MySql分组后随机获取每组一条数据的操作

作者:小道仙 时间:2024-01-26 21:12:11 

思路:先随机排序然后再分组就好了。

1、创建表:


CREATE TABLE `xdx_test` (
`id` int(11) NOT NULL,
`name` varchar(255) DEFAULT NULL,
`class` varchar(255) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

2、插入数据


INSERT INTO xdx_test VALUES (1, '张三-1','1');
INSERT INTO xdx_test VALUES (2, '李四-1','1');
INSERT INTO xdx_test VALUES (3, '王五-1','1');
INSERT INTO xdx_test VALUES (4, '张三-2','2');
INSERT INTO xdx_test VALUES (5, '李四-2','2');
INSERT INTO xdx_test VALUES (6, '王五-2','2');
INSERT INTO xdx_test VALUES (7, '张三-3','3');
INSERT INTO xdx_test VALUES (8, '李四-3','3');
INSERT INTO xdx_test VALUES (9, '王五-3','3');

3、查询语句


SELECT * FROM
(SELECT * FROM xdx_test ORDER BY RAND()) a
GROUP BY a.class

4、查询结果

3 王五-1 1

5 李四-2 2

9 王五-3 3

3 王五-1 1

4 张三-2 2

7 张三-3 3

2 李四-1 1

5 李四-2 2

8 李四-3 3

补充知识:mysql实现随机获取几条数据的方法(效率和离散型比较)

sql语句有几种写法、效率、以及离散型 比较

1:SELECT * FROM tablename ORDER BY RAND() LIMIT 想要获取的数据条数;

2:SELECT *FROM `table` WHERE id >= (SELECT FLOOR( MAX(id) * RAND()) FROM `table` ) ORDER BY id LIMIT 想要获取的数据条数;

3:SELECT * FROM `table` AS t1 JOIN (SELECT ROUND(RAND() * (SELECT MAX(id) FROM `table`)) AS id) AS t2 WHERE t1.id >= t2.id

ORDER BY t1.id ASC LIMIT 想要获取的数据条数;

4:SELECT * FROM `table`WHERE id >= (SELECT floor(RAND() * (SELECT MAX(id) FROM `table`))) ORDER BY id LIMIT 想要获取的数据条数;

5:SELECT * FROM `table` WHERE id >= (SELECT floor( RAND() * ((SELECT MAX(id) FROM `table`)-(SELECT MIN(id) FROM `table`)) + (SELECT MIN(id) FROM `table`))) ORDER BY id LIMIT 想要获取的数据条数;

6:SELECT * FROM `table` AS t1 JOIN (SELECT ROUND(RAND() * ((SELECT MAX(id) FROM `table`)-(SELECT MIN(id) FROM `table`))+(SELECT MIN(id) FROM `table`)) AS id) AS t2 WHERE t1.id >= t2.id ORDER BY t1.id LIMIT 想要获取的数据条数;

1的查询时间>>2的查询时间>>5的查询时间>6的查询时间>4的查询时间>3的查询时间,也就是3的效率最高。

以上6种只是单纯的从效率上做了比较;

上面的6种随机数抽取可分为2类:

第一个的离散型比较高,但是效率低;其他5个都效率比较高,但是存在离散性不高的问题;

怎么解决效率和离散型都满足条件啦?

我们有一个思路就是: 写一个存储过程;

select * FROM test t1 JOIN (SELECT ROUND(RAND() * ((SELECT MAX(id) FROM test)-(SELECT MIN(id) FROM test)) + (SELECT MIN(id) FROM test)) AS id) t2 where t1.id >= t2.id limit 1

每次取出一条,然后循环写入一张临时表中;最后返回 select 临时表就OK;

这样既满足了效率又解决了离散型的问题;可以兼并二者的优点;

下面是具体存储过程的伪代码


DROP PROCEDURE IF EXISTS `evaluate_Check_procedure`;
DELIMITER ;;
CREATE DEFINER=`root`@`%` PROCEDURE `evaluate_Check_procedure`(IN startTime datetime, IN endTime datetime,IN checkNum INT,IN evaInterface VARCHAR(36))
BEGIN

