眾所周知,在MySQL中,如果直接 ORDER BY RAND() 的話,效率非常差,因為會多次執行。事實上,如果等值查詢也是用 RAND() 的話也如此,我們先來看看下面這幾個SQL的不同執行計劃和執行耗時。
首先,看下建表DDL,這是一個沒有顯式自增主鍵的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
往這個表裡灌入一些測試數據,至少10萬以上, id 字段也是亂序的。
[yejr@imysql]> select count(*) from t_innodb_random\G *************************** 1. row *************************** count(*): 393216
1、常量等值檢索:
[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)
可以看到執行計劃很不錯,是常量等值查詢,速度非常快。
2、使用RAND()函數乘以常量,求得隨機數後檢索:
[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)
可以看到執行計劃很糟糕,雖然是只掃描索引,但是做了全索引掃描,效率非常差。因為WHERE條件中包含了RAND(),使得MySQL把它當做變量來處理,無法用常量等值的方式查詢,效率很低。
我們把常量改成取t_innodb_random表的最大id值,再乘以RAND()求得隨機數後檢索看看什麼情況:
[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,執行計劃依然是全索引掃描,執行耗時也基本相當。
3、改造成普通子查詢模式 ,這裡有兩次子查詢
[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,執行計劃也不好,執行耗時較慢。
4、改造成JOIN關聯查詢,不過最大值還是用常量表示
[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)
這時候執行計劃就非常完美了,和最開始的常量等值查詢是一樣的了,執行耗時也非常之快。
這種方法雖然很好,但是有可能查詢不到記錄,改造范圍查找,但結果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,雖然執行計劃也是全索引掃描,但是因為有了LIMIT 1,只需要找到一條記錄,即可終止掃描,所以效率還是很快的。
小結:
從數據庫中隨機取一條記錄時,可以把RAND()生成隨機數放在JOIN子查詢中以提高效率。
5、再來看看用ORDRR BY RAND()方式一次取得多個隨機值的方式:
[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)
全索引掃描,生成排序臨時表,太差太慢了。
6、把隨機數放在子查詢裡看看:
[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,這個看起來還不賴:)
7、仿照上面的方法,改成JOIN和隨機數子查詢關聯
[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,全索引檢索,發現符合記錄的條件後,直接取得1000行,這個方法是最快的。
綜上,想從MySQL數據庫中隨機取一條或者N條記錄時,最好把RAND()生成隨機數放在JOIN子查詢中以提高效率。
上面說了那麼多的廢話,最後簡單說下,就是把下面這個SQL:
SELECT id FROM table ORDER BY RAND() LIMIT n;
改造成下面這個:
SELECT id FROM table t1 JOIN (SELECT RAND() * (SELECT MAX(id) FROM table) AS nid) t2 ON t1.id > t2.nid LIMIT n;
如果想要達到完全隨機,還可以改成下面這種寫法:
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中直接取得隨機數了,不用再在程序中構造一串隨機數去檢索了。