关于“[DEPRECATED] Run a Big Data Text Processing Pipeline in Cloud Dataflow”的评价

Good walkthrough. I think it is beneficial to touch more on the code to understand how a Cloud Dataflow pipeline could be reconstructed. Another approach could be to start from the ground up and build out this data flow pipeline rather than starting with the finished product.

Garrett W. · 评论over 7 years之前

Neelabh K. · 评论over 7 years之前

Sathish K. · 评论over 7 years之前

Tord N. · 评论over 7 years之前

Tim S. · 评论over 7 years之前

OK

David N. · 评论over 7 years之前

Jonathan B. · 评论over 7 years之前

If you can offer more information about the map reduce java part will be great!

Xi C. · 评论over 7 years之前

Miriam Q. · 评论over 7 years之前

Kushal N. · 评论over 7 years之前

Yinxi Z. · 评论over 7 years之前

Wojciech Z. · 评论over 7 years之前

SAIKRISHNA G. · 评论over 7 years之前

Deepti G. · 评论over 7 years之前

Again, would be nice to actually write some of this code rather than copypasta. Don't hand hold too much

George G. · 评论over 7 years之前

Very straight forward and fairly intuitive, which the other labs have not been. Maybe I am getting the hang of it.

Nick C. · 评论over 7 years之前

Johnnie NG .. · 评论over 7 years之前

Özlem A. · 评论over 7 years之前

Sergio G. · 评论over 7 years之前

David T. · 评论over 7 years之前

Jordi J. · 评论over 7 years之前

Akeno R. · 评论over 7 years之前

JT J. · 评论over 7 years之前

API Library names listed do not match those in the GCP API Library, they are only similar. Google Dataflow API Stackdriver Logging API Google Cloud Storage Google Cloud Storage JSON API BigQuery API Google Cloud Pub/Sub API Google Cloud Datastore API Should also mention that if you click on the header "API" it will sort the list alphabetically. There is no "Refresh" for the Dataflow console so the only way I found to update the status was to click on the Flow name then the back arrow at top-left.

Harold K. · 评论over 7 years之前

Michael I. · 评论over 7 years之前