微信搜索lxw1234bigdata | 邀请体验：数阅–数据管理、OLAP分析与可视化平台 | 赞助作者：赞助作者

Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE

Hive lxw1234@qq.com 160296℃ 6评论

继续学习这四个分析函数。

注意： 这几个函数不支持WINDOW子句。（什么是WINDOW子句，点此查看前面的文章 ）

Hive版本为 apache-hive-0.13.1

数据准备：

cookie1,2015-04-10 10:00:02,url2
cookie1,2015-04-10 10:00:00,url1
cookie1,2015-04-10 10:03:04,1url3
cookie1,2015-04-10 10:50:05,url6
cookie1,2015-04-10 11:00:00,url7
cookie1,2015-04-10 10:10:00,url4
cookie1,2015-04-10 10:50:01,url5
cookie2,2015-04-10 10:00:02,url22
cookie2,2015-04-10 10:00:00,url11
cookie2,2015-04-10 10:03:04,1url33
cookie2,2015-04-10 10:50:05,url66
cookie2,2015-04-10 11:00:00,url77
cookie2,2015-04-10 10:10:00,url44
cookie2,2015-04-10 10:50:01,url55

CREATE EXTERNAL TABLE lxw1234 (
cookieid string,
createtime string,  --页面访问时间
url STRING       --被访问页面
) ROW FORMAT DELIMITED 
FIELDS TERMINATED BY ',' 
stored as textfile location '/tmp/lxw11/';


hive> select * from lxw1234;
OK
cookie1 2015-04-10 10:00:02     url2
cookie1 2015-04-10 10:00:00     url1
cookie1 2015-04-10 10:03:04     1url3
cookie1 2015-04-10 10:50:05     url6
cookie1 2015-04-10 11:00:00     url7
cookie1 2015-04-10 10:10:00     url4
cookie1 2015-04-10 10:50:01     url5
cookie2 2015-04-10 10:00:02     url22
cookie2 2015-04-10 10:00:00     url11
cookie2 2015-04-10 10:03:04     1url33
cookie2 2015-04-10 10:50:05     url66
cookie2 2015-04-10 11:00:00     url77
cookie2 2015-04-10 10:10:00     url44
cookie2 2015-04-10 10:50:01     url55

LAG

LAG(col,n,DEFAULT) 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）

SELECT cookieid,
createtime,
url,
ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
LAG(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS last_1_time,
LAG(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS last_2_time 
FROM lxw1234;


cookieid createtime             url    rn       last_1_time             last_2_time
-------------------------------------------------------------------------------------------
cookie1 2015-04-10 10:00:00     url1    1       1970-01-01 00:00:00     NULL
cookie1 2015-04-10 10:00:02     url2    2       2015-04-10 10:00:00     NULL
cookie1 2015-04-10 10:03:04     1url3   3       2015-04-10 10:00:02     2015-04-10 10:00:00
cookie1 2015-04-10 10:10:00     url4    4       2015-04-10 10:03:04     2015-04-10 10:00:02
cookie1 2015-04-10 10:50:01     url5    5       2015-04-10 10:10:00     2015-04-10 10:03:04
cookie1 2015-04-10 10:50:05     url6    6       2015-04-10 10:50:01     2015-04-10 10:10:00
cookie1 2015-04-10 11:00:00     url7    7       2015-04-10 10:50:05     2015-04-10 10:50:01
cookie2 2015-04-10 10:00:00     url11   1       1970-01-01 00:00:00     NULL
cookie2 2015-04-10 10:00:02     url22   2       2015-04-10 10:00:00     NULL
cookie2 2015-04-10 10:03:04     1url33  3       2015-04-10 10:00:02     2015-04-10 10:00:00
cookie2 2015-04-10 10:10:00     url44   4       2015-04-10 10:03:04     2015-04-10 10:00:02
cookie2 2015-04-10 10:50:01     url55   5       2015-04-10 10:10:00     2015-04-10 10:03:04
cookie2 2015-04-10 10:50:05     url66   6       2015-04-10 10:50:01     2015-04-10 10:10:00
cookie2 2015-04-10 11:00:00     url77   7       2015-04-10 10:50:05     2015-04-10 10:50:01


last_1_time: 指定了往上第1行的值，default为'1970-01-01 00:00:00'  
             cookie1第一行，往上1行为NULL,因此取默认值 1970-01-01 00:00:00
             cookie1第三行，往上1行值为第二行值，2015-04-10 10:00:02
             cookie1第六行，往上1行值为第五行值，2015-04-10 10:50:01
last_2_time: 指定了往上第2行的值，为指定默认值
						 cookie1第一行，往上2行为NULL
						 cookie1第二行，往上2行为NULL
						 cookie1第四行，往上2行为第二行值，2015-04-10 10:00:02
						 cookie1第七行，往上2行为第五行值，2015-04-10 10:50:01

