DP-203 Practice Question: Secure, monitor, and optimize data storage and data processing
You are monitoring Azure Stream Analytics job performance. The job is falling behind in processing real-time data. You notice that the SU (Streaming Unit) utilization is consistently at 90% or higher. What is the most appropriate action to improve throughput?
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
✓
Increase the number of Streaming Units (SUs)
When SU utilization is consistently at 90% or higher, the job is resource-constrained, which leads to backpressure and falling behind. The most direct way to improve throughput is to increase the number of Streaming Units (SUs), as this adds more compute capacity. Option A (changing output to use a partition scheme) can improve performance in some cases but is not the immediate step and may not resolve high SU utilization. Option B (reducing window duration) can cause data loss or inaccurate results, and does not address the resource bottleneck. Option D (decreasing event ordering tolerance) also risks data loss and is not a throughput improvement measure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the output to use a partition scheme
Why it's wrong here
Partitioning may help but scaling is more direct
- ✗
Reduce the window duration in the query
Why it's wrong here
Would reduce accuracy, not necessarily throughput
- ✓
Increase the number of Streaming Units (SUs)
Why this is correct
Scaling out increases processing capacity
- ✗
Decrease the event ordering tolerance
Why it's wrong here
Might reduce throughput
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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