Question: What does Cloud Dataproc do to help organizations avoid expensive underutilized clusters?
- Cloud Dataproc runs clusters ephemerally; in other words, only when needed.
- Cloud Dataproc charges at a per-minute rate for each cluster, reducing costs.
- Cloud Dataproc attaches storage or hard drives to each node of the cluster.
- Cloud Dataproc runs clusters indefinitely, cutting down on wasted time typically spent on spinning up resources.
Explanation
Dataproc helps reduce wasted infrastructure by making Hadoop and Spark clusters fast to create and delete. Clusters can be used only for the duration of a job or workflow instead of remaining idle. This supports cost efficiency because resources are not kept running when processing is complete. The service fits big data processing needs where temporary cluster capacity is more efficient than long-running infrastructure.
Why the other options are incorrect
Per-minute rate describes pricing, but it does not identify the operating model that avoids idle clusters.
Attached storage describes infrastructure configuration, not the way Dataproc reduces underutilization.
Indefinite clusters increases the risk of idle resource waste and conflicts with the intended cost-saving model.
Source for verification
https://cloud.google.com/dataproc/docs/concepts/overview
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