mysql實現隨機獲取幾條數據的方法(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 想要獲取的數據條數;

2:SELECT *FROM `table` WHERE id >= (SELECT FLOOR( MAX(id) * RAND()) FROM `table` ) ORDER BY id LIMIT 想要獲取的數據條數;

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 想要獲取的數據條數;

4:SELECT * FROM `table`WHERE id >= (SELECT floor(RAND() * (SELECT MAX(id) FROM `table`))) ORDER BY id LIMIT 想要獲取的數據條數;

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 想要獲取的數據條數;

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 想要獲取的數據條數;

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種隨機數抽取可分爲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;

怎麼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,然後循環寫入一張臨時表中;最後返回  select 臨時表就OK;

這樣既滿足了效率又解決了離散型的問題;可以兼併二者的優點;

下面是具體存儲過程的僞代碼

 

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 ,存放隨機取出的數據 
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 '字節數',
  `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 '結束時間',
  `SOURCE_NE_IP` varchar(39) DEFAULT NULL COMMENT '源網元IP',
  `SOURCE_NE_PORT` int(5) DEFAULT NULL COMMENT '源網元端口',
  `DESTINATION_NE_IP` varchar(39) DEFAULT NULL COMMENT '目的網元IP',
  `DESTINATION_NE_PORT` int(5) DEFAULT NULL COMMENT '目的網元端口',
  `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;
   -- 這裏的checkNum是需要隨機獲取的數據數,比如隨機獲取10條,那這裏就是10,通過while循環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;
     -- 這裏獲取的記錄有可能會重複,如果是重複數據,我們則不往臨時表中插入此條數據,再進行下一次隨機數據的獲取。依次類推,直到隨機數據取夠爲止;
    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;  
 -- 最後我們將所有的隨機數查詢出來,以結果集的形式返回給後臺
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 ;

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