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
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>-compute#developer.gserviceaccount.com 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.
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
Related
I'm trying to follow this GCP guide for importing CSV files from a Google Cloud Bucket into Cloud Spanner with GCP Dataflow.
The first time I tried the job it failed because there were some problems with the format of my CSV files and the manifest JSON. However after fixing those issues I keep running into this error:
Startup of the worker pool in zone us-central1-b failed to bring up any of the desired 2 workers. ZONE_RESOURCE_POOL_EXHAUSTED: Instance 'import-XXXXX' creation failed: The zone 'projects/mycoolproject/zones/us-central1-b' does not have enough resources available to fulfill the request. Try a different zone, or try again later.
After looking through the GCP docs, the only reference I found to this was this page here which suggest simply waiting (doesn't say how long one should expect to wait) or moving the job location. So I tried running the job in northamerica-northeast1 and I'm getting the exact same error.
I'm following the GCP Dataflow/Spanner CSV import guide step by step and I can't figure out what I'm doing wrong. I've never used Dataflow before so maybe there's something obvious I'm missing?
I should also note that my team doesn't use any Compute Engine resources but the docs don't say anything about having to manually enable such resources, only the Dataflow API.
What am I doing wrong?
Last week I installed the Docker/Kubernetes based version of Spring Cloud Data Flow
Although there were not overt errors, things are not working correctly.
I am able to create streams and tasks in the web UI and Spring Cloud Data Flow Shell but nothing runs.
I am most interested in Tasks.
When I create them, they all show with a Task Status of UNKNOWN.
Unfortunately, no matter how many times I launch them, the status always remains UNKNOWN.
I'm able to delete them but what magic must I use to make them run?
There's nothing apparent from the description as to what has failed. Perhaps if you can update it with more details, it'd be useful.
From a troubleshooting standpoint, when deploying streams or if the launch of Tasks' fails for any reason, they will be logged in the SCDF-server/Skipper-server logs. You'd have to tail the logs of the respective pod to learn more about the failures.
Also, it'd be useful to verify the output of kubectl describe pod/<POD_NAME> to see what's causing the stream/task pods not to start successfully. They're usually listed towards the end of this command-output.
The usual suspects are due to pods' health-check failures and/or the stream/task application docker images aren't resolvable at runtime. You'll see the reasons in the logs, of course.
This was a misconfiguration on my end.
I'm able to run as expected now.
I was trying to cancel a google dataflow job, but it has been stuck "cancelling" for like 15mins now.
When I run the command: gcloud beta dataflow jobs list --status=active
It shows the job as active. I then run the command: gcloud beta dataflow jobs cancel [job id here].
It prompts me that it has been canceled, but it still appears as active in the status list.
These types of Google-end issues are best reported in the Public Issue Tracker where the engineering team responsible can be notified.
Providing further information in the issue report to Google such as your project number and the job ID of the stuck Dataflow job will help in resolving the issue more quickly.
My Dataflow job is failing with the following message, how should I debug?
Workflow failed. Causes: (65a939e801f185b6): Unable to bring up enough
workers: minimum 1, actual 0.
The service will output this message when it is unable to allocate a virtual machine from Compute Engine to execute the job. Please check your quota in the console.
I had problems with the same thing. However, switching zone solved the problem for me. I believe it gives the same error message sometimes when there are no free resources.
I'm getting the following error in the recent jobs I'm trying to submit:
2015-01-07T15:51:56.404Z: (893c24e7fd2fd6de): Workflow failed.
Causes: (893c24e7fd2fd601):
There was a problem creating the GCE VMs or starting Dataflow on the VMs so no data was processed. Possible causes:
1. A failure in user code on in the worker.
2. A failure in the Dataflow code.
Next Steps:
1. Check the GCE serial console for possible errors in the logs.
2. Look for similar issues on http://stackoverflow.com/questions/tagged/google-cloud-dataflow.
There are no other errors.
What does this error mean?
Sorry for the trouble.
The Dataflow starts up VM instances and then launches an agent on those VMs. Those agents then do the heavy lifting of executing your code (e.g. ParDo's, reading and writing) your Data.
The error indicates the job failed because no agents were requesting work. As a result, the service marked the job as a failure because it wasn't making any progress and never would since there weren't any agents to process your data.
So we need to figure out where in the agent startup process things failed.
The first thing to check is whether the VMs actually started. When you run your job do you see any VMs created in your project? It might take a minute or two for the VMs to startup but they should appear shortly after the runner prints out the message "Starting worker pool setup". The VMs should be named something like
<PREFIX-OF-JOB-NAME>-<TIMESTAMP>-<random hexadecimal number>-<instance number>
Only a prefix of the job name is used to ensure we don't exceed GCE name limits.
If the VMs startup the next thing to do is to inspect the worker logs to look for errors indicating problems in launching the agent.
The easiest way to access the logs is using the UI. Go to the Google Cloud Console and then select the Dataflow option in the left hand frame. You should see a list of your jobs. You can click on the job in question. This should show you a graph of your job. On the right side you should see a button "view logs". Please click that. You should then see a UI for navigating the logs and you can look for errors.
The second option is to look for the logs on GCS. The location to look for is:
gs://PATH TO YOUR STAGING DIRECTORY/logs/JOB-ID/VM-ID/LOG-FILE
You might see multiple log files. The one we are most interested in is the one that starts with "start_java_worker". If that log file doesn't exist then the worker didn't make enough progress to actually upload the file; or else there might have been a permission problem uploading the log file.
In that case the best thing to do is to try to ssh into one of the VMs before it gets torn down. You should have about 15 minutes before the job fails and the VMs are deleted.
Once you login to the VM you can find all the logs in
/var/log/dataflow/...
The log we care most about at this point is:
/var/log/dataflow/taskrunner/harness/start_java_worker-SOME ID.log
If there is a problem starting the code that runs on the VM that log should tell us. That log and the other logs should also tell us if there is a permission problem that prevents the code running on the worker from being able to access Dataflow.
Please take a look and let us know if you find anything.
Apart from Jeremy Lewi's great answer, I would like to add that I've seen this error appear when you don't enable the proper Google APIs in the Developers Console, as mentioned here, which leads to a permission issue, like Jeremy said.