Forum Discussion

Anonymous's avatar
Anonymous
Not applicable
5 years ago

Visual Exceeding Available Resources

Hi everyone,

A user has recently started getting an error "The visual has exceeded the available resources. Try filtering to decrease the amount of data displayed". The error mentions a few solution suggestions. First it suggests simplifying the query or calculations but the user said the data imports are small and running fine. The next suggestion is modifying the per-query limit in our premium capacity but this is already set pretty high. 

 

I am trying to determine if this could be related to our premium capacity being overloaded (as the CPU consumption does seem to be higher around this time if I check the performance metrics) or if it is actually related to the visual itself being too large/too intensive in terms of calculations. Has anyone seen this error before and do you have any insight as to the root cause?

 

Thank you so much.

Need Help

2 Replies

  • GilbertQ's avatar
    GilbertQ
    Super User
    5 years ago
    Hi there

    If this is running on a power BI Premium App Workspace I would use the Premium Capacity App and see what is happening at that time with regards to your resources.

    I would also suggest looking at the dataset, making sure it is using the Star Schema, then having optimal DAX measures written. And then finally look at the visual that is being used to see if that too is consuming a lot of resources?

    You can use DAX Studio to open the PBIX and see how much memory the dataset is consuming when opened: https://www.sqlbi.com/tools/vertipaq-analyzer/
  • v-deddai1-msft's avatar
    v-deddai1-msft
    Community Support
    5 years ago

    Hi  Anonymous ,

     

    When you run a DAX query in Power BI it will always use a certain amount of memory; inefficient DAX calculations can cause a query to try to grab a lot of memory.

     

    First you can try to changed the Query Memory Limit % setting :

     

    And you can follow the tips to optimize your report：

     

    1.Do not expose in a view a column that is not necessary in the Power BI data model.

    2.Optimize the DAX calculation used in this visual effect.

    3.Remove unnecessary precision or split granularity values to reduce cardinality（Significantly reduce highly unique datetime values by splitting the date and time into separate columns. ）

     

    And also refer to https://www.sqlbi.com/articles/data-import-best-practices-in-power-bi/ 

     

    If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

     

    Best Regards,

    Dedmon Dai