我是这样做的:

select * 
from table_with_600k_rows
where rand() < 10/600000
limit 10

我喜欢它，因为它不需要其他表，写起来很简单，执行起来非常快。

我改进了@Riedsio的答案。这是我在一个有间隙的大型均匀分布表上能找到的最有效的查询(测试从一个有> 2.6B行的表中获得1000个随机行)。

(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max := (SELECT MAX(id) FROM table)) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
(SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1)

让我来解释一下发生了什么。

(SELECT MAX(id) FROM table) 我在计算并保存最大值。对于非常大的表，每次需要一行时计算MAX(id)都会有轻微的开销 SELECT FLOOR(rand() * @max) + 1 as rand) 获取一个随机id SELECT id FROM table INNER JOIN(… 这就填补了空白。基本上，如果你在间隙中随机选择一个数字，它就会选择下一个id。假设间隙是均匀分布的，这应该不是问题。

进行联合可以帮助您将所有内容放入一个查询中，从而避免进行多个查询。它还可以节省计算MAX(id)的开销。根据您的应用程序，这可能非常重要，也可能无关紧要。

注意，这只获取id，并以随机顺序获取它们。如果你想做更高级的事情，我建议你这样做:

SELECT t.id, t.name -- etc, etc
FROM table t
INNER JOIN (
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max := (SELECT MAX(id) FROM table)) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1) UNION
    (SELECT id FROM table INNER JOIN (SELECT FLOOR(RAND() * @max) + 1 as rand) r on id > rand LIMIT 1)
) x ON x.id = t.id
ORDER BY t.id

使用下面的简单查询从表中获取随机数据。

SELECT user_firstname ,
COUNT(DISTINCT usr_fk_id) cnt
FROM userdetails 
GROUP BY usr_fk_id 
ORDER BY cnt ASC  
LIMIT 10

SELECT
  * 
FROM
  table_with_600k_rows
WHERE
  RAND( ) 
ORDER BY
  id DESC 
LIMIT 30;

Id是主键，按Id排序， 解释table_with_600k_rows，发现该行不扫描整个表

以下内容应该是快速的，公正的，独立于id列的。但是，它不能保证返回的行数与请求的行数匹配。

SELECT *
FROM t
WHERE RAND() < (SELECT 10 / COUNT(*) FROM t)

解释:假设你想要100行中的10行，那么每一行都有1/10的概率被选中，这可以通过WHERE RAND() < 0.1来实现。这种方法不能保证有10行;但是如果查询运行了足够多的次数，那么每次执行的平均行数将在10左右，并且表中的每一行都将被均匀地选择。

我想这是最好的办法了。

SELECT id, id * RAND( ) AS random_no, first_name, last_name
FROM user
ORDER BY random_no