HIVE分析窗口函数: LAG,LEAD,FIRST_VALUE,LAST_VALUE

本文转载自:lxw的大数据田地 » Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE

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:

   
   
   
   
  1. cookie1,2015-04-10 10:00:02,url2
  2. cookie1,2015-04-10 10:00:00,url1
  3. cookie1,2015-04-10 10:03:04,1url3
  4. cookie1,2015-04-10 10:50:05,url6
  5. cookie1,2015-04-10 11:00:00,url7
  6. cookie1,2015-04-10 10:10:00,url4
  7. cookie1,2015-04-10 10:50:01,url5
  8. cookie2,2015-04-10 10:00:02,url22
  9. cookie2,2015-04-10 10:00:00,url11
  10. cookie2,2015-04-10 10:03:04,1url33
  11. cookie2,2015-04-10 10:50:05,url66
  12. cookie2,2015-04-10 11:00:00,url77
  13. cookie2,2015-04-10 10:10:00,url44
  14. cookie2,2015-04-10 10:50:01,url55
  15.  
  16. CREATE EXTERNAL TABLE lxw1234 (
  17. cookieid string,
  18. createtime string, --页面访问时间
  19. url STRING --被访问页面
  20. ) ROW FORMAT DELIMITED
  21. FIELDS TERMINATED BY ','
  22. stored as textfile location '/tmp/lxw11/';
  23.  
  24.  
  25. hive> select * from lxw1234;
  26. OK
  27. cookie1 2015-04-10 10:00:02 url2
  28. cookie1 2015-04-10 10:00:00 url1
  29. cookie1 2015-04-10 10:03:04 1url3
  30. cookie1 2015-04-10 10:50:05 url6
  31. cookie1 2015-04-10 11:00:00 url7
  32. cookie1 2015-04-10 10:10:00 url4
  33. cookie1 2015-04-10 10:50:01 url5
  34. cookie2 2015-04-10 10:00:02 url22
  35. cookie2 2015-04-10 10:00:00 url11
  36. cookie2 2015-04-10 10:03:04 1url33
  37. cookie2 2015-04-10 10:50:05 url66
  38. cookie2 2015-04-10 11:00:00 url77
  39. cookie2 2015-04-10 10:10:00 url44
  40. 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)

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
  5. LAG(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS last_1_time,
  6. LAG(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS last_2_time
  7. FROM lxw1234;
  8.  
  9.  
  10. cookieid createtime url rn last_1_time last_2_time
  11. -------------------------------------------------------------------------------------------
  12. cookie1 2015-04-10 10:00:00 url1 1 1970-01-01 00:00:00 NULL
  13. cookie1 2015-04-10 10:00:02 url2 2 2015-04-10 10:00:00 NULL
  14. cookie1 2015-04-10 10:03:04 1url3 3 2015-04-10 10:00:02 2015-04-10 10:00:00
  15. cookie1 2015-04-10 10:10:00 url4 4 2015-04-10 10:03:04 2015-04-10 10:00:02
  16. cookie1 2015-04-10 10:50:01 url5 5 2015-04-10 10:10:00 2015-04-10 10:03:04
  17. cookie1 2015-04-10 10:50:05 url6 6 2015-04-10 10:50:01 2015-04-10 10:10:00
  18. cookie1 2015-04-10 11:00:00 url7 7 2015-04-10 10:50:05 2015-04-10 10:50:01
  19. cookie2 2015-04-10 10:00:00 url11 1 1970-01-01 00:00:00 NULL
  20. cookie2 2015-04-10 10:00:02 url22 2 2015-04-10 10:00:00 NULL
  21. cookie2 2015-04-10 10:03:04 1url33 3 2015-04-10 10:00:02 2015-04-10 10:00:00
  22. cookie2 2015-04-10 10:10:00 url44 4 2015-04-10 10:03:04 2015-04-10 10:00:02
  23. cookie2 2015-04-10 10:50:01 url55 5 2015-04-10 10:10:00 2015-04-10 10:03:04
  24. cookie2 2015-04-10 10:50:05 url66 6 2015-04-10 10:50:01 2015-04-10 10:10:00
  25. cookie2 2015-04-10 11:00:00 url77 7 2015-04-10 10:50:05 2015-04-10 10:50:01
  26.  
  27.  
  28. last_1_time: 指定了往上第1行的值,default'1970-01-01 00:00:00'
  29. cookie1第一行,往上1行为NULL,因此取默认值 1970-01-01 00:00:00
  30. cookie1第三行,往上1行值为第二行值,2015-04-10 10:00:02
  31. cookie1第六行,往上1行值为第五行值,2015-04-10 10:50:01
  32. last_2_time: 指定了往上第2行的值,为指定默认值
  33. cookie1第一行,往上2行为NULL
  34. cookie1第二行,往上2行为NULL
  35. cookie1第四行,往上2行为第二行值,2015-04-10 10:00:02
  36. 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)

