问题导读:
1、Hive分析窗口函数SUM如何实现?
2、Hive分析窗口函数AVG脚本如何编写?
3、Hive分析窗口函数MIN、MAX脚本如何实现?
Hive中提供了越来越多的分析函数,用于完成负责的统计分析。抽时间将所有的分析窗口函数理一遍,将陆续发布。
今天先看几个基础的,SUM、AVG、MIN、MAX。
用于实现分组内所有和连续累积的统计。
Hive版本为 apache-hive-0.13.1数据准备
- CREATE EXTERNAL TABLE lxw1234 (
- cookieid string,
- createtime string, --day
- pv INT
- ) ROW FORMAT DELIMITED
- FIELDS TERMINATED BY ','
- stored as textfile location '/tmp/lxw11/';
-
- DESC lxw1234;
- cookieid STRING
- createtime STRING
- pv INT
-
- hive> select * from lxw1234;
- OK
- cookie1 2015-04-10 1
- cookie1 2015-04-11 5
- cookie1 2015-04-12 7
- cookie1 2015-04-13 3
- cookie1 2015-04-14 2
- cookie1 2015-04-15 4
- cookie1 2015-04-16 4
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SUM — 注意,结果和ORDER BY相关,默认为升序
- SELECT cookieid,
- createtime,
- pv,
- SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
- SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
- SUM(pv) OVER(PARTITION BY cookieid) AS pv3, --分组内所有行
- SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4, --当前行+往前3行
- SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5, --当前行+往前3行+往后1行
- SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 ---当前行+往后所有行
- FROM lxw1234;
-
- cookieid createtime pv pv1 pv2 pv3 pv4 pv5 pv6
- -----------------------------------------------------------------------------
- cookie1 2015-04-10 1 1 1 26 1 6 26
- cookie1 2015-04-11 5 6 6 26 6 13 25
- cookie1 2015-04-12 7 13 13 26 13 16 20
- cookie1 2015-04-13 3 16 16 26 16 18 13
- cookie1 2015-04-14 2 18 18 26 17 21 10
- cookie1 2015-04-15 4 22 22 26 16 20 8
- cookie1 2015-04-16 4 26 26 26 13 13 4
-
-
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pv1: 分组内从起点到当前行的pv累积,如,11号的pv1=10号的pv+11号的pv, 12号=10号+11号+12号
pv2: 同pv1
pv3: 分组内(cookie1)所有的pv累加
pv4: 分组内当前行+往前3行,如,11号=10号+11号, 12号=10号+11号+12号, 13号=10号+11号+12号+13号, 14号=11号+12号+13号+14号
pv5: 分组内当前行+往前3行+往后1行,如,14号=11号+12号+13号+14号+15号=5+7+3+2+4=21
pv6: 分组内当前行+往后所有行,如,13号=13号+14号+15号+16号=3+2+4+4=13,14号=14号+15号+16号=2+4+4=10
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:起点,UNBOUNDED PRECEDING 表示从前面的起点, UNBOUNDED FOLLOWING:表示到后面的终点
–其他AVG,MIN,MAX,和SUM用法一样。
- --AVG
- SELECT cookieid,
- createtime,
- pv,
- AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
- AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
- AVG(pv) OVER(PARTITION BY cookieid) AS pv3, --分组内所有行
- AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4, --当前行+往前3行
- AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5, --当前行+往前3行+往后1行
- AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 ---当前行+往后所有行
- FROM lxw1234;
- cookieid createtime pv pv1 pv2 pv3 pv4 pv5 pv6
- -----------------------------------------------------------------------------
- cookie1 2015-04-10 1 1.0 1.0 3.7142857142857144 1.0 3.0 3.7142857142857144
- cookie1 2015-04-11 5 3.0 3.0 3.7142857142857144 3.0 4.333333333333333 4.166666666666667
- cookie1 2015-04-12 7 4.333333333333333 4.333333333333333 3.7142857142857144 4.333333333333333 4.0 4.0
- cookie1 2015-04-13 3 4.0 4.0 3.7142857142857144 4.0 3.6 3.25
- cookie1 2015-04-14 2 3.6 3.6 3.7142857142857144 4.25 4.2 3.3333333333333335
- cookie1 2015-04-15 4 3.6666666666666665 3.6666666666666665 3.7142857142857144 4.0 4.0 4.0
- cookie1 2015-04-16 4 3.7142857142857144 3.7142857142857144 3.7142857142857144 3.25 3.25 4.0
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- --MIN
- SELECT cookieid,
- createtime,
- pv,
- MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
- MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
- MIN(pv) OVER(PARTITION BY cookieid) AS pv3, --分组内所有行
- MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4, --当前行+往前3行
- MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5, --当前行+往前3行+往后1行
- MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 ---当前行+往后所有行
- FROM lxw1234;
-
- cookieid createtime pv pv1 pv2 pv3 pv4 pv5 pv6
- -----------------------------------------------------------------------------
- cookie1 2015-04-10 1 1 1 1 1 1 1
- cookie1 2015-04-11 5 1 1 1 1 1 2
- cookie1 2015-04-12 7 1 1 1 1 1 2
- cookie1 2015-04-13 3 1 1 1 1 1 2
- cookie1 2015-04-14 2 1 1 1 2 2 2
- cookie1 2015-04-15 4 1 1 1 2 2 4
- cookie1 2015-04-16 4 1 1 1 2 2 4
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- ----MAX
- SELECT cookieid,
- createtime,
- pv,
- MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
- MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
- MAX(pv) OVER(PARTITION BY cookieid) AS pv3, --分组内所有行
- MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4, --当前行+往前3行
- MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5, --当前行+往前3行+往后1行
- MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 ---当前行+往后所有行
- FROM lxw1234;
-
- cookieid createtime pv pv1 pv2 pv3 pv4 pv5 pv6
- -----------------------------------------------------------------------------
- cookie1 2015-04-10 1 1 1 7 1 5 7
- cookie1 2015-04-11 5 5 5 7 5 7 7
- cookie1 2015-04-12 7 7 7 7 7 7 7
- cookie1 2015-04-13 3 7 7 7 7 7 4
- cookie1 2015-04-14 2 7 7 7 7 7 4
- cookie1 2015-04-15 4 7 7 7 7 7 4
- cookie1 2015-04-16 4 7 7 7 4 4 4
-
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其他函数的介绍将陆续整理发布。。
相关内容:
Hive分析窗口函数(一) SUM,AVG,MIN,MAX
Hive分析窗口函数(二) NTILE,ROW_NUMBER,RANK,DENSE_RANK
Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE
Hive分析窗口函数(五) GROUPING SETS,GROUPING__ID,CUBE,ROLLUP
资料来源:http://029bigdata.com/?p=176
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