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mysql的rand函数可以生成一个0到1之间的随机数,进行一定的放大即可得到一个随机数。再通过条件查询来限制新随机数没有在表中出现过。如下所示:
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SELECT FLOOR(RAND() * 99999) AS random_numFROM numbers
WHERE "random_num" NOT IN (SELECT my_number FROM numbers)
LIMIT 1
MYSQL 取随机数
2010年04月26日 星期一 09:48
mysql 取随机数
--对一个表取任意随机数
SELECT *
FROM TMP_XF_TEST
WHERE ID = (SELECT FLOOR(RAND() * (SELECT MAX(ID) FROM TMP_XF_TEST)))
order by id LIMIT 1;
--有条件性的取随机数
SELECT *
FROM TMP_XF_TEST
WHERE ID = (SELECT FLOOR(RAND() *
((SELECT MAX(ID) FROM TMP_XF_TEST WHERE GID = 9) -
(SELECT MIN(ID) FROM TMP_XF_TEST WHERE GID = 9))) +
(SELECT MIN(ID) FROM TMP_XF_TEST WHERE GID = 9))
AND GID = 9
ORDER BY ID LIMIT 1;
--gid上存在索引
或者
SELECT *
FROM TMP_XF_TEST AS t1 JOIN
(SELECT ROUND(RAND() * ((SELECT MAX(id) FROM TMP_XF_TEST WHERE GID = 9)-(SELECT MIN(id) FROM TMP_XF_TEST WHERE GID = 9))
+(SELECT MIN(id) FROM TMP_XF_TEST WHERE GID = 9)) AS id) AS t2
WHERE t1.id = t2.id AND t1.GID = 9
ORDER BY t1.id LIMIT 1;
#########
不要用下面的杯具写法
mysql insert into tmp_xf_test(user_nick,gid,item_id,gmt_create,gmt_modified,memo)
- select user_nick,gid,item_id,gmt_create,gmt_modified,memo from tmp_xf_test;
Query OK, 165888 rows affected (9.65 sec)
Records: 165888 Duplicates: 0 Warnings: 0
mysql SELECT *
- FROM `tmp_xf_test`
- WHERE id = (SELECT FLOOR( MAX(id) * RAND()) FROM `tmp_xf_test` )
- ORDER BY id LIMIT 1;
+-----+-----------+-----+---------+---------------------+---------------------+--------------------+
| id | user_nick | gid | item_id | gmt_create | gmt_modified | memo |
+-----+-----------+-----+---------+---------------------+---------------------+--------------------+
| 467 | 玄风 | 9 | 123 | 2010-04-26 14:56:39 | 2010-04-26 14:56:39 | 玄风测试使用的数据 |
+-----+-----------+-----+---------+---------------------+---------------------+--------------------+
1 row in set (51.12 sec)
mysql explain SELECT *
- FROM `tmp_xf_test`
- WHERE id = (SELECT FLOOR( MAX(id) * RAND()) FROM `tmp_xf_test` )
- ORDER BY id LIMIT 1\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: tmp_xf_test
type: index
possible_keys: NULL
key: PRIMARY
key_len: 8
ref: NULL
rows: 1
Extra: Using where
*************************** 2. row ***************************
id: 2
select_type: UNCACHEABLE SUBQUERY
table: tmp_xf_test
type: index
possible_keys: NULL
key: idx_tmp_xf_test_gid
key_len: 4
ref: NULL
rows: 331954
Extra: Using index
2 rows in set (0.01 sec)
---
mysql SELECT * FROM `tmp_xf_test` t1 join
- (SELECT FLOOR( MAX(id) * RAND()) as id FROM `tmp_xf_test` ) as t2
- where t1.id =t2.id
- ORDER BY t1.id LIMIT 1;
+-------+-----------+-----+---------+---------------------+---------------------+--------------------+-------+
| id | user_nick | gid | item_id | gmt_create | gmt_modified | memo | id |
+-------+-----------+-----+---------+---------------------+---------------------+--------------------+-------+
| 40311 | 玄风 | 9 | 123 | 2010-04-28 15:47:19 | 2010-04-28 15:47:19 | 玄风测试使用的数据 | 40311 |
+-------+-----------+-----+---------+---------------------+---------------------+--------------------+-------+
1 row in set (0.14 sec)
##############
mysql SELECT * FROM `tmp_xf_test`
- WHERE id = (SELECT floor(RAND() * (SELECT MAX(id) FROM `tmp_xf_test`)))
- ORDER BY id LIMIT 1;
+------+-----------+-----+---------+---------------------+---------------------+--------------------+
| id | user_nick | gid | item_id | gmt_create | gmt_modified | memo |
+------+-----------+-----+---------+---------------------+---------------------+--------------------+
| 1352 | 玄风 | 9 | 123 | 2010-04-28 15:47:19 | 2010-04-28 15:47:19 | 玄风测试使用的数据 |
+------+-----------+-----+---------+---------------------+---------------------+--------------------+
1 row in set (0.00 sec)
mysql explain SELECT * FROM `tmp_xf_test`
- WHERE id = (SELECT floor(RAND() * (SELECT MAX(id) FROM `tmp_xf_test`)))
- ORDER BY id LIMIT 1\G
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: tmp_xf_test
type: index
possible_keys: NULL
key: PRIMARY
key_len: 8
ref: NULL
rows: 1
Extra: Using where
*************************** 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
2 rows in set, 1 warning (0.00 sec)
对应的另外一种杯具写法是:
SELECT *
FROM TMP_XF_TEST
WHERE ID = (SELECT FLOOR(RAND() * (MAX(ID) - MIN(ID))) + MIN(ID) MID
FROM TMP_XF_TEST
WHERE GID = 9)
AND GID = 9 LIMIT 1;
随机不能保证不重复,银行卡号不是随机生成,
随机取过值后要自己判断是否重复,重复了再取,再判断,
如果要取的值的位数都一样的话,告诉你个简单的方法,
比如取3位随机整数mt_rand(100,999);
不用循环着一位一位的取
给你提供一个思路你看是否可行;
1.随机数不用MYSQL生成,用程序(如PHP)生成,范围在ID的最大和最小之间;
2.根据生成的随机数去数据库直接查询,如果没有就重复一次操作;
从mysql数据库表中随机获取数据
其实,从数据库随机获取数据,很简单,只须用到一个rand()函数;
select * from table_name order by rand() limit 0,5;
下面是一个小实例:
从文章表中随机获取5条数据。
$dblink=mysql_connect("localhost","root","123456");
mysql_query("set names utf8");
mysql_select_db("aixuexi");
$sql="select * from waxx_article order by rand() limit 0,5";
$rs=mysql_query($sql);
while($row=mysql_fetch_array($rs)){
$rows[]=$row;
}
if($rows){
foreach($rows as $v){
?
div style="width:350px;height:35px;line-height:35px;border:1px solid #ccc;"?php echo $v['title']; ?/div
?php
}
}else{
echo "暂无文章";
}
MySql数据库随机函授Rand()可以产生0~1之间带小数的随机数,只要将括号中的参数留空,所产生的数是完全随机的,出现重复的几率不大,但是不可避免会有重复的可能,如果需要完全避免重复,可以先用随机函数产生一堆数字,然后用剔除其中的重复数这个办法来实现。
例如先用循环产生一批随机数并存入数据表中,再用
select distinct colName from tableName;
选出无重复的随机数予以应用