DP-600 · Question #83
You have a Microsoft Power BI semantic model that contains measures. The measures use multiple CALCULATE functions and a FILTER function. You are evaluating the performance of the measures. In which…
The correct answer is D. when the FILTER function references a column from a single table that uses Import mode. KEEPFILTERS is a modifier function that changes how CALCULATE applies filters - instead of overriding existing filters, it intersects with them. The performance benefit of replacing FILTER with KEEPFILTERS applies specifically when FILTER is iterating over a single column of a…
Question
You have a Microsoft Power BI semantic model that contains measures. The measures use multiple CALCULATE functions and a FILTER function. You are evaluating the performance of the measures. In which use case will replacing the FILTER function with the KEEPFILTERS function reduce execution time?
Options
- Awhen the FILTER function uses a nested calculate function
- Bwhen the FILTER function references a measure
- Cwhen the FILTER function references columns from multiple tables
- Dwhen the FILTER function references a column from a single table that uses Import mode
How the community answered
(60 responses)- A3% (2)
- B8% (5)
- C17% (10)
- D72% (43)
Explanation
KEEPFILTERS is a modifier function that changes how CALCULATE applies filters - instead of overriding existing filters, it intersects with them. The performance benefit of replacing FILTER with KEEPFILTERS applies specifically when FILTER is iterating over a single column of a table in Import mode. In this scenario, FILTER(Table, Table[Column] = value) iterates over every row, while KEEPFILTERS operates at the filter context level without row-by-row iteration, allowing the VertiPaq engine to use its column store compression and in-memory bitmaps efficiently. It does NOT help when FILTER references a measure (measures require row context evaluation), multiple tables (cross-table iteration is needed), or nested CALCULATE (different execution pattern).
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