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  • Hive的窗口函数

    这老哥的窗口函数总结的十分不错,我就拿来主义了,附上地址 http://lxw1234.com/archives/2015/04/190.htm

    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。

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  • 原文地址:https://www.cnblogs.com/kingning/p/14106185.html
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