DP-600 · Question #203
You have a Fabric tenant that contains 30 CSV files in OneLake. The files are updated daily. You create a Microsoft Power BI semantic model named Model1 that uses the CSV files as a data source. You c
The correct answer is D. Only refresh complete days is selected.. When 'Only refresh complete days' is selected in Power BI incremental refresh, the engine must process and validate full-day partitions for all 30 CSV files. CSV files in OneLake do not support query folding, meaning date/time filter predicates cannot be pushed back to the source
Question
You have a Fabric tenant that contains 30 CSV files in OneLake. The files are updated daily. You create a Microsoft Power BI semantic model named Model1 that uses the CSV files as a data source. You configure incremental refresh for Model1 and publish the model to an F64 capacity in the Fabric tenant. When you initiate a refresh of Model1, the refresh fails after running out of resources. What is a possible cause of the failure?
Options
- AXMLA Endpoint is set to Read Only.
- BQuery folding is occurring.
- CThe data type of the column used to partition the data has changed.
- DOnly refresh complete days is selected.
- EQuery folding is NOT occurring.
How the community answered
(64 responses)- A3% (2)
- B6% (4)
- C2% (1)
- D73% (47)
- E16% (10)
Explanation
When 'Only refresh complete days' is selected in Power BI incremental refresh, the engine must process and validate full-day partitions for all 30 CSV files. CSV files in OneLake do not support query folding, meaning date/time filter predicates cannot be pushed back to the source. Instead, the entire dataset must be loaded into the engine's memory so filters can be applied in-memory. Combined with the 'complete days' requirement forcing evaluation of every historical partition to confirm completeness, this results in extreme memory consumption that exhausts F64 capacity resources. Option A (read-only XMLA) would block write operations but not cause resource exhaustion. Option E (no query folding) is a contributing factor for CSV sources but is not itself the configuration choice that triggers the failure - Option D is the specific setting that forces the expensive full-partition evaluation.
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