Your company is planning to migrate their on-premises Hadoop environment to the cloud. Increasing storage cost and maintenance of data stored in HDFS is a major concern for your company. You also want

Question

Options

• AMigrate your data stored in Hadoop to BigQuery.
• BCreate Compute Engine instances with HDD instead of SSD to save costs.
• CCreate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop
• DCreate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop code

• A
  5% (2)
• B
  3% (1)
• C
  11% (4)
• D
  81% (30)

Explanation

Cloud Dataproc is GCP's managed Hadoop and Spark service, so existing Hadoop jobs can run with minimal code changes. The key distinction from option C is that option D involves migrating the data from HDFS to Cloud Storage (GCS), which eliminates the HDFS storage cost and maintenance burden while preserving the Hadoop processing layer. GCS replaces HDFS as the persistent storage layer (using the gs:// path prefix), which is a well-supported pattern. Option A (BigQuery) would require rewriting analytics jobs. Option B (Compute Engine with HDD) does not address the Hadoop ecosystem management complexity. Option C may retain HDFS on Dataproc, which doesn't fully solve the storage cost concern.

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