Databricks SDK for JavaScript
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    Type Alias TerminationCode_Code

    TerminationCode_Code:
        | typeof TerminationCode_Code[keyof typeof TerminationCode_Code]
        | string & {}

    The code indicates why the run was terminated. Additional codes might be introduced in future releases.

    • SUCCESS: The run was completed successfully.
    • SUCCESS_WITH_FAILURES: The run was completed successfully but some child runs failed.
    • USER_CANCELED: The run was successfully canceled during execution by a user.
    • CANCELED: The run was canceled during execution by the platform; for example, if the maximum run duration was exceeded.
    • SKIPPED: Run was never executed, for example, if the upstream task run failed, the dependency type condition was not met, or there were no material tasks to execute.
    • INTERNAL_ERROR: The run encountered an unexpected error. Refer to the state message for further details.
    • DRIVER_ERROR: The run encountered an error while communicating with the Spark Driver.
    • CLUSTER_ERROR: The run failed due to a cluster error. Refer to the state message for further details.
    • REPOSITORY_CHECKOUT_FAILED: Failed to complete the checkout due to an error when communicating with the third party service.
    • INVALID_CLUSTER_REQUEST: The run failed because it issued an invalid request to start the cluster.
    • WORKSPACE_RUN_LIMIT_EXCEEDED: The workspace has reached the quota for the maximum number of concurrent active runs. Consider scheduling the runs over a larger time frame.
    • FEATURE_DISABLED: The run failed because it tried to access a feature unavailable for the workspace.
    • CLUSTER_REQUEST_LIMIT_EXCEEDED: The number of cluster creation, start, and upsize requests have exceeded the allotted rate limit. Consider spreading the run execution over a larger time frame.
    • STORAGE_ACCESS_ERROR: The run failed due to an error when accessing the customer blob storage. Refer to the state message for further details.
    • RUN_EXECUTION_ERROR: The run was completed with task failures. For more details, refer to the state message or run output.
    • UNAUTHORIZED_ERROR: The run failed due to a permission issue while accessing a resource. Refer to the state message for further details.
    • LIBRARY_INSTALLATION_ERROR: The run failed while installing the user-requested library. Refer to the state message for further details. The causes might include, but are not limited to: The provided library is invalid, there are insufficient permissions to install the library, and so forth.
    • MAX_CONCURRENT_RUNS_EXCEEDED: The scheduled run exceeds the limit of maximum concurrent runs set for the job.
    • MAX_SPARK_CONTEXTS_EXCEEDED: The run is scheduled on a cluster that has already reached the maximum number of contexts it is configured to create. See: Link.
    • RESOURCE_NOT_FOUND: A resource necessary for run execution does not exist. Refer to the state message for further details.
    • INVALID_RUN_CONFIGURATION: The run failed due to an invalid configuration. Refer to the state message for further details.
    • CLOUD_FAILURE: The run failed due to a cloud provider issue. Refer to the state message for further details.
    • MAX_JOB_QUEUE_SIZE_EXCEEDED: The run was skipped due to reaching the job level queue size limit.
    • DISABLED: The run was never executed because it was disabled explicitly by the user.
    • BREAKING_CHANGE: Run failed because of an intentional breaking change in Spark, but it will be retried with a mitigation config.
    • CLUSTER_TERMINATED_BY_USER: The run failed because the externally managed cluster entered an unusable state, likely due to the user terminating or restarting it outside the jobs service.