The job run failed because task dependency types are temporarily disabled

[GabrieleMuciacc]

I am trying the recently released conditional tasks (https://docs.databricks.com/en/workflows/jobs/conditional-tasks.html). I have created a workflow where the leaf task depends on multiple tasks and its run_if property is set as AT_LEAST_ONE_SUCCESS. However, when I try to run the workflow it immediately fails with "The job run failed because task dependency types are temporarily disabled" and I could not find any explanation of the error message in the online documentation. Can anyone share more info about this?

[Kaniz_Fatma]

Hi @GabrieleMuciacc,  This could be caused by a change in the cluster configuration or a temporary issue with the Databricks service.

To resolve this issue, you can try the following steps:

1. Check the cluster configuration to see if any recent changes might have caused this issue.
2. Try re-running the job to see if it succeeds consistently.
3. If the issue persists, please file a support ticket with Databricks support for further assistance. 

[GabrieleMuciacc]

Hi @Kaniz_Fatma , the problem looks somehow related to clusters. This is what I have done:

1. deploy the workflow using dbx
2. try to run: it fails with the above error
3. manually change the cluster definition (e.g., change the runtime)
4. try to run: it works
5. manually undo the change and try to run: it still works

I have compared the JSON definition of the workflow before and after the manual changes and it looks identical. Any suggestion?

[Kaniz_Fatma]

Hi @GabrieleMuciacc, I have a few suggestions,

- Double-check the cluster configuration and ensure it meets the job requirements. For example, check if the runtime version is compatible with the job.

- Check if any custom libraries or packages are required for the job to run. Make sure that they are installed on the cluster.
- Try creating a new cluster and running the job to see if the issue persists.
- Check the event logs for the cluster to see if there are any errors or warnings that may be related to the issue.
- If the issue persists, you can raise a support ticket with Databricks for further assistance.