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Exam Professional Cloud Developer topic 1 question 71 discussion

Actual exam question from Google's Professional Cloud Developer
Question #: 71
Topic #: 1
[All Professional Cloud Developer Questions]

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 to make minimal changes to existing data analytics jobs and existing architecture.
How should you proceed with the migration?

  • A. Migrate your data stored in Hadoop to BigQuery. Change your jobs to source their information from BigQuery instead of the on-premises Hadoop environment.
  • B. Create Compute Engine instances with HDD instead of SSD to save costs. Then perform a full migration of your existing environment into the new one in Compute Engine instances.
  • C. Create a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop environment to the new Cloud Dataproc cluster. Move your HDFS data into larger HDD disks to save on storage costs.
  • D. Create a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop code objects to the new cluster. Move your data to Cloud Storage and leverage the Cloud Dataproc connector to run jobs on that data.
Show Suggested Answer Hide Answer
Suggested Answer: D 🗳️
by donchick at Dec. 21, 2020, 10:07 p.m.

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donchick
Highly Voted 3 years, 7 months ago
I'd choose D.
upvoted 7 times
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syu31svc
Highly Voted 3 years ago
https://cloud.google.com/architecture/hadoop/hadoop-gcp-migration-overview: "Keeping your data in a persistent HDFS cluster using Dataproc is more expensive than storing your data in Cloud Storage, which is what we recommend, as explained later. Keeping data in an HDFS cluster also limits your ability to use your data with other Google Cloud products." "Google Cloud includes Dataproc, which is a managed Hadoop and Spark environment. You can use Dataproc to run most of your existing jobs with minimal alteration, so you don't need to move away from all of the Hadoop tools you already know" D is the answer
upvoted 6 times
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__rajan__
Most Recent 10 months, 2 weeks ago
Selected Answer: D
Option D is correct.
upvoted 1 times
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tranvanchau9494
11 months, 1 week ago
D is correct
upvoted 1 times
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omermahgoub
1 year, 6 months ago
Option D is the most appropriate choice because it allows you to migrate your Hadoop code objects to a Cloud Dataproc cluster, which is a fully-managed Apache Hadoop and Apache Spark service on Google Cloud. This will allow you to make minimal changes to your existing data analytics jobs and existing architecture. Additionally, moving your data to Cloud Storage and using the Cloud Dataproc connector to run jobs on that data will allow you to take advantage of the scalability, durability, and security of Cloud Storage while also minimizing storage costs.
upvoted 1 times
omermahgoub
1 year, 6 months ago
A would involve a significant change to your existing data analytics jobs and architecture, as it would involve migrating your data to BigQuery and changing your jobs to source their information from BigQuery instead of Hadoop. B is not a feasible option because Compute Engine instances do not have the capability to run HDFS. C would not allow you to save on storage costs as it involves moving your data to larger HDD disks rather than a more cost-effective storage solution like Cloud Storage.
upvoted 1 times
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tomato123
1 year, 11 months ago
Selected Answer: D
D is correct
upvoted 2 times
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tomato123
1 year, 11 months ago
D is correct
upvoted 1 times
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szl0144
2 years, 2 months ago
D is correct
upvoted 1 times
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C (25%)
B (20%)
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