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Question 234 - DP-203 discussion

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You need to design a solution that will process streaming data from an Azure Event Hub and output the data to Azure Data Lake Storage. The solution must ensure that analysts can interactively query the streaming data. What should you use?

A.
event triggers in Azure Data Factory
Answers
A.
event triggers in Azure Data Factory
B.
Azure Stream Analytics and Azure Synapse notebooks
Answers
B.
Azure Stream Analytics and Azure Synapse notebooks
C.
Structured Streaming in Azure Databricks
Answers
C.
Structured Streaming in Azure Databricks
D.
Azure Queue storage and read-access geo-redundant storage (RA-GRS)
Answers
D.
Azure Queue storage and read-access geo-redundant storage (RA-GRS)
Suggested answer: C

Explanation:

Apache Spark Structured Streaming is a fast, scalable, and fault-tolerant stream processing API. You can use it to perform analytics on your streaming data in near real-time. With Structured Streaming, you can use SQL queries to process streaming data in the same way that you would process static data.

Azure Event Hubs is a scalable real-time data ingestion service that processes millions of data in a matter of seconds. It can receive large amounts of data from multiple sources and stream the prepared data to Azure Data Lake or Azure Blob storage.

Azure Event Hubs can be integrated with Spark Structured Streaming to perform the processing of messages in near real-time. You can query and analyze the processed data as it comes by using a Structured Streaming query and Spark SQL.

Reference:

https://k21academy.com/microsoft-azure/data-engineer/structured-streaming-with-azure-event-hubs/

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asked 02/10/2024
Anirban Ganguly
48 questions
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