根据T-SQL中的源表填充列数据

Question

我不确定我的问题甚至措辞正确，但在这里。

我有了对表地址FK引用，电子邮件，电话（这些有1对多与联系人）的表称为联系人。我需要创建一个将提取所有数据的查询，并具有一个名为Contact Method的列，该列显示该行来自哪个子表。

Contact: ID, AddressID, EmailID, PhoneID 
Address: ID, Line1, City, State 
Email : ID, EAddress 
Phone : ID, Number, Extension 

我需要的结果表看起来像这样：

ContactMethod | ID | [Value1] | [Value2] | [Value3] 

Address   2  N5980 Onalaska  WI 
Email   8  myEmail@ 
Phone   5  555-5555 1234 

另外，它可以列出行中的所有组合的列，如果这是简单的，我可以用正常工作。即

ContactMethad | ID | Line1 | City | State | ID | EAddress | ID | Number | Extension 

我看着PIVOT，这是整洁，但似乎并没有通过自身来解决我的问题。我需要将它与COALESCE结合吗？

感谢您的任何帮助。

---

编辑

我的数据，上表联系是这样的：

ID | AddressID | PhoneID | EmailID 

1  3   null  null 
2  null   null  7 
3  null   5  null 
4  4   null  null 
5  null   6   null 

提出的解决方案，除了工作，我得到的每ID 3行。合理？

Answer 1

可以逆转置使用CROSS APPLY和VALUES子句，以获得结果的数据：

select d.ContactMethod, d.id, d.Value1, d.Value2, d.Value3 
from contacts c 
left join address a 
    on c.addressid = a.id 
left join email e 
    on c.emailid = e.id 
left join phone p 
    on c.phoneid = p.id 
cross apply 
(
    values 
    ('Address', c.addressid, a.Line1, a.City, a.State), 
    ('Email', c.emailid, e.eAddress, '', ''), 
    ('Phone', c.phoneid, p.number, cast(p.extension as varchar(10)), '') 
) d (ContactMethod, id, Value1, Value2, Value3) 

见SQL Fiddle with Demo。

这给出结果：

| CONTACTMETHOD | ID | VALUE1 | VALUE2 | VALUE3 | 
----------------------------------------------------- 
|  Address | 2 | N5980 | Onalaska |  WI | 
|   Email | 8 | myEmail@ |   |  | 
|   Phone | 5 | 555-5555 |  1234 |  | 

如果你想你的第二个结果，那么您可以使用多个连接来得到它：

select cm.ContactMethod, 
    a.id addressid, 
    a.line1, 
    a.city, 
    a.state, 
    e.id emailid, 
    e.eaddress, 
    p.id phoneid, 
    p.number, 
    p.extension 
from contacts c 
cross join 
(
    VALUES ('Address'),('Email'),('Phone') 
) cm (ContactMethod) 
left join address a 
    on c.addressid = a.id 
    and cm.ContactMethod = 'Address' 
left join email e 
    on c.emailid = e.id 
    and cm.ContactMethod = 'Email' 
left join phone p 
    on c.phoneid = p.id 
    and cm.ContactMethod = 'Phone'; 

见SQL Fiddle with Demo。其结果是：

| CONTACTMETHOD | ADDRESSID | LINE1 |  CITY | STATE | EMAILID | EADDRESS | PHONEID | NUMBER | EXTENSION | 
---------------------------------------------------------------------------------------------------------------- 
|  Address |   2 | N5980 | Onalaska |  WI | (null) | (null) | (null) | (null) | (null) | 
|   Email | (null) | (null) | (null) | (null) |  8 | myEmail@ | (null) | (null) | (null) | 
|   Phone | (null) | (null) | (null) | (null) | (null) | (null) |  5 | 555-5555 |  1234 | 

