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DP-203 Practice Question: A company uses Azure Synapse Analytics with…
A company uses Azure Synapse Analytics with dedicated SQL pools. They notice that query performance degrades significantly during peak hours. They have already scaled up the Data Warehouse Units (DWU) to the maximum. Which action should they take next to improve performance?
⚠ Common exam trap
It's easy for candidates to confuse result-set caching with materialized views or index maintenance, assuming that only index rebuilds or scaling can fix performance, but result-set caching is a lightweight, no-cost configuration change that directly addresses repeated query patterns during peak load.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable result-set caching.
When a dedicated SQL pool is already at maximum DWU, further scaling is not possible. Enabling result-set caching stores query results in the SSD-based cache of the SQL pool, allowing repeated queries to be served directly from cache without re-scanning data or re-computing aggregations. This reduces I/O and CPU pressure during peak hours, improving performance for recurring queries without requiring additional compute resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable result-set caching.
Why this is correct
Result-set caching stores query results in the SSD cache, reducing compute resource usage and improving performance for repeated queries.
- ✗
Rebuild all clustered columnstore indexes.
Why it's wrong here
Rebuilding indexes can improve performance but is a maintenance task, not the immediate step for peak-hour degradation.
- ✗
Increase the number of concurrency slots.
Why it's wrong here
Increasing concurrency slots allows more queries to run simultaneously but does not improve individual query performance.
- ✗
Move the data to Azure Data Lake Storage Gen2.
Why it's wrong here
Moving data does not directly improve query performance on the dedicated SQL pool.
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