BigQuery / SQL: заполнение пробелов в виде повторяющихся строк между годами

Question

У меня очень похожий сценарий, показанный в этой теме: Дублирующие группы записей для заполнения нескольких пробелов в датах в Google BigQuery

Используемый мной запрос выглядит следующим образом:

WITH history AS (
  SELECT 2012 AS d, 'a' AS product, 'x' AS partner, 10 AS value UNION ALL
  SELECT 2010 AS d, 'b' AS product, 'x' AS partner, 15 AS value UNION ALL
  SELECT 2014 AS d, 'a' AS product, 'y' AS partner, 11 AS value UNION ALL
  SELECT 2012 AS d, 'b' AS product, 'y' AS partner, 16 AS value UNION ALL
  SELECT 2015 AS d, 'b' AS product, 'x' AS partner, 13 AS value UNION ALL
  SELECT 2017 AS d, 'a' AS product, 'y' AS partner, 15 AS value UNION ALL
  SELECT 2017 AS d, 'a' AS product, 'x' AS partner, 15 AS value 
),
daterange AS (
  SELECT EXTRACT(YEAR FROM fiscalYear) as date_in_range
  FROM UNNEST(
    GENERATE_DATE_ARRAY(DATE('2010-01-01'), CURRENT_DATE(), INTERVAL 1 YEAR)
    ) AS fiscalYear),
temp AS (
  SELECT d, product, partner, value, LEAD(d) OVER(PARTITION BY product, partner ORDER BY d) AS next_d
  FROM history
  ORDER BY product, partner, d
)
SELECT date_in_range, product, partner, value
FROM daterange
JOIN temp
ON daterange.date_in_range >= temp.d 
AND (daterange.date_in_range < temp.next_d OR temp.next_d IS NULL)
ORDER BY product, partner, date_in_range

Одна вещь, которую я заметил, которая не идеально подходит для моего сценария, это то, что даты для каждого продукта, комбинации партнеров не всегда начинаются в 2010 году, и это то, чего я хочу.

Таким образом, выходные данные для каждого продукта-партнера должны иметь date_in_range [2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019]

Выходные данные, которые возвращает этот запрос::

+---------------+---------+---------+-------+
| date_in_range | product | partner | value |
+---------------+---------+---------+-------+
| 2012          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2013          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2014          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2015          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2016          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2017          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2018          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2019          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2014          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2015          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2016          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2017          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2018          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2019          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2010          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2011          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2012          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2013          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2014          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2015          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2016          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2017          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2018          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2019          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2012          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2013          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2014          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2015          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2016          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2017          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2018          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2019          | b       | y       | 16    |
+---------------+---------+---------+-------+

Требуемый вывод:

+---------------+---------+---------+-------+
| date_in_range | product | partner | value |
+---------------+---------+---------+-------+
| 2010          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2011          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2012          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2013          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2014          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2015          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2016          | a       | x       | 10    |
+---------------+---------+---------+-------+
| 2017          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2018          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2019          | a       | x       | 15    |
+---------------+---------+---------+-------+
| 2010          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2011          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2012          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2013          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2014          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2015          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2016          | a       | y       | 11    |
+---------------+---------+---------+-------+
| 2017          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2018          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2019          | a       | y       | 15    |
+---------------+---------+---------+-------+
| 2010          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2011          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2012          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2013          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2014          | b       | x       | 15    |
+---------------+---------+---------+-------+
| 2015          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2016          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2017          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2018          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2019          | b       | x       | 13    |
+---------------+---------+---------+-------+
| 2010          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2011          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2012          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2013          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2014          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2015          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2016          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2017          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2018          | b       | y       | 16    |
+---------------+---------+---------+-------+
| 2019          | b       | y       | 16    |
+---------------+---------+---------+-------+

Answer 1

Ниже для стандартного SQL BigQuery

#standardSQL
WITH history AS (
  SELECT 2012 AS d, 'a' AS product, 'x' AS partner, 10 AS value UNION ALL
  SELECT 2010 AS d, 'b' AS product, 'x' AS partner, 15 AS value UNION ALL
  SELECT 2014 AS d, 'a' AS product, 'y' AS partner, 11 AS value UNION ALL
  SELECT 2012 AS d, 'b' AS product, 'y' AS partner, 16 AS value UNION ALL
  SELECT 2015 AS d, 'b' AS product, 'x' AS partner, 13 AS value UNION ALL
  SELECT 2017 AS d, 'a' AS product, 'y' AS partner, 15 AS value UNION ALL
  SELECT 2017 AS d, 'a' AS product, 'x' AS partner, 15 AS value 
),
daterange AS (
  SELECT EXTRACT(YEAR FROM fiscalYear) AS date_in_range
  FROM UNNEST(
    GENERATE_DATE_ARRAY(DATE('2010-01-01'), CURRENT_DATE(), INTERVAL 1 YEAR)
    ) AS fiscalYear),
history_ext AS (
  SELECT date_in_range, x.product, x.partner, value
  FROM daterange dr
  CROSS JOIN (SELECT DISTINCT product, partner FROM history) x
  LEFT JOIN history h
  ON dr.date_in_range = h.d
  AND STRUCT(h.product, h.partner) = STRUCT(x.product, x.partner)
)
SELECT date_in_range, product, partner, 
COALESCE(
  value, 
  LAST_VALUE(value IGNORE NULLS) OVER(PARTITION BY product, partner ORDER BY date_in_range ROWS BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING),
  FIRST_VALUE(value IGNORE NULLS) OVER(PARTITION BY product, partner ORDER BY date_in_range ROWS BETWEEN 1 FOLLOWING AND UNBOUNDED FOLLOWING) 
) AS value
FROM history_ext
ORDER BY product, partner, date_in_range   

и возвращает

Row date_in_range   product partner value    
1   2010    a   x   10   
2   2011    a   x   10   
3   2012    a   x   10   
4   2013    a   x   10   
5   2014    a   x   10   
6   2015    a   x   10   
7   2016    a   x   10   
8   2017    a   x   15   
9   2018    a   x   15   
10  2019    a   x   15   
11  2010    a   y   11   
12  2011    a   y   11   
13  2012    a   y   11   
14  2013    a   y   11   
15  2014    a   y   11   
16  2015    a   y   11   
17  2016    a   y   11   
18  2017    a   y   15   
19  2018    a   y   15   
20  2019    a   y   15   
21  2010    b   x   15   
22  2011    b   x   15   
23  2012    b   x   15   
24  2013    b   x   15   
25  2014    b   x   15   
26  2015    b   x   13   
27  2016    b   x   13   
28  2017    b   x   13   
29  2018    b   x   13   
30  2019    b   x   13   
31  2010    b   y   16   
32  2011    b   y   16   
33  2012    b   y   16   
34  2013    b   y   16   
35  2014    b   y   16   
36  2015    b   y   16   
37  2016    b   y   16   
38  2017    b   y   16   
39  2018    b   y   16   
40  2019    b   y   16