Sql server 2005 将表行分组并将结果连接到另一个表

我有这三张桌子：

表1：

表2：

表3：

表1和表3具有一对多关系，表3具有多个链接行。表3每个InvoiceId最多有2行

任务

我想对表3行进行分组以得出以下结果：

    InvoiceId       AcceptDate1      AcceptDate2
    --------------------------------------------
        3              AAAA             BBBB
        6              CCCC             null
        4              DDDD             null
      and ....

然后将这些结果与表1和表2合并，得出：

    InvoiceId     InvoiceNumber        AcceptDate1    AcceptDate2      Name
    --------------------------------------------------------------------------
       3               1                  AAAA           BBBB          Name2
       4               2                  DDDD           null          Name2
       7               3                  EEEE           GGGG          Name2
       8               4                  null           null          Name2
       6               1                  CCCC           null          Name1
       9               2                  FFFF           null          Name1

AcceptDate1和AcceptDate2是静态的。

您需要的是

这使得：

InvoiceId   InvoiceNumber AcceptDate1             AcceptDate2             CompanyName
----------- ------------- ----------------------- ----------------------- --------------------------------------------------
3           1             2012-01-01 00:00:00.000 2012-01-02 00:00:00.000 Name2
4           2             2012-01-04 00:00:00.000 NULL                    Name2
6           1             NULL                    2012-01-03 00:00:00.000 Name1
7           3             2012-01-05 00:00:00.000 2012-01-07 00:00:00.000 Name2
9           2             NULL                    2012-01-06 00:00:00.000 Name1

(5 row(s) affected)

---

我需要一个新表，将表3中每个InvoiceId的AcceptDate合并到一行中，然后将这个新表与其他两个表连接起来。我需要一个表3上的查询，该查询创建一个具有以下列的新表：InvoiceId、AcceptDate1、AcceptDate2。如果invoiceId在表3中只有一条记录，则只有AcceptDate1填充，AcceptDate2为空。我不能用英语很好地解释。SORRY@MichaelBuen谢谢你的信息链接@Behnam我了解您的需求，您能告诉我们从表3中选择哪个AcceptDate，针对哪个AcceptType吗？

    InvoiceId       AcceptDate1      AcceptDate2
    --------------------------------------------
        3              AAAA             BBBB
        6              CCCC             null
        4              DDDD             null
      and ....

    InvoiceId     InvoiceNumber        AcceptDate1    AcceptDate2      Name
    --------------------------------------------------------------------------
       3               1                  AAAA           BBBB          Name2
       4               2                  DDDD           null          Name2
       7               3                  EEEE           GGGG          Name2
       8               4                  null           null          Name2
       6               1                  CCCC           null          Name1
       9               2                  FFFF           null          Name1

BEGIN TRAN

create table #table1 (InvoiceId int, InvoiceNumber int, CompanyId int)
create table #table2 (CompanyId int, CompanyName varchar(50))
create table #table3 (InvoiceId int, AcceptDate datetime, AcceptType char(1))
insert into #table1 values (3, 1, 2)
insert into #table1 values (4, 2, 2)
insert into #table1 values (6, 1, 1)
insert into #table1 values (7, 3, 2)
insert into #table1 values (8, 4, 2)
insert into #table1 values (9, 2, 1)
insert into #table2 values (1, 'Name1')
insert into #table2 values (2, 'Name2')
insert into #table3 values (3, '2012-01-01', 'o')
insert into #table3 values (3, '2012-01-02', 'p')
insert into #table3 values (6, '2012-01-03', 'p')
insert into #table3 values (4, '2012-01-04', 'o')
insert into #table3 values (7, '2012-01-05', 'o')
insert into #table3 values (9, '2012-01-06', 'p')
insert into #table3 values (7, '2012-01-07', 'p')

SELECT #table1.InvoiceId, #table1.InvoiceNumber, t.o as [AcceptDate1], t.p as [AcceptDate2], #table2.CompanyName
FROM #table3 pivot (max(AcceptDate) for AcceptType IN ("o", "p")) as t
JOIN #table1 on #table1.InvoiceId = t.InvoiceId
JOIN #table2 on #table2.CompanyId = #table1.CompanyId

ROLLBACK

InvoiceId   InvoiceNumber AcceptDate1             AcceptDate2             CompanyName
----------- ------------- ----------------------- ----------------------- --------------------------------------------------
3           1             2012-01-01 00:00:00.000 2012-01-02 00:00:00.000 Name2
4           2             2012-01-04 00:00:00.000 NULL                    Name2
6           1             NULL                    2012-01-03 00:00:00.000 Name1
7           3             2012-01-05 00:00:00.000 2012-01-07 00:00:00.000 Name2
9           2             NULL                    2012-01-06 00:00:00.000 Name1

(5 row(s) affected)