思路：先隨機排序然后再分組就好了。
1、創(chuàng)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、插入數(shù)據(jù)
INSERT INTO xdx_test VALUES (1, '張三-1','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, '張三-2','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, '張三-3','3');
INSERT INTO xdx_test VALUES (8, '李四-3','3');
INSERT INTO xdx_test VALUES (9, '王五-3','3');
3、查詢語句
SELECT * FROM
(SELECT * FROM xdx_test ORDER BY RAND()) a
GROUP BY a.class
4、查詢結(jié)果
3 王五-1 1
5 李四-2 2
9 王五-3 3
3 王五-1 1
4 張三-2 2
7 張三-3 3
2 李四-1 1
5 李四-2 2
8 李四-3 3
補充知識：mysql實現(xiàn)隨機獲取幾條數(shù)據(jù)的方法（效率和離散型比較）
sql語句有幾種寫法、效率、以及離散型 比較
1：SELECT * FROM tablename ORDER BY RAND() LIMIT 想要獲取的數(shù)據(jù)條數(shù)；
2：SELECT *FROM `table` WHERE id >= (SELECT FLOOR( MAX(id) * RAND()) FROM `table` ) ORDER BY id LIMIT 想要獲取的數(shù)據(jù)條數(shù);
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 想要獲取的數(shù)據(jù)條數(shù);
4：SELECT * FROM `table`WHERE id >= (SELECT floor(RAND() * (SELECT MAX(id) FROM `table`))) ORDER BY id LIMIT 想要獲取的數(shù)據(jù)條數(shù);
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 想要獲取的數(shù)據(jù)條數(shù);
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 想要獲取的數(shù)據(jù)條數(shù);
1的查詢時間>>2的查詢時間>>5的查詢時間>6的查詢時間>4的查詢時間>3的查詢時間，也就是3的效率最高。
以上6種只是單純的從效率上做了比較；
上面的6種隨機數(shù)抽取可分為2類：
第一個的離散型比較高，但是效率低；其他5個都效率比較高，但是存在離散性不高的問題；
怎么解決效率和離散型都滿足條件啦？
我們有一個思路就是： 寫一個存儲過程；
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
每次取出一條，然后循環(huán)寫入一張臨時表中；最后返回 select 臨時表就OK；
這樣既滿足了效率又解決了離散型的問題；可以兼并二者的優(yōu)點；
下面是具體存儲過程的偽代碼
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
-- 新建一張臨時表 ,存放隨機取出的數(shù)據(jù)
create temporary table if not exists xdr_authen_tmp (
`ID` bigint(20) NOT NULL AUTO_INCREMENT COMMENT '序號',
`LENGTH` int(5) DEFAULT NULL COMMENT '字節(jié)數(shù)',
`INTERFACE` int(3) NOT NULL COMMENT '接口',
`XDR_ID` varchar(32) NOT NULL COMMENT 'XDR ID',
`MSISDN` varchar(32) DEFAULT NULL COMMENT '用戶號碼',
`PROCEDURE_START_TIME` datetime NOT NULL DEFAULT '0000-00-00 00:00:00' COMMENT '開始時間',
`PROCEDURE_END_TIME` datetime DEFAULT NULL COMMENT '結(jié)束時間',
`SOURCE_NE_IP` varchar(39) DEFAULT NULL COMMENT '源網(wǎng)元IP',
`SOURCE_NE_PORT` int(5) DEFAULT NULL COMMENT '源網(wǎng)元端口',
`DESTINATION_NE_IP` varchar(39) DEFAULT NULL COMMENT '目的網(wǎng)元IP',
`DESTINATION_NE_PORT` int(5) DEFAULT NULL COMMENT '目的網(wǎng)元端口',
`INSERT_DATE` datetime DEFAULT NULL COMMENT '插入時間',
`EXTEND1` varchar(50) DEFAULT NULL COMMENT '擴展1',
`EXTEND2` varchar(50) DEFAULT NULL COMMENT '擴展2',
`EXTEND3` varchar(50) DEFAULT NULL COMMENT '擴展3',
`EXTEND4` varchar(50) DEFAULT NULL COMMENT '擴展4',
`EXTEND5` varchar(50) DEFAULT NULL COMMENT '擴展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;
-- 這里的checkNum是需要隨機獲取的數(shù)據(jù)數(shù)，比如隨機獲取10條，那這里就是10，通過while循環(huán)來逐個獲取單個隨機記錄；
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;
-- 這里獲取的記錄有可能會重復，如果是重復數(shù)據(jù)，我們則不往臨時表中插入此條數(shù)據(jù)，再進行下一次隨機數(shù)據(jù)的獲取。依次類推，直到隨機數(shù)據(jù)取夠為止；
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;
-- 最后我們將所有的隨機數(shù)查詢出來，以結(jié)果集的形式返回給后臺
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 ;
以上這篇MySql分組后隨機獲取每組一條數(shù)據(jù)的操作就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持腳本之家。
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