Using cluster pools reduces the cluster startup time. So in this case, the reports can be refreshed quickly and not having to wait long for the cluster to start
In Databricks, cluster pools are used to manage and optimize the allocation of cluster resources. They help ensure that clusters are efficiently provisioned and reused, which can reduce startup times and improve cost management.
Given the options:
A. An automated report needs to be refreshed as quickly as possible. B. An automated report needs to be made reproducible. C. An automated report needs to be tested to identify errors. D. An automated report needs to be version-controlled across multiple collaborators. E. An automated report needs to be runnable by all stakeholders.
The most appropriate answer is:
A. An automated report needs to be refreshed as quickly as possible.
Cluster pools are designed to minimize the time it takes to start up clusters by keeping a pool of pre-warmed instances available. This is particularly useful for scenarios where quick access to computing resources is crucial, such as in the case of refreshing automated reports quickly.
Considering the recommendation to create pools based on workloads and to pre-populate pools to ensure instances are available when clusters need them, the most suitable option would be:
E. An automated report needs to be runnable by all stakeholders.
This aligns with the concept of pre-populating pools to ensure that instances are readily available when needed, enabling the automated report to be executed promptly whenever stakeholders require it without waiting for instance acquisition.
E is correct for sure. For data team , their tasks is not just to refresh a report. They equally want to share the cluster for running their queries. Please read at below:
https://docs.databricks.com/en/compute/pool-best-practices.html#create-pools-based-on-workloads
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