无需创建新日历即可填充 BigQuery (SQL) 中的缺失日期

Question

我正在尝试创建一个 SQL，以便我可以在 Google Data Studio 中通过 BigQuery 的连接制作一个时间序列图表。你可以在下面看到我的 SQL。

WITH 
CTE_1 AS
(SELECT ID, Date, Min_Predict, Max_Predict, Interval
,ROW_NUMBER() OVER (PARTITION BY ID ORDER BY Date) AS row_num
FROM
    table),
    CTE_2 AS
(SELECT Date, Min_Predict, Max_Predict,
SUM(Min_Predict) OVER (ORDER BY Date) AS Min,
SUM(Max_Predict) OVER (ORDER BY Date) AS Max
FROM CTE_1
WHERE
    row_num = 1 AND Interval = 'A')

SELECT Date, Min, Max
From CTE_2
GROUP BY Date, Min, Max
ORDER BY Date

结果我得到了这张表。

Row ProgressDate            EstMin  EstMax  
1   2017-07-21T00:00:00Z    0.125   0.25
2   2017-07-24T00:00:00Z    5.125   5.375
3   2017-07-25T00:00:00Z    8.75    10.25
4   2017-07-26T00:00:00Z    10.0    12.0
5   2017-07-27T00:00:00Z    10.5    12.75
6   2017-08-01T00:00:00Z    15.25   19.125
7   2017-08-02T00:00:00Z    15.5    19.375
8   2017-08-05T00:00:00Z    16.25   20.625

如您所见，我缺少日期，例如在 21.07 和 24.07 之间。如何用前一天的数据填充那些缺失的日期？因为在数据工作室中，我在那些日子里丢失了数据，我可以将它们等于 0 但我不想要这个。

Answer 1

以下是 BigQuery 标准 SQL 并基于您当前的结果

#standardSQL
WITH your_current_result AS (
  ......
), days AS (
  SELECT day
  FROM (
    SELECT 
      MIN(DATE(TIMESTAMP(ProgressDate))) min_dt, 
      MAX(DATE(TIMESTAMP(ProgressDate))) max_dt
    FROM your_current_result
  ), UNNEST(GENERATE_DATE_ARRAY(min_dt, max_dt)) day
)
SELECT day, 
  LAST_VALUE(EstMin IGNORE NULLS) OVER(ORDER BY day) EstMin,
  LAST_VALUE(EstMax IGNORE NULLS) OVER(ORDER BY day) EstMax
FROM days
LEFT JOIN your_current_result
ON day = DATE(TIMESTAMP(ProgressDate))
-- ORDER BY day   

您可以使用问题中的输出示例来测试，玩上面

#standardSQL
WITH your_current_result AS (
  SELECT '2017-07-21T00:00:00Z' ProgressDate, 0.125 EstMin, 0.25 EstMax UNION ALL
  SELECT '2017-07-24T00:00:00Z', 5.125, 5.375 UNION ALL
  SELECT '2017-07-25T00:00:00Z', 8.75, 10.25 UNION ALL
  SELECT '2017-07-26T00:00:00Z', 10.0, 12.0 UNION ALL
  SELECT '2017-07-27T00:00:00Z', 10.5, 12.75 UNION ALL
  SELECT '2017-08-01T00:00:00Z', 15.25, 19.125 UNION ALL
  SELECT '2017-08-02T00:00:00Z', 15.5, 19.375 UNION ALL
  SELECT '2017-08-05T00:00:00Z', 16.25, 20.625 
), days AS (
  SELECT day
  FROM (
    SELECT 
      MIN(DATE(TIMESTAMP(ProgressDate))) min_dt, 
      MAX(DATE(TIMESTAMP(ProgressDate))) max_dt
    FROM your_current_result
  ), UNNEST(GENERATE_DATE_ARRAY(min_dt, max_dt)) day
)
SELECT day, 
  LAST_VALUE(EstMin IGNORE NULLS) OVER(ORDER BY day) EstMin,
  LAST_VALUE(EstMax IGNORE NULLS) OVER(ORDER BY day) EstMax
FROM days
LEFT JOIN your_current_result
ON day = DATE(TIMESTAMP(ProgressDate))
ORDER BY day  

结果

Row day         EstMin  EstMax   
1   2017-07-21  0.125   0.25     
2   2017-07-22  0.125   0.25     
3   2017-07-23  0.125   0.25     
4   2017-07-24  5.125   5.375    
5   2017-07-25  8.75    10.25    
6   2017-07-26  10.0    12.0     
7   2017-07-27  10.5    12.75    
8   2017-07-28  10.5    12.75    
9   2017-07-29  10.5    12.75    
10  2017-07-30  10.5    12.75    
11  2017-07-31  10.5    12.75    
12  2017-08-01  15.25   19.125   
13  2017-08-02  15.5    19.375   
14  2017-08-03  15.5    19.375   
15  2017-08-04  15.5    19.375   
16  2017-08-05  16.25   20.625