开窗函数查询
1．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
2．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
3．创建本地business.txt，导入数据
[luomk@hadoop102 datas]$ vi business.txt
4．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;
5．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;
6．相关函数说明
OVER()：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化而变化
CURRENT ROW：当前行
PRECEDING n：往前n行数据
FOLLOWING n：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。