Free DP-203 Exam Braindumps
Data Engineering on Microsoft Azure (Replaced with DP-700) Questions 94–98 (page: 22)

HOTSPOT (Drag and Drop is not supported)
You have an Azure data factory named adf1 that contains a pipeline named ExecProduct. ExecProduct contains a data flow named Product.

The Product data flow contains the following transformations:

1. WeeklyData: A source that points to a CSV file in an Azure Data Lake Storage Gen2 account with 20 columns
2. ProductColumns: A select transformation that selects from WeeklyData six columns named ProductID, ProductDescr, ProductSubCategory, ProductCategory, ProductStatus, and ProductLastUpdated
3. ProductRows: An aggregate transformation
4. ProductList: A sink that outputs data to an Azure Synapse Analytics dedicated SQL pool

The Aggregate settings for ProductRows are configured as shown in the following exhibit.



For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

You manage an enterprise data warehouse in Azure Synapse Analytics.

Users report slow performance when they run commonly used queries. Users do not report performance changes for infrequently used queries.

You need to monitor resource utilization to determine the source of the performance issues.

Which metric should you monitor?

HOTSPOT (Drag and Drop is not supported)
You have an Azure Synapse Analytics serverless SQL pool.

You have an Apache Parquet file that contains 10 columns.
You need to query data from the file. The solution must return only two columns.

How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

You have an Azure Synapse Analytics workspace that contains an Apache Spark pool named SparkPool1. SparkPool1 contains a Delta Lake table named SparkTable1.

You need to recommend a solution that supports Transact-SQL queries against the data referenced by SparkTable1. The solution must ensure that the queries can use partition elimination.

What should you include in the recommendation?

You are designing a sales transactions table in an Azure Synapse Analytics dedicated SQL pool. The table will contain approximately 60 million rows per month and will be partitioned by month. The table will use a clustered column store index and round-robin distribution.

Approximately how many rows will there be for each combination of distribution and partition?