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Answer: Google Cloud Dataproc
The question requires scaling Apache Spark and Hadoop jobs with minimal operations work and code changes. Google Cloud Dataproc (B) is specifically designed as a managed service for Apache Spark and Hadoop, offering automated cluster management, easy scaling, and compatibility with existing code. The community discussion shows 100% consensus on B, with high upvotes for comments explaining Dataproc's suitability. Other options are less suitable: Dataflow (A) is for data stream/batch processing but not optimized for Spark/Hadoop; Compute Engine (C) requires manual cluster management; Kubernetes Engine (D) involves container orchestration complexity, not direct Spark/Hadoop support.
Author: LeetQuiz Editorial Team
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Your company anticipates a significant rise in the volume and scale of Apache Spark and Hadoop jobs in your on-premises data center. You need to leverage the cloud to scale for this upcoming demand while minimizing operational overhead and code modifications. Which product should you use?
A
Google Cloud Dataflow
B
Google Cloud Dataproc
C
Google Compute Engine
D
Google Kubernetes Engine
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