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?

AUse Dataproc to migrate Hadoop clusters to Google Cloud, and Cloud Storage to handle any HDFS use cases Convert your ETL pipelines to Dataflow.

BUse Bigtable for your large workloads, with connections to Cloud Storage to handle any HDFS use cases Orchestrate your pipelines with Cloud Composer.

CUse Dataproc to migrate your Hadoop clusters to Google Cloud, and Cloud Storage to handle any HDFS use cases. Use Cloud Data Fusion to visually design and deploy your ETL pipelines.

DUse Dataproc to migrate Hadoop clusters to Google Cloud, and Cloud Storage to handle any HDFS use cases. Orchestrate your pipelines with Cloud Composer..

Show Suggested Answer

Suggested Answer: C

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

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Edward

9 hours 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.

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