具有多列聚合的 SQL Server 数据透视表
我有一张桌子:
create table mytransactions(country varchar(30), totalcount int, numericmonth int, chardate char(20), totalamount money)
该表有以下记录:
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 36, 7, 'Jul-12', 699.96)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 44, 8, 'Aug-12', 1368.71)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 52, 9, 'Sep-12', 1161.33)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 50, 10, 'Oct-12', 1099.84)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 38, 11, 'Nov-12', 1078.94)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 63, 12, 'Dec-12', 1668.23)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 11, 7, 'Jul-12', 257.82)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 5, 8, 'Aug-12', 126.55)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 7, 9, 'Sep-12', 92.11)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 12, 10, 'Oct-12', 103.56)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 21, 11, 'Nov-12', 377.68)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 3, 12, 'Dec-12', 14.35)
Go
这是 select * 的样子:
This is what a select * looks like:
Country TotalCount numericmonth chardate totalamount
--------- ---------- ----------- -------- -----------
Australia 36 7 Jul-12 699.96
Australia 44 8 Aug-12 1368.71
Australia 52 9 Sep-12 1161.33
Australia 50 10 Oct-12 1099.84
Australia 38 11 Nov-12 1078.94
Australia 63 12 Dec-12 1668.23
Austria 11 7 Jul-12 257.82
Austria 5 8 Aug-12 126.55
Austria 7 9 Sep-12 92.11
Austria 12 10 Oct-12 103.56
Austria 21 11 Nov-12 377.68
Austria 3 12 Dec-12 14.35
我想旋转这个记录集，使它看起来像这样:
I want to pivot this record set so it looks like this:
Australia Australia Austria Austria
# of Transactions Total $ amount # of Transactions Total $ amount
----------------- -------------- ----------------- --------------
Jul-12 36 699.96 11 257.82
Aug-12 44 1368.71 5 126.55
Sep-12 52 1161.33 7 92.11
Oct-12 50 1099.84 12 103.56
Nov-12 38 1078.94 21 377.68
Dec-12 63 1668.23 3 14.35
这是迄今为止我想出的数据透视代码:
This is the pivot code I've come up with so far:
select * from mytransactions
pivot (sum (totalcount) for country in ([Australia], [Austria])) as pvt
这是我得到的:
numericmonth chardate totalamount Australia Austria
----------- -------- ---------- --------- -------
7 Jul-12 257.82 NULL 11
7 Jul-12 699.96 36 NULL
8 Aug-12 126.55 NULL 5
8 Aug-12 1368.71 44 NULL
9 Sep-12 92.11 NULL 7
9 Sep-12 1161.33 52 NULL
10 Oct-12 103.56 NULL 12
10 Oct-12 1099.84 50 NULL
11 Nov-12 377.68 NULL 21
11 Nov-12 1078.94 38 NULL
12 Dec-12 14.35 NULL 3
12 Dec-12 1668.23 63 NULL
我可以手动聚合表变量循环中的记录，但是似乎pivot 可以做到这一点.
I can manually aggregate the records in a table variable loop, however it seems that pivot might be able to do this.
是否可以使用pivot获取我想要的记录集，或者还有其他我不知道的工具吗?
Is is possible to get the record set I want using pivot or is there another tool that I'm not aware of?
谢谢
推荐答案
我会通过应用 UNPIVOT 和 PIVOT 函数来获得最终结果结果.unpivot 从 totalcount 和 totalamount 列中获取值，并将它们放入具有多行的一列中.然后，您可以根据这些结果进行调整.:
I would do this slightly different by applying both the UNPIVOT and the PIVOT functions to get the final result. The unpivot takes the values from both the totalcount and totalamount columns and places them into one column with multiple rows. You can then pivot on those results.:
select chardate,
Australia_totalcount as [Australia # of Transactions],
Australia_totalamount as [Australia Total $ Amount],
Austria_totalcount as [Austria # of Transactions],
Austria_totalamount as [Austria Total $ Amount]
from
(
select
numericmonth,
chardate,
country +'_'+col col,
value
from
(
select numericmonth,
country,
chardate,
cast(totalcount as numeric(10, 2)) totalcount,
cast(totalamount as numeric(10, 2)) totalamount
from mytransactions
) src
unpivot
(
value
for col in (totalcount, totalamount)
) unpiv
) s
pivot
(
sum(value)
for col in (Australia_totalcount, Australia_totalamount,
Austria_totalcount, Austria_totalamount)
) piv
order by numericmonth
参见SQL Fiddle with Demo.
如果你有未知数量的country名称，那么你可以使用动态SQL:
If you have an unknown number of country names, then you can use dynamic SQL:
DECLARE @cols AS NVARCHAR(MAX),
@colsName AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)
select @cols = STUFF((SELECT distinct ',' + QUOTENAME(country +'_'+c.col)
from mytransactions
cross apply
(
select 'TotalCount' col
union all
select 'TotalAmount'
) c
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
select @colsName
= STUFF((SELECT distinct ', ' + QUOTENAME(country +'_'+c.col)
+' as ['
+ country + case when c.col = 'TotalCount' then ' # of Transactions]' else 'Total $ Amount]' end
from mytransactions
cross apply
(
select 'TotalCount' col
union all
select 'TotalAmount'
) c
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set @query
= 'SELECT chardate, ' + @colsName + '
from
(
select
numericmonth,
chardate,
country +''_''+col col,
value
from
(
select numericmonth,
country,
chardate,
cast(totalcount as numeric(10, 2)) totalcount,
cast(totalamount as numeric(10, 2)) totalamount
from mytransactions
) src
unpivot
(
value
for col in (totalcount, totalamount)
) unpiv
) s
pivot
(
sum(value)
for col in (' + @cols + ')
) p
order by numericmonth'
execute(@query)
参见SQL Fiddle with Demo
两者都给出结果:
| CHARDATE | AUSTRALIA # OF TRANSACTIONS | AUSTRALIA TOTAL $ AMOUNT | AUSTRIA # OF TRANSACTIONS | AUSTRIA TOTAL $ AMOUNT |
--------------------------------------------------------------------------------------------------------------------------------------
| Jul-12 | 36 | 699.96 | 11 | 257.82 |
| Aug-12 | 44 | 1368.71 | 5 | 126.55 |
| Sep-12 | 52 | 1161.33 | 7 | 92.11 |
| Oct-12 | 50 | 1099.84 | 12 | 103.56 |
| Nov-12 | 38 | 1078.94 | 21 | 377.68 |
| Dec-12 | 63 | 1668.23 | 3 | 14.35 |
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