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Databricks Tools

Databricks Edit Cluster

Tool to edit an existing Databricks cluster configuration. Use when you need to modify cluster settings such as size, Spark version, node types, or cloud-specific attributes. The cluster must be in RUNNING or TERMINATED state. If updated while RUNNING, it will restart to apply c…

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Use Databricks Edit Cluster

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Inputs

  • autoscaleobject
    Autoscaling configuration for cluster workers.
  • policy_idstring
    Cluster policy ID to validate configuration and preset defaults
  • cluster_idstring
    Required
    Unique identifier of the cluster to edit. The cluster must be in RUNNING or TERMINATED state
  • spark_confobject
    Custom Spark configuration key-value pairs
  • custom_tagsobject
    User-defined resource tags (max 45 tags). Serverless clusters should have ResourceClass=Serverless tag
  • num_workersinteger
    Number of worker nodes. Total Spark nodes = num_workers + 1 (driver). Use 0 for single-node clusters. Required unless using autoscale
  • cluster_namestring
    User-defined name for the cluster; does not need to be unique
  • docker_imageobject
    Docker container configuration.
  • init_scriptsarray
    Initialization scripts executed sequentially at cluster startup
  • node_type_idstring
    Node type for worker nodes (e.g., 'i3.xlarge' for AWS, 'Standard_DS3_v2' for Azure, 'n2-highmem-4' for GCP). Not needed if instance_pool_id is specified
  • spark_versionstring
    Required
    Runtime version of the cluster (e.g., '11.3.x-scala2.12', '12.2.x-scala2.12', '13.x-scala2.12')
  • workload_typeobject
    Workload type restrictions for cluster usage.

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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