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DP-203 · Question #269

The Complex event processing streaming solution which Jeffrey is working on the IoT platform, is a hybrid cloud platform where few data sources are transformed into on-premises Big Data platform…

The correct answer is A. Spark Structured Streaming / Apache Storm. Option A is correct because Spark Structure Streaming/ Apache Storm can be used for complex event processing for real-time data streams on-premises. Option B is incorrect because Apache ignite can't help with real-time event processing with UDF jobs processing. Option C is…

Submitted by krish.m· Mar 30, 2026Develop data processing

Question

The Complex event processing streaming solution which Jeffrey is working on the IoT platform, is a hybrid cloud platform where few data sources are transformed into on-premises Big Data platform. The on-premises data center and Azure services are connected via a virtual network gateway. What kind of resources can he choose for this on-premises Big data platform connected to Azure via virtual network gateway, complex data processing and execution UDF jobs on java?

Options

  • ASpark Structured Streaming / Apache Storm
  • BApache Ignite
  • CApache Airflow
  • DApache Kafka
  • ENone of the above

How the community answered

(32 responses)
  • A
    72% (23)
  • B
    3% (1)
  • C
    3% (1)
  • D
    16% (5)
  • E
    6% (2)

Explanation

Option A is correct because Spark Structure Streaming/ Apache Storm can be used for complex event processing for real-time data streams on-premises. Option B is incorrect because Apache ignite can't help with real-time event processing with UDF jobs processing. Option C is incorrect because Apache Airflow is a platform for programmatically authoring, monitoring workflows. Option D is incorrect because Apache Kafka is used for publishing and consuming event streams in pub-sub scenarios. https://docs.microsoft.com/en-us/azure/stream-analytics/streaming-technologies

Topics

#complex event processing#Spark Structured Streaming#IoT hybrid cloud#UDF jobs

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