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Question 276 - Professional Machine Learning Engineer discussion

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You are the lead ML engineer on a mission-critical project that involves analyzing massive datasets using Apache Spark. You need to establish a robust environment that allows your team to rapidly prototype Spark models using Jupyter notebooks. What is the fastest way to achieve this?

A.

Configure a Compute Engine instance with Spark and use Jupyter notebooks.

Answers
A.

Configure a Compute Engine instance with Spark and use Jupyter notebooks.

B.

Set up a Dataproc cluster with Spark and use Jupyter notebooks.

Answers
B.

Set up a Dataproc cluster with Spark and use Jupyter notebooks.

C.

Set up a Vertex AI Workbench instance with a Spark kernel.

Answers
C.

Set up a Vertex AI Workbench instance with a Spark kernel.

D.

Use Colab Enterprise with a Spark kernel.

Answers
D.

Use Colab Enterprise with a Spark kernel.

Suggested answer: B

Explanation:

Dataproc provides a managed Spark environment and integrates with Jupyter notebooks, ideal for large datasets and rapid prototyping. It reduces setup time compared to manual Spark configurations on Compute Engine or Vertex AI. Colab Enterprise is more suitable for small-scale prototyping rather than extensive Spark-based analysis.

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asked 07/11/2024
Jay Barre
37 questions
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