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
  5. LEAD(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS next_1_time,
  6. LEAD(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS next_2_time
  7. FROM lxw1234;
  8.  
  9.  
  10. cookieid createtime url rn next_1_time next_2_time
  11. -------------------------------------------------------------------------------------------
  12. cookie1 2015-04-10 10:00:00 url1 1 2015-04-10 10:00:02 2015-04-10 10:03:04
  13. cookie1 2015-04-10 10:00:02 url2 2 2015-04-10 10:03:04 2015-04-10 10:10:00
  14. cookie1 2015-04-10 10:03:04 1url3 3 2015-04-10 10:10:00 2015-04-10 10:50:01
  15. cookie1 2015-04-10 10:10:00 url4 4 2015-04-10 10:50:01 2015-04-10 10:50:05
  16. cookie1 2015-04-10 10:50:01 url5 5 2015-04-10 10:50:05 2015-04-10 11:00:00
  17. cookie1 2015-04-10 10:50:05 url6 6 2015-04-10 11:00:00 NULL
  18. cookie1 2015-04-10 11:00:00 url7 7 1970-01-01 00:00:00 NULL
  19. cookie2 2015-04-10 10:00:00 url11 1 2015-04-10 10:00:02 2015-04-10 10:03:04
  20. cookie2 2015-04-10 10:00:02 url22 2 2015-04-10 10:03:04 2015-04-10 10:10:00
  21. cookie2 2015-04-10 10:03:04 1url33 3 2015-04-10 10:10:00 2015-04-10 10:50:01
  22. cookie2 2015-04-10 10:10:00 url44 4 2015-04-10 10:50:01 2015-04-10 10:50:05
  23. cookie2 2015-04-10 10:50:01 url55 5 2015-04-10 10:50:05 2015-04-10 11:00:00
  24. cookie2 2015-04-10 10:50:05 url66 6 2015-04-10 11:00:00 NULL
  25. cookie2 2015-04-10 11:00:00 url77 7 1970-01-01 00:00:00 NULL
  26.  
  27. --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

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
  5. FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS first1
  6. FROM lxw1234;
  7.  
  8. cookieid createtime url rn first1
  9. ---------------------------------------------------------
  10. cookie1 2015-04-10 10:00:00 url1 1 url1
  11. cookie1 2015-04-10 10:00:02 url2 2 url1
  12. cookie1 2015-04-10 10:03:04 1url3 3 url1
  13. cookie1 2015-04-10 10:10:00 url4 4 url1
  14. cookie1 2015-04-10 10:50:01 url5 5 url1
  15. cookie1 2015-04-10 10:50:05 url6 6 url1
  16. cookie1 2015-04-10 11:00:00 url7 7 url1
  17. cookie2 2015-04-10 10:00:00 url11 1 url11
  18. cookie2 2015-04-10 10:00:02 url22 2 url11
  19. cookie2 2015-04-10 10:03:04 1url33 3 url11
  20. cookie2 2015-04-10 10:10:00 url44 4 url11
  21. cookie2 2015-04-10 10:50:01 url55 5 url11
  22. cookie2 2015-04-10 10:50:05 url66 6 url11
  23. 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

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
  5. LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1
  6. FROM lxw1234;
  7.  
  8.  
  9. cookieid createtime url rn last1
  10. -----------------------------------------------------------------
  11. cookie1 2015-04-10 10:00:00 url1 1 url1
  12. cookie1 2015-04-10 10:00:02 url2 2 url2
  13. cookie1 2015-04-10 10:03:04 1url3 3 1url3
  14. cookie1 2015-04-10 10:10:00 url4 4 url4
  15. cookie1 2015-04-10 10:50:01 url5 5 url5
  16. cookie1 2015-04-10 10:50:05 url6 6 url6
  17. cookie1 2015-04-10 11:00:00 url7 7 url7
  18. cookie2 2015-04-10 10:00:00 url11 1 url11
  19. cookie2 2015-04-10 10:00:02 url22 2 url22
  20. cookie2 2015-04-10 10:03:04 1url33 3 1url33
  21. cookie2 2015-04-10 10:10:00 url44 4 url44
  22. cookie2 2015-04-10 10:50:01 url55 5 url55
  23. cookie2 2015-04-10 10:50:05 url66 6 url66
  24. 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

