Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Google Exam Professional Data Engineer Topic 3 Question 83 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 83
Topic #: 3
[All Professional Data Engineer Questions]

You need to modernize your existing on-premises data strategy. Your organization currently uses.

* Apache Hadoop clusters for processing multiple large data sets, including on-premises Hadoop Distributed File System (HDFS) for data replication.

* Apache Airflow to orchestrate hundreds of ETL pipelines with thousands of job steps.

You need to set up a new architecture in Google Cloud that can handle your Hadoop workloads and requires minimal changes to your existing orchestration processes. What should you do?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Benton at May 12, 2024, 01:23 PM

Limited Time Offer

25%

Off

Get Premium Professional Data Engineer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel
Chantell
2 days ago
Option B is an interesting approach, but I'm not sure Bigtable is the best fit for the large workloads mentioned in the question. I'd probably go with Option C for its more holistic solution.
upvoted 0 times
...
Anisha
18 days ago
I'm leaning towards Option D. Using Dataproc and Cloud Composer seems like a straightforward approach that aligns well with the existing orchestration processes.
upvoted 0 times
Evangelina
4 days ago
I agree, sticking with what you know can make the transition smoother.
upvoted 0 times
...
Amber
9 days ago
Option D sounds like a good choice. It keeps things simple and aligned with what you already have in place.
upvoted 0 times
...
...
Edward
23 days ago
Option C looks like the most comprehensive solution. Migrating Hadoop to Dataproc and using Cloud Storage for HDFS, while leveraging Cloud Data Fusion for visual ETL design, seems like a great way to modernize the architecture with minimal changes.
upvoted 0 times
Lenna
6 days ago
I agree, using Dataproc for migration, Cloud Storage for HDFS, and Cloud Data Fusion for ETL pipelines sounds like a solid plan.
upvoted 0 times
...
Leanora
8 days ago
Option C looks like the most comprehensive solution. Migrating Hadoop to Dataproc and using Cloud Storage for HDFS, while leveraging Cloud Data Fusion for visual ETL design, seems like a great way to modernize the architecture with minimal changes.
upvoted 0 times
...
...
Cordelia
1 months ago
We should also consider converting our ETL pipelines to Dataflow for better efficiency.
upvoted 0 times
...
Cory
1 months ago
I agree, and we can use Cloud Storage to handle any HDFS use cases.
upvoted 0 times
...
Cordelia
1 months ago
I think we should use Dataproc to migrate our Hadoop clusters to Google Cloud.
upvoted 0 times
...

Save Cancel