仅做记录，原文：https://blog.csdn.net/scgaliguodong123_/article/details/60135385
窗口函数与分析函数
应用场景：
（1）用于分区排序
（2）动态Group By
（3）Top N
（4）累计计算
（5）层次查询
窗口函数
FIRST_VALUE：取分组内排序后，截止到当前行，第一个值
LAST_VALUE： 取分组内排序后，截止到当前行，最后一个值
LEAD(col,n,DEFAULT) ：用于统计窗口内往下第n行值。第一个参数为列名，第二个参数为往下第n行（可选，默认为1），第三个参数为默认值（当往下第n行为NULL时候，取默认值，如不指定，则为NULL）
LAG(col,n,DEFAULT) ：与lead相反，用于统计窗口内往上第n行值。第一个参数为列名，第二个参数为往上第n行（可选，默认为1），第三个参数为默认值（当往上第n行为NULL时候，取默认值，如不指定，则为NULL）
OVER从句
1、使用标准的聚合函数COUNT、SUM、MIN、MAX、AVG
2、使用PARTITION BY语句，使用一个或者多个原始数据类型的列
3、使用PARTITION BY与ORDER BY语句，使用一个或者多个数据类型的分区或者排序列
4、使用窗口规范，窗口规范支持以下格式：
---------------------
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(
ROWS
| RANGE)
BETWEEN
(UNBOUNDED | [num]) PRECEDING
AND
([num] PRECEDING |
CURRENT
ROW | (UNBOUNDED | [num]) FOLLOWING)
(
ROWS
| RANGE)
BETWEEN
CURRENT
ROW
AND
(
CURRENT
ROW | (UNBOUNDED | [num]) FOLLOWING)
(
ROWS
| RANGE)
BETWEEN
[num] FOLLOWING
AND
(UNBOUNDED | [num]) FOLLOWING
|
当ORDER BY后面缺少窗口从句条件，窗口规范默认是 RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW.
当ORDER BY和窗口从句都缺失, 窗口规范默认是 ROW BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING.
OVER从句支持以下函数， 但是并不支持和窗口一起使用它们。
Ranking函数: Rank, NTile, DenseRank, CumeDist, PercentRank.
Lead 和 Lag 函数.
分析函数
ROW_NUMBER() 从1开始，按照顺序，生成分组内记录的序列,比如，按照pv降序排列，生成分组内每天的pv名次,ROW_NUMBER()的应用场景非常多，再比如，获取分组内排序第一的记录;获取一个session中的第一条refer等。
RANK() 生成数据项在分组中的排名，排名相等会在名次中留下空位
DENSE_RANK() 生成数据项在分组中的排名，排名相等会在名次中不会留下空位
CUME_DIST 小于等于当前值的行数/分组内总行数。比如，统计小于等于当前薪水的人数，所占总人数的比例
PERCENT_RANK 分组内当前行的RANK值-1/分组内总行数-1
NTILE(n) 用于将分组数据按照顺序切分成n片，返回当前切片值，如果切片不均匀，默认增加第一个切片的分布。NTILE不支持ROWS BETWEEN，比如 NTILE(2) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW)。
Hive2.1.0及以后支持Distinct
在聚合函数（SUM, COUNT and AVG）中，支持distinct，但是在ORDER BY 或者 窗口限制不支持。
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COUNT
(
DISTINCT
a) OVER (PARTITION
BY
c)
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Hive 2.2.0中在使用ORDER BY和窗口限制时支持distinct
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COUNT
(
DISTINCT
a) OVER (PARTITION
BY
c
ORDER
BY
d
ROWS
BETWEEN
1 PRECEDING
AND
1 FOLLOWING)
|
Hive2.1.0及以后支持在OVER从句中支持聚合函数
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SELECT
rank() OVER (
ORDER
BY
sum
(b))
FROM
T
GROUP
BY
a;
|
测试数据集：
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##
COUNT
、
SUM
、
MIN
、
MAX
、
AVG
select
user_id,
user_type,
sales,
--默认为从起点到当前行
sum
(sales) OVER(PARTITION
BY
user_type
ORDER
BY
sales
asc
)
AS
sales_1,
--从起点到当前行，结果与sales_1不同。
sum
(sales) OVER(PARTITION
BY
user_type
ORDER
BY
sales
asc
ROWS
BETWEEN
UNBOUNDED PRECEDING
AND
CURRENT
ROW)
AS
sales_2,
--当前行+往前3行
sum
(sales) OVER(PARTITION
BY
user_type
ORDER
BY
sales
asc
ROWS
BETWEEN
3 PRECEDING
AND
CURRENT
ROW)
AS
sales_3,
