Class ClustersClient

Change the owner of the cluster. You must be an admin and the cluster must be terminated to perform this operation. The service principal application ID can be supplied as an argument to owner_username.

Creates a new Spark cluster. This method will acquire new instances from the cloud provider if necessary. This method is asynchronous; the returned cluster_id can be used to poll the cluster status. When this method returns, the cluster will be in a PENDING state. The cluster will be usable once it enters a RUNNING state. Note: may not be able to acquire some of the requested nodes, due to cloud provider limitations (account limits, spot price, etc.) or transient network issues.

If acquires at least 85% of the requested on-demand nodes, cluster creation will succeed. Otherwise the cluster will terminate with an informative error message.

Rather than authoring the cluster's JSON definition from scratch, Databricks recommends filling out the create compute UI and then copying the generated JSON definition from the UI.

Terminates the Spark cluster with the specified ID. The cluster is removed asynchronously. Once the termination has completed, the cluster will be in a TERMINATED state. If the cluster is already in a TERMINATING or TERMINATED state, nothing will happen.

Updates the configuration of a cluster to match the provided attributes and size. A cluster can be updated if it is in a RUNNING or TERMINATED state.

If a cluster is updated while in a RUNNING state, it will be restarted so that the new attributes can take effect.

If a cluster is updated while in a TERMINATED state, it will remain TERMINATED. The next time it is started using the clusters/start API, the new attributes will take effect. Any attempt to update a cluster in any other state will be rejected with an INVALID_STATE error code.

Clusters created by the Databricks Jobs service cannot be edited.

Updates a cluster to be compliant with the current version of its policy. A cluster can be updated if it is in a RUNNING or TERMINATED state.

If a cluster is updated while in a RUNNING state, it will be restarted so that the new attributes can take effect.

If a cluster is updated while in a TERMINATED state, it will remain TERMINATED. The next time the cluster is started, the new attributes will take effect.

Clusters created by the Databricks Jobs, SDP, or Models services cannot be enforced by this API. Instead, use the "Enforce job policy compliance" API to enforce policy compliance on jobs.

Retrieves the information for a cluster given its identifier. Clusters can be described while they are running, or up to 60 days after they are terminated.

Returns the policy compliance status of a cluster. Clusters could be out of compliance if their policy was updated after the cluster was last edited.

Returns a list of availability zones where clusters can be created in (For example, us-west-2a). These zones can be used to launch a cluster.

Returns the policy compliance status of all clusters that use a given policy. Clusters could be out of compliance if their policy was updated after the cluster was last edited.

Return information about all pinned and active clusters, and all clusters terminated within the last 30 days. Clusters terminated prior to this period are not included.

Retrieves a list of events about the activity of a cluster. This API is paginated. If there are more events to read, the response includes all the parameters necessary to request the next page of events.

Returns a list of supported Spark node types. These node types can be used to launch a cluster.

Returns the list of available Spark versions. These versions can be used to launch a cluster.

Permanently deletes a Spark cluster. This cluster is terminated and resources are asynchronously removed.

In addition, users will no longer see permanently deleted clusters in the cluster list, and API users can no longer perform any action on permanently deleted clusters.

Pinning a cluster ensures that the cluster will always be returned by the ListClusters API. Pinning a cluster that is already pinned will have no effect. This API can only be called by workspace admins.

Resizes a cluster to have a desired number of workers. This will fail unless the cluster is in a RUNNING state.

Restarts a Spark cluster with the supplied ID. If the cluster is not currently in a RUNNING state, nothing will happen.

Starts a terminated Spark cluster with the supplied ID. This works similar to createCluster except:

• The previous cluster id and attributes are preserved.
• The cluster starts with the last specified cluster size.
• If the previous cluster was an autoscaling cluster, the current cluster starts with the minimum number of nodes.
• If the cluster is not currently in a TERMINATED state, nothing will happen.
• Clusters launched to run a job cannot be started.

Unpinning a cluster will allow the cluster to eventually be removed from the ListClusters API. Unpinning a cluster that is not pinned will have no effect. This API can only be called by workspace admins.

Updates the configuration of a cluster to match the partial set of attributes and size. Denote which fields to update using the update_mask field in the request body. A cluster can be updated if it is in a RUNNING or TERMINATED state. If a cluster is updated while in a RUNNING state, it will be restarted so that the new attributes can take effect. If a cluster is updated while in a TERMINATED state, it will remain TERMINATED. The updated attributes will take effect the next time the cluster is started using the clusters/start API. Attempts to update a cluster in any other state will be rejected with an INVALID_STATE error code. Clusters created by the Databricks Jobs service cannot be updated.