How to make this SQL query using IN (with many numeric IDs) more efficient?

Question

I've been waiting over an hour already for this query, so I know I'm probably doing something wrong. Is there efficient way to tailor this query: ?

select RespondentID, MIN(SessionID) as 'SID'
from BIG_Sessions (nolock)
where RespondentID in (
1418283,
1419863,
1421188,
1422101,
1431384,
1435526,
1437284,
1441394,
/* etc etc THOUSANDS */
1579244 )
    and EntryDate between
    '07-11-2011' and '07-31-2012'
GROUP BY RespondentID 

I kknow that my date range is pretty big, but I can't change that part (the dates are spread all over) .

Also, the reason for MIN(SessionID) is because otherwise we get many SessionID's for each Respondent, and one suffices(it's taking MIN on an alphanumeric ID like ach2a23a-adhsdx123... and getting the first alphabetically)

Thanks

Answer 1

1. Put your thousands of numbers in a temporary table.
2. Index the number field in that table.
3. Index the RespondentID field in BIG_SESSIONS
4. Join the two tables

eg:

select RespondentID, MIN(SessionID) as 'SID' 
from BIG_Sessions (nolock) 
    inner join RespondentsFilterTable 
        on BIG_SESSIONS.RespondentID = RespondentsFilterTable.RespondentID
where EntryDate between '07-11-2011' and '07-31-2012' 
GROUP BY BIG_Sessions.RespondentID

You could add indexes to EntryDate and SessionID as well, but if you're adding to big_sessions frequently, this could be counter productive elsewhere

In general, you can can get hints of how performance of a query can be improved by studying the estimated (or if possible actual) execution plans.

Answer 2

If the smallest and largest ids in the IN statement are known beforehands and depending on how many ids are in the table then adding a respondedID > [smallest_known_id-1] AND respondedID < [largest_known_id+1] prior to the IN statement would help limiting the problem