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Question 103 - DP-203 discussion

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

Explanation:

D: 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

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asked 02/10/2024
Chris Morris
39 questions
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