This will create a public issue which anybody can view and comment on.
This issue report has been forwarded to the PRODUCT engineering team so that they may investigate it, but there is no ETA for a resolution at this time. Future updates regarding this issue will be provided here.
Problem you have encountered:
The issue being experienced is that the client is attempting to run an already deleted (failed) Dataproc job, instead of failing instantly as we would expect for a deleted job, the job still runs in Dataproc continually in the 'Waiting for Job Output' status.
This also happens if the first job runs successfully to completion. Basically, deleting the job (failed or not) and using the same job id for a subsequent job will lead to the same undesirable behavior.
What you expected to happen: Job is terminated immediately as the first job
Steps to reproduce:
Creating a Dataproc cluster
Submitting a (failing) job
Once the job has failed, delete the job
Submit a new job with the same id with the same (failing) parameters
Observe that the job goes into running state
Other information:
We filter out jobs that have already run before based on job id and do not run them again. As a result, the second job does not start in Yarn at all even though it shows as running in the UI
Description
This will create a public issue which anybody can view and comment on.
This issue report has been forwarded to the PRODUCT engineering team so that they may investigate it, but there is no ETA for a resolution at this time. Future updates regarding this issue will be provided here.
Problem you have encountered:
The issue being experienced is that the client is attempting to run an already deleted (failed) Dataproc job, instead of failing instantly as we would expect for a deleted job, the job still runs in Dataproc continually in the 'Waiting for Job Output' status.
This also happens if the first job runs successfully to completion. Basically, deleting the job (failed or not) and using the same job id for a subsequent job will lead to the same undesirable behavior.
What you expected to happen: Job is terminated immediately as the first job
Steps to reproduce:
Other information: We filter out jobs that have already run before based on job id and do not run them again. As a result, the second job does not start in Yarn at all even though it shows as running in the UI