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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
A. An automated report needs to be refreshed as quickly as possible.
Cluster pools are typically used in distributed computing environments, such as cloud-based data platforms like Databricks. They allow you to pre-allocate a set of compute resources (a cluster) for specific tasks or workloads. In this case, if an automated report needs to be refreshed as quickly as possible, you can allocate a cluster pool with sufficient resources to ensure fast data processing and report generation. This helps ensure that the report is generated with minimal latency and can be delivered to stakeholders in a timely manner. Cluster pools allow you to optimize resource allocation for high-demand, time-sensitive tasks like real-time report generation.
Cluster pools in Databricks are used to ensure that a set of pre-warmed clusters is readily available to run workloads. This means that when a job is submitted, it can be executed more quickly because there is no need to wait for a cluster to spin up. Therefore, if a data team needs to refresh an automated report as quickly as possible, they will want to utilize cluster pools to ensure that the job can be executed as quickly as possible.
You can attach a cluster to a pool of idle instances for the driver and worker nodes to speed up cluster startup time. Instances from the pools are used to form the cluster.
Even according to this article, the right option is 'A'. Quote: 'You can attach a cluster to a pool of idle instances for the driver and worker nodes to speed up cluster startup time'
Yes I admit I was mistaken. The right option is A. Thanks for pointing it out.
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