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Answer: Create isolated environments for each project within the cluster, each with its own set of libraries.
Option B provides a structured approach to managing library conflicts by isolating dependencies to specific projects or teams. This method allows for the use of different library versions without conflict, ensuring that each project can run with the libraries it requires without affecting others.
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In a scenario where you are tasked with optimizing a Databricks cluster running the Databricks Runtime for Machine Learning, which is experiencing performance issues during model training due to library conflicts, describe the steps you would take to resolve these issues. Consider the need to maintain access to necessary libraries while preventing conflicts.
A
Remove all libraries from the cluster and reinstall them one by one, testing for conflicts.
B
Create isolated environments for each project within the cluster, each with its own set of libraries.
C
Upgrade the Databricks Runtime for Machine Learning to the latest version, which may have resolved library conflicts.
D
Instruct data scientists to install only the libraries they need in their individual notebook sessions.
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