Hive函数:LAG,LEAD,FIRST_VALUE,LAST_VALUE
参考自大数据田地:http://lxw1234.com/archives/2015/04/190.htm
测试数据准备:
create external table test_data ( 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 '/user/jc_rc_ftp/test_data'; select * from test_data l; +-------------+----------------------+---------+--+ | l.cookieid | l.createtime | l.url | +-------------+----------------------+---------+--+ | 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 test_data; +-----------+----------------------+---------+-----+----------------------+----------------------+--+ | 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 | +-----------+----------------------+---------+-----+----------------------+----------------------+--+
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 test_data; +-----------+----------------------+---------+-----+----------------------+----------------------+--+ | 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 | +-----------+----------------------+---------+-----+----------------------+----------------------+--+
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 test_data; +-----------+----------------------+---------+-----+---------+--+ | 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 test_data; +-----------+----------------------+---------+-----+---------+--+ | 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 | +-----------+----------------------+---------+-----+---------+--+ 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 DESC) AS last1 FROM test_data; +-----------+----------------------+---------+-----+---------+--+ | cookieid | createtime | url | rn | last1 | +-----------+----------------------+---------+-----+---------+--+ | cookie1 | 2015-04-10 11:00:00 | url7 | 7 | url7 | | cookie1 | 2015-04-10 10:50:05 | url6 | 6 | url6 | | cookie1 | 2015-04-10 10:50:01 | url5 | 5 | url5 | | cookie1 | 2015-04-10 10:10:00 | url4 | 4 | url4 | | cookie1 | 2015-04-10 10:03:04 | 1url3 | 3 | 1url3 | | cookie1 | 2015-04-10 10:00:02 | url2 | 2 | url2 | | cookie1 | 2015-04-10 10:00:00 | url1 | 1 | url1 | | cookie2 | 2015-04-10 11:00:00 | url77 | 7 | url77 | | cookie2 | 2015-04-10 10:50:05 | url66 | 6 | url66 | | cookie2 | 2015-04-10 10:50:01 | url55 | 5 | url55 | | cookie2 | 2015-04-10 10:10:00 | url44 | 4 | url44 | | cookie2 | 2015-04-10 10:03:04 | 1url33 | 3 | 1url33 | | cookie2 | 2015-04-10 10:00:02 | url22 | 2 | url22 | | cookie2 | 2015-04-10 10:00:00 | url11 | 1 | url11 | +-----------+----------------------+---------+-----+---------+--+
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 test_data; +-----------+----------------------+---------+---------+--+ | cookieid | createtime | url | first2 | +-----------+----------------------+---------+---------+--+ | cookie1 | 2015-04-10 10:00:02 | url2 | url2 | | cookie1 | 2015-04-10 10:50:01 | url5 | url2 | | cookie1 | 2015-04-10 10:10:00 | url4 | url2 | | cookie1 | 2015-04-10 11:00:00 | url7 | url2 | | cookie1 | 2015-04-10 10:50:05 | url6 | url2 | | cookie1 | 2015-04-10 10:03:04 | 1url3 | url2 | | cookie1 | 2015-04-10 10:00:00 | url1 | url2 | | cookie2 | 2015-04-10 10:50:01 | url55 | url55 | | cookie2 | 2015-04-10 10:10:00 | url44 | url55 | | cookie2 | 2015-04-10 11:00:00 | url77 | url55 | | cookie2 | 2015-04-10 10:50:05 | url66 | url55 | | cookie2 | 2015-04-10 10:03:04 | 1url33 | url55 | | cookie2 | 2015-04-10 10:00:00 | url11 | url55 | | cookie2 | 2015-04-10 10:00:02 | url22 | url55 | +-----------+----------------------+---------+---------+--+ SELECT cookieid, createtime, url, LAST_VALUE(url) OVER(PARTITION BY cookieid) AS last2 FROM test_data; +-----------+----------------------+---------+--------+--+ | cookieid | createtime | url | last2 | +-----------+----------------------+---------+--------+--+ | cookie1 | 2015-04-10 10:00:02 | url2 | url1 | | cookie1 | 2015-04-10 10:50:01 | url5 | url1 | | cookie1 | 2015-04-10 10:10:00 | url4 | url1 | | cookie1 | 2015-04-10 11:00:00 | url7 | url1 | | cookie1 | 2015-04-10 10:50:05 | url6 | url1 | | cookie1 | 2015-04-10 10:03:04 | 1url3 | url1 | | cookie1 | 2015-04-10 10:00:00 | url1 | url1 | | cookie2 | 2015-04-10 10:50:01 | url55 | url22 | | cookie2 | 2015-04-10 10:10:00 | url44 | url22 | | cookie2 | 2015-04-10 11:00:00 | url77 | url22 | | cookie2 | 2015-04-10 10:50:05 | url66 | url22 | | cookie2 | 2015-04-10 10:03:04 | 1url33 | url22 | | cookie2 | 2015-04-10 10:00:00 | url11 | url22 | | cookie2 | 2015-04-10 10:00:02 | url22 | url22 | +-----------+----------------------+---------+--------+--+ 14 rows selected (78.058 seconds)
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 test_data 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 | +-----------+----------------------+---------+-----+---------+--------+--+
基础才是编程人员应该深入研究的问题,比如:
1)List/Set/Map内部组成原理|区别
2)mysql索引存储结构&如何调优/b-tree特点、计算复杂度及影响复杂度的因素。。。
3)JVM运行组成与原理及调优
4)Java类加载器运行原理
5)Java中GC过程原理|使用的回收算法原理
6)Redis中hash一致性实现及与hash其他区别
7)Java多线程、线程池开发、管理Lock与Synchroined区别
8)Spring IOC/AOP 原理;加载过程的。。。
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