Validate Data Quality for a Batch Data Pipeline using Serverless for Apache Spark Reviews

Pravin P. · Reviewed yaklaşık 4 saat ago

Michele M. · Reviewed yaklaşık 5 saat ago

Felipe S. · Reviewed yaklaşık 6 saat ago

César B. · Reviewed yaklaşık 11 saat ago

Cristina T. · Reviewed yaklaşık 12 saat ago

It is impossible to complete the lab due to the lack to create dataproc resources on us-central1

Michele M. · Reviewed yaklaşık 15 saat ago

Bruno S. · Reviewed yaklaşık 16 saat ago

Choh J. · Reviewed yaklaşık 18 saat ago

bueno

Victor Santiago G. · Reviewed yaklaşık 22 saat ago

JACQUELINE ALEJANDRA V. · Reviewed 1 gün ago

JACQUELINE ALEJANDRA V. · Reviewed 1 gün ago

JACQUELINE ALEJANDRA V. · Reviewed 1 gün ago

Alejandra C. · Reviewed 1 gün ago

Jesús Martin R. · Reviewed 1 gün ago

Juan S. · Reviewed 1 gün ago

Carlos C. · Reviewed 1 gün ago

Great

Lina Marcela C. · Reviewed 1 gün ago

LTI 伴. · Reviewed 2 gün ago

Mallikarjunarao G. · Reviewed 2 gün ago

Juan José G. · Reviewed 2 gün ago

Adarsh S. · Reviewed 2 gün ago

excellent

Seshadri K. · Reviewed 3 gün ago

Sheraz A. · Reviewed 3 gün ago

Sebastian C. · Reviewed 3 gün ago

The lab job failed with the following error: Multiple Errors: - Failed to create batch autoscaling policy - Not authorized to requested resource. I dont know if it was a timing issue or something but according to Google Gemini I needed to do the following and then reexecuting the job fixed it for me. # Assign Dataproc Worker role gcloud projects add-iam-policy-binding $GOOGLE_CLOUD_PROJECT \ --member="serviceAccount:583522980681-compute@developer.gserviceaccount.com" \ --role="roles/dataproc.worker" # Assign Dataproc Editor role (often needed for Batch management) gcloud projects add-iam-policy-binding $GOOGLE_CLOUD_PROJECT \ --member="serviceAccount:583522980681-compute@developer.gserviceaccount.com" \ --role="roles/dataproc.editor"

Sayed Fawad Ali S. · Reviewed 3 gün ago