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Answer: Leverage the Databricks cluster pools feature to minimize startup time
The correct answer leverages the Databricks pools feature, which significantly reduces cluster start and auto-scaling times by maintaining a set of idle, ready-to-use instances. When a cluster is linked to a pool, its nodes are created from the pool's idle instances. If no idle instances are available, the pool expands by allocating a new instance to meet the cluster's needs. Instances released by a cluster return to the pool, becoming available for other clusters. This efficient reuse of instances ensures quicker startup times. For more details, refer to the documentation on Cluster Pools in Databricks.
Author: LeetQuiz Editorial Team
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As a data engineer tasked with creating a summary of a dataset for reporting, you've scheduled a Databricks notebook as a job. However, you've observed that it takes approximately 10 minutes for the cluster to start. Which of the following solutions can effectively address this delay?
A
Disable the auto-terminate option of the cluster to ensure it's always operational
B
Configure an additional job to initiate before the main job, ensuring the cluster is active beforehand
C
Opt for a High Concurrent cluster over a Standard cluster to mitigate the issue
D
Leverage the Databricks cluster pools feature to minimize startup time
E
Utilize a Job Cluster for creating a new cluster to decrease the startup duration
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