To learn more about selecting and configuring clusters to run tasks, see Use Databricks compute with your jobs. You can also configure a cluster for each task when you create or edit a task. A shared cluster option is provided if you have configured a New Job Cluster for a previous task. To add another task, click in the DAG view. See Configure an expected completion time or a timeout for a task. To optionally configure the task’s expected duration or timeout, click + Add next to Duration threshold. To optionally configure a retry policy for the task, click + Add next to Retries. To filter notifications and reduce the number of emails sent, check Mute notifications for skipped runs, Mute notifications for canceled runs, or Mute notifications until the last retry. Failure notifications are sent on initial task failure and any subsequent retries. To optionally receive notifications for task start, success, or failure, click + Add next to Emails. For information on the requirements for formatting and passing parameters, see Pass parameters to a Databricks job task. To add dependent libraries, click + Add next to Dependent libraries. To open the cluster on a new page, click the icon to the right of the cluster name and description. New Job Cluster: Click Edit in the Cluster drop-down menu and complete the cluster configuration.Įxisting All-Purpose Cluster: Select an existing cluster in the Cluster drop-down menu. In the Cluster drop-down menu, select either New job cluster or Existing All-Purpose Clusters. See Task type options.Ĭonfigure the cluster where the task runs. In the Type drop-down menu, select the type of task to run. Replace Add a name for your job… with your job name.Įnter a name for the task in the Task name field. Handling large queries in interactive workflows.Run tasks conditionally in a Databricks job.Pass context about job runs into job tasks.Share information between tasks in a Databricks job.
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