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[英]T-SQL Pivot table not using IN and values from another column in the pivot data based on MIN() & MAX
[英]Populate Column Data based on source table in T-SQL
我不确定我的问题的措词是否正确,但这是正确的。
我有一个名为Contacts的表,该表具有对表Address,Email和Phone的FK引用( 这些与Contacts一对一 )。 我需要创建一个将提取所有数据的查询,并有一个名为Contact Method的列,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
我需要结果表如下所示:
ContactMethod | ID | [Value1] | [Value2] | [Value3]
Address 2 N5980 Onalaska WI
Email 8 myEmail@
Phone 5 555-5555 1234
或者它可以列出一行中的所有组合列,如果这更简单,我也可以使用它。 即
ContactMethad | ID | Line1 | City | State | ID | EAddress | ID | Number | Extension
我看着PIVOT ,这很整洁,但似乎并没有解决我的问题。 我需要将它与COALESCE结合使用吗?
谢谢你的帮助。
编辑
我的数据,表格上的联系人看起来像这样:
ID | AddressID | PhoneID | EmailID
1 3 null null
2 null null 7
3 null 5 null
4 4 null null
5 null 6 null
建议的解决方案有效,除了我每个ID获得3行。 说得通?
您可以使用CROSS APPLY
和VALUES
子句取消数据以获取结果:
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)
请参阅SQL Fiddle with Demo 。
这给出了结果:
| CONTACTMETHOD | ID | VALUE1 | VALUE2 | VALUE3 |
-----------------------------------------------------
| Address | 2 | N5980 | Onalaska | WI |
| Email | 8 | myEmail@ | | |
| Phone | 5 | 555-5555 | 1234 | |
如果您想要第二个结果,那么您可以使用多个连接来获取它:
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';
请参阅SQL Fiddle with Demo 。 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,根据您的更改,您可以将查询更改为以下内容。
第一个带有三个value
列,然后您可以添加一个WHERE
子句来过滤掉任何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
请参阅SQL Fiddle with Demo 。 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 |
如果您希望将结果放在一行中,那么您将需要使用UNPIVOT
函数:
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';
请参阅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) |
进入第二列布局要容易得多。 为此你只需要加入:
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
我只是使用SELECT *
,但是您实际上必须列出所有列,因为您不希望所有列。 如果您不必在每个子表中都有一行,则需要使用LEFT OUTER JOIN
而不是JOIN
。
有关JOIN的更多详细信息,请检阅此系列: http : //sqlity.net/zh/1146/a-join-a-day-introduction/
如果您需要多行,可以使用:
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'
使用“ spread out”版本的优点是您不必处理数据类型的不兼容性。
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