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具有动态生成列、聚合函数和无聚合列的 SQL Pivot

转载 作者:行者123 更新时间:2023-12-04 14:27:21 25 4
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我有以下查询:

WITH preEKBE AS(
SELECT
EKPO . MANDT,
EKPO . EBELN,
EKPO . EBELP,
DD07T.DDTEXT AS c_Meaning,
EKBE . VGABE,
EKBE . DMBTR,
EKBE . MENGE,
COUNT(VGABE) OVER(PARTITION BY EKBE . EBELN, EKBE . EBELP, ZEKKN) AS c_COUNT,
CONVERT (varchar(10),MIN(EKBE . BLDAT) OVER ( PARTITION BY EKBE . EBELN, EKBE . EBELP, EKBE . VGABE),104) AS c_EBKE_BLDAT_First,
CONVERT (varchar(10),MIN(EKBE . BUDAT) OVER ( PARTITION BY EKBE . EBELN, EKBE . EBELP, EKBE . VGABE),104) AS c_EKBE_BUDAT_First,
CONVERT (varchar(10),MAX(EKBE . BLDAT) OVER ( PARTITION BY EKBE . EBELN, EKBE . EBELP, EKBE . VGABE),104) AS c_EBKE_BLDAT_Last,
CONVERT (varchar(10),MAX(EKBE . BUDAT) OVER ( PARTITION BY EKBE . EBELN, EKBE . EBELP, EKBE . VGABE),104) AS c_EKBE_BUDAT_Last
FROM EKPO

LEFT JOIN EKKO
ON EKPO . MANDT = EKKO . MANDT
AND EKPO . EBELN = EKKO . EBELN

LEFT JOIN EKBE
ON EKPO . MANDT = EKBE . MANDT
AND EKPO . EBELN = EKBE . EBELN
AND EKPO . EBELP = EKBE . EBELP

LEFT JOIN DD07T
ON DD07T . DOMNAME = 'VGABE'
AND DD07T . DOMVALUE_L = EKBE.VGABE
AND DD07T . DDLANGUAGE = 'D'
)

SELECT * INTO #preEKBE FROM preEKBE
ORDER BY EBELN , EBELP

它为我生成了这张表
+-------+------------+-------+-----------------------------+-------+---------+----------+---------+--------------------+--------------------+-------------------+-------------------+
| MANDT | EBELN | EBELP | c_Meaning | VGABE | DMBTR | MENGE | c_COUNT | c_EBKE_BLDAT_First | c_EKBE_BUDAT_First | c_EBKE_BLDAT_Last | c_EKBE_BUDAT_Last |
+-------+------------+-------+-----------------------------+-------+---------+----------+---------+--------------------+--------------------+-------------------+-------------------+
| 800 | 3000000004 | 00001 | Wareneingang | 1 | 27.95 | 1.000 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 |
| 800 | 3000000004 | 00001 | Rechnungseingang | 2 | 27.95 | 1.000 | 1 | 19.12.2000 | 21.12.2000 | 19.12.2000 | 21.12.2000 |
| 800 | 3000000004 | 00002 | Wareneingang | 1 | 10.95 | 1.000 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 |
| 800 | 3000000004 | 00002 | Rechnungseingang | 2 | 10.95 | 1.000 | 1 | 19.12.2000 | 21.12.2000 | 19.12.2000 | 21.12.2000 |
| 800 | 4500008499 | 00010 | Wareneingang | 1 | 268.43 | 1.000 | 1 | 27.03.2000 | 27.03.2000 | 27.03.2000 | 27.03.2000 |
| 800 | 4500008499 | 00010 | Leistungserfassungsblatt | 9 | 268.43 | 1.000 | 1 | 27.03.2000 | 27.03.2000 | 27.03.2000 | 27.03.2000 |
| 800 | 4500010470 | 00010 | Wareneingang | 1 | 0.00 | 1092.000 | 6 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 |
| 800 | 4500010470 | 00010 | Wareneingang | 1 | 0.00 | 3512.000 | 6 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 |
| 800 | 4500010470 | 00010 | Warenausgabe für Umlagerung | 6 | 1615.52 | 3512.000 | 6 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 |
| 800 | 4500010470 | 00010 | Warenausgabe für Umlagerung | 6 | 502.32 | 1092.000 | 6 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 |
| 800 | 4500010470 | 00010 | Lieferung zu Umlagerung | 8 | 0.00 | 1092.000 | 6 | 01.01.1900 | 07.02.2001 | 01.01.1900 | 07.02.2001 |
| 800 | 4500010470 | 00010 | Lieferung zu Umlagerung | 8 | 0.00 | 3512.000 | 6 | 01.01.1900 | 07.02.2001 | 01.01.1900 | 07.02.2001 |
+-------+------------+-------+-----------------------------+-------+---------+----------+---------+--------------------+--------------------+-------------------+-------------------+

