关于shell调用MySQL存储过程的问题

前天收到一个任务，要统计每天ETL的运行情况，感觉每天从给的SQL语句一个一个的查询影响效率。

就行用写一个存储过程来实现，然后通过shell调用这个存储过程来自动跑数据，写到相应的文件里~

思路就是这样，废话不说，上一下写好的代码。

DELIMITER // 
create procedure sp_etl_info_day (in statis_date int)
begin
declare num_day int default 0;
declare num_month int default 0;
declare num_hour int default 0;
declare num_total int default 0;
declare num_add_lastday int default 0;
declare num_schedule_run int default 0;
declare num_run int default 0;
declare num_succeed int default 0;
declare num_failed int default 0;
declare num_failed1 int default 0;
declare num_killed int default 0;
declare num_waited int default 0;
declare num_norun int default 0;
declare num_man_run int default 0;
declare num_norun_lastday int default 0;
declare rate_wz_etl FLOAT default 0;
declare rate_js_etl FLOAT default 0;
select count(*) into num_day from schedule where isOnline=1 and scheduleOption like "%1#day%";
select count(*) into num_month from schedule where isOnline=1 and scheduleOption like "%1#month%";
select count(*) into num_hour from schedule where isOnline=1 and scheduleOption like "%1#hour%";
set num_total=num_day+num_month+num_hour;
select count(distinct scheduleId) into num_schedule_run from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1);
select count(*) into num_run from (select count(*) as count, scheduleId,period from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) group by scheduleId) a;
select count(*) into num_failed from (select count(*) as count, scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Failed" group by scheduleId) a where a.scheduleId not in (select scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Succeed" group by scheduleId);
select count(*) into num_killed from (select count(*) as count, scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Killed" group by scheduleId) a where a.scheduleId not in (select scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Succeed" group by scheduleId);
set num_succeed=num_run-num_failed-num_killed;
set rate_wz_etl=round(num_succeed/num_run,4);
set num_failed1=num_failed+num_killed;
select CONCAT("日：",num_day,"个",",月：",num_month,"个",",小时：",num_hour,"个",",计划运行控制流",num_schedule_run,"个",",共",num_total,"个"
,',昨天共启动控制流：',num_run,'个',',正常执行成功',num_succeed,'个',',报错',num_failed1,'个',',昨天调度运行完整率：',rate_wz_etl) as "ETL日报";
select reserved2, flowName,source from flow where id in (
select originalFlowId from schedule where id in (
select distinct scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Failed"
and scheduleId not in(
select scheduleId from schedule_execution where DATE_FORMAT(startTime,'%Y%m%d')=statis_date and scheduleId in ( select id from schedule where isOnline=1) and status="Succeed" )));

end ;//
DELIMITER ;

过程写好，下面就开始编写shell调用该存储过程了~

#!/bin/sh  
  
##  用来统计ETL日运行情况  
##  the script is executed at 10 o'clock by every day.  
DATE=$(date +%Y%m%d --date '1 days ago')  
USER=user  
PASSWD=****** 
DATABASE=user  
time=$(date +%Y%m%d --date '1 days ago') 
FILE=/home/mysql/etl_log/log/ETL_$time.txt  

  
echo "the date:"${DATE}  
  
SQL="mysql -u${USER} -p${PASSWD} -D ${DATABASE} -e \"call sp_etl_info_day(${DATE})\""  
echo ${SQL}
echo $SQL>>${FILE} 
 
mysql -u${USER} -p${PASSWD} -D ${DATABASE} -e "call sp_etl_info_day(${DATE})">>$FILE

exit

以后每天只要去对应的目录下查看文件就行啦~~

省去了不少时间~

我想这大概就是思路，在工作期间，尽量避免重复的工作量，把程序能做的让程序自动做~这样可以更高效的工作~

文章来源: dataclub.blog.csdn.net，作者：数据社，版权归原作者所有，如需转载，请联系作者。

原文链接：dataclub.blog.csdn.net/article/details/50687282