Azure Databricks · Arazzo Workflow
Azure Databricks Update a Job and Re-run It
Version 1.0.0
Partially update a job's settings, then trigger and poll a fresh run.
View Spec
View on GitHub
AnalyticsApache SparkBig DataData EngineeringMachine LearningArazzoWorkflows
Provider
Workflows
update-job-and-rerun
Partially update a job, then run it and wait for the run to finish.
Reads the job, calls updateJob to change the timeout, triggers runJobNow, then polls getJobRun until life_cycle_state is TERMINATED.
1
getJob
getJob
Read the job to capture its current name and confirm it exists before updating.
2
updateJob
updateJob
Partially update the job settings with a new timeout. Only the supplied settings are changed; all others are left intact.
3
runJobNow
runJobNow
Trigger a fresh run of the updated job and capture the run_id for polling.
4
pollRun
getJobRun
Retrieve the run state. Repeat until the run life_cycle_state is TERMINATED, then end with the final result_state.