关于“Running Apache Spark jobs on Cloud Dataproc”的评价

Chamoun S. · 已于 over 3 years前审核

José C. · 已于 over 3 years前审核

Oscar Andres V. · 已于 over 3 years前审核

Rustem S. · 已于 over 3 years前审核

Job I entered is not running

Meenakshi L. · 已于 over 3 years前审核

Shireesh R. · 已于 over 3 years前审核

Vijayasarathy A. · 已于 over 3 years前审核

Daniel M. · 已于 over 3 years前审核

Jing C. · 已于 over 3 years前审核

Shivakumar A. · 已于 over 3 years前审核

Yogesh P. · 已于 over 3 years前审核

SIVA T. · 已于 over 3 years前审核

Joel D. · 已于 over 3 years前审核

Excelent! Only bugs final steps. When i execute cloud shell code.

Alfonso Gustavo Q. · 已于 over 3 years前审核

Felipe T. · 已于 over 3 years前审核

Delano L. · 已于 over 3 years前审核

Ritu B. · 已于 over 3 years前审核

personally I find this very boring, but other than that very good lab

Luis A. · 已于 over 3 years前审核

Esra K. · 已于 over 3 years前审核

todo bien

Consultor E. · 已于 over 3 years前审核

Federico S. · 已于 over 3 years前审核

Dávid G. · 已于 over 3 years前审核

Aleksandr K. · 已于 over 3 years前审核

This is not clear and could use an image. I believe I followed the right instructions but did not see a change in the output report. Navigate to your storage bucket and note that the output report, /sparktodp/report.png has an updated time-stamp indicating that the stand-alone job has completed successfully. The storage bucket used by this Job for input and output data storage is the bucket that is used just the Project ID as the name.

Alexandre M. · 已于 over 3 years前审核