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Microsoft Exam DP-203 Topic 10 Question 81 Discussion

Actual exam question for Microsoft's DP-203 exam
Question #: 81
Topic #: 10
[All DP-203 Questions]

You are creating an Apache Spark job in Azure Databricks that will ingest JSON-formatted data.

You need to convert a nested JSON string into a DataFrame that will contain multiple rows.

Which Spark SQL function should you use?

Show Suggested Answer Hide Answer
Suggested Answer: A, B

the two types of activities that you can use to execute SP1 areStored ProcedureandLookup.

A Stored Procedure activity executes a stored procedure on an Azure SQL Database or Azure Synapse Analytics or SQL Server1.You can specify the stored procedure name and parameters in the activity settings1.

A Lookup activity retrieves a dataset from any data source that returns a single row of data with four columns2.You can use a query to execute a stored procedure as the source of the Lookup activity2.You can then store the values in the columns as pipeline variables by using expressions2.

https://learn.microsoft.com/en-us/azure/data-factory/transform-data-using-stored-procedure


by Annabelle at Dec 25, 2023, 07:35 PM

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Rebecka
17 days ago
I'm not sure about explode. Maybe we should consider using extract instead.
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Elli
18 days ago
I agree with Ozell. Explode is the right Spark SQL function for this task.
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Ressie
18 days ago
I'm going to go with C) coalesce, because that's what I do with my socks when they go missing. Wait, what was the question again?
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Ozell
19 days ago
I think we should use explode to convert the nested JSON string into multiple rows.
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Simona
19 days ago
Jokester
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Vincent
23 days ago
I'm not sure, but I think A) explode makes sense for this scenario.
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Elouise
1 months ago
I agree with Jade, because explode is used to create multiple rows from nested data.
upvoted 0 times
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Jade
1 months ago
I think the answer is A) explode.
upvoted 0 times
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