窗口函数（开窗函数）
1 相关函数说明
普通的聚合函数聚合的行集是组,开窗函数聚合的行集是窗口。因此,普通的聚合函数每组(Group by)只返回一个值，而开窗函数则可为窗口中的每行都返回一个值。简单理解，就是对查询的结果多出一列，这一列可以是聚合值，也可以是排序值。
开窗函数一般分为两类,聚合开窗函数和排序开窗函数。
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而变
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,default_val)：往前第 n 行数据
LEAD(col,n, default_val)：往后第 n 行数据
NTILE(n)：把有序窗口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, 将每个顾客的 cost 按照日期进行累加
（4）查询每个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
[root@localhost 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 "/usr/soft/datas/business.txt" into table business;
5.1 over() 初体验
select name,count(*) from business;FAILED: SemanticException [Error 10025]: Line 1:7 Expression not in GROUP BY key 'name'
-- 使用over()函数：
select name,count(*) over() from business;
over() 类似于group by，但是在分组时，每一个字段都单独作为一组
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 distinct(name) from business where substring(orderdate,0,7) = '2017-04';select count(*),name from (select name from business where substring(orderdate,0,7)='2017-04' group by name)t1;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） 将每个顾客的 cost 按照日期进行累加
select * from business order by name,orderdate; --按照姓名和日期排序select name,orderdate,cost,sum(cost) over(partition by name order by orderdate) from business; --按照姓名和日期排序,同时累加costselect name,orderdate,cost,sum(cost) over(partition by name order by orderdate rows between UNBOUNDED PRECEDING and current row) from business ;
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;
-- rows 必须跟在 order by 子句之后，对排序的结果进行限制，使用固定的行数来限制分区中的数据行数量
（4） 查看顾客上次的购买时间
--原始语句
select name,orderdate,lag(orderdate,1) over(partition by name order by orderdate )
from business;--添加默认值
select name,orderdate,lag(orderdate,1,'1900-01-01') over(partition by name order by orderdate )
from business;--延申
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) sortedfrom business
) t
where sorted = 1;
