MySQL下的RAND()优化案例分析
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;
如果想要达到完全随机,还可以改成下面这种写法:
SELECT id FROM table t1 JOIN (SELECT round(RAND() * (SELECT MAX(id) FROM table)) AS nid FROM table LIMIT n) t2 ON t1.id = t2.nid;
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。