编辑＃1，根据你的改变，你可以改变查询到以下。

第一个与三个value列，那么你可以只添加一个WHERE子句过滤掉任何null值：

select c.ID, ContactMethod, Value1, Value2, Value3 
from contacts c 
left join address a 
    on c.addressid = a.id 
left join email e 
    on c.emailid = e.id 
left join phone p 
    on c.phoneid = p.id 
cross apply 
(
    values 
    ('Address', c.addressid, a.Line1, a.City, a.State), 
    ('Email', c.emailid, e.eAddress, null, null), 
    ('Phone', c.phoneid, p.number, cast(p.extension as varchar(10)), null) 
) d (ContactMethod, id, Value1, Value2, Value3) 
where value1 is not null 
    or value2 is not null 
    or value3 is not null 

见SQL Fiddle with Demo。其结果是：

ID | CONTACTMETHOD |   VALUE1 | VALUE2 | VALUE3 | 
--------------------------------------------------------------- 
| 1 |  Address |    N5980 | Onalaska |  WI | 
| 2 |   Email |   myEmail@ | (null) | (null) | 
| 3 |   Phone |   555-5555 |  1234 | (null) | 
| 4 |  Address | 1417 Saint Andrew | La Crosse |  WI | 

如果你想在一个单列的结果，那么你将要使用的UNPIVOT功能：

select * 
from 
(
    select id, 
    case col 
     when 'addressid' then 'address' 
     when 'emailid' then 'email' 
     when 'phoneid' then 'phone' end ContactMethod, 
    contact_id 
    from contacts 
    unpivot 
    (
    contact_id 
    for col in (addressid, emailid, phoneid) 
) unpiv 
) c 
left join address a 
    on c.contact_id = a.id 
    and c.ContactMethod = 'Address' 
left join email e 
    on c.contact_id = e.id 
    and c.ContactMethod = 'Email' 
left join phone p 
    on c.contact_id = p.id 
    and c.ContactMethod = 'Phone'; 

见SQL Fiddle with Demo。此查询的结果是：

| ID | CONTACTMETHOD | CONTACT_ID |    LINE1 |  CITY | STATE | EADDRESS | NUMBER | EXTENSION | 
-------------------------------------------------------------------------------------------------------------- 
| 1 |  address |   2 |    N5980 | Onalaska |  WI | (null) | (null) | (null) | 
| 2 |   email |   8 |   (null) | (null) | (null) | myEmail@ | (null) | (null) | 
| 3 |   phone |   5 |   (null) | (null) | (null) | (null) | 555-5555 |  1234 | 
| 4 |  address |   3 | 1417 Saint Andrew | La Crosse |  WI | (null) | (null) | (null) | 

Answer 2

到达第二列布局要容易得多。对于你只需要加入：

SELECT * 
FROM dbo.Contact c 
JOIN dbo.Address a 
ON c.AddressID = a.ID 
JOIN dbo. Email e 
ON c. EmailID = e.ID 
JOIN dbo. Phone p 
ON c. PhoneID = p.ID 

我只是用SELECT *，但是你必须实际列出所有列，你不希望所有的人。如果你不一定在每个子表中有一行，你需要使用LEFT OUTER JOIN而不是仅仅是JOIN。

如需详细了解JOIN的结帐这个系列：http://sqlity.net/en/1146/a-join-a-day-introduction/

---

如果你需要多行，你可以使用这个：

SELECT * 
FROM dbo.Contact c 
CROSS JOIN (VALUES('Address','Email','Phone'))X(ContactMethod) 
LEFT JOIN dbo.Address a 
ON c.AddressID = a.ID 
AND X.ContactMethod = 'Address' 
LEFT JOIN dbo. Email e 
ON c. EmailID = e.ID 
AND X.ContactMethod = 'Email' 
LEFT JOIN dbo. Phone p 
ON c. PhoneID = p.ID 
AND X.ContactMethod = 'Phone' 

与“摊开”版去的优点是您不必处理数据类型不兼容问题。