sql - 如何根据 SQL Server 中的值取消透视列和 GROUP BY？

我想计算每年不同的 PID 和 VID 计数。

条件:

1. Separate count for column A or B or C or D  having value 1  ( A_to_D) 
2. Separate count for column E  having value 1  (E)
3. Separate count for column F  having value 1   (F)
4. Separate count for ALL A to F column are NULL  (ALL_NULL)

在输出中，我想要一个单独的新列 Alpha ，其中包含以下值:

A_to_D, E, F and ALL_Null

表的当前输出:

PID VID Flag    Date        A       B       C       D       E       F
1   A1  0       10/17/2013  NULL    NULL    NULL    NULL    NULL    NULL
2   A2  1       5/27/2014   1       NULL    NULL    1       NULL    NULL
3   A3  NULL    2/23/2015   NULL    NULL    NULL    NULL    1       NULL
4   A4  NULL    12/6/2013   NULL    0       NULL    NULL    NULL    NULL
5   A5  NULL    7/14/2016   NULL    NULL    NULL    NULL    NULL    1
6   A6  NULL    4/29/2015   NULL    1       1       NULL    NULL    NULL
7   A7  1       9/30/2016   1       NULL    NULL    NULL    NULL    NULL
8   A8  NULL    6/28/2016   NULL    NULL    NULL    NULL    NULL    NULL
9   A9  1       11/20/2013  NULL    NULL    NULL    NULL    NULL    NULL
10  A10 2       10/8/2015   NULL    1       NULL    NULL    NULL    NULL

这里:

select datepart(Year,date) ,Count(distinct PID) ,Count( distinct VID)
from table
where A is not null or B is Not NUll or C is not null 
   or D is not null or E is not Null or F is not null
group by datepart(Year,date)

预期输出:

Year        Count_PID       Count_VID       Alpha    
2013                                        A_to_D
2013                                        E
2013                                        F
2013            2               2           ALL_NULL
2014            1               1           A_to_D
2014                                        E
2014                                        F
2014                                        ALL_NULL
2015            2               2           A_to_D
2015            1               1           E
2015                                        F
2015                                        ALL_NULL
2016            2               2           A_to_D
2016                                        E
2016            1                           F   
2016            1                           ALL_NULL

最佳答案

我选择使用公用表表达式 (cte) 来保存基本计数，这些基本计数是使用 case 表达式针对 8 个不同条件(4 个用于 PID，4 个用于 VID)中的每一个条件形成的。然后，cte 用作最终结果所需的年份维度的来源，该最终结果交叉连接到 4 个 alpha 标签的列表。然后再次使用 cte(两次)(未旋转)以将计数左连接到所请求的最终行结构中。该结果中的 Null 是故意的，但如果需要，可以通过在最终 select 子句中使用 coalesce() 或 isnull() 来替换为空字符串。请注意，我更喜欢使用 cross apply 和 values 进行“unpivot”，因为它允许对生成的行进行几乎所见即所得的布局，因为它至少与 具有相同的效率>unpivot 命令(引用如下)。

演示地址:SQL Fiddle

CREATE TABLE Table1
    ([PID] int, [VID] varchar(3), [Flag] varchar(4), [Date] datetime, [A] varchar(4), [B] varchar(4), [C] varchar(4), [D] varchar(4), [E] varchar(4), [F] varchar(4))
;

INSERT INTO Table1
    ([PID], [VID], [Flag], [Date], [A], [B], [C], [D], [E], [F])
VALUES
    (1, 'A1', '0', '2013-10-17 00:00:00', NULL, NULL, NULL, NULL, NULL, NULL),
    (2, 'A2', '1', '2014-05-27 00:00:00', '1', NULL, NULL, '1', NULL, NULL),
    (3, 'A3', NULL, '2015-02-23 00:00:00', NULL, NULL, NULL, NULL, '1', NULL),
    (4, 'A4', NULL, '2013-12-06 00:00:00', NULL, '0', NULL, NULL, NULL, NULL),
    (5, 'A5', NULL, '2016-07-14 00:00:00', NULL, NULL, NULL, NULL, NULL, '1'),
    (6, 'A6', NULL, '2015-04-29 00:00:00', NULL, '1', '1', NULL, NULL, NULL),
    (7, 'A7', '1', '2016-09-30 00:00:00', '1', NULL, NULL, NULL, NULL, NULL),
    (8, 'A8', NULL, '2016-06-28 00:00:00', NULL, NULL, NULL, NULL, NULL, NULL),
    (9, 'A9', '1', '2013-11-20 00:00:00', NULL, NULL, NULL, NULL, NULL, NULL),
    (10, 'A10', '2', '2015-10-08 00:00:00', NULL, '1', NULL, NULL, NULL, NULL)
;

建议的查询:

