窗口函数
1.相关函数说明
COVER():指定分析函数工作的数据窗口大小,这个数据窗口大小可能会随着行的变而变化 CURRENT ROW:当前行 n PRECEDING:往前n行数据 n FOLLOWING:往后n行数据 UNBOUNDED:起点,UNBOUNDED PRECEDING 表示从前面的起点, UNBOUNDED FOLLOWING表示到后面的终点 LAG(col,n):往前第n行数据 LEAD(col,n):往后第n行数据
NTILE(n):把有序分区中的行分发到指定数据的组中,各个组有编号,编号从1开始,对于每一行,NTILE返回此行所属的组的编号。注意:n必须为int类型。
2.数据准备:name,orderdate,cost
jack,2017-01-01,10 tony,2017-01-02,15 jack,2017-02-03,23 tony,2017-01-04,29 jack,2017-01-05,46 jack,2017-04-06,42 tony,2017-01-07,50 jack,2017-01-08,55 mart,2017-04-08,62 mart,2017-04-09,68 neil,2017-05-10,12 mart,2017-04-11,75 neil,2017-06-12,80 mart,2017-04-13,94
3.需求
(1)查询在2017年4月份购买过的顾客及总人数
(2)查询顾客的购买明细及月购买总额
(3)上述的场景,要将cost按照日期进行累加
(4)查询顾客上次的购买时间
(5)查询前20%时间的订单信息
4.创建本地business.txt,导入数据
[atguigu@hadoop102 datas]$ vi business.txt
5.创建hive表并导入数据
create table business( name string, orderdate string, cost int ) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';
load data local inpath "/opt/module/datas/business.txt" into table business; |
6.按需求查询数据
(1)查询在2017年4月份购买过的顾客及总人数
select name,count(*) over () from business where substring(orderdate,1,7) = '2017-04' group by name; |
(2)查询顾客的购买明细及月购买总额
select name,orderdate,cost,sum(cost) over(partition by month(orderdate)) from business; |
(3)上述的场景,要将cost按照日期进行累加
select name,orderdate,cost, sum(cost) over() as sample1,--所有行相加 sum(cost) over(partition by name) as sample2,--按name分组,组内数据相加 sum(cost) over(partition by name order by orderdate) as sample3,--按name分组,组内数据累加 sum(cost) over(partition by name order by orderdate rows between UNBOUNDED PRECEDING and current row ) as sample4 ,--和sample3一样,由起点到当前行的聚合 sum(cost) over(partition by name order by orderdate rows between 1 PRECEDING and current row) as sample5, --当前行和前面一行做聚合 sum(cost) over(partition by name order by orderdate rows between 1 PRECEDING AND 1 FOLLOWING ) as sample6,--当前行和前边一行及后面一行 sum(cost) over(partition by name order by orderdate rows between current row and UNBOUNDED FOLLOWING ) as sample7 --当前行及后面所有行 from business; |
(4)查看顾客上次的购买时间
select name,orderdate,cost, lag(orderdate,1,'1900-01-01') over(partition by name order by orderdate ) as time1, lag(orderdate,2) over (partition by name order by orderdate) as time2 from business; |
(5)查询前20%时间的订单信息
select * from ( select name,orderdate,cost, ntile(5) over(order by orderdate) sorted from business ) t where sorted = 1; |
来源:https://www.cnblogs.com/alexzhang92/p/10650990.html