LEAD

与LAG相反
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）

SELECT cookieid,
createtime,
url,
ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
LEAD(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS next_1_time,
LEAD(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS next_2_time 
FROM lxw1234;


cookieid createtime             url    rn       next_1_time             next_2_time 
-------------------------------------------------------------------------------------------
cookie1 2015-04-10 10:00:00     url1    1       2015-04-10 10:00:02     2015-04-10 10:03:04
cookie1 2015-04-10 10:00:02     url2    2       2015-04-10 10:03:04     2015-04-10 10:10:00
cookie1 2015-04-10 10:03:04     1url3   3       2015-04-10 10:10:00     2015-04-10 10:50:01
cookie1 2015-04-10 10:10:00     url4    4       2015-04-10 10:50:01     2015-04-10 10:50:05
cookie1 2015-04-10 10:50:01     url5    5       2015-04-10 10:50:05     2015-04-10 11:00:00
cookie1 2015-04-10 10:50:05     url6    6       2015-04-10 11:00:00     NULL
cookie1 2015-04-10 11:00:00     url7    7       1970-01-01 00:00:00     NULL
cookie2 2015-04-10 10:00:00     url11   1       2015-04-10 10:00:02     2015-04-10 10:03:04
cookie2 2015-04-10 10:00:02     url22   2       2015-04-10 10:03:04     2015-04-10 10:10:00
cookie2 2015-04-10 10:03:04     1url33  3       2015-04-10 10:10:00     2015-04-10 10:50:01
cookie2 2015-04-10 10:10:00     url44   4       2015-04-10 10:50:01     2015-04-10 10:50:05
cookie2 2015-04-10 10:50:01     url55   5       2015-04-10 10:50:05     2015-04-10 11:00:00
cookie2 2015-04-10 10:50:05     url66   6       2015-04-10 11:00:00     NULL
cookie2 2015-04-10 11:00:00     url77   7       1970-01-01 00:00:00     NULL

--逻辑与LAG一样，只不过LAG是往上，LEAD是往下。

FIRST_VALUE

取分组内排序后，截止到当前行，第一个值

SELECT cookieid,
createtime,
url,
ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS first1 
FROM lxw1234;

cookieid  createtime            url     rn      first1
---------------------------------------------------------
cookie1 2015-04-10 10:00:00     url1    1       url1
cookie1 2015-04-10 10:00:02     url2    2       url1
cookie1 2015-04-10 10:03:04     1url3   3       url1
cookie1 2015-04-10 10:10:00     url4    4       url1
cookie1 2015-04-10 10:50:01     url5    5       url1
cookie1 2015-04-10 10:50:05     url6    6       url1
cookie1 2015-04-10 11:00:00     url7    7       url1
cookie2 2015-04-10 10:00:00     url11   1       url11
cookie2 2015-04-10 10:00:02     url22   2       url11
cookie2 2015-04-10 10:03:04     1url33  3       url11
cookie2 2015-04-10 10:10:00     url44   4       url11
cookie2 2015-04-10 10:50:01     url55   5       url11
cookie2 2015-04-10 10:50:05     url66   6       url11
cookie2 2015-04-10 11:00:00     url77   7       url11

LAST_VALUE

取分组内排序后，截止到当前行，最后一个值

SELECT cookieid,
createtime,
url,
ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1 
FROM lxw1234;


cookieid  createtime            url    rn       last1  
-----------------------------------------------------------------
cookie1 2015-04-10 10:00:00     url1    1       url1
cookie1 2015-04-10 10:00:02     url2    2       url2
cookie1 2015-04-10 10:03:04     1url3   3       1url3
cookie1 2015-04-10 10:10:00     url4    4       url4
cookie1 2015-04-10 10:50:01     url5    5       url5
cookie1 2015-04-10 10:50:05     url6    6       url6
cookie1 2015-04-10 11:00:00     url7    7       url7
cookie2 2015-04-10 10:00:00     url11   1       url11
cookie2 2015-04-10 10:00:02     url22   2       url22
cookie2 2015-04-10 10:03:04     1url33  3       1url33
cookie2 2015-04-10 10:10:00     url44   4       url44
cookie2 2015-04-10 10:50:01     url55   5       url55
cookie2 2015-04-10 10:50:05     url66   6       url66
cookie2 2015-04-10 11:00:00     url77   7       url77

如果不指定ORDER BY，则默认按照记录在文件中的偏移量进行排序，会出现错误的结果

SELECT cookieid,
createtime,
url,
FIRST_VALUE(url) OVER(PARTITION BY cookieid) AS first2  
FROM lxw1234;

cookieid  createtime            url     first2
----------------------------------------------
cookie1 2015-04-10 10:00:02     url2    url2
cookie1 2015-04-10 10:00:00     url1    url2
cookie1 2015-04-10 10:03:04     1url3   url2
cookie1 2015-04-10 10:50:05     url6    url2
cookie1 2015-04-10 11:00:00     url7    url2
cookie1 2015-04-10 10:10:00     url4    url2
cookie1 2015-04-10 10:50:01     url5    url2
cookie2 2015-04-10 10:00:02     url22   url22
cookie2 2015-04-10 10:00:00     url11   url22
cookie2 2015-04-10 10:03:04     1url33  url22
cookie2 2015-04-10 10:50:05     url66   url22
cookie2 2015-04-10 11:00:00     url77   url22
cookie2 2015-04-10 10:10:00     url44   url22
cookie2 2015-04-10 10:50:01     url55   url22

