DP-700 · Question #10
You have a Fabric F32 capacity that contains a workspace. The workspace contains a warehouse named DW1 that is modeled by using MDS metadata. Surrogate keys. DW1 contains a single fact table that…
The correct answer is B. Increase the capacity. To resolve performance degradation and errors in Direct Lake reports on a growing fact table, increasing the Fabric capacity is the most direct solution for best query performance.
Question
Options
- AChange the MD5 hash to SHA256.
- BIncrease the capacity.
- CEnable v-Order.
- DModify the surrogate keys to use a different data type.
- ECreate views.
How the community answered
(45 responses)- A2% (1)
- B80% (36)
- D11% (5)
- E7% (3)
Why each option
To resolve performance degradation and errors in Direct Lake reports on a growing fact table, increasing the Fabric capacity is the most direct solution for best query performance.
Changing hashing algorithms like MD5 to SHA256 is relevant for security or data integrity, not for resolving Direct Lake query performance issues or resource errors.
When Direct Lake reports experience performance degradation and errors due to a significantly growing fact table, it indicates that the current Fabric capacity (F32) is likely insufficient to handle the increased query workload. Increasing the capacity provides more computational resources (CPU and memory), directly resolving resource exhaustion and improving query performance for larger datasets, thereby meeting the 'best query performance' requirement.
Enabling v-Order optimizes the underlying Delta Lake file format for faster reads, which can improve performance. However, if the underlying capacity is exhausted, v-Order alone might not prevent query errors due to insufficient resources.
Modifying the data type of surrogate keys is a significant data model change and is unlikely to be the primary cause or solution for general performance degradation and errors in reports on a large fact table.
Creating views provides a logical abstraction over tables but does not inherently improve the underlying query performance of the fact table itself or address resource-related errors.
Concept tested: Direct Lake Performance Optimization (Capacity Scaling)
Source: https://learn.microsoft.com/en-us/fabric/enterprise/about-capacity-management
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