menu

ETL Processing on GCP Using Dataflow and BigQuery

Go to Lab

2289 Reviews

Huzaen J. · Reviewed about 6 hours ago

Muhammad A. · Reviewed about 6 hours ago

Puneet C. · Reviewed about 7 hours ago

Wei Lun K. · Reviewed about 7 hours ago

Ankit G. · Reviewed about 7 hours ago

Puneet C. · Reviewed about 7 hours ago

Chun Yu C. · Reviewed about 8 hours ago

Good but little slow

Eli K. · Reviewed about 8 hours ago

Sridhar E. · Reviewed about 8 hours ago

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. · Reviewed about 11 hours ago

Punyanuch S. · Reviewed about 13 hours ago

Andrew Z. · Reviewed about 15 hours ago

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

Thatchapoom T. · Reviewed about 16 hours ago

Graciela G. · Reviewed about 19 hours ago

Jorge A. · Reviewed about 23 hours ago

Nicholas F. · Reviewed 1 day ago

Dmytro R. · Reviewed 1 day ago

Cliff L. · Reviewed 1 day ago

atmi t. · Reviewed 1 day ago

Murali K. · Reviewed 1 day ago

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

Salvador L. · Reviewed 1 day ago

Too slow execution of dataflow

Salvador L. · Reviewed 1 day ago

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

Pierre G. · Reviewed 1 day ago

Connor M. · Reviewed 2 days ago

AASTHA A. · Reviewed 2 days ago