Sql 缺少值的BIGQUERY移动平均值_Sql_Google Bigquery_Moving Average

Sql 缺少值的BIGQUERY移动平均值

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Sql 缺少值的BIGQUERY移动平均值,sql,google-bigquery,moving-average,Sql,Google Bigquery,Moving Average,我有以下数据 with dummy_data as ( SELECT '2017-01-01' as ref_month, 18 as value, 1 as id UNION ALL SELECT '2017-02-01' as ref_month, 20 as value, 1 as id UNION ALL SELECT '2017-03-01' as ref_month, 22 as value, 1 as id -- UNION ALL SELECT '2017-04-01' as

我有以下数据

with dummy_data as 
(
SELECT '2017-01-01' as ref_month, 18 as value, 1 as id
UNION ALL SELECT '2017-02-01' as ref_month, 20 as value, 1 as id
UNION ALL SELECT '2017-03-01' as ref_month, 22 as value, 1 as id
-- UNION ALL SELECT '2017-04-01' as ref_month, 28 as value, 1 as id
UNION ALL SELECT '2017-05-01' as ref_month, 30 as value, 1 as id
UNION ALL SELECT '2017-06-01' as ref_month, 37 as value, 1 as id
UNION ALL SELECT '2017-07-01' as ref_month, 42 as value, 1 as id
-- UNION ALL SELECT '2017-08-01' as ref_month, 55 as value, 1 as id
-- UNION ALL SELECT '2017-09-01' as ref_month, 49 as value, 1 as id
UNION ALL SELECT '2017-10-01' as ref_month, 51 as value, 1 as id
UNION ALL SELECT '2017-11-01' as ref_month, 57 as value, 1 as id
UNION ALL SELECT '2017-12-01' as ref_month, 56 as value, 1 as id
UNION ALL SELECT '2017-01-01' as ref_month, 18 as value, 2 as id
UNION ALL SELECT '2017-02-01' as ref_month, 20 as value, 2 as id
UNION ALL SELECT '2017-03-01' as ref_month, 22 as value, 2 as id
UNION ALL SELECT '2017-04-01' as ref_month, 28 as value, 2 as id
-- UNION ALL SELECT '2017-05-01' as ref_month, 30 as value, 2 as id
-- UNION ALL SELECT '2017-06-01' as ref_month, 37 as value, 2 as id
UNION ALL SELECT '2017-07-01' as ref_month, 42 as value, 2 as id
UNION ALL SELECT '2017-08-01' as ref_month, 55 as value, 2 as id
UNION ALL SELECT '2017-09-01' as ref_month, 49 as value, 2 as id
-- UNION ALL SELECT '2017-10-01' as ref_month, 51 as value, 2 as id
UNION ALL SELECT '2017-11-01' as ref_month, 57 as value, 2 as id
UNION ALL SELECT '2017-12-01' as ref_month, 56 as value, 2 as id
)

我想计算每个id的移动平均值。我知道你可以做如下的事情

select 
    id
  , ref_month
  , avg(value) over (partition by id order by ref_month ROWS BETWEEN 5 PRECEDING AND CURRENT ROW ) as moving_avg
from 
    dummy_data

但正如您从我的虚拟数据中看到的，有一些缺少的值。当缺少一些值时，如何轻松计算移动平均线？我想先计算一个完整的日期范围

date_range AS
(
  SELECT reference_month
  FROM UNNEST(
      GENERATE_DATE_ARRAY(PARSE_DATE('%Y-%m-%d', (SELECT MIN(ref_month) FROM dummy_data)), PARSE_DATE('%Y-%m-%d', (SELECT MAX(ref_month) FROM dummy_data)), INTERVAL 1 MONTH)
  ) AS reference_month
)

然后用ID做笛卡尔积，然后用我的虚拟数据连接回来，但这似乎是一种反模式。有没有关于如何以最佳方式实现这一点的想法？谢谢

编辑：

预期结果：对于id 1：

2017-01-01  18
2017-02-01  19
2017-03-01  20
2017-05-01  18
2017-06-01  21.8
2017-07-01  26.2
2017-10-01  26
2017-11-01  30
2017-12-01  32.8

对于id 2：

2017-01-01  18
2017-02-01  19
2017-03-01  20
2017-04-01  22
2017-07-01  18.4
2017-08-01  25
2017-09-01  29.2
2017-11-01  40.6
2017-12-01  43.4

这应该起作用：

with dummy_data as 
(
SELECT '2017-01-01' as ref_month, 18 as value, 1 as id
UNION ALL SELECT '2017-02-01' as ref_month, 20 as value, 1 as id
UNION ALL SELECT '2017-03-01' as ref_month, 22 as value, 1 as id
-- UNION ALL SELECT '2017-04-01' as ref_month, 28 as value, 1 as id
UNION ALL SELECT '2017-05-01' as ref_month, 30 as value, 1 as id
UNION ALL SELECT '2017-06-01' as ref_month, 37 as value, 1 as id
UNION ALL SELECT '2017-07-01' as ref_month, 42 as value, 1 as id
-- UNION ALL SELECT '2017-08-01' as ref_month, 55 as value, 1 as id
-- UNION ALL SELECT '2017-09-01' as ref_month, 49 as value, 1 as id
UNION ALL SELECT '2017-10-01' as ref_month, 51 as value, 1 as id
UNION ALL SELECT '2017-11-01' as ref_month, 57 as value, 1 as id
UNION ALL SELECT '2017-12-01' as ref_month, 56 as value, 1 as id
UNION ALL SELECT '2017-01-01' as ref_month, 18 as value, 2 as id
UNION ALL SELECT '2017-02-01' as ref_month, 20 as value, 2 as id
UNION ALL SELECT '2017-03-01' as ref_month, 22 as value, 2 as id
UNION ALL SELECT '2017-04-01' as ref_month, 28 as value, 2 as id
-- UNION ALL SELECT '2017-05-01' as ref_month, 30 as value, 2 as id
-- UNION ALL SELECT '2017-06-01' as ref_month, 37 as value, 2 as id
UNION ALL SELECT '2017-07-01' as ref_month, 42 as value, 2 as id
UNION ALL SELECT '2017-08-01' as ref_month, 55 as value, 2 as id
UNION ALL SELECT '2017-09-01' as ref_month, 49 as value, 2 as id
-- UNION ALL SELECT '2017-10-01' as ref_month, 51 as value, 2 as id
UNION ALL SELECT '2017-11-01' as ref_month, 57 as value, 2 as id
UNION ALL SELECT '2017-12-01' as ref_month, 56 as value, 2 as id
)


