_innodb_random where id = (select round(rand()*(select max(id) from t_innodb_random)) as nid)\G
Empty set (0.27 sec)

可以看到,执行计划也不好,执行耗时较慢。

4、改造成JOIN关联查询,不过最大值还是用常量表示

[yejr@imysql]> explain select id from t_innodb_random t1 join (select round(rand()*13241324) as id2) as t2 where t1.id = t2.id2\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: <derived2>
type: system
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1
Extra:
*************************** 2. row ***************************
id: 1
select_type: PRIMARY
table: t1
type: ref
possible_keys: idx_id
key: idx_id
key_len: 4
ref: const
rows: 1
Extra: Using where; Using index
*************************** 3. row ***************************
id: 2
select_type: DERIVED
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: No tables used

[yejr@imysql]> select id from t_innodb_random t1 join (select round(rand()*13241324) as id2) as t2 where t1.id = t2.id2\G
Empty set (0.00 sec)

这时候执行计划就非常完美了,和最开始的常量等值查询是一样的了,执行耗时也非常之快。
这种方法虽然很好,但是有可能查询不到记录,改造范围查找,但结果LIMIT 1就可以了:

[yejr@imysql]> explain select id from t_innodb_random where id > (select round(rand()*(select max(id) from t_innodb_random)) as nid) limit 1\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using where; Using index
*************************** 2. row ***************************
id: 3
select_type: SUBQUERY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away

[yejr@imysql]> select id from t_innodb_random where id > (select round(rand()*(select max(id) from t_innodb_random)) as nid) limit 1\G
*************************** 1. row ***************************
id: 1301
1 row in set (0.00 sec)

可以看到,虽然执行计划也是全索引扫描,但是因为有了LIMIT 1,只需要找到一条记录,即可终止扫描,所以效率还是很快的。

小结:
从数据库中随机取一条记录时,可以把RAND()生成随机数放在JOIN子查询中以提高效率。

5、再来看看用ORDRR BY RAND()方式一次取得多个随机值的方式:

[yejr@imysql]> explain select id from t_innodb_random order by rand() limit 1000\G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using index; Using temporary; Using filesort

[yejr@imysql]> select id from t_innodb_random order by rand() limit 1000;
1000 rows in set (0.41 sec)

全索引扫描,生成排序临时表,太差太慢了。

6、把随机数放在子查询里看看:

[yejr@imysql]> explain select id from t_innodb_random where id > (select rand() * (select max(id) from t_innodb_random) as nid) limit 1000\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: t_innodb_random
type: index
possible_keys: NULL
key: idx_id
key_len: 4
ref: NULL
rows: 393345
Extra: Using where; Using index
*************************** 2. row ***************************
id: 3
select_type: SUBQUERY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away

[yejr@imysql]> select id from t_innodb_random where id > (select rand() * (select max(id) from t_innodb_random) as nid) limit 1000\G
1000 rows in set (0.04 sec)

嗯,提速了不少,这个看起来还不赖:)

7、仿照上面的方法,改成JOIN和随机数子查询关联

[yejr@imysql]> explain select id from t_innodb_random t1 join (select rand() * (select max(id) from t_innodb_random) as nid) t2 on t1.id > t2.nid limit 1000\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: <derived2>
type: system
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: 1
Extra:
*************************** 2. row ***************************
id: 1
select_type: PRIMARY
table: t1
type: range
possible_keys: idx_id
key: idx_id
key_len: 4
ref: NULL
rows: 196672
Extra: Using where; Using index
*************************** 3. row ***************************
id: 2
select_type: DERIVED
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: No tables used
*************************** 4. row ***************************
id: 3
select_type: SUBQUERY
table: NULL
type: NULL
possible_keys: NULL
key: NULL
key_len: NULL
ref: NULL
rows: NULL
Extra: Select tables optimized away

[yejr@imysql]> select id from t_innodb_random t1 join (select rand() * (select max(id) from t_innodb_random) as nid) t2 on t1.id > t2.nid limit 1000\G
1000 rows in set (0.00 sec)

可以看到,全索引检索,发现符合记录的条件后,直接取得1000行,这个方法是最快的。

综上,想从MySQL数据库中随机取一条或者N条记录时,最好把RAND()生成随机数放在JOIN子查询中以提高效率。
上面说了那么多的废话,最后简单说下,就是把下面这个SQL:

SELECT id FROM table ORDER BY RAND() LIMIT n;

改造成下面这个:

SELECT id FROM table t1 JOIN (SELECT RAND() * (SELECT MAX(id) FROM table) AS nid) t2 ON t1.id > t2.nid LIMIT n;

就可以享受在SQL中直接取得随机数了,不用再在程序中构造一串随机数去检索了。

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