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. FIRST_VALUE(url) OVER(PARTITION BY cookieid) AS first2
  5. FROM lxw1234;
  6.  
  7. cookieid createtime url first2
  8. ----------------------------------------------
  9. cookie1 2015-04-10 10:00:02 url2 url2
  10. cookie1 2015-04-10 10:00:00 url1 url2
  11. cookie1 2015-04-10 10:03:04 1url3 url2
  12. cookie1 2015-04-10 10:50:05 url6 url2
  13. cookie1 2015-04-10 11:00:00 url7 url2
  14. cookie1 2015-04-10 10:10:00 url4 url2
  15. cookie1 2015-04-10 10:50:01 url5 url2
  16. cookie2 2015-04-10 10:00:02 url22 url22
  17. cookie2 2015-04-10 10:00:00 url11 url22
  18. cookie2 2015-04-10 10:03:04 1url33 url22
  19. cookie2 2015-04-10 10:50:05 url66 url22
  20. cookie2 2015-04-10 11:00:00 url77 url22
  21. cookie2 2015-04-10 10:10:00 url44 url22
  22. cookie2 2015-04-10 10:50:01 url55 url22
  23.  
  24. SELECT cookieid,
  25. createtime,
  26. url,
  27. LAST_VALUE(url) OVER(PARTITION BY cookieid) AS last2
  28. FROM lxw1234;
  29.  
  30. cookieid createtime url last2
  31. ----------------------------------------------
  32. cookie1 2015-04-10 10:00:02 url2 url5
  33. cookie1 2015-04-10 10:00:00 url1 url5
  34. cookie1 2015-04-10 10:03:04 1url3 url5
  35. cookie1 2015-04-10 10:50:05 url6 url5
  36. cookie1 2015-04-10 11:00:00 url7 url5
  37. cookie1 2015-04-10 10:10:00 url4 url5
  38. cookie1 2015-04-10 10:50:01 url5 url5
  39. cookie2 2015-04-10 10:00:02 url22 url55
  40. cookie2 2015-04-10 10:00:00 url11 url55
  41. cookie2 2015-04-10 10:03:04 1url33 url55
  42. cookie2 2015-04-10 10:50:05 url66 url55
  43. cookie2 2015-04-10 11:00:00 url77 url55
  44. cookie2 2015-04-10 10:10:00 url44 url55
  45. 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:

   
   
   
   
  1. SELECT cookieid,
  2. createtime,
  3. url,
  4. ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
  5. LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1,
  6. FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime DESC) AS last2
  7. FROM lxw1234
  8. ORDER BY cookieid,createtime;
  9.  
  10. cookieid createtime url rn last1 last2
  11. -------------------------------------------------------------
  12. cookie1 2015-04-10 10:00:00 url1 1 url1 url7
  13. cookie1 2015-04-10 10:00:02 url2 2 url2 url7
  14. cookie1 2015-04-10 10:03:04 1url3 3 1url3 url7
  15. cookie1 2015-04-10 10:10:00 url4 4 url4 url7
  16. cookie1 2015-04-10 10:50:01 url5 5 url5 url7
  17. cookie1 2015-04-10 10:50:05 url6 6 url6 url7
  18. cookie1 2015-04-10 11:00:00 url7 7 url7 url7
  19. cookie2 2015-04-10 10:00:00 url11 1 url11 url77
  20. cookie2 2015-04-10 10:00:02 url22 2 url22 url77
  21. cookie2 2015-04-10 10:03:04 1url33 3 1url33 url77
  22. cookie2 2015-04-10 10:10:00 url44 4 url44 url77
  23. cookie2 2015-04-10 10:50:01 url55 5 url55 url77
  24. cookie2 2015-04-10 10:50:05 url66 6 url66 url77
  25. 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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