Databricks Certified Data Engineer - Associate
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Which of the following describes a scenario in which a data engineer will want to use a Job cluster instead of an all-purpose cluster?
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UAnonymous
A
An ad-hoc analytics report needs to be developed while minimizing compute costs.
B
A data team needs to collaborate on the development of a machine learning model.
C
An automated workflow needs to be run every 30 minutes.
D
A Databricks SQL query needs to be scheduled for upward reporting.
E
A data engineer needs to manually investigate a production error.
Explanation:
Job clusters are ephemeral clusters that are created and terminated for individual jobs or scheduled workflows. They are ideal for automated, recurring, production tasks because they provide isolation, reproducibility, and cost control (clusters run only for the duration of the job). An automated workflow that runs every 30 minutes is a classic use case for job clusters. In contrast, all-purpose clusters are intended for interactive, collaborative development and ad-hoc investigation (options A, B, and E). Databricks SQL scheduled queries typically use SQL warehouses/SQL endpoints rather than job clusters (option D). Therefore option C is the correct choice.
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