Serverless Data Processing with Dataflow - Monitoring, Logging and Error Reporting for Dataflow Jobs recensioni

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Success

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I can't do task 4 and 5 # Launch the pipeline python3 my_pipeline.py \ --project=${PROJECT_ID} \ --region=us-central1 \ --output gs://$PROJECT_ID/results/prefix \ --tempLocation=gs://$PROJECT_ID/temp/ \ --max_num_workers=5 \ --runner=DataflowRunner WARNING:apache_beam.options.pipeline_options:Unable to create default GCS bucket. Traceback (most recent call last): File "/home/student_04_8c11d2ecccdc/my_pipeline.py", line 50, in <module> run() File "/home/student_04_8c11d2ecccdc/my_pipeline.py", line 40, in run p = beam.Pipeline(options=PipelineOptions(pipeline_args)) File "/home/student_04_8c11d2ecccdc/.local/lib/python3.9/site-packages/apache_beam/pipeline.py", line 203, in __init__ raise ValueError( ValueError: Pipeline has validations errors: Invalid Project ID (). Please make sure you specified the Project ID, not project number. Missing GCS path option: temp_location. Missing GCS path option: staging_location.

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I am writing to inform you that we are currently experiencing an ongoing issue with the lab - "Serverless Data Processing with Dataflow - Monitoring, Logging and Error Reporting for Dataflow Jobs". We understand that this may cause inconvenience to you and we apologize for any disruption to your learning.

Abhinandh J. · Recensione inserita circa 2 anni fa