选择在Hive中满足条件的前一行。

Question

选择在Hive中满足条件的前一行。

sqlhivewindow-functionslagmoving-average

8

我有这样的产品数据

Product   Date            Sales   Availbility
    xyz      2017-12-31      724.5   6.0
    xyz      2018-01-07      362.25  7.0
    xyz      2018-01-14      281.75  7.0
    xyz      2018-01-21      442.75  7.0
    xyz      2018-01-28      442.75  6.0
    xyz      2018-02-04      402.5   7.0
    xyz      2018-02-11      201.25  3.0
    xyz      2018-02-18      120.75  0.0
    xyz      2018-02-25      40.25   0.0
    xyz      2018-03-11      201.25  0.0
    xyz      2018-03-18      483.0   5.0
    xyz      2018-03-25      322.0   7.0
    xyz      2018-04-01      241.5   7.0
    xyz      2018-04-08      281.75  7.0
    xyz      2018-04-15      523.25  7.0
    xyz      2018-04-22      241.5   7.0
    xyz      2018-04-29      362.25  7.0

数据没有排序（一个小问题），我想要做的是，无论在可用性列（第四列）中有多少个0，我都想要取前三周（这三周的可用性都是满的，即7）的平均值。

类似下面的方式：

xyz      2017-12-31      724.5   6.0     Null 
xyz      2018-01-07      362.25  7.0     362.25 ( Same value for weeks with availbility = 7) 
xyz      2018-01-14      281.75  7.0     281.75
xyz      2018-01-21      442.75  7.0     442.75 
xyz      2018-01-28      442.75  6.0     361 (362 + 281 + 362/3)the prior fully availble week avg which is avilble)
xyz      2018-02-04      402.5   7.0     402
xyz      2018-02-11      201.25  3.0     375 (402 + 442 + 281 /3)
xyz      2018-02-18      120.75  0.0     375 ( Same since 375 is the most recent 4 fully availble average)
xyz      2018-02-25      40.25   0.0     375
xyz      2018-03-11      201.25  0.0     375
xyz      2018-03-18      483.0   5.0     375
xyz      2018-03-25      322.0   7.0     322
xyz      2018-04-01      241.5   7.0     241
xyz      2018-04-08      281.75  7.0     281
xyz      2018-04-15      523.25  7.0     523
xyz      2018-04-22      241.5   7.0     241
xyz      2018-04-29      362.25  7.0     362

我尝试通过找到仅包括完全可用的三周平均值并将其与其余几周合并来解决这个问题，后来尝试使用滞后函数来检索最近的平均值。

select a.*,lag(case when a.Full_availble_sales >0 then a.Full_availble_sales end,1) over (partition by a.asin order by a.week_beginning) as Four_wk_avg  from (select asin,week_beginning,avg(sales) as weekly_sales,sum(available_to_purchase) as weekly_availbility,0 as Full_availble_sales from t1 where asin = 'xyz' group by asin,week_beginning having sum(available_to_purchase) < 7
union all
select t.asin,t.week_beginning,t.weekly_sales,t.weekly_availbility,avg(t.weekly_sales) over (partition by t.asin order by t.week_beginning rows between 3 preceding and current row ) as Full_availble_sales from 
(select asin,week_beginning,avg(sales) as weekly_sales,sum(available_to_purchase) as weekly_availbility from t1 where asin = 'xyz' group by asin,week_beginning having sum(available_to_purchase) = 7)t ) a  order by a.week_beginning

输出结果为

xyz      2017-12-31      724.5   6.0     0.0     NULL
xyz      2018-01-07      362.25  7.0     362.25  NULL
xyz      2018-01-14      281.75  7.0     322.0   362.25
xyz      2018-01-21      442.75  7.0     362.25  322.0
xyz      2018-01-28      442.75  6.0     0.0     362.25
xyz      2018-02-04      402.5   7.0     372.3125        NULL
xyz      2018-02-11      201.25  3.0     0.0     372.3125
xyz      2018-02-18      120.75  0.0     0.0     NULL
xyz      2018-02-25      40.25   0.0     0.0     NULL
xyz      2018-03-11      201.25  0.0     0.0     NULL
xyz      2018-03-18      483.0   5.0     0.0     NULL
xyz      2018-03-25      322.0   7.0     362.25  NULL
xyz      2018-04-01      241.5   7.0     352.1875        362.25
xyz      2018-04-08      281.75  7.0     311.9375        352.1875
xyz      2018-04-15      523.25  7.0     342.125 311.9375
xyz      2018-04-22      241.5   7.0     322.0   342.125
xyz      2018-04-29      362.25  7.0     352.1875        322.0

