Reputation: 337
i've got the below code, and it operates just fine, only it takes a couple of seconds to calculate the answer - i was wondering whether there is a quicker/neater way of writing this code - and if so, what am i doing wrong?
thanks
select case when
(select LSCCert from matterdatadef where ptmatter=$Matter$) is not null then
(
(select case when
(SELECT top 1 dbo.matterdatadef.ptmatter
From dbo.workinprogress, dbo.MatterDataDef
where ptclient=(
select top 1 dbo.workinprogress.ptclient
from dbo.workinprogress
where dbo.workinprogress.ptmatter = $matter$)
and dbo.matterdatadef.LSCCert=(
select top 1 dbo.matterdatadef.LSCCert
from dbo.matterdatadef
where dbo.matterdatadef.ptmatter = $matter$)
)=ptMatter then (
SELECT isnull((DateAdd(mm, 6, (
select top 1 Date
from OfficeClientLedger
where (pttrans=3)
and ptmatter=$matter$
order by date desc))),
(DateAdd(mm, 3, (
SELECT DateAdd
FROM LAMatter
WHERE ptMatter = $Matter$)))
)
)
end
from lamatter
where ptmatter=$matter$)
)
end
Upvotes: 1
Views: 155
Reputation: 425013
It looks like this your sql was generated from a reporting tool. The problem is you are executing the SELECT top 1 dbo.matterdatadef.ptmatter...
query for every row of table lamatter
. Further slowing execution, within that query you are recalculating comparison values for both ptclient and LSCCert - values that aren't going to change during execution.
Better to use proper joins and craft the query to execute each part only once by avoiding correlated subqueries (queries that reference values in joined tables and must be executed for every row of that table). Calculated values are OK, as long as they are calculated only once - ie from within the final where clause.
Here is a trivial example to demonstrate a correlated subquery:
Bad sql:
select a, b from table1
where a = (select c from table2 where d = b)
Here the sub-select is run for every row, which will be slow, especially without an index on table2(d)
Better sql:
select a, b from table1, table2
where a = c and d = a
Here the database will scan each table at most once, which will be fast
Upvotes: 1