Reputation: 12216
I'm not sure my question is even worded correctly but here goes.
I have a table called Contacts that has FK references to tables Address, Email, Phone (these have 1 to many with Contacts). I need to create a query that will pull all the data and has a column called Contact Method that shows which sub table that row came from.
Contact: ID, AddressID, EmailID, PhoneID
Address: ID, Line1, City, State
Email : ID, EAddress
Phone : ID, Number, Extension
I need the resulting table to look like this:
ContactMethod | ID | [Value1] | [Value2] | [Value3]
Address 2 N5980 Onalaska WI
Email 8 myEmail@
Phone 5 555-5555 1234
Alternatively it could list all the combined columns in a row if that's simpler, I can work with that as well. i.e.
ContactMethad | ID | Line1 | City | State | ID | EAddress | ID | Number | Extension
I looked at PIVOT, which is neat but doesn't seem to solve my problem by itself. Do I need to combine it with COALESCE?
Thanks for any help.
EDIT
My data, on table Contact would look like this:
ID | AddressID | PhoneID | EmailID
1 3 null null
2 null null 7
3 null 5 null
4 4 null null
5 null 6 null
The proposed solution works except that I get 3 rows per ID. Make sense?
Upvotes: 2
Views: 1362
Reputation: 247850
You can unpivot the data using a CROSS APPLY
and VALUES
clause to get the result:
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)
See SQL Fiddle with Demo.
This gives the result:
| CONTACTMETHOD | ID | VALUE1 | VALUE2 | VALUE3 |
-----------------------------------------------------
| Address | 2 | N5980 | Onalaska | WI |
| Email | 8 | myEmail@ | | |
| Phone | 5 | 555-5555 | 1234 | |
If you want your second result, then you can use multiple joins to get it:
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';
See SQL Fiddle with Demo. The result is:
| 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 |
Edit #1, based on your changes you can alter the queries to the the following.
The first one with the three value
columns, then you can just add a WHERE
clause to filter out any null
values:
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
See SQL Fiddle with Demo. The result is:
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 |
If you want the results in a single row, then you will want to use the UNPIVOT
function:
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';
See SQL Fiddle with Demo. The result of this query is:
| 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) |
Upvotes: 7
Reputation: 11813
It is a lot easier to get to the second column layout. For that you just need to join:
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
I just used SELECT *
, but you will have to actually list all the columns as you do not want all of them. If you do not necessarily have a row in each child table you need to use LEFT OUTER JOIN
instead of just JOIN
.
For more details about JOINs checkout this series: http://sqlity.net/en/1146/a-join-a-day-introduction/
If you need multiple rows you can use this:
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'
The advantage of going with the "spread out" version is that you do not have to deal with data type incompatibilities.
Upvotes: 0