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Bug Report T306333
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Top N percent feature operates inefficiently in Server Mode

created 9 years ago

[DevExpress Support Team: CLONED FROM T291311: Top x percent not applied correctly on PivotGrid in Server Mode]
HI

Also,  on the record set we are currently running with that has over a million rows, the methodology you are implementing where your query builds a list of values for the top x% and then executes more queries providing that list as an 'in' list we get the following error: "The query processor ran out of internal resources and could not produce a query plan. This is a rare event and only expected for extremely complex queries or queries that reference a very large number of tables or partitions. Please simplify the query. If you believe you have received this message in error, contact Customer Support Services for more information."

Many Thanks
Pete

Show previous comments (2)
DevExpress Support Team 9 years ago

    At present we do not have any news regarding. Please let us know if this issue is critical for you. In this case, we will try to process it with higher priority.

    PC PC
    Pete Coales 9 years ago

      Constant
      Thank you.  It is critical for us so please escalate.
      Many Thanks
      Pete

      DevExpress Support Team 9 years ago

        I have notified our developers that this issue is  critical for you. We are working on it and will inform you of our results in the near future.

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        Answers approved by DevExpress Support

        created 9 years ago

        We have fixed the issue described in this ticket and will include the fix in our next maintenance update. To apply this solution before the official update, request a hotfix by clicking the corresponding link for product versions you require.

        Note: Hotfixes may be unavailable for beta versions and updates that are about to be released.

        Additional information:

        The issue is fixed. Now, PivotGridControl selects TopN items by using the SubSelect statement. Please note that this operation can cause performance issues with large databases. So, it's recommended to use data pre-aggregation or an OLAP data source if you need to work with large databases.

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