--当前行+往前3行+往后1行
sum
(sales) OVER(PARTITION
BY
user_type
ORDER
BY
sales
asc
ROWS
BETWEEN
3 PRECEDING
AND
1 FOLLOWING)
AS
sales_4,
--当前行+往后所有行
sum
(sales) OVER(PARTITION
BY
user_type
ORDER
BY
sales
asc
ROWS
BETWEEN
CURRENT
ROW
AND
UNBOUNDED FOLLOWING)
AS
sales_5,
--分组内所有行
SUM
(sales) OVER(PARTITION
BY
user_type)
AS
sales_6
from
order_detail
order
by
user_type,
sales,
user_id
+
----------+------------+--------+----------+----------+----------+----------+----------+----------+--+
| user_id | user_type | sales | sales_1 | sales_2 | sales_3 | sales_4 | sales_5 | sales_6 |
+
----------+------------+--------+----------+----------+----------+----------+----------+----------+--+
| liiu | new | 1 | 2 | 2 | 2 | 4 | 22 | 23 |
| qibaqiu | new | 1 | 2 | 1 | 1 | 2 | 23 | 23 |
| zhangsa | new | 2 | 4 | 4 | 4 | 7 | 21 | 23 |
| wanger | new | 3 | 7 | 7 | 7 | 12 | 19 | 23 |
| lilisi | new | 5 | 17 | 17 | 15 | 21 | 11 | 23 |
| qishili | new | 5 | 17 | 12 | 11 | 16 | 16 | 23 |
| wutong | new | 6 | 23 | 23 | 19 | 19 | 6 | 23 |
| lisi | old | 1 | 1 | 1 | 1 | 3 | 6 | 6 |
| wangshi | old | 2 | 3 | 3 | 3 | 6 | 5 | 6 |
| liwei | old | 3 | 6 | 6 | 6 | 6 | 3 | 6 |
+
----------+------------+--------+----------+----------+----------+----------+----------+----------+--+
注意:
结果和
ORDER
BY
相关,默认为升序
如果不指定
ROWS
BETWEEN
,默认为从起点到当前行;
如果不指定
ORDER
BY
，则将分组内所有值累加;
关键是理解
ROWS
BETWEEN
含义,也叫做WINDOW子句：
PRECEDING：往前
FOLLOWING：往后
CURRENT
ROW：当前行
UNBOUNDED：无界限（起点或终点）
UNBOUNDED PRECEDING：表示从前面的起点
UNBOUNDED FOLLOWING：表示到后面的终点
其他
COUNT
、
AVG
，
MIN
，
MAX
，和
SUM
用法一样。
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## first_value与last_value
select
user_id,
user_type,
ROW_NUMBER() OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
row_num,
first_value(user_id) over (partition
by
user_type
order
by
sales
desc
)
as
max_sales_user,
first_value(user_id) over (partition
by
user_type
order
by
sales
asc
)
as
min_sales_user,
last_value(user_id) over (partition
by
user_type
order
by
sales
desc
)
as
curr_last_min_user,
last_value(user_id) over (partition
by
user_type
order
by
sales
asc
)
as
curr_last_max_user
from
order_detail;
+
----------+------------+----------+-----------------+-----------------+---------------------+---------------------+--+
| user_id | user_type | row_num | max_sales_user | min_sales_user | curr_last_min_user | curr_last_max_user |
+
----------+------------+----------+-----------------+-----------------+---------------------+---------------------+--+
| wutong | new | 7 | wutong | qibaqiu | wutong | wutong |
| lilisi | new | 6 | wutong | qibaqiu | qishili | lilisi |
| qishili | new | 5 | wutong | qibaqiu | qishili | lilisi |
| wanger | new | 4 | wutong | qibaqiu | wanger | wanger |
