Processamento ETL no Google Cloud com o Dataflow e o BigQuery (Python) avaliações

80300 avaliações

I had to add the following permissions on compute engine service account for this to work: Dataflow Admin Cloud Dataflow Service Agent Editor

Sarma P. · Revisado há over 5 years

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yasunori s. · Revisado há over 5 years

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Madhi v. · Revisado há over 5 years

Piyush K. · Revisado há over 5 years

CLI not connected

gopi g. · Revisado há over 5 years

Madhi v. · Revisado há over 5 years

NA

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kavya p. · Revisado há over 5 years

wasn't able to finnish because i received this error File "/usr/local/lib/python3.7/site-packages/dataflow_worker/batchworker.py", line 649, in do_work work_executor.execute()

Sergio B. · Revisado há over 5 years

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Adisak S. · Revisado há over 5 years

Tetsuki T. · Revisado há over 5 years

Kiril Y. · Revisado há over 5 years

Awesome

Ramkrishna A. · Revisado há over 5 years

This is the worst lab I have taken so far here on qwiklabs, and to think the topic was supposed to be the most familiar to me. After going through the lab I actually feel more lost, even though I've been doing ETL the last 15 years (though not on cloud until ~2 years ago). Even though I also use Cloud Shell/gsutil/etc whenever possible when working, I wish in learning mediums such as this, the lab used more visual approach. The lab just says "here's code, understand on your own then run it. You have one hour." Even creating a bucket or a dataset would have been much simpler and informative if we did it via UI, instead of being given the complete code for us to just copy paste. TL;DR more UI steps, less Cloud Shell Finally, even if I preferred the codes over the UI, the 1-hour time limit is a bit tight, especially since Dataflow takes its time starting up.

Jan A. · Revisado há over 5 years

very good

Frederick A. · Revisado há over 5 years

Axel Z. · Revisado há over 5 years

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