SELECT cookieid,
createtime,
url,
LAST_VALUE(url) OVER(PARTITION BY cookieid) AS last2  
FROM lxw1234;

cookieid  createtime            url     last2
----------------------------------------------
cookie1 2015-04-10 10:00:02     url2    url5
cookie1 2015-04-10 10:00:00     url1    url5
cookie1 2015-04-10 10:03:04     1url3   url5
cookie1 2015-04-10 10:50:05     url6    url5
cookie1 2015-04-10 11:00:00     url7    url5
cookie1 2015-04-10 10:10:00     url4    url5
cookie1 2015-04-10 10:50:01     url5    url5
cookie2 2015-04-10 10:00:02     url22   url55
cookie2 2015-04-10 10:00:00     url11   url55
cookie2 2015-04-10 10:03:04     1url33  url55
cookie2 2015-04-10 10:50:05     url66   url55
cookie2 2015-04-10 11:00:00     url77   url55
cookie2 2015-04-10 10:10:00     url44   url55
cookie2 2015-04-10 10:50:01     url55   url55

如果想要取分组内排序后最后一个值，则需要变通一下：

SELECT cookieid,
createtime,
url,
ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1,
FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime DESC) AS last2 
FROM lxw1234 
ORDER BY cookieid,createtime;

cookieid  createtime            url     rn     last1    last2
-------------------------------------------------------------
cookie1 2015-04-10 10:00:00     url1    1       url1    url7
cookie1 2015-04-10 10:00:02     url2    2       url2    url7
cookie1 2015-04-10 10:03:04     1url3   3       1url3   url7
cookie1 2015-04-10 10:10:00     url4    4       url4    url7
cookie1 2015-04-10 10:50:01     url5    5       url5    url7
cookie1 2015-04-10 10:50:05     url6    6       url6    url7
cookie1 2015-04-10 11:00:00     url7    7       url7    url7
cookie2 2015-04-10 10:00:00     url11   1       url11   url77
cookie2 2015-04-10 10:00:02     url22   2       url22   url77
cookie2 2015-04-10 10:03:04     1url33  3       1url33  url77
cookie2 2015-04-10 10:10:00     url44   4       url44   url77
cookie2 2015-04-10 10:50:01     url55   5       url55   url77
cookie2 2015-04-10 10:50:05     url66   6       url66   url77
cookie2 2015-04-10 11:00:00     url77   7       url77   url77

提示：在使用分析函数的过程中，要特别注意ORDER BY子句，用的不恰当，统计出的结果就不是你所期望的。

点此查看所有Hive窗口分析函数的文章

如果觉得本博客对您有帮助，请 赞助作者 。

转载请注明：lxw的大数据田地 » Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE

喜欢 (178)
赏
分享 (0)
发表我的评论
取消评论
表情

Hi，您需要填写昵称和邮箱！

  • 昵称 (必填)
  • 邮箱 (必填)
  • 网址
(6)个小伙伴在吐槽
  1. first_value() last_value() 的结果是否等价于 max() min()? 且max() min()还省去了order by的部分
    daodan0072016-09-26 11:37 回复
    • 当然不等价。
      lxw1234@qq.com2016-09-26 14:52 回复
  2. hc.sql("SELECT QUOTATIONNO " //--报价单号 +" ,ENDDATE " //--终保日期 +" ,LAG(substr(STARTDATE,1,10),fg) " +" OVER(PARTITION BY VEHICLE_ID,QUOTE_ROUNT ORDER BY STARTDATE) AS STATDATE " //--车辆对应的起保日期 +" ,ROW_NUMBER() OVER(PARTITION BY VEHICLE_ID,QUOTE_ROUNT ORDER BY ENDDATE DESC) RC " //--分组排序序号 +"FROM tmp_cpi_main_car_list10_2 ") lag报错。。。。。 org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException: Lag amount must be a integer value int was passed as parameter 1.
    null2018-02-05 13:54 回复
    • lag函数第二个参数不能，为其他字段。。oracle则可以
      null2018-02-05 18:35 回复
  3. 注意： 这几个函数不支持WINDOW子句。（什么是WINDOW子句，点此查看前面的文章 ） 现在是不是已经支持WINDOW子句了
    程七2021-03-25 18:05 回复
  4. lag/lead函数在presto中的的第二个参数（表示排序的参数）的含义和hive不一样 presto从0开始，hive从1开始，，，其他没差别 算是一个坑吧
    西海2022-01-21 15:30 回复