现在我有了一个可以部分工作的动态 Pivot。
DECLARE @cols AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)

select @cols = STUFF((SELECT ',' + QUOTENAME(col + '_' + VGABE)
from #preEKBE t
cross apply
(
select 'c_DMBTR', 1 union all
select 'c_MENGE', 2 union all
select 'c_COUNT', 3
) c (col, so)
group by col, so, VGABE
order by VGABE, so
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')

set @query
= 'SELECT EBELN, EBELP,' + @cols + N'
from
(
select
t.EBELN,
t.EBELP,
new_col = c.orig_col + ''_'' + VGABE,
c.value
from #preEKBE t

cross apply
(
select ''c_MENGE'', t.MENGE union all
select ''c_DMBTR'', t.DMBTR union all
select ''c_COUNT'', t.c_COUNT
) c (orig_col, value)
) x
pivot
(
sum(value)
for new_col in (' + @cols + N')
) p
order by EBELN , EBELP'
exec sp_executesql @query;

给我一个结果:
+------------+-------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| EBELN | EBELP | c_DMBTR_1 | c_MENGE_1 | c_COUNT_1 | c_DMBTR_2 | c_MENGE_2 | c_COUNT_2 | c_DMBTR_6 | c_MENGE_6 | c_COUNT_6 | c_DMBTR_7 | c_MENGE_7 | c_COUNT_7 | c_DMBTR_8 | c_MENGE_8 | c_COUNT_8 | c_DMBTR_9 | c_MENGE_9 | c_COUNT_9 | c_DMBTR_P | c_MENGE_P | c_COUNT_P | c_DMBTR_R | c_MENGE_R | c_COUNT_R |
+------------+-------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| 3000000004 | 00001 | 27.950 | 1.000 | 1.000 | 27.950 | 1.000 | 1.000 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| 3000000004 | 00002 | 10.950 | 1.000 | 1.000 | 10.950 | 1.000 | 1.000 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
+------------+-------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+

由于列 VGABE,我需要动态查询创建新的列名,可以有未使用的值,我只想要 VGABE正在使用的值。

现在的问题是我想添加更多也应该动态生成的列。当有 VGABE与 1 相比,我需要一个名为 c_Meaning_1 (nvarchar) 的列它将具有与 DD07T 连接的值.
c_COUNT_代表每个 VGABE 的计数每条记录的值(value)。此列完美运行。

在这些列之后,我还需要添加列 c_BLDAT_First_ , c_BUDAT_First_ , c_BLDAT_Last_ , 和 c_BUDAT_Last_值为 VGABE连接在新列名的末尾。该值在 CTE 中计算。

有没有办法在没有临时表的情况下直接使用CTE?

我不知道如何解决这个问题,因为我正在处理多种数据类型,而且它们的聚合方式各不相同。当 VGABE 的值分别为 1 和 9 时那么它应该是这样的:
+---------------+-----------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+---------------------------+------------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+
| C_MEANING_1 | C_DMBTR_1 | C_MENGE_1 | C_COUNT_1 | C_EBKE_BLDAT_FIRST_1 | C_EKBE_BUDAT_FIRST_1 | C_EBKE_BLDAT_LAST_1 | C_EKBE_BUDAT_LAST_1 | C_MEANING_9 | C_DMBTR_9 | C_MENGE_9 | C_COUNT_9 | C_EBKE_BLDAT_FIRST_9 | C_EKBE_BUDAT_FIRST_9 | C_EBKE_BLDAT_LAST_9 | C_EKBE_BUDAT_LAST_9 |
+---------------+-----------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+---------------------------+------------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+
| Wareneingang: | 10,00 | 1 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 | Leistungserfassungsblatt: | 0 | 0 | 0 | NULL | NULL | NULL | NULL |
| Wareneingang: | 0 | 0 | 0 | NULL | NULL | NULL | NULL | Leistungserfassungsblatt: | 20 | 2 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 |
+---------------+-----------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+---------------------------+------------+-----------+-----------+----------------------+----------------------+---------------------+---------------------+

