Develop a Batch Processing Solution DP-203 Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   In Azure Synapse Analytics, which type of pool provides on-demand, pay-per-query SQL processing for data stored in Azure Data Lake Storage Gen2, without requiring you to provision dedicated compute?

   • ADedicated SQL pool
   • BData flow pool
   • CSpark pool
   • DServerless SQL pool
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2. 7foundation · easy

   In Azure Synapse Analytics dedicated SQL pool, which action increases the number of compute nodes to improve query performance for large batch loads?

   • AScale up the data warehouse unit (DWU) setting
   • BCreate additional external tables
   • CPause the dedicated SQL pool
   • DEnable row-level security
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4. 8application · medium

   A data science team uses Azure Databricks to develop and run batch processing jobs. They have a Python notebook that performs data cleaning and feature engineering. The team wants to schedule this notebook to run daily and integrate it with other data processing steps in a pipeline. What should the team do?

   • AUse the Databricks job scheduler to run the notebook daily, and then manually trigger other data processing steps.
   • BCreate an Azure Data Factory pipeline with a 'Databricks Notebook' activity that references the notebook and schedule the pipeline to run daily.
   • CConvert the notebook to a Python script and run it as an Azure Function on a schedule.
   • DUse a 'Web' activity in an Azure Data Factory pipeline to call the Databricks API to run the notebook.
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5. 9expert · hard

   A data engineering team is loading data from Azure Data Lake Storage Gen2 into a dedicated SQL pool in Azure Synapse Analytics using PolyBase. The load is taking longer than expected, and the team suspects that the data is not being loaded in parallel. They need to improve the load performance. What should the team do?

   • AUse a 'COPY INTO' statement instead of PolyBase, as it is always faster for loading data from ADLS Gen2.
   • BIncrease the DWU of the dedicated SQL pool to provide more compute resources for the load.
   • CEnsure that the source data files are split into multiple files of similar size, and that the external table is created with a reasonable number of partitions.
   • DCreate an external table with a single partition to reduce the overhead of partition management.
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6. 10application · medium

   A financial services company loads large CSV files from Azure Data Lake Storage Gen2 into a dedicated SQL pool in Azure Synapse Analytics every night. The current load takes over two hours, exceeding the batch window. The data engineering team wants to reduce the load time without changing the source data format or the target table schema. What should the team do first?

   • ACreate an external table with a smaller row group size to speed up the PolyBase load.
   • BSplit the CSV files into smaller chunks and load them sequentially using multiple PolyBase statements.
   • CUse a COPY INTO statement instead of PolyBase to load the data, as it is always faster for CSV files.
   • DIncrease the service level of the dedicated SQL pool to a higher DWU setting before the load and scale it back down after the load completes.
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