关于“使用 Dataflow 和 BigQuery (Python) 在 Google Cloud 上进行 ETL 处理”的评价

Sridhar E. · 已于 about 7 years前审核

The lab needs more time. There is just enough time to give a quick read of the python code files. An additional 30 min should be good. The explanation in Step5 & Step6 (see below) just repeat of that from the Step2. Adding a block diagram like in the DataFlow charts would be good. You will now build a Dataflow pipeline with a TextIO source and a BigQueryIO destination to ingest data into BigQuery. More specifically, it will: Ingest the files from GCS. Filter out the header row in the files. Convert the lines read to dictionary objects. Output the rows to BigQuery.

Sreedevi G. · 已于 about 7 years前审核

Punyanuch S. · 已于 about 7 years前审核

Andrew Z. · 已于 about 7 years前审核

Dataflow is long shutting down worker it may longer than 3 min calculate to 50% of all processes that's very inefficiency.

Thatchapoom T. · 已于 about 7 years前审核

Graciela G. · 已于 about 7 years前审核

Jorge F. · 已于 about 7 years前审核

Nicholas F. · 已于 about 7 years前审核

Dmytro R. · 已于 about 7 years前审核

Cliff L. · 已于 about 7 years前审核

atmi t. · 已于 about 7 years前审核

Murali K. · 已于 about 7 years前审核

Too slow execution of dataflow, I need more practice it seems

Salvador L. · 已于 about 7 years前审核

Too slow execution of dataflow

Salvador L. · 已于 about 7 years前审核

Good lab but too long to finish it one hour Dataflow is quite slow

Pierre G. · 已于 about 7 years前审核

Connor M. · 已于 about 7 years前审核

AASTHA A. · 已于 about 7 years前审核

Appu V. · 已于 about 7 years前审核

Pratap S. · 已于 about 7 years前审核

Alejandro G. · 已于 about 7 years前审核

Alex K. · 已于 about 7 years前审核

need more time.

Sri N. · 已于 about 7 years前审核

Masthanaiah C. · 已于 about 7 years前审核

Atul C. · 已于 about 7 years前审核

Anton Z. · 已于 about 7 years前审核