Comments (2)
Is it possible to use the same pipeline as the tutorial where Airflow & AirflowScheduler are running locally but pull data from BigQuery?
Yes
How does GCP authentication work in this scenario?
It works pretty much the same as kubeflow example, you need to have GOOGLE_APPLICATION_CREDENTIALS setup in your env(in airflow scheduler and webserver console), and set '--project=xxx' in your beam_pipeline_args
So basically you can use the taxi_pipeline_simple.py example, with example gen change to BigQueryExampleGen, and beam_pipeline_args setup in additional_pipeline_args
'beam_pipeline_args': [
'--runner=DirectRunner',
'--project=xxx',
],
To debug,
You can try the query in BigQuery web ui console to see if it work, and then try the same query in code
(the query in taxi_pipeline_kubeflow.py should work for you too)
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Got it to work, thanks!
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