In Azure Synapse Analytics, what is the purpose of a workload classification?

To encrypt data at rest using different encryption keys.

To automatically scale the dedicated SQL pool based on query load.

To physically separate data into different storage accounts.

To assign incoming requests to a workload group and apply a set of resource limits.

A team runs a Spark job on a fixed-size cluster in Azure Synapse Analytics. The job has multiple stages, and the Spark UI shows that the cluster is idle for long periods between stages. You need to reduce the overall job runtime without changing the cluster size. What should you do?

Use a fair scheduler to allocate resources evenly across stages.

Review the job's dependency graph and consider coalescing stages or using caching to avoid recomputation.

Enable dynamic allocation to scale executors up and down during the job.

Increase the number of shuffle partitions to reduce stage execution time.

Which strategy is commonly used to mitigate data skew in a Spark job?

Increase the number of files in the input path.

Use a salted key to distribute skewed keys across more partitions.

Disable dynamic allocation to keep executors constant.

Reduce the number of partitions to increase data per partition.

A data lake stores streaming data as JSON files in Azure Data Lake Storage Gen2. Each file is about 100 KB. A daily batch Spark job reads all files to produce a report. The job takes 2 hours, mostly due to file open overhead. The team wants to reduce the job duration without changing the report logic. Which action should be taken?

Change the file format to Avro.

Use Azure Data Factory to copy the files into a single file.

Run a compaction job to merge small files into larger ones.

Increase the Spark cluster's executor memory.

Microsoft Certified:Azure Data Engineer Associate

Domain 3Objective 3

Optimize and Troubleshoot Data Storage and Data Processing DP-203 Practice Questions (Page 7)

Part of the Secure, monitor, and optimize data storage and data processing domain, which accounts for 30–35% of the DP-203 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~12–23 in this domain), expect 4–8 from this objective — we provide 38 practice questions to prepare you well beyond it. (estimate)

38questions here

8free pages

8concepts

30–35%of the exam

Questions 31–35

31foundation · easy
Which type of index is generally recommended for large fact tables in Azure Synapse Analytics to optimize query performance?
Select an answer first
32foundation · easy
In Azure Synapse Analytics, what is the purpose of a workload classification?
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33application · medium
A team runs a Spark job on a fixed-size cluster in Azure Synapse Analytics. The job has multiple stages, and the Spark UI shows that the cluster is idle for long periods between stages. You need to reduce the overall job runtime without changing the cluster size. What should you do?
Select an answer first
34foundation · easy
Which strategy is commonly used to mitigate data skew in a Spark job?
Select an answer first
35application · medium
A data lake stores streaming data as JSON files in Azure Data Lake Storage Gen2. Each file is about 100 KB. A daily batch Spark job reads all files to produce a report. The job takes 2 hours, mostly due to file open overhead. The team wants to reduce the job duration without changing the report logic. Which action should be taken?
Select an answer first

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