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LAG,LEAD,FIRST_VALUE,LAST_VALUE 注意： 这几个函数不支持WINDOW子句 数据准备： 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 LAGLAG(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 10:50:01last_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 LEAD--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
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