Implementing an Azure Data Solution (legacy) — Question 3

A company has a real-time data analysis solution that is hosted on Microsoft Azure. The solution uses Azure Event Hub to ingest data and an Azure Stream
Analytics cloud job to analyze the data. The cloud job is configured to use 120 Streaming Units (SU).
You need to optimize performance for the Azure Stream Analytics job.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer options

• A. Implement event ordering
• B. Scale the SU count for the job up
• C. Implement Azure Stream Analytics user-defined functions (UDF)
• D. Scale the SU count for the job down
• E. Implement query parallelization by partitioning the data output
• F. Implement query parallelization by partitioning the data input

Correct answer: B, F

Explanation

Increasing the SU count for the job (B) allows for more resources to be allocated to processing, which can improve performance. Additionally, implementing query parallelization by partitioning the data input (F) can enhance throughput by allowing multiple processing operations to occur simultaneously. The other options do not directly address performance optimization in the same effective manner.