2
votes

I am using Google Dataprep to start Dataflow jobs and am facing some difficulties.

For background, we used Dataprep for some weeks and it worked without problem before we started to have authorization issues with the service account. When we finally solved this, we restarted the jobs we used to launch but they failed with "The Dataflow appears to be stuck.".

We tried with another very simple job but we met the same error. Here are the full error messages, the job fails after one hour being stuck:

Dataflow -

(1ff58651b9d6bab2): Workflow failed. Causes: (1ff58651b9d6b915): The Dataflow appears to be stuck.

Dataprep -

The Dataflow job (ID: 2017-11-15_00_23_23-9997011066491247322) failed. Please 
contact Support and provide the Dataprep Job ID 20825 and the Dataflow Job ID.

It seems this kind of error has various origins and I have no clue about where to start. Thanks in advance

2
Looking into this job. So far looks like the worker VM was launched, but it never reported back to the service. Could be some sort of network configuration issue. While look at it on Dataflow service side, you could look at worker logs on stackdriver (I need to request extra level of authorization to look at worker logs).Raghu Angadi

2 Answers

1
votes

Please check if there have been any changes to your project's default network. This is the common reason for workers not being able to contact the service, causing 1 hour timeouts.

Update:

After looking into further, <project-number>[email protected] service account for Compute Engine is missing under 'Editor' role. This is usually automatically created. Probably this was removed later by mistake. See 'Compute Engine Service Account' section in https://cloud.google.com/dataflow/security-and-permissions.

We are working on fixes to improve early detection of such missing permissions so that the failure points the root cause better.

This implies your other Dataflow jobs fail similarly as well.

1
votes

the best route would be to contact Google Support. The issue is related to the Dataflow side and would require some more research on the Dataflow backend by Google