select 
    id
  , ref_month
  , avg(avg(value)) over (partition by id order by ref_month) as moving_avg
from 
    dummy_data
    group by id
  , ref_month

如果希望将值视为0，而希望为5，则一系列滞后可能是最简单的方法：

select id, ref_month,
       (value +
        (case when lag(ref_month) over (partition by id order by ref_month) > date_add(ref_month, interval -4 month)
              then lag(value, 1) over (partition by id order by ref_month)
              else 0
         end) +
        (case when lag(ref_month, 2) over (partition by id order by ref_month) > date_add(ref_month, interval -4 month)
              then lag(value, 2) over (partition by id order by ref_month)
              else 0
         end) +
        (case when lag(ref_month, 3) over (partition by id order by ref_month) > date_add(ref_month, interval -4 month)
              then lag(value, 3) over (partition by id order by ref_month)
              else 0
         end) +
        (case when lag(ref_month, 4) over (partition by id order by ref_month) > date_add(ref_month, interval -4 month)
              then lag(value, 4) over (partition by id order by ref_month)
              else 0
         end)
       ) / 
       least(5, date_diff(min(ref_month) over (partition by id), ref_month))
from dummy_data;

查询比逻辑更复杂。它基本上是将最近的五个值除以5相加。但它会影响边界条件以及缺少的值。

下面是针对BigQuery标准SQL的，并且实际有效！：o 它假设您的ref_month是日期数据类型，如果您将其作为字符串-仍然可以-请参阅我答案底部的注释

标准SQL 选择身份证件参考月，滚动六天的总价值/ 最后一个月滚动六天的位置 -首个月滚动六天的位置 + 1 作为正确的\u移动\u平均值从…起选择id、参考月份、值、，日期/月份，'2016-01-01'，月份/月份位置从虚拟数据窗口滚动六天按id顺序按月份分区\u位置范围在前5行和当前行之间您可以使用下面的示例数据测试/使用它

标准SQL 使用虚拟_数据作为选择日期“2017-01-01”作为参考月，选择18作为值，选择1作为id UNION ALL选择日期“2017-02-01”作为参考月，选择20作为值，选择1作为id UNION ALL选择日期“2017-03-01”作为参考月，选择22作为值，选择1作为id -UNION ALL选择日期“2017-04-01”作为参考月，选择28作为值，选择1作为id UNION ALL选择日期“2017-05-01”作为参考月，选择30作为值，选择1作为id UNION ALL选择日期“2017-06-01”作为参考月，选择37作为值，选择1作为id UNION ALL选择日期“2017-07-01”作为参考月，选择42作为值，选择1作为id -UNION ALL选择日期“2017-08-01”作为参考月，55作为值，1作为id -UNION ALL选择日期“2017-09-01”作为参考月，49作为值，1作为id UNION ALL选择日期“2017-10-01”作为参考月，51作为值，1作为id UNION ALL选择日期“2017-11-01”作为参考月，选择57作为值，选择1作为id UNION ALL选择日期“2017-12-01”作为参考月，选择56作为值，选择1作为id UNION ALL选择日期“2017-01-01”作为参考月，18作为值，2作为id UNION ALL选择日期“2017-02-01”作为参考月，选择20作为值，选择2作为id UNION ALL选择日期“2017-03-01”作为参考月，选择22作为值，选择2作为id UNION ALL选择日期“2017-04-01”作为参考月，选择28作为值，选择2作为id -UNION ALL选择日期“2017-05-01”作为参考月，选择30作为值，选择2作为id -UNION ALL选择日期“2017-06-01”作为参考月，选择37作为值，选择2作为id UNION ALL选择日期“2017-07-01”作为参考月，选择42作为值，选择2作为id UNION ALL选择日期“2017-08-01”作为参考月，55作为值，2作为id UNION ALL选择日期“2017-09-01”作为参考月，49作为值，2作为id -UNION ALL选择日期“2017-10-01”作为参考月，51作为值，2作为id UNION ALL选择日期“2017-11-01”作为参考月，选择57作为值，选择2作为id UNION ALL选择日期“2017-12-01”作为参考月，选择56作为值，选择2作为id 选择身份证件参考月，滚动六天的总价值/ 最后一个月滚动六天的位置 -首个月滚动六天的位置 + 1 作为正确的\u移动\u平均值从…起选择id、参考月份、值、，日期/月份，'2016-01-01'，月份/月份位置从虚拟数据窗口滚动六天，按id按顺序按月份分区位置范围在前5行和当前行之间以1,2的顺序排列为了帮助您探索逻辑-请参阅下面的上述查询的扩展版本-它甚至所有中间值都传播到非常外部的select，以便您可以查看所有内容