DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are monitoring an Azure Synapse Analytics dedicated SQL pool that is experiencing performance degradation during peak hours. You notice that some queries are being queued due to resource contention. You need to optimize query performance without scaling the Data Warehouse Units (DWUs). Which action should you take?
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
✓
Configure result-set caching for the dedicated SQL pool.
Result-set caching can significantly reduce query time for repeated queries by storing results in SSD, reducing resource contention. Option A is wrong because increasing DWUs changes the scale, which is not allowed per the requirement. Option B is wrong because materialized views help but do not directly address contention from repeated queries. Option D is wrong because workload classification manages concurrency but does not reduce resource usage for repeated queries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the DWU setting to allocate more resources.
Why it's wrong here
Scaling up violates the requirement to not scale DWUs.
- ✗
Create materialized views for frequently joined tables.
Why it's wrong here
Materialized views improve read performance but do not reduce contention from repeated queries as effectively as result-set caching.
- ✓
Configure result-set caching for the dedicated SQL pool.
Why this is correct
Result-set caching stores query results in SSD, reducing resource usage for repeated queries and alleviating contention.
- ✗
Implement workload classification and assign the queries to a higher importance level.
Why it's wrong here
Workload classification manages concurrency and priority but does not reduce the resource consumption of repeated queries.
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Written by Johnson Ajibi, MSc IT Security
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