每个 VGABE value 应该按照上面给出的顺序有一个自己的列。如果您需要更多信息,请询问我。我将 SQL Server 2014 与 SQL Management Studio 2014 和 TSQL 一起使用。

最佳答案

好吧,您在这里有点困惑,因为您想将具有多行的多个列转换为更多列,最重要的是您需要为每个列使用不同的聚合,因为其中一些您需要SUM和其他你必须使用 MAXMIN (在字符串/日期上)。

您应该 而不是直接进入动态sql 版本总是 尝试使用较小版本的静态查询来获得正确的逻辑。在我看来,这使得使用动态 SQL 变得更加容易,因为您无需猜测该做什么或什么不正常。

我首先从一个查询开始,该查询获取您需要求和的每个项目的总数。

select ebeln, ebelp, 
c_Meaning,
vgabe,
dmbtr = cast(sum(dmbtr) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
menge = cast(sum(menge) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_count = cast(sum(c_count) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_EBKE_BLDAT_First = cast(c_EBKE_BLDAT_First as varchar(50)),
c_EKBE_BUDAT_First = cast(c_EKBE_BUDAT_First as varchar(50)),
c_EBKE_BLDAT_Last = cast(c_EBKE_BLDAT_Last as varchar(50)),
c_EKBE_BUDAT_Last = cast(c_EKBE_BUDAT_Last as varchar(50))
from preEKBE

SQL Fiddle with Demo .这将获得您在最终结果中所需的所有值,因为您将获得 ebeln 组合的总和。 , ebelp , 和 vgabe .您会看到我还将所有值都转换为相同的数据类型 - 这对于下一步是必要的 - 逆透视。由于所有数据都将存储在同一列中,因此它们需要相同的数据类型。
select d.ebeln, d.ebelp,
new_col = c.orig_col + '_' + cast(d.vgabe as varchar(2)),
c.value
from
(
select ebeln, ebelp,
c_Meaning,
vgabe,
dmbtr = cast(sum(dmbtr) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
menge = cast(sum(menge) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_count = cast(sum(c_count) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_EBKE_BLDAT_First = cast(c_EBKE_BLDAT_First as varchar(50)),
c_EKBE_BUDAT_First = cast(c_EKBE_BUDAT_First as varchar(50)),
c_EBKE_BLDAT_Last = cast(c_EBKE_BLDAT_Last as varchar(50)),
c_EKBE_BUDAT_Last = cast(c_EKBE_BUDAT_Last as varchar(50))
from preEKBE
) d
cross apply
(
select 'c_Meaning', c_Meaning union all
select 'c_MENGE', menge union all
select 'c_DMBTR', dmbtr union all
select 'c_count', c_count union all
select 'c_EBKE_BLDAT_First', c_EBKE_BLDAT_First union all
select 'c_EKBE_BUDAT_First', c_EKBE_BUDAT_First union all
select 'c_EBKE_BLDAT_Last', c_EBKE_BLDAT_Last union all
select 'c_EKBE_BUDAT_Last', c_EKBE_BUDAT_Last
) c (orig_col, value)

SQL Fiddle with Demo .现在你的数据看起来像这样:
|      EBELN | EBELP |              NEW_COL |                       VALUE |
|------------|-------|----------------------|-----------------------------|
| 3000000004 | 1 | c_Meaning_1 | Wareneingang |
| 3000000004 | 1 | c_MENGE_1 | 1 |
| 3000000004 | 1 | c_DMBTR_1 | 27.95 |
| 3000000004 | 1 | c_count_1 | 1 |
| 3000000004 | 1 | c_EBKE_BLDAT_First_1 | 19.12.2000 |
| 3000000004 | 1 | c_EKBE_BUDAT_First_1 | 19.12.2000 |

