Serverless Data Processing with Dataflow - Batch Analytics Pipelines with Dataflow (Python) recensioni

The dataflow jobs failed with "Startup of the worker pool in us-east1 failed to bring up any of the desired 1 workers. This is likely a quota issue or a Compute Engine stockout. The service will retry." There was also an SSL Certificate error to the GCS bucket which I solved by "gcloud auth application-default login" and clicking the link and pasting the code from the link. Thirdly, part 2 of the lab required dill imports which I installed with the following command. pip install apache-beam[dill]

Sayed Fawad Ali S. · Recensione inserita circa 10 ore fa

spent two hours getting message not sufficient workers/resources, in zone/region, but restricted from selecting another.

Ferdie O. · Recensione inserita 1 giorno fa

Had many errors running the pipeline due to missing certificates. Fixed it by adding: export GCE_METADATA_MTLS_MODE=none

Martin H. · Recensione inserita 3 giorni fa

vicente b. · Recensione inserita 4 giorni fa

The lab is very cool, but in all of the course labs I am hitting the problem that I cannot run dataflow jobs in the specified regions and zones because no workers are available in those zones (though I am running the jobs multiple times). It completely ruins the learning experience, because I am not able to finish any lab though they are very well prepared. Please, add the option to switch to different regions and zones or keep some compute quota for Qwik labs.

Jan K. · Recensione inserita 5 giorni fa

ZONE_RESOURCE_POOL_EXHAUSTED getting this error frequently

Ashok K. · Recensione inserita 5 giorni fa

Gustavo L. · Recensione inserita 6 giorni fa

Allan L. · Recensione inserita 6 giorni fa

Harsh A. · Recensione inserita 7 giorni fa

Guilherme A. · Recensione inserita 13 giorni fa

Wayne F. · Recensione inserita 13 giorni fa

Luis Antonio C. · Recensione inserita 13 giorni fa

Luis Antonio C. · Recensione inserita 14 giorni fa

already submitted feedback for this lab, with the issues that i've encountered

Rafael D. · Recensione inserita 14 giorni fa

WARNING:urllib3.connectionpool:Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1017)'))': /computeMetadata/v1/instance/service-accounts/default/?recursive=true Traceback (most recent call last): File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/solution/batch_user_traffic_pipeline.py", line 99, in <module> run() File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/solution/batch_user_traffic_pipeline.py", line 78, in run (p | 'ReadFromGCS' >> beam.io.ReadFromText(known_args.input_path) File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/textio.py", line 808, in __init__ self._source = self._source_class( File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/textio.py", line 144, in __init__ super().__init__( File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/filebasedsource.py", line 127, in __init__ self._validate() File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/options/value_provider.py", line 193, in _f return fnc(self, *args, **kwargs) File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/filebasedsource.py", line 190, in _validate match_result = FileSystems.match([pattern], limits=[1])[0] File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/filesystems.py", line 240, in match return filesystem.match(patterns, limits) File "/home/jupyter/training-data-analyst/quests/dataflow_python/3_Batch_Analytics/lab/df-env/lib/python3.10/site-packages/apache_beam/io/filesystem.py", line 779, in match raise BeamIOError("Match operation failed", exceptions) apache_beam.io.filesystem.BeamIOError: Match operation failed with exceptions {'gs://qwiklabs-gcp-04-497cbdcab972/events.json': RefreshError(TransportError("Failed to retrieve https://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/?recursive=true from the Google Compute Engine metadata service. Compute Engine Metadata server unavailable. Last exception: HTTPSConnectionPool(host='metadata.google.internal', port=443): Max retries exceeded with url: /computeMetadata/v1/instance/service-accounts/default/?recursive=true (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1017)')))"))}

Mykola O. · Recensione inserita 14 giorni fa

Mara Malina F. · Recensione inserita 15 giorni fa

Daniela L. · Recensione inserita 15 giorni fa

Gabriela C. · Recensione inserita 16 giorni fa

Luis Antonio C. · Recensione inserita 19 giorni fa

Leighton C. · Recensione inserita 19 giorni fa

There are some issues with running the dataflow; first, the version of a library has to be downgraded: pip install "google-auth==2.43.0" due to error: https://github.com/googleapis/google-cloud-python/issues/16090. Secondly, one has to specify the machine type and in the part B additionally have to set worker zone: options.view_as(beam.options.pipeline_options.WorkerOptions).machine_type = "e2-standard-4" options.view_as(beam.options.pipeline_options.WorkerOptions).worker_zone = "us-west1-c"

Przemyslaw S. · Recensione inserita 19 giorni fa

Anatolii L. · Recensione inserita 23 giorni fa

don't enough resources

Anatolii L. · Recensione inserita 25 giorni fa

Liberty B. · Recensione inserita 25 giorni fa

Ram krishna Reddy S. · Recensione inserita circa un mese fa