Databricks Certified Data Engineer - Associate
A data engineer is tasked with optimizing compute resources in a Databricks workspace to enhance cost efficiency while ensuring compliance with organizational data access policies. The engineer needs to filter clusters based on their access permissions to identify and terminate idle clusters. Considering the need to preserve all data, notebooks, and resources for future use, which of the following statements accurately describes the filtering capability in the Databricks workspace and the consequence of terminating a cluster? (Choose one correct answer)
Simulated
A
Clusters can be filtered by the user's access level, and terminating a cluster will permanently delete all data, notebooks, and resources associated with it, impacting future access.
B
Clusters can be filtered by the user's access level, and terminating a cluster will only stop the cluster from running; all data, notebooks, and resources remain available for future use, ensuring no loss of work.
C
Clusters can only be filtered by cluster name or ID, and terminating a cluster will permanently delete all data, notebooks, and resources associated with it, leading to potential data loss.
D
Clusters can only be filtered by cluster name or ID, and terminating a cluster will only stop the cluster from running; all data, notebooks, and resources remain available for future use, with no impact on stored work.
Explanation:
In the Databricks workspace, users can filter clusters based on their access level, allowing them to view only the clusters they have permission to access. Terminating a cluster stops the compute resources but does not delete any data, notebooks, or resources stored in the workspace or external storage. This ensures that all work remains available for future use, aligning with best practices for cost efficiency and data preservation.