Clusters
The Clusters API allows you to create, start, edit, list, terminate, and delete clusters.
Azure Databricks maps cluster node instance types to compute units known as DBUs. See the instance
type pricing page for a list of the supported instance types and their corresponding DBUs.
A Azure Databricks cluster is a set of computation resources and configurations on which you run
data engineering, data science, and data analytics workloads, such as production
ETL pipelines, streaming analytics, ad-hoc analytics, and machine learning.
You run these workloads as a set of commands in a notebook or as an automated job.
Azure Databricks makes a distinction between all-purpose clusters and job clusters. You use
all-purpose clusters to analyze data collaboratively using interactive notebooks. You use
job clusters to run fast and robust automated jobs.
You can create an all-purpose cluster using the UI, CLI, or REST API. You can manually
terminate and restart an all-purpose cluster. Multiple users can share such clusters to do
collaborative interactive analysis.
IMPORTANT: Azure Databricks retains cluster configuration information for terminated clusters for 30 days. To keep an all-purpose cluster configuration even after it has been
terminated for more than 30 days, an administrator can pin a cluster to the cluster list.