Forum Discussion
Refreshing Failure
- 1 year ago
Hi Florcita,
Thank you for reaching out to the Microsoft fabric community forum. Thank you pallavi_r, and Deku, for your inputs on this issue.After reviewing the details you provided, I have identified few workarounds that may help resolve the issue. Please follow these steps:
If you are using Power BI Pro, consider upgrading to Power BI Premium (P1 or higher). For Premium users, monitor capacity usage in the Power BI Admin Portal and scale up if necessary. To check capacity: Go to Power BI Service → Admin Portal → Capacity Settings → Review memory consumption.
What is Power BI Premium? - Power BI | Microsoft Learn
Enable Large Dataset Storage Format if it is not already enabled, as the dataset might be hitting memory limits. To enable this option in Power BI Service, go to Dataset Settings → Enable Large Dataset Storage Format.Large semantic models in Power BI Premium - Power BI | Microsoft Learn
Use Aggregations: Pre-aggregate data in the Trade Order table to reduce granularity. Avoid Using Calculated Columns: Instead, create calculations in Power Query or use DAX measures. Remove Unused Relationships: Remove tables not used in relationships to free up memory. Reduce Cardinality: For columns with high cardinality (e.g., timestamps), consider rounding them to date level instead of datetime.
User-defined aggregations - Power BI | Microsoft Learn
For Premium capacity users, Hybrid Tables allow a mix of Import and DirectQuery, reducing memory usage. Ensure filters and transformations are pushed to the source using query folding in Power Query. Use native SQL queries in Power Query when dealing with large datasets from SQL Server.
I hope this could resolve your issue, if you need any further assistance, feel free to reach out.
If this post helps, then please give us ‘Kudos’ and consider Accept it as a solution to help the other members find it more quickly.Thank you for using Microsoft Community Forum.
Hi Florcita ,
There are multiple factors involved as mentioned below. We need to find out is this your real data size or there is any issue in the model which needs to be fixed. The below points ensure that model is optimized.
1. Size of the dataset - The F64 equivalent to P1 capacity can handle max 25 gb of memory. I used to get this error with dataset size crossing 13+ gb because during refresh, memory gets doubled during refresh.
2.Ensure you have dataset in large dataset format
3. Incremental refresh - hope you have taken care of incremental refresh for large dataset, otherwise these error is inevitable.
4.Calculated columns - Calculated columns makes the model size bigger. So prefer to use measure for aggregated values.
5.Reduce the granularity of data wherever possible
6.Check if there is unnecessary columns, tables to reduce the memory of dataset
Can you please share more details like what is the sku used and have you tried incremental refresh.
Thanks,
Pallavi