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Editorial Team
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Editorial Team
Asked: May 13, 20262026-05-13T14:27:03+00:00 2026-05-13T14:27:03+00:00

I have this webapplication tool which queries over data and shows it in a

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I have this webapplication tool which queries over data and shows it in a grid. Now a lot of people use it so it has to be quite performant.

The thing is, I needed to add a couple of extra fields through joins and now it takes forever for the query to run.

If I in sql server run the following query:

select top 100 *
from bam_Prestatie_AllInstances p
join bam_Zending_AllRelationships r on p.ActivityID = r.ReferenceData
join bam_Zending_AllInstances z on r.ActivityID = z.ActivityID
where p.PrestatieZendingOntvangen >= '2010-01-26' and p.PrestatieZendingOntvangen < '2010-01-27'

This takes about 35-55seconds, which is waaay too long. Because this is only a small one.

If I remove one of the two date checks it only takes 1second. If I remove the two joins it also takes only 1 second.

When I use a queryplan on this I can see that 100% of the time is spend on the indexing of the PrestatieZendingOntvangen field. If I set this field to be indexed, nothing changes.

Anybody have an idea what to do?

Because my clients are starting to complain about time-outs etc.

Thanks

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  1. Editorial Team
    Editorial Team
    2026-05-13T14:27:03+00:00Added an answer on May 13, 2026 at 2:27 pm

    Besides the obvious question of an index on the bam_Prestatie_AllInstances.PrestatieZendingOntvangen column, also check if you have indices for the foreign key columns:

    • p.ActivityID (table: bam_Prestatie_AllInstances)
    • r.ReferenceData (table: bam_Zending_AllRelationships)
    • r.ActivityID (table: bam_Zending_AllRelationships)
    • z.ActivityID (table: bam_Zending_AllInstance)

    Indexing the foreign key fields can help speed up JOINs on those fields quite a bit!

    Also, as has been mentioned already: try to limit your fields being selected by specifying a specific list of fields – rather than using SELECT * – especially if you join several tables, just the sheer number of columns you select (multiplied by the number of rows you select) can cause massive data transfer – and if you don’t need all those columns, that’s just wasted bandwidth!

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