SQL/BIGQUERY 运行 日期中有 GAP 的平均值

SQL/BIGQUERY Running Average with GAPs in Dates

我在 BigQuery/SQL 中遇到移动平均线问题,我有 table 'SCORES' 并且我需要在使用用户对数据进行分组时制作 30 天移动平均线,问题是我的日期不是连续的,例如其中有间隔。

下面是我当前的代码:

SELECT user, date,
      AVG(score) OVER (PARTITION BY user ORDER BY date)
FROM SCORES;

我不知道如何将日期限制添加到该行中,或者这是否可能。

我目前的 table 看起来像这样,但当然有更多的用户:

user    date    score
AA  13/02/2018  2.00
AA  15/02/2018  3.00
AA  17/02/2018  4.00
AA  01/03/2018  5.00
AA  28/03/2018  6.00

然后我需要它变成这样:

user    date    score   30D Avg
AA  13/02/2018  2.00    2.00
AA  15/02/2018  3.00    2.50
AA  17/02/2018  4.00    3.00
AA  01/03/2018  5.00    3.50
AA  28/03/2018  6.00    5.50

在最后一行中,由于日期原因,它只向后测量一个(向后最多 30 天)有什么方法可以在 SQL 中实现这个,还是我要求太多了?

您想使用 range between。为此,您需要一个整数,因此:

select s.*,
       avg(score) over (partition by user
                        order by days
                        range between 29 preceding and current row
                       ) as avg_30day
from (select s.*, date_diff(s.date, date('2000-01-01'), day) as days
      from scores s
     ) s;

date_diff() 的替代方法是 unix_date():

select s.*,
       avg(score) over (partition by user
                        order by unix_days
                        range between 29 preceding and current row
                       ) as avg_30day
from (select s.*, unix_date(s.date) as unix_days
      from scores s
     ) s;

以下适用于 BigQuery 标准 SQL

#standardSQL
SELECT *,
  AVG(score) OVER (
    PARTITION BY user 
    ORDER BY UNIX_DATE(PARSE_DATE('%d/%m/%Y', date))
    RANGE BETWEEN 29 PRECEDING AND CURRENT ROW
  ) AS avg_30day 
FROM `project.dataset.scores` 

您可以使用问题中的虚拟数据测试/玩上面的内容

#standardSQL
WITH `project.dataset.scores` AS (
  SELECT 'AA' user, '13/02/2018' date, 2.00 score UNION ALL
  SELECT 'AA', '15/02/2018', 3.00 UNION ALL
  SELECT 'AA', '17/02/2018', 4.00 UNION ALL
  SELECT 'AA', '01/03/2018', 5.00 UNION ALL
  SELECT 'AA', '28/03/2018', 6.00 
)
SELECT *,
  AVG(score) OVER (
    PARTITION BY user 
    ORDER BY UNIX_DATE(PARSE_DATE('%d/%m/%Y', date))
    RANGE BETWEEN 29 PRECEDING AND CURRENT ROW
  ) AS avg_30day 
FROM `project.dataset.scores` 

结果

Row user    date        score   avg_30day    
1   AA      13/02/2018  2.0     2.0  
2   AA      15/02/2018  3.0     2.5  
3   AA      17/02/2018  4.0     3.0  
4   AA      01/03/2018  5.0     3.5  
5   AA      28/03/2018  6.0     5.5