Answer-first summary for fast verification
Answer: Cluster size cannot go below the minimum number of workers selected while enabling autoscaling
Autoscaling in Databricks dynamically adjusts the number of workers to match the job's requirements, offering benefits like faster workload execution and cost reduction. However, the cluster size can temporarily go below the minimum number of workers if instances are terminated by the cloud provider, contrary to the incorrect statement. Databricks will attempt to re-provision instances to maintain the minimum worker count. Learn more about [Cluster Size and Autoscaling](https://docs.databricks.com/clusters/configure.html#autoscaling).
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
Which statement about autoscaling a cluster in Databricks is incorrect?
A
Autoscaling clusters can reduce overall costs compared to a statically-sized cluster
B
Cluster size cannot go below the minimum number of workers selected while enabling autoscaling
C
Workloads can run faster compared to a constant-sized under-provisioned cluster
D
You need to configure the Min Workers and Max Workers to enable autoscaling for a cluster
E
Autoscaling makes it easier to achieve high cluster utilization, because you don't need to provision the cluster to match a workload
No comments yet.