| zhangsa | new | 3 | wutong | qibaqiu | zhangsa | zhangsa |
| liiu | new | 2 | wutong | qibaqiu | qibaqiu | liiu |
| qibaqiu | new | 1 | wutong | qibaqiu | qibaqiu | liiu |
| liwei | old | 3 | liwei | lisi | liwei | liwei |
| wangshi | old | 2 | liwei | lisi | wangshi | wangshi |
| lisi | old | 1 | liwei | lisi | lisi | lisi |
+
----------+------------+----------+-----------------+-----------------+---------------------+---------------------+--+
## lead与lag
select
user_id,device_id,
lead(device_id) over (
order
by
sales)
as
default_after_one_line,
lag(device_id) over (
order
by
sales)
as
default_before_one_line,
lead(device_id,2) over (
order
by
sales)
as
after_two_line,
lag(device_id,2,
'abc'
) over (
order
by
sales)
as
before_two_line
from
order_detail;
+
----------+-------------+-------------------------+--------------------------+-----------------+------------------+--+
| user_id | device_id | default_after_one_line | default_before_one_line | after_two_line | before_two_line |
+
----------+-------------+-------------------------+--------------------------+-----------------+------------------+--+
| qibaqiu | fds | fdsfagwe |
NULL
| 543gfd | abc |
| liiu | fdsfagwe | 543gfd | fds | f332 | abc |
| lisi | 543gfd | f332 | fdsfagwe | dfsadsa323 | fds |
| wangshi | f332 | dfsadsa323 | 543gfd | hfd | fdsfagwe |
| zhangsa | dfsadsa323 | hfd | f332 | 65ghf | 543gfd |
| liwei | hfd | 65ghf | dfsadsa323 | fds | f332 |
| wanger | 65ghf | fds | hfd | dsfgg | dfsadsa323 |
| qishili | fds | dsfgg | 65ghf | 543gdfsd | hfd |
| lilisi | dsfgg | 543gdfsd | fds |
NULL
| 65ghf |
| wutong | 543gdfsd |
NULL
| dsfgg |
NULL
| fds |
+
----------+-------------+-------------------------+--------------------------+-----------------+------------------+--+
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## RANK、ROW_NUMBER、DENSE_RANK
select
user_id,user_type,sales,
RANK() over (partition
by
user_type
order
by
sales
desc
)
as
r,
ROW_NUMBER() over (partition
by
user_type
order
by
sales
desc
)
as
rn,
DENSE_RANK() over (partition
by
user_type
order
by
sales
desc
)
as
dr
from
order_detail;
+
----------+------------+--------+----+-----+-----+--+
| user_id | user_type | sales | r | rn | dr |
+
----------+------------+--------+----+-----+-----+--+
| wutong | new | 6 | 1 | 1 | 1 |
| qishili | new | 5 | 2 | 2 | 2 |
| lilisi | new | 5 | 2 | 3 | 2 |
| wanger | new | 3 | 4 | 4 | 3 |
| zhangsa | new | 2 | 5 | 5 | 4 |
| qibaqiu | new | 1 | 6 | 6 | 5 |
| liiu | new | 1 | 6 | 7 | 5 |
| liwei | old | 3 | 1 | 1 | 1 |
| wangshi | old | 2 | 2 | 2 | 2 |
| lisi | old | 1 | 3 | 3 | 3 |
+
----------+------------+--------+----+-----+-----+--+
## NTILE
select
user_type,sales,
--分组内将数据分成2片