-- 新建一张临时表 ,存放随机取出的数据


create temporary table if not exists xdr_authen_tmp (
`ID` bigint(20) NOT NULL AUTO_INCREMENT COMMENT '序号',
`LENGTH` int(5) DEFAULT NULL COMMENT '字节数',
`INTERFACE` int(3) NOT NULL COMMENT '接口',
`XDR_ID` varchar(32) NOT NULL COMMENT 'XDR ID',
`MSISDN` varchar(32) DEFAULT NULL COMMENT '用户号码',
`PROCEDURE_START_TIME` datetime NOT NULL DEFAULT '0000-00-00 00:00:00' COMMENT '开始时间',
`PROCEDURE_END_TIME` datetime DEFAULT NULL COMMENT '结束时间',
`SOURCE_NE_IP` varchar(39) DEFAULT NULL COMMENT '源网元IP',
`SOURCE_NE_PORT` int(5) DEFAULT NULL COMMENT '源网元端口',
`DESTINATION_NE_IP` varchar(39) DEFAULT NULL COMMENT '目的网元IP',
`DESTINATION_NE_PORT` int(5) DEFAULT NULL COMMENT '目的网元端口',
`INSERT_DATE` datetime DEFAULT NULL COMMENT '插入时间',
`EXTEND1` varchar(50) DEFAULT NULL COMMENT '扩展1',
`EXTEND2` varchar(50) DEFAULT NULL COMMENT '扩展2',
`EXTEND3` varchar(50) DEFAULT NULL COMMENT '扩展3',
`EXTEND4` varchar(50) DEFAULT NULL COMMENT '扩展4',
`EXTEND5` varchar(50) DEFAULT NULL COMMENT '扩展5',
PRIMARY KEY (`ID`,`PROCEDURE_START_TIME`),
KEY `index_procedure_start_time` (`PROCEDURE_START_TIME`),
KEY `index_source_dest_ip` (`SOURCE_NE_IP`,`DESTINATION_NE_IP`),
KEY `index_xdr_id` (`XDR_ID`)
) ENGINE = InnoDB DEFAULT CHARSET=utf8;

BEGIN
DECLARE j INT;
DECLARE i INT;

DECLARE CONTINUE HANDLER FOR NOT FOUND SET i = 1;

-- 这里的checkNum是需要随机获取的数据数,比如随机获取10条,那这里就是10,通过while循环来逐个获取单个随机记录;


SET j = 0;
WHILE j < checkNum DO
set @sqlexi = concat( ' SELECT t1.ID,t1.LENGTH,t1.LOCAL_PROVINCE,t1.LOCAL_CITY,t1.OWNER_PROVINCE,t1.OWNER_CITY,t1.ROAMING_TYPE,t1.INTERFACE,t1.XDR_ID,t1.RAT,t1.IMSI,t1.IMEI,t1.MSISDN,t1.PROCEDURE_START_TIME,t1.PROCEDURE_END_TIME,t1.TRANSACTION_TYPE,t1.TRANSACTION_STATUS,t1.SOURCE_NE_IP,t1.SOURCE_NE_PORT,t1.DESTINATION_NE_IP,t1.DESTINATION_NE_PORT,t1.RESULT_CODE,t1.EXPERIMENTAL_RESULT_CODE,t1.ORIGIN_REALM,t1.DESTINATION_REALM,t1.ORIGIN_HOST,t1.DESTINATION_HOST,t1.INSERT_DATE',
   ' into @ID,@LENGTH,@LOCAL_PROVINCE,@LOCAL_CITY,@OWNER_PROVINCE,@OWNER_CITY,@ROAMING_TYPE,@INTERFACE,@XDR_ID,@RAT,@IMSI,@IMEI,@MSISDN,@PROCEDURE_START_TIME,@PROCEDURE_END_TIME,@TRANSACTION_TYPE,@TRANSACTION_STATUS,@SOURCE_NE_IP,@SOURCE_NE_PORT,@DESTINATION_NE_IP,@DESTINATION_NE_PORT,@RESULT_CODE,@EXPERIMENTAL_RESULT_CODE,@ORIGIN_REALM,@DESTINATION_REALM,@ORIGIN_HOST,@DESTINATION_HOST,@INSERT_DATE ',
   ' FROM xdr_authen t1 JOIN (SELECT ROUND(RAND() * ((SELECT MAX(id) FROM xdr_authen)-(SELECT MIN(id) FROM xdr_authen)) + (SELECT MIN(id) FROM xdr_authen)) AS id) t2',
   ' WHERE t1.PROCEDURE_START_TIME >= "',startTime,'"',
      ' AND t1.PROCEDURE_START_TIME < "',endTime,'"',' AND t1.INTERFACE IN (',evaInterface,')',
      ' and t1.id >= t2.id limit 1');
PREPARE sqlexi FROM @sqlexi;
EXECUTE sqlexi;
DEALLOCATE PREPARE sqlexi;

