• Hive学习之路 (十六)Hive分析窗口函数(四) LAG、LEAD、FIRST_VALUE和LAST_VALUE


    数据准备

    数据格式

    cookie4.txt

    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

    创建表

    use cookie;
    drop table if exists cookie4;
    create table cookie4(cookieid string, createtime string, url string) 
    row format delimited fields terminated by ',';
    load data local inpath "/home/hadoop/cookie4.txt" into table cookie4;
    select * from cookie4;

    玩一玩LAG

    说明

    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)

    查询语句

    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 cookie.cookie4;

    查询结果

    结果说明

    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

    玩一玩LEAD

    说明

    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)

    查询语句

    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 cookie.cookie4;

    查询结果

    结果说明

    --逻辑与LAG一样,只不过LAG是往上,LEAD是往下。

    玩一玩FIRST_VALUE

    说明

    取分组内排序后,截止到当前行,第一个值

    查询语句

    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 cookie.cookie4;

    查询结果

    玩一玩LAST_VALUE

    说明

    取分组内排序后,截止到当前行,最后一个值

    查询语句

    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 cookie.cookie4;

    查询结果

    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

    如果想要取分组内排序后最后一个值,则需要变通一下

    查询语句

    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 cookie.cookie4 
    order by cookieid,createtime;

    查询结果

     

    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/qingyunzong/p/8798606.html
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