Forum Discussion
How to exclude large historical table from refresh in Power BI?
- 1 year ago
Hi everyone!
I wanted to share how I finally resolved the issue I posted about earlier regarding excluding a large historical table from refresh in Power BI.🧩 The problem recap:
We had a large fact table (~200M rows, 93 columns), and incremental refresh failed during full dataset refresh due to timeout and memory limits – partitions weren’t being created.
We attempted a Hot & Cold Data approach by splitting into historical and current tables in Power Query and appending them, but even with “Include in refresh” disabled for historical, Power BI still queried it during refresh.
Using DAX UNION to combine both tables increased dataset size and hurt performance due to additional in-memory tables and complex measures.
✅ What worked:
We switched to custom partitioning using Tabular Editor and SQL Server Management Studio (SSMS).
I created one partition per year manually and gradually loaded data year by year.
This approach allowed us to:
Successfully configure incremental refresh.
Avoid timeouts.
Reduce memory pressure during refresh.
🚀 Bonus:
Once all partitions were added and processed, incremental refresh ran smoothly.
This method avoided unnecessary reloading of historical data during refresh and ensured performance remained stable.
I hope this helps someone facing a similar challenge. Feel free to ask if you’d like more technical details! 😊
Hi everyone!
I wanted to share how I finally resolved the issue I posted about earlier regarding excluding a large historical table from refresh in Power BI.
🧩 The problem recap:
We had a large fact table (~200M rows, 93 columns), and incremental refresh failed during full dataset refresh due to timeout and memory limits – partitions weren’t being created.
We attempted a Hot & Cold Data approach by splitting into historical and current tables in Power Query and appending them, but even with “Include in refresh” disabled for historical, Power BI still queried it during refresh.
Using DAX UNION to combine both tables increased dataset size and hurt performance due to additional in-memory tables and complex measures.
✅ What worked:
We switched to custom partitioning using Tabular Editor and SQL Server Management Studio (SSMS).
I created one partition per year manually and gradually loaded data year by year.
This approach allowed us to:
Successfully configure incremental refresh.
Avoid timeouts.
Reduce memory pressure during refresh.
🚀 Bonus:
Once all partitions were added and processed, incremental refresh ran smoothly.
This method avoided unnecessary reloading of historical data during refresh and ensured performance remained stable.
I hope this helps someone facing a similar challenge. Feel free to ask if you’d like more technical details! 😊
- v-menakakota1 year ago
Community Support
Hi katushka_enko ,
Please accept your reply as accept as solution,so the community members can easily find it.
Thank you.