hive以半小时为维度进行统计的需求

从2020/04/22日开始，往延3天，按req_id关联，统计曝光事件与点击事件之间的时间间隔分布情况，按30分钟为粒度，
点击事件字段：req_id,clickTime，
曝光事件字段：req_id，exposureTime
需要统计clickTime-exposureTime在各个时间差（30分钟，60分钟，90分钟。。。）的百分率
数据结果如下：

时间间隔(单位分钟) 占比情况（%） 备注
30 80
60 95
90 96
120 98
150 99
思路：
1.用req_id 关联点击事件left join 曝光事件，且曝光时间和点击事件都存在的情况下，click[20200422],exposure[20200420,20200421,20200422]
2.获取点击时间和曝光时间
3.利用2步骤中的 点击时间-曝光时间差 得到 时间差
4.计算各个时间差的占比

function etldata() {
    echo "start etldata"

    beeline -e "
		select 
		time
		,count
		,sum
		,sum(rate) over(rows between UNBOUNDED PRECEDING and CURRENT ROW)
		from(
			select
				time
				,count
				,sum
				,(count*100.00)/sum as rate
				from
				(
						select 
						time
						,count
						,sum(count) over() as sum
						from(
							select 
							(time+1)*30 as time
							,count(*) as count
							from 
							(
								select
								  click.req_id
								  ,click.rtime as ctime
								  ,expo.rtime as etime
								  ,floor((click.rtime-expo.rtime)/1000/60/30) as time
								  ,row_number() over(partition by expo.req_id) as rn
								  from (
										select rtime,req_id
										from tmp.ad_click_b
											where data_date=2020042406
								  ) click
								  left join 
									  (
										select rtime,req_id
										from tmp.ad_exposure_b
											where data_date>=2020042404 and data_date<=2020042406	
									  ) expo on click.req_id = expo.req_id
							)cli_epo where rn=1 group by time 
						)t2

				)t1 
		)t order by time asc
	 "

   echo "end etldata"
}

function main() {

    etldata
}

main