这不是我想要的。

- av abhishiek

1个回答

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原文链接

- Chananel P · Accepted Answer

这将完成任务（在窗口上使用聚合函数avg和max_by）

WITH
   tt1  (Product,Date_week_beginning,Sales,Availbility) AS 
      ( SELECT * FROM ( VALUES 
      ('xyz','2017-12-31',  724.5   ,6.0),
      ('xyz','2018-01-07',  362.25  ,7.0),
      ('xyz','2018-01-14',  281.75  ,7.0),
      ('xyz','2018-01-21',  442.75  ,7.0),
      ('xyz','2018-01-28',  442.75  ,6.0),
      ('xyz','2018-02-04',  402.5   ,7.0),
      ('xyz','2018-02-11',  201.25  ,3.0),
      ('xyz','2018-02-18',  120.75  ,0.0),
      ('xyz','2018-02-25',  40.25   ,0.0),
      ('xyz','2018-03-11',  201.25  ,0.0),
      ('xyz','2018-03-18',  483.0   ,5.0),
      ('xyz','2018-03-25',  322.0   ,7.0),
      ('xyz','2018-04-01',  241.5   ,7.0),
      ('xyz','2018-04-08',  281.75  ,7.0),
      ('xyz','2018-04-15',  523.25  ,7.0),
      ('xyz','2018-04-22',  241.5   ,7.0),
      ('xyz','2018-04-29',  362.25  ,7.0) )  
   ), tt2 AS (
      SELECT *, avg(sales) OVER (partition by Product order by if(Availbility = 7.0,1),Date_week_beginning ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) avg3
      FROM tt1
   )
   SELECT Product,Date_week_beginning,Sales,Availbility, 
          CASE WHEN Availbility = 7.0 THEN Sales
             ELSE
                 max_by(if(Availbility = 7.0,avg3),(Availbility = 7.0, Date_week_beginning) ) OVER (partition by Product order by Date_week_beginning)
             END new_col   
   FROM tt2
   ORDER BY Product,Date_week_beginning

结果完全符合要求：

Product Date_week_beginning Sales    Availbility  new_col
xyz     2017-12-31          724.5    6.0          NULL
xyz     2018-01-07          362.25   7.0          362.25
xyz     2018-01-14          281.75   7.0          281.75
xyz     2018-01-21          442.75   7.0          442.75
xyz     2018-01-28          442.75   6.0          362.25
xyz     2018-02-04          402.5    7.0          402.5
xyz     2018-02-11          201.25   3.0          375.6666666666667
xyz     2018-02-18          120.75   0.0          375.6666666666667
xyz     2018-02-25          40.25    0.0          375.6666666666667
xyz     2018-03-11          201.25   0.0          375.6666666666667
xyz     2018-03-18          483.0    5.0          375.6666666666667
xyz     2018-03-25          322.0    7.0          322.0
xyz     2018-04-01          241.5    7.0          241.5
xyz     2018-04-08          281.75   7.0          281.75
xyz     2018-04-15          523.25   7.0          523.25
xyz     2018-04-22          241.5    7.0          241.5
xyz     2018-04-29          362.25   7.0          362.25

我假设问题中有两个错别字（可以从示例中验证）：

1. 问题中的这一行是错误的：361 (362 + 281 + 362/3)the prior fully availble week avg which is avilble) 应该是 361 (442 + 281 + 362/3)the prior fully availble week avg which is avilble) 2. 句子：“what I want to do is that wherever we have 0 in the availbility column (4th column)..” 应该是 “what I want to do is that wherever we do not have 7.0 in the availbility column (4th column)..”