I'm fairly certain in this case the query can be written without the use of any CASE
statements, actually:
DECLARE @From DATE = '20140101'
declare @To DATE = '20140201'
SELECT Mortgage.lender, Mortgage.amountRequested, Profile.caseTypeId,
COUNT(Issue.issued) as issued,
COUNT(Pass.passed) as passed,
COUNT(Receive.received) as received,
COUNT(Offer.offered) as offered
FROM BPS.dbo.tbl_Profile_Mortgage as Mortgage
JOIN BPS.dbo.tbl_Profile as Profile
ON Mortgage.fk_profileId = Profile.id
AND Profile.caseTypeId = 2
LEFT JOIN (VALUES (1, @From, @To)) Issue(issued, rangeFrom, rangeTo)
ON Mortgage.DateAppIssued >= Issue.rangeFrom
AND Mortgage.DateAppIssued < Issue.rangeTo
LEFT JOIN (VALUES (2, @From, @To)) Pass(passed, rangeFrom, rangeTo)
ON Mortgage.DatePassed >= Pass.rangeFrom
AND Mortgage.DatePassed < Pass.rangeTo
LEFT JOIN (VALUES (3, @From, @To)) Receive(received, rangeFrom, rangeTo)
ON Mortgage.DateAppRcvd >= Receive.rangeFrom
AND Mortgage.DateAppRcvd < Receive.rangeTo
LEFT JOIN (VALUES (4, @From, @To)) Offer(offered, rangeFrom, rangeTo)
ON Mortgage.DateOffered >= Offer.rangeFrom
AND Mortgage.DateOffered < Offer.rangeTo
WHERE Mortgage.lender > ''
AND (Issue.issued IS NOT NULL
OR Pass.passed IS NOT NULL
OR Receive.received IS NOT NULL
OR Offer.offered IS NOT NULL)
GROUP BY Mortgage.lender, Mortgage.amountRequested, Profile.caseTypeId
(not tested, as I lack a provided data set).
... Okay, some explanations are in order, because some of this is slightly non-intuitive.
First off, read this blog entry for tips about dealing with date/time/timestamp ranges (interestingly, this also applies to all other non-integral types). This is why I modified the @To
date - so the range could be safely queried without needing to convert types (and thus ignore indices). I've also made sure to choose a safe format - depending on how you're calling this query, this is a non issue (ie, parameterized queries taking an actual Date
type are essentially format-less).
......
COUNT(Issue.issued) as issued,
......
LEFT JOIN (VALUES (1, @From, @To)) Issue(issued, rangeFrom, rangeTo)
ON Mortgage.DateAppIssued >= Issue.rangeFrom
AND Mortgage.DateAppIssued < Issue.rangeTo
.......
What's the difference between COUNT(*)
and COUNT(<expression>)
? If <expression>
evaluates to null
, it's ignored. Hence the LEFT JOIN
s; if the entry for the mortgage isn't in the given date range for the column, the dummy table doesn't attach, and there's no column to count. Unfortunately, I'm not sure how the interplay between the dummy table, LEFT JOIN
, and COUNT()
here will appear to the optimizer - the joins should be able to use indices, but I don't know if it's smart enough to be able to use that for the COUNT()
here too....
(Issue.issued IS NOT NULL
OR Pass.passed IS NOT NULL
OR Receive.received IS NOT NULL
OR Offer.offered IS NOT NULL)
This is essentially telling it to ignore rows that don't have at least one of the columns. They wouldn't be "counted" in any case (well, they'd likely have 0
) - there's no data for the function to consider - but they would show up in the results, which probably isn't what you want. I'm not sure if the optimizer is smart enough to use this to restrict which rows it operates over - that is, turn the JOIN
conditions into a way to restrict the various date columns, as if they were in the WHERE
clause too. If the query runs slow, try adding the date restrictions to the WHERE
clause and see if it helps.