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.

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 output




 

Suggested Answer: BF

Scale out the query by allowing the system to process each input partition separately.
F: A Stream Analytics job definition includes inputs, a query, and output. Inputs are where the job reads the data stream from.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization

This question is in DP-201 Designing an Azure Data Solution Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate



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