Forum Discussion
Get Error in Service
- 1 year ago
Hi Anonymous
The error you're encountering in Power BI Service — "Resource Governing: This query uses more memory than the configured limit" — indicates that the visual or its underlying DAX query is exceeding the per-query memory limit allowed by your current license tier, which is Power BI Pro. In Pro, the memory and CPU resources allocated for dataset processing and visual rendering are more constrained compared to Power BI Premium. Despite your efforts to simplify the DAX for the visual, it's likely that the combination of data volume, relationships, calculated columns/measures, or visuals themselves still leads to high memory usage (in your case, 1,331 MB, which hits the exact memory ceiling for a Pro environment).
This issue typically doesn’t occur in Power BI Desktop because the desktop version uses your local machine’s resources without the same memory throttling. But once published to the Power BI Service, queries are governed based on your tenant’s capacity tier.
To resolve this:
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Simplify the visual: Reduce the number of fields, complex measures, or visual filters.
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Avoid complex calculated columns/measures especially ones using iterators like
SUMX, FILTER, or nested IF conditions.
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Reduce data granularity: Use aggregations or summarized tables instead of detailed data.
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Optimize the model: Remove unnecessary columns, relationships, or hidden fields that increase model size and complexity.
Since you are on Pro, and not Premium, you cannot increase the memory limits. If the report must run in its current state, consider moving the workspace to a Power BI Premium capacity (P SKU or F SKU in Fabric), where the per-query memory limit is higher and adjustable by an admin.
For now, use tools like Performance Analyzer in Power BI Desktop and DAX Studio to find the most expensive queries/measures, and reduce their memory footprint.
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Hi Anonymous ,
Thank you for the clear explanation Poojara_D12 , it really helped understand the root cause more clearly. I’d like to share a few additional suggestions.
1. Consider breaking large visuals into smaller ones or using fewer fields, as this can improve performance.
2. When writing DAX, try to avoid memory intensive functions like SUMX and FILTER where possible optimizing these can be beneficial.
3. Aggregating data before loading it into Power BI and using summarized tables instead of full transactional data can help reduce the load.
4. Tools such as Performance Analyzer and DAX Studio are useful for identifying which queries are using the most memory.
If the report is business critical and still exceeds Pro memory limits, consider exploring Premium capacity (F SKU), which offers a higher and adjustable memory limit per query.
— Yugandhar
Community Support Team.