NTILE(2) OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
nt2,
--分组内将数据分成3片
NTILE(3) OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
nt3,
--分组内将数据分成4片
NTILE(4) OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
nt4,
--将所有数据分成4片
NTILE(4) OVER(
ORDER
BY
sales)
AS
all_nt4
from
order_detail
order
by
user_type,
sales
+
------------+--------+------+------+------+----------+--+
| user_type | sales | nt2 | nt3 | nt4 | all_nt4 |
+
------------+--------+------+------+------+----------+--+
| new | 1 | 1 | 1 | 1 | 1 |
| new | 1 | 1 | 1 | 1 | 1 |
| new | 2 | 1 | 1 | 2 | 2 |
| new | 3 | 1 | 2 | 2 | 3 |
| new | 5 | 2 | 2 | 3 | 4 |
| new | 5 | 2 | 3 | 3 | 3 |
| new | 6 | 2 | 3 | 4 | 4 |
| old | 1 | 1 | 1 | 1 | 1 |
| old | 2 | 1 | 2 | 2 | 2 |
| old | 3 | 2 | 3 | 3 | 2 |
+
------------+--------+------+------+------+----------+--+
求取sale前20%的用户ID
select
user_id
from
(
select
user_id,
NTILE(5) OVER(
ORDER
BY
sales
desc
)
AS
nt
from
order_detail
)A
where
nt=1;
## CUME_DIST、PERCENT_RANK
select
user_id,user_type,sales,
--没有partition,所有数据均为1组
CUME_DIST() OVER(
ORDER
BY
sales)
AS
cd1,
--按照user_type进行分组
CUME_DIST() OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
cd2
from
order_detail;
+
----------+------------+--------+------+----------------------+--+
| user_id | user_type | sales | cd1 | cd2 |
+
----------+------------+--------+------+----------------------+--+
| liiu | new | 1 | 0.3 | 0.2857142857142857 |
| qibaqiu | new | 1 | 0.3 | 0.2857142857142857 |
| zhangsa | new | 2 | 0.5 | 0.42857142857142855 |
| wanger | new | 3 | 0.7 | 0.5714285714285714 |
| lilisi | new | 5 | 0.9 | 0.8571428571428571 |
| qishili | new | 5 | 0.9 | 0.8571428571428571 |
| wutong | new | 6 | 1.0 | 1.0 |
| lisi | old | 1 | 0.3 | 0.3333333333333333 |
| wangshi | old | 2 | 0.5 | 0.6666666666666666 |
| liwei | old | 3 | 0.7 | 1.0 |
+
----------+------------+--------+------+----------------------+--+
select
user_type,sales
--分组内总行数
SUM
(1) OVER(PARTITION
BY
user_type)
AS
s,
--RANK值
RANK() OVER(
ORDER
BY
sales)
AS
r,
PERCENT_RANK() OVER(
ORDER
BY
sales)
AS
pr,
--分组内
PERCENT_RANK() OVER(PARTITION
BY
user_type
ORDER
BY
sales)
AS
prg
from
order_detail;
+
----+-----+---------------------+---------------------+--+
| s | r | pr | prg |
+
----+-----+---------------------+---------------------+--+
| 7 | 1 | 0.0 | 0.0 |
| 7 | 1 | 0.0 | 0.0 |
| 7 | 4 | 0.3333333333333333 | 0.3333333333333333 |
| 7 | 6 | 0.5555555555555556 | 0.5 |
| 7 | 8 | 0.7777777777777778 | 0.6666666666666666 |
| 7 | 8 | 0.7777777777777778 | 0.6666666666666666 |
| 7 | 10 | 1.0 | 1.0 |
| 3 | 1 | 0.0 | 0.0 |
| 3 | 4 | 0.3333333333333333 | 0.5 |
| 3 | 6 | 0.5555555555555556 | 1.0 |
+
----+-----+---------------------+---------------------+--+
|