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Answer: Create a Dataproc cluster using preemptible worker instances.
The question explicitly states two key requirements: minimize costs and minimize infrastructure management effort. Option B (Dataproc with preemptible worker instances) best satisfies both requirements. Dataproc is a fully managed service that reduces infrastructure management overhead compared to manual deployment (options C and D). Preemptible instances provide significant cost savings (up to 70-80% discount) compared to standard instances, which aligns with the cost minimization goal. While some community comments argue that preemptible instances require fault tolerance and may not always save costs due to potential job disruptions, the question does not specify critical or time-sensitive workloads. Hadoop jobs for data science teams are typically batch-oriented and can tolerate some interruptions, making preemptible instances suitable. The community discussion shows strong support for B (60% vs 40% for A), with highly upvoted comments emphasizing that 'minimize costs' directly points to preemptible instances. Options C and D are eliminated because manual deployment increases management effort, contradicting the requirement.
Author: LeetQuiz Editorial Team
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You need to migrate Hadoop jobs for your company's Data Science team without changing the existing infrastructure. Your goal is to minimize both costs and infrastructure management overhead. What is the recommended approach?
A
Create a Dataproc cluster using standard worker instances.
B
Create a Dataproc cluster using preemptible worker instances.
C
Manually deploy a Hadoop cluster on Compute Engine using standard instances.
D
Manually deploy a Hadoop cluster on Compute Engine using preemptible instances.