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Answer: An automated workflow needs to be run every 1 hour
Databricks distinguishes between all-purpose clusters and job clusters. All-purpose clusters are ideal for interactive analysis and collaboration among multiple users, as they can be manually terminated and restarted. Job clusters, on the other hand, are created by the Databricks job scheduler for running automated jobs. These clusters terminate once the job is complete and cannot be restarted, making them suitable for fast and robust automated workflows. Learn More: [Databricks Clusters](https://docs.databricks.com/clusters/index.html)
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When is it preferable to use a job cluster over an all-purpose cluster in Databricks?
A
A data analyst needs to schedule a Databricks SQL query for upward reporting
B
A team of data scientists need to collaborate on testing of a machine learning model
C
An ad-hoc analytics report needs to be developed using some data visualizations
D
A data engineer needs to manually debug and fix a production error
E
An automated workflow needs to be run every 1 hour
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