最后,您将应用 PIVOT 函数:
select ebeln, 
ebelp,
c_Meaning_1, c_MENGE_1, c_DMBTR_1, c_count_1,
c_EBKE_BLDAT_First_1, c_EKBE_BUDAT_First_1,
c_EBKE_BLDAT_Last_1, c_EKBE_BUDAT_Last_1
from
(
select d.ebeln, d.ebelp,
new_col = c.orig_col + '_' + cast(d.vgabe as varchar(2)),
c.value
from
(
select ebeln, ebelp,
c_Meaning,
vgabe,
dmbtr = cast(sum(dmbtr) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
menge = cast(sum(menge) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_count = cast(sum(c_count) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_EBKE_BLDAT_First = cast(c_EBKE_BLDAT_First as varchar(50)),
c_EKBE_BUDAT_First = cast(c_EKBE_BUDAT_First as varchar(50)),
c_EBKE_BLDAT_Last = cast(c_EBKE_BLDAT_Last as varchar(50)),
c_EKBE_BUDAT_Last = cast(c_EKBE_BUDAT_Last as varchar(50))
from preEKBE
) d
cross apply
(
select 'c_Meaning', c_Meaning union all
select 'c_MENGE', menge union all
select 'c_DMBTR', dmbtr union all
select 'c_count', c_count union all
select 'c_EBKE_BLDAT_First', c_EBKE_BLDAT_First union all
select 'c_EKBE_BUDAT_First', c_EKBE_BUDAT_First union all
select 'c_EBKE_BLDAT_Last', c_EBKE_BLDAT_Last union all
select 'c_EKBE_BUDAT_Last', c_EKBE_BUDAT_Last
) c (orig_col, value)
) src
pivot
(
max(value)
for new_col in (c_Meaning_1, c_MENGE_1, c_DMBTR_1, c_count_1,
c_EBKE_BLDAT_First_1, c_EKBE_BUDAT_First_1,
c_EBKE_BLDAT_Last_1, c_EKBE_BUDAT_Last_1)
) piv;

SQL Fiddle with Demo .

现在您有了工作逻辑,您可以将其转换为动态 sql:
DECLARE @cols AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)

select @cols = STUFF((SELECT ',' + QUOTENAME(col + '_' + cast(VGABE as varchar(2)))
from preEKBE t
cross apply
(
select 'c_meaning', 0 union all
select 'c_DMBTR', 1 union all
select 'c_MENGE', 2 union all
select 'c_COUNT', 3 union all
select 'c_EBKE_BLDAT_FIRST', 4 union all
select 'c_EKBE_BUDAT_FIRST', 5 union all
select 'c_EBKE_BLDAT_LAST', 6 union all
select 'c_EKBE_BUDAT_LAST', 7
) c (col, so)
group by col, so, VGABE
order by VGABE, so
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')


set @query
= 'SELECT EBELN, EBELP, ' + @cols + N'
from
(
select d.ebeln,
d.ebelp,
new_col = c.orig_col + ''_'' + cast(d.vgabe as varchar(2)),
c.value
from
(
select ebeln, ebelp,
c_Meaning,
vgabe,
dmbtr = cast(sum(dmbtr) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
menge = cast(sum(menge) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_count = cast(sum(c_count) over(partition by ebeln, ebelp, vgabe) as varchar(50)),
c_EBKE_BLDAT_First = cast(c_EBKE_BLDAT_First as varchar(50)),
c_EKBE_BUDAT_First = cast(c_EKBE_BUDAT_First as varchar(50)),
c_EBKE_BLDAT_Last = cast(c_EBKE_BLDAT_Last as varchar(50)),
c_EKBE_BUDAT_Last = cast(c_EKBE_BUDAT_Last as varchar(50))
from preEKBE
) d
cross apply
(
select ''c_meaning'', d.c_meaning union all
select ''c_MENGE'', d.MENGE union all
select ''c_DMBTR'', d.DMBTR union all
select ''c_COUNT'', d.c_COUNT union all
select ''c_EBKE_BLDAT_First'', d.c_EBKE_BLDAT_First union all
select ''c_EKBE_BUDAT_First'', d.c_EKBE_BUDAT_First union all
select ''c_EBKE_BLDAT_Last'', d.c_EBKE_BLDAT_Last union all
select ''c_EKBE_BUDAT_Last'', d.c_EKBE_BUDAT_Last
) c (orig_col, value)
) x
pivot
(
max(value)
for new_col in (' + @cols + N')
) p
order by EBELN , EBELP'

exec sp_executesql @query;

