Processamento de dados sem servidor com o Dataflow: como criar um Pipeline ETL usando Apache Beam e Dataflow (Python) avaliações

Svetak S. · Revisado há 4 hours

Francisco M. · Revisado há 11 hours

Leonardo M. · Revisado há 1 day

Issue with the project id. There is no parent organization to select.

Vanitha H. · Revisado há 1 day

médiocre

Kasraoui W. · Revisado há 1 day

Igor d. · Revisado há 1 day

Ana N. · Revisado há 2 days

having error on Run your pipeline task, even using the solution code provided in the lab. Traceback (most recent call last): File "/home/jupyter/training-data-analyst/quests/dataflow_python/1_Basic_ETL/lab/my_pipeline.py", line 108, in <module> run() File "/home/jupyter/training-data-analyst/quests/dataflow_python/1_Basic_ETL/lab/my_pipeline.py", line 92, in run | 'ReadFromGCS' >> beam.io.ReadFromText(input) File "/home/jupyter/training-data-analyst/quests/dataflow_python/1_Basic_ETL/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/1_Basic_ETL/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/1_Basic_ETL/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/1_Basic_ETL/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/1_Basic_ETL/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/1_Basic_ETL/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/1_Basic_ETL/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-02-c763640af21b/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)')))"))}

yumeng y. · Revisado há 2 days

proper folders were not cloned for all the tasks

Shaik S. · Revisado há 2 days

Sriyansh S. · Revisado há 2 days

Sriyansh S. · Revisado há 2 days

Luis Antonio C. · Revisado há 3 days

Jyoti S. · Revisado há 3 days

Luis Antonio C. · Revisado há 3 days

Luis Antonio C. · Revisado há 3 days

Could not get the pipeline to run due to multiple errors. Even the solution would not run. Very disappointing to be kicked out of the lab and lose progress before being able to resolve / troubleshoot. Errors were around: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1017)'))': /computeMetadata/v1/instance/service-accounts/default/?recursive=true and Compute Engine Medadata server unavailable.

Mariette D. · Revisado há 4 days

too complex, needs more direction on what to do

Oscar O. · Revisado há 5 days

Daniela L. · Revisado há 5 days

problema con la infrectuctura (falta de espacio)

Gabriela C. · Revisado há 5 days

Luis Antonio C. · Revisado há 6 days

Could not complete Part1 Task 6 run the pipeline (using the provided Solution code) due to the following error: raise BeamIOError("Match operation failed", exceptions) apache_beam.io.filesystem.BeamIOError: Match operation failed with exceptions {'gs://qwiklabs-gcp-00-f5855126f119/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)')))"))}

Lingmin M. · Revisado há 6 days

Qwiklabs Dataflow Lab Fix Summary Problems SSL/Metadata auth failure — google-auth 2.44.0+ broke the default HTTP transport, causing CERTIFICATE_VERIFY_FAILED errors when the notebook tried to reach GCP's metadata server Zone resource exhaustion — n1-standard-1 (Dataflow's default) was completely unavailable across all us-central1 zones for Qwiklabs accounts Pipeline exits early — p.run() doesn't wait for completion, causing silent failures argparse rejects extra flags — parse_args() blocks passing extra Beam arguments like --worker_machine_type Fixes 1. Fix SSL auth error bashexport GCE_METADATA_MTLS_MODE=none 2. Use e2-standard-2 machine type Add to your run command: bash--worker_machine_type=e2-standard-2 3. Fix pipeline code In my_pipeline.py: python# Change this: opts = parser.parse_args() options = PipelineOptions() p.run() # To this: opts, pipeline_args = parser.parse_known_args() options = PipelineOptions(pipeline_args) p.run().wait_until_finish() 4. Full working command bashcd $BASE_DIR export PROJECT_ID=$(gcloud config get-value project) export GCE_METADATA_MTLS_MODE=none python3 my_pipeline.py \ --project=${PROJECT_ID} \ --region=us-central1 \ --stagingLocation=gs://$PROJECT_ID/staging/ \ --tempLocation=gs://$PROJECT_ID/temp/ \ --runner=DataflowRunner \ --worker_machine_type=e2-standard-2 5. For the Dataflow Template UI Under Optional Parameters → uncheck "Use default machine type" → Series: E2 → Machine type: e2-standard-2

David O. · Revisado há 6 days

console did not open

Nihal Hussain M. · Revisado há 6 days

Mara Malina F. · Revisado há 6 days

VERY BAD>> I am unable to run my jobs are with DataflowRunner as I am always getting resources contraints errors.. job is not able to spn up us-cerntral1 region.. I am getting same error in all labs which requires to submit jobs on dataflow. I am able to run with DirectRunner. Please help in this as I have spent too many hours but end up getting same error again and again

Mallikarjunarao G. · Revisado há 7 days