Multiple Choice Flashcards on 02 Databricks Certified Machine Learning Profes...

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Flashcard Practice Databricks Certified Machine Learning Professional Multiple Choice

A company reports that exploratory notebooks become unresponsive whenever nightly model training starts. Training, feature engineering, and ad hoc analysis all share the same all-purpose cluster. Which architecture change best addresses the performance bottleneck?

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Disable MLflow tracking during training so the shared cluster has fewer writes. Store model artifacts in a different schema while leaving compute unchanged. Run notebooks and training on the same cluster but ask users to avoid heavy commands at night. Move scheduled ML pipelines to autoscaling job clusters and keep notebook compute separate.

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