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Download Data Engineering on Microsoft Azure Exam Dumps

NEW QUESTION 33
You use PySpark in Azure Databricks to parse the following JSON input.

You need to output the data in the following tabular format.

How should you complete the PySpark code? To answer, drag the appropriate values to he correct targets. Each value may be used once, more than once or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.Column.alias.html
https://docs.microsoft.com/en-us/azure/databricks/sql/language-manual/functions/explode

 

NEW QUESTION 34
You have an Azure subscription that contains an Azure Databricks workspace named databricks1 and an Azure Synapse Analytics workspace named synapse1. The synapse1 workspace contains an Apache Spark pool named pool1.
You need to share an Apache Hive catalog of pool1 with databricks1.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

 

NEW QUESTION 35
You plan to create an Azure Data Factory pipeline that will include a mapping data flow.
You have JSON data containing objects that have nested arrays.
You need to transform the JSON-formatted data into a tabular dataset. The dataset must have one tow for each item in the arrays.
Which transformation method should you use in the mapping data flow?

A. flattenB. unpivotC. alter rowD. new branch

Answer: A

Explanation:
Explanation
Use the flatten transformation to take array values inside hierarchical structures such as JSON and unroll them into individual rows. This process is known as denormalization.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/data-flow-flatten

 

NEW QUESTION 36
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