-- 这里获取的记录有可能会重复,如果是重复数据,我们则不往临时表中插入此条数据,再进行下一次随机数据的获取。依次类推,直到随机数据取够为止;


select count(1) into @num from xdr_authen_tmp where id = @ID;

if @num > 0 or i=1 then
 SET j = j;
ELSE
 insert into xdr_authen_tmp(ID,LENGTH,LOCAL_PROVINCE,LOCAL_CITY,OWNER_PROVINCE,OWNER_CITY,ROAMING_TYPE,INTERFACE,XDR_ID,RAT,IMSI,IMEI,MSISDN,PROCEDURE_START_TIME,PROCEDURE_END_TIME,TRANSACTION_TYPE,TRANSACTION_STATUS,SOURCE_NE_IP,SOURCE_NE_PORT,DESTINATION_NE_IP,DESTINATION_NE_PORT,RESULT_CODE,EXPERIMENTAL_RESULT_CODE,ORIGIN_REALM,DESTINATION_REALM,ORIGIN_HOST,DESTINATION_HOST,INSERT_DATE)
 VALUES(@ID,@LENGTH,@LOCAL_PROVINCE,@LOCAL_CITY,@OWNER_PROVINCE,@OWNER_CITY,@ROAMING_TYPE,@INTERFACE,@XDR_ID,@RAT,@IMSI,@IMEI,@MSISDN,@PROCEDURE_START_TIME,@PROCEDURE_END_TIME,@TRANSACTION_TYPE,@TRANSACTION_STATUS,@SOURCE_NE_IP,@SOURCE_NE_PORT,@DESTINATION_NE_IP,@DESTINATION_NE_PORT,@RESULT_CODE,@EXPERIMENTAL_RESULT_CODE,@ORIGIN_REALM,@DESTINATION_REALM,@ORIGIN_HOST,@DESTINATION_HOST,@INSERT_DATE);

SET j = j + 1;
end if;
SET i=0;

END WHILE;

-- 最后我们将所有的随机数查询出来,以结果集的形式返回给后台


select ID,LENGTH,LOCAL_PROVINCE,LOCAL_CITY,OWNER_PROVINCE,OWNER_CITY,ROAMING_TYPE,INTERFACE,XDR_ID,RAT,IMSI,IMEI,MSISDN,PROCEDURE_START_TIME,PROCEDURE_END_TIME,TRANSACTION_TYPE,TRANSACTION_STATUS,SOURCE_NE_IP,SOURCE_NE_PORT,DESTINATION_NE_IP,DESTINATION_NE_PORT,RESULT_CODE,EXPERIMENTAL_RESULT_CODE,ORIGIN_REALM,DESTINATION_REALM,ORIGIN_HOST,DESTINATION_HOST,INSERT_DATE from xdr_authen_tmp;

END;
truncate TABLE xdr_authen_tmp;

END
;;
DELIMITER ;

来源:https://blog.csdn.net/Tomwildboar/article/details/107191107

标签:MySql,分组,随机,数据
0
投稿

猜你喜欢

  • python实现QQ定时发送新年祝福信息

    2023-12-19 08:11:59
  • 基于JS实现简单的样式切换效果代码

    2024-04-22 13:08:53
  • python编程进阶之异常处理用法实例分析

    2023-01-27 16:39:24
  • Python使用pyenv实现多环境管理

    2022-10-23 00:18:23
  • pyqt5实现绘制ui,列表窗口,滚动窗口显示图片的方法

    2023-03-22 16:52:56
  • php计算两个整数的最大公约数常用算法小结

    2023-11-20 00:29:01
  • Python运用于数据分析的简单教程

    2023-08-14 07:49:13
  • AJAX缓存的问题解决办法

    2009-04-26 14:47:00
  • Python 异之如何同时运行多个协程详解

    2023-11-27 12:47:23
  • Go语言Http Server框架实现一个简单的httpServer

    2024-02-19 11:04:33
  • Pycharm使用时会出现的问题之cv2无法安装解决

    2022-12-26 06:24:49
  • 在SQL触发器或存储过程中获取在程序登录的用户

    2012-01-29 18:01:32
  • PyCharm 设置数据库,查询数据库语句方式

    2024-01-19 22:05:07
  • python3实现163邮箱SMTP发送邮件

    2021-02-28 07:59:19
  • Access的特点及其概念问答

    2009-09-10 19:00:00
  • JavaScript 经典实例日常收集整理(常用经典)

    2023-09-15 07:40:56
  • OpenCV每日函数之BarcodeDetector类条码检测器

    2023-03-28 02:22:39
  • 模型训练时GPU利用率太低的原因及解决

    2021-02-05 22:22:07
  • python中doctest库实例用法

    2022-07-22 16:52:30
  • Python pip安装第三方库的攻略分享

    2023-02-15 07:53:26
  • asp之家 网络编程 m.aspxhome.com