![]() ![]() Certain parts of your pipeline may be more computationally demanding than others, and Databricks automatically adds additional workers during these phases of your job (and removes them when they’re no longer needed).Īutoscaling makes it easier to achieve high cluster utilization, because you don’t need to provision the cluster to match a workload. With autoscaling, Databricks dynamically reallocates workers to account for the characteristics of your job. ![]() When you provide a range for the number of workers, Databricks chooses the appropriate number of workers required to run your job. When you provide a fixed size cluster, Databricks ensures that your cluster has the specified number of workers. When you create a Databricks cluster, you can either provide a fixed number of workers for the cluster or provide a minimum and maximum number of workers for the cluster. Handling large queries in interactive workflows.Launch a compute resource with the instance profile.Customize containers with Databricks Container Services. ![]()
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