SQL Fiddle with Demo .这给出了最终结果:
|      EBELN | EBELP |  C_MEANING_1 | C_DMBTR_1 | C_MENGE_1 | C_COUNT_1 | C_EBKE_BLDAT_FIRST_1 | C_EKBE_BUDAT_FIRST_1 | C_EBKE_BLDAT_LAST_1 | C_EKBE_BUDAT_LAST_1 |      C_MEANING_2 | C_DMBTR_2 | C_MENGE_2 | C_COUNT_2 | C_EBKE_BLDAT_FIRST_2 | C_EKBE_BUDAT_FIRST_2 | C_EBKE_BLDAT_LAST_2 | C_EKBE_BUDAT_LAST_2 |                 C_MEANING_6 | C_DMBTR_6 | C_MENGE_6 | C_COUNT_6 | C_EBKE_BLDAT_FIRST_6 | C_EKBE_BUDAT_FIRST_6 | C_EBKE_BLDAT_LAST_6 | C_EKBE_BUDAT_LAST_6 |             C_MEANING_8 | C_DMBTR_8 | C_MENGE_8 | C_COUNT_8 | C_EBKE_BLDAT_FIRST_8 | C_EKBE_BUDAT_FIRST_8 | C_EBKE_BLDAT_LAST_8 | C_EKBE_BUDAT_LAST_8 |              C_MEANING_9 | C_DMBTR_9 | C_MENGE_9 | C_COUNT_9 | C_EBKE_BLDAT_FIRST_9 | C_EKBE_BUDAT_FIRST_9 | C_EBKE_BLDAT_LAST_9 | C_EKBE_BUDAT_LAST_9 |
|------------|-------|--------------|-----------|-----------|-----------|----------------------|----------------------|---------------------|---------------------|------------------|-----------|-----------|-----------|----------------------|----------------------|---------------------|---------------------|-----------------------------|-----------|-----------|-----------|----------------------|----------------------|---------------------|---------------------|-------------------------|-----------|-----------|-----------|----------------------|----------------------|---------------------|---------------------|--------------------------|-----------|-----------|-----------|----------------------|----------------------|---------------------|---------------------|
| 3000000004 | 1 | Wareneingang | 27.95 | 1 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 | Rechnungseingang | 27.95 | 1 | 1 | 19.12.2000 | 21.12.2000 | 19.12.2000 | 21.12.2000 | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) |
| 3000000004 | 2 | Wareneingang | 10.95 | 1 | 1 | 19.12.2000 | 19.12.2000 | 19.12.2000 | 19.12.2000 | Rechnungseingang | 10.95 | 1 | 1 | 19.12.2000 | 21.12.2000 | 19.12.2000 | 21.12.2000 | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) |
| 4500008499 | 10 | Wareneingang | 268.43 | 1 | 1 | 27.03.2000 | 27.03.2000 | 27.03.2000 | 27.03.2000 | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | Leistungserfassungsblatt | 268.43 | 1 | 1 | 27.03.2000 | 27.03.2000 | 27.03.2000 | 27.03.2000 |
| 4500010470 | 10 | Wareneingang | 0.00 | 4604 | 12 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) | Warenausgabe für Umlagerung | 2117.84 | 4604 | 12 | 07.02.2001 | 07.02.2001 | 07.02.2001 | 07.02.2001 | Lieferung zu Umlagerung | 0.00 | 4604 | 12 | 01.01.1900 | 07.02.2001 | 01.01.1900 | 07.02.2001 | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) |

关于具有动态生成列、聚合函数和无聚合列的 SQL Pivot,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/26156667/

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