/* common table expression used so the results may be reused */
with cte as (
      select
            year([date]) [Year]
          , count(distinct pA_to_D) pA_to_D
          , count(distinct pE) pE
          , count(distinct pF) pF
          , count(distinct pALL_NULL) pALL_NULL
          , count(distinct vA_to_D) vA_to_D
          , count(distinct vE) vE
          , count(distinct vF) vF
          , count(distinct vALL_NULL) vALL_NULL
      from (
            select
                  pid, vid, flag, [date]
                , case when a = 1 or b = 1 or c = 1 or d = 1 then pid end pA_to_D
                , case when E = 1 then pid end pE
                , case when F = 1 then pid end pF
                , case when coalesce(a,b,c,d,e,f) IS NULL then pid end pALL_NULL
                , case when flag is not null and a = 1 or b = 1 or c = 1 or d = 1 then vid end vA_to_D
                , case when flag is not null and E = 1 then vid end vE
                , case when flag is not null and F = 1 then vid end vF
                , case when flag is not null and coalesce(a,b,c,d,e,f) IS NULL then vid end vALL_NULL
            from Table1
            ) t
      group by 
           year([date])
  )
select
       y.[Year], p.count_pid, v.count_vid, a.alpha
from (select distinct [Year] from cte) y
cross join (
        select 'A_to_D' as Alpha union all
        select 'E'               union all
        select 'F'               union all
        select 'ALL_NULL'
        ) a
left join (
      select cte.Year, ca.alpha, ca.count_pid
      from cte
      cross apply (
          values
                ('A_to_D'  ,pA_to_D)
              , ('E'       ,pE)
              , ('F'       ,pF)
              , ('ALL_NULL',pALL_NULL)
            ) ca (alpha, count_pid)
       where ca.count_pid > 0
       ) p on y.[Year] = p.[Year] and a.alpha = p.alpha
left join (
      select cte.Year, ca.alpha, ca.count_vid
      from cte
      cross apply (
          values
                ('A_to_D'  ,vA_to_D)
              , ('E'       ,vE)
              , ('F'       ,vF)
              , ('ALL_NULL',vALL_NULL)
            ) ca (alpha, count_vid)
       where ca.count_vid > 0
       ) v on y.[Year] = v.[Year] and a.alpha = v.alpha
;

<强> Results :

| Year | count_pid | count_vid |    alpha |
|------|-----------|-----------|----------|
| 2013 |    (null) |    (null) |   A_to_D |
| 2013 |    (null) |    (null) |        E |
| 2013 |    (null) |    (null) |        F |
| 2013 |         2 |         2 | ALL_NULL |
| 2014 |         1 |         1 |   A_to_D |
| 2014 |    (null) |    (null) |        E |
| 2014 |    (null) |    (null) |        F |
| 2014 |    (null) |    (null) | ALL_NULL |
| 2015 |         2 |         2 |   A_to_D |
| 2015 |         1 |    (null) |        E |
| 2015 |    (null) |    (null) |        F |
| 2015 |    (null) |    (null) | ALL_NULL |
| 2016 |         1 |         1 |   A_to_D |
| 2016 |    (null) |    (null) |        E |
| 2016 |         1 |    (null) |        F |
| 2016 |         1 |    (null) | ALL_NULL |

有关使用 CROSS APPLY 和 VALUES 进行 UNPIVOT 的详细信息，请参阅 Spotlight on UNPIVOT, Part 1作者:布拉德·舒尔茨

最内部查询:

查看初始结果有助于跟踪后续操作。这是 cte 中最里面的子查询，作为单独的查询，结果如下:

/* initial results, prior to unpivot */
           select
                  pid, vid, flag, [date]
                , case when a = 1 or b = 1 or c = 1 or d = 1 then pid end pA_to_D
                , case when E = 1 then pid end pE
                , case when F = 1 then pid end pF
                , case when coalesce(a,b,c,d,e,f) IS NULL then pid end pALL_NULL
                , case when flag is not null and a = 1 or b = 1 or c = 1 or d = 1 then vid end vA_to_D
                , case when flag is not null and E = 1 then vid end vE
                , case when flag is not null and F = 1 then vid end vF
                , case when flag is not null and coalesce(a,b,c,d,e,f) IS NULL then vid end vALL_NULL
            from Table1
            order by [date]
;

<强> Results :

| pid | vid |   flag |                 date | pA_to_D |     pE |     pF | pALL_NULL | vA_to_D |     vE |     vF | vALL_NULL |
|-----|-----|--------|----------------------|---------|--------|--------|-----------|---------|--------|--------|-----------|
|   1 |  A1 |      0 | 2013-10-17T00:00:00Z |  (null) | (null) | (null) |         1 |  (null) | (null) | (null) |        A1 |
|   9 |  A9 |      1 | 2013-11-20T00:00:00Z |  (null) | (null) | (null) |         9 |  (null) | (null) | (null) |        A9 |
|   4 |  A4 | (null) | 2013-12-06T00:00:00Z |  (null) | (null) | (null) |    (null) |  (null) | (null) | (null) |    (null) |
|   2 |  A2 |      1 | 2014-05-27T00:00:00Z |       2 | (null) | (null) |    (null) |      A2 | (null) | (null) |    (null) |
|   3 |  A3 | (null) | 2015-02-23T00:00:00Z |  (null) |      3 | (null) |    (null) |  (null) | (null) | (null) |    (null) |
|   6 |  A6 | (null) | 2015-04-29T00:00:00Z |       6 | (null) | (null) |    (null) |      A6 | (null) | (null) |    (null) |
|  10 | A10 |      2 | 2015-10-08T00:00:00Z |      10 | (null) | (null) |    (null) |     A10 | (null) | (null) |    (null) |
|   8 |  A8 | (null) | 2016-06-28T00:00:00Z |  (null) | (null) | (null) |         8 |  (null) | (null) | (null) |    (null) |
|   5 |  A5 | (null) | 2016-07-14T00:00:00Z |  (null) | (null) |      5 |    (null) |  (null) | (null) | (null) |    (null) |
|   7 |  A7 |      1 | 2016-09-30T00:00:00Z |       7 | (null) | (null) |    (null) |      A7 | (null) | (null) |    (null) |

关于sql - 如何根据 SQL Server 中的值取消透视列和 GROUP BY？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/47199461/

sql - 如何根据 SQL Server 中的值取消透视列和 GROUP BY？

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