Use Serverless for Apache Spark to Load BigQuery Reviews

14197 reviews

Tomi A. · Reviewed أكثر من سنة ago

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麗奈 谷. · Reviewed أكثر من سنة ago

Thank you so much!

J JESUS G. · Reviewed أكثر من سنة ago

Juan C. · Reviewed أكثر من سنة ago

The below instruction could have been in little more detail. As I found dataproc identification tool not visible. Next, you're going to set a few environment variables into VM instance terminal and execute a Spark template to load data into BigQuery. Set the following environment variables for the Dataproc Serverless environment.

Sameer S. · Reviewed أكثر من سنة ago

sandeep s. · Reviewed أكثر من سنة ago

Jason M. · Reviewed أكثر من سنة ago

error when submitting spark job ERROR: (gcloud.beta.dataproc.batches.submit.pyspark) Batch job is FAILED. Detail: Insufficient 'CPUS' quota. Requested 12.0, available 11.0. Your resource request exceeds your available quota. See https://cloud.google.com/compute/resource-usage. Use https://cloud.google.com/docs/quotas/view-manage#requesting_higher_quota to request additional quota. Running auto diagnostics on the batch. It may take few minutes before diagnostics output is available. Please check diagnostics output by running 'gcloud dataproc batches describe' command.

max s. · Reviewed أكثر من سنة ago

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Sergiu D. · Reviewed أكثر من سنة ago

Thanks Google

Wisdom K. · Reviewed أكثر من سنة ago

Task 3.2 fails as the spark job needs additional IAM permissions to run the script. After adding the required permission the script passed without any issues. Lab needs to be updated with this additional step.

Vamshi K. · Reviewed أكثر من سنة ago

Kirit C. · Reviewed أكثر من سنة ago

there are some errors - just re-try after 2-3 mins

Tomasz M. · Reviewed أكثر من سنة ago

Maitreyee R. · Reviewed أكثر من سنة ago

Dawid G. · Reviewed أكثر من سنة ago

Dmitry P. · Reviewed أكثر من سنة ago

Task 3 check didn't work, but I was able to see the data in Task 4. Seems like something wrong with the check in Task 3.

Nick F. · Reviewed أكثر من سنة ago

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Creative P. · Reviewed أكثر من سنة ago

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