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Google Professional Cloud Developer Exam - Topic 16 Question 101 Discussion

Actual exam question for Google's Professional Cloud Developer exam
Question #: 101
Topic #: 16
[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?

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Suggested Answer: D

by Jaime at Jan 26, 2025, 04:24 PM

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Lera
6 months ago
Surprised to see so many options, thought it’d be simpler!
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Tammara
6 months ago
Moving to HDD? That sounds risky for performance.
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Marjory
6 months ago
Isn't BigQuery better for analytics though?
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Veda
7 months ago
Totally agree, option D seems the best for minimal changes!
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Dana
7 months ago
I heard Cloud Dataproc is great for Hadoop migrations.
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Elly
7 months ago
I'm a bit confused about the cost implications of using HDD versus SSD in Compute Engine. I thought SSDs were generally better for performance, but maybe HDDs are cheaper?
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Frederic
7 months ago
I practiced a similar question about migrating Hadoop, and I feel like using Cloud Dataproc makes sense since it supports Hadoop jobs directly.
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Ezekiel
7 months ago
I think migrating to BigQuery could be a good choice, but it might require more changes to the analytics jobs than we want.
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Leontine
8 months ago
I remember we discussed how Cloud Dataproc can help with minimal changes to existing jobs, but I'm not sure if moving data to Cloud Storage is the best option.
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Moon
8 months ago
I feel pretty confident about this one. The key is to leverage a managed service like Cloud Dataproc to handle the migration, and then use Cloud Storage for the data to reduce costs. Option D seems like the best approach to me.
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Lai
8 months ago
Option C looks promising - using Cloud Dataproc to migrate the Hadoop environment while moving the data to larger, cheaper storage. That could be a good balance of cost savings and minimal changes.
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Malcom
8 months ago
Hmm, I'm a bit confused by the options. Migrating to BigQuery seems like a big change, and I'm not sure if that would really meet the requirement of minimal changes. I'll have to think this through carefully.
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Thora
8 months ago
This seems like a straightforward migration question. I'd focus on minimizing changes to the existing architecture and jobs, so I'm leaning towards option D.
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Louvenia
8 months ago
I think I'm leaning towards Option C. Migrating to a Dataproc cluster and using larger HDD disks seems like a good balance of cost savings and minimal changes.
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Juan
8 months ago
I'm a bit confused by the differences between the Dataproc and BigQuery options. I'll need to research those more to decide.
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Leonida
8 months ago
Option D sounds promising - migrating the code and using Cloud Storage could help minimize changes while saving on storage costs.
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Audria
8 months ago
Hmm, the options seem to cover a range of approaches. I'll need to think through the pros and cons of each one.
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Thurman
8 months ago
This looks like a tricky question. I'll need to carefully consider the requirements around minimal changes and cost savings.
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Kristofer
1 year ago
Option A looks tempting, but I'm not sure BigQuery is the best fit for our existing Hadoop-based analytics jobs. Rewriting all those jobs seems like a lot of unnecessary work. Option D seems like the perfect balance of cost savings and minimal changes to our architecture.
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Rodolfo
11 months ago
Let's proceed with creating a Cloud Dataproc cluster and migrating our Hadoop code objects to the new cluster.
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Amie
11 months ago
We should definitely consider moving our data to Cloud Storage and leveraging the Cloud Dataproc connector.
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Rima
12 months ago
Option D does seem like a good balance of cost savings and minimal changes to our architecture.
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Jacob
12 months ago
I agree, rewriting all those jobs for BigQuery does seem like a lot of unnecessary work.
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Selene
1 year ago
Haha, Option B is a classic 'let's just throw more hardware at the problem' approach. I doubt our management would be too impressed with that strategy. We need a more strategic, cloud-focused solution like what's described in Option D.
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Vonda
1 year ago
I'm a bit skeptical about Option C. Migrating HDFS data to larger HDD disks doesn't seem like it will address the core issue of high storage costs. We should look for a solution that truly optimizes our storage costs, like Option D.
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Mitzie
1 year ago
Yeah, moving our data to Cloud Storage and using the Cloud Dataproc connector sounds like a more efficient solution.
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Daryl
1 year ago
I agree, Option D seems like a better choice for optimizing storage costs.
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Corinne
1 year ago
I prefer option D. Moving our data to Cloud Storage and using the Cloud Dataproc connector for running jobs seems like a more scalable solution for our company's needs.
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Cassie
1 year ago
Option D seems like the most straightforward approach. It allows us to keep our existing Hadoop code while migrating the data to the more cost-effective Cloud Storage. The Cloud Dataproc connector will make it easy to run our jobs on the new data location.
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Tyisha
1 year ago
Yes, it's important to find a solution that minimizes changes to our existing data analytics jobs and architecture.
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Kaycee
1 year ago
We should definitely consider moving our data to Cloud Storage to save on storage costs.
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Darrel
1 year ago
I agree, leveraging the Cloud Dataproc connector will definitely make it easier to run our jobs on the new data location.
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Dallas
1 year ago
Option D seems like the most straightforward approach. It allows us to keep our existing Hadoop code while migrating the data to the more cost-effective Cloud Storage.
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Solange
1 year ago
I agree with Nathalie. Option C seems like the most efficient way to proceed with the migration while minimizing changes to our existing architecture.
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Nathalie
1 year ago
I think option C sounds like a good plan. It allows us to migrate our Hadoop environment to Cloud Dataproc and save on storage costs by moving data to larger HDD disks.
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