Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
Databricks Certified Machine Learning Professional · Databricks
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
- Correct answer : A — Because the inference job resolves the alias to a model version at run time, picking up a new assignment on its next run. A . The alias is resolved to whichever version currently holds it each time the inference job runs, so reassigning the Champion alias is enough for the next scheduled run to load the new version with no code or config edits. B . Unity Catalog does not automatically restart or re-trigger jobs when an alias changes; the inference job simply resolves the alias the next time it happens to run on its own schedule or trigger. C . There is no permanent caching of a specific model version tied to the alias that requires a manual clear; each run resolves the alias fresh, which is exactly what lets the new version take effect automatically. D . Aliases are a property of the registered model and its versions in Unity Catalog, not of the job's cluster configuration, so cluster settings have nothing to do with how the alias is resolved.