关于“PDE Prep: Cloud Managed Apache Spark Cluster Operations and Maintenance”的评价

Vinicius H. · 已于 almost 5 years前审核

Luciana B. · 已于 almost 5 years前审核

Bruno C. · 已于 almost 5 years前审核

Jorge S. · 已于 almost 5 years前审核

Bruno C. · 已于 almost 5 years前审核

Couldn't complete task 4 because versions of cluster are different, there is no 1.3 version

Luis Arinobu O. · 已于 almost 5 years前审核

mjtelco-test-2のjobでエラーになりませんでした。dataprocとしては処理性能が向上したので良いとは思いますが、シナリオの見直しが必要と感じました。

秀吾 沼. · 已于 almost 5 years前审核

Again for the 3rd time, we try to execute the lab. A mistake should be raised when creating and running job mjtelco-test-2, anyway even following the relevant instructions the job,expected to fail for lack of memory, runs perfectly and the result is not recorded in the score.

Nicola P. · 已于 almost 5 years前审核

Did the lab again to try again. Job does not fail where it should fail with available images. gcloud dataproc clusters create mjtelco \ --project qwiklabs-gcp-01-15432c8f587b \ --region=us-central1 \ --zone=us-central1-a \ --master-machine-type=n1-standard-2 \ --worker-machine-type=n1-standard-2 \ --image-version=1.4-debian10 \ gcloud dataproc jobs submit \ pyspark gs://qwiklabs-gcp-01-15432c8f587b/benchmark.py \ --id=mjtelco-test-2 \ --cluster=mjtelco \ --max-failures-per-hour=1 \ --region=us-central1 \ -- 220 After submit, job executes perfectly, no java out of memory error here.

Dirk H. · 已于 almost 5 years前审核

The lab is become old and has multiple issues 1. The image used in the lab is no longer listed in GCP, so I had to take a higher version image. 2. The first job ran fine, the second job also, even though the dataproc cluster was created with the provided settings. 3. Since the second job ran succesful, the objective could not be completed, re-running the job was not possible due to already having ran a job with the same job-id, other naming would mean the lab couldn't validate the success of the objective. Overall the idea is good, but this lab is needs to be updated.

Dirk H. · 已于 almost 5 years前审核

The step with "failed job" has a problem: using 220 as argument doesn't make the job fail anymore.

Daniel S. · 已于 almost 5 years前审核

Md I. · 已于 almost 5 years前审核

Md I. · 已于 almost 5 years前审核

Thauren H. · 已于 almost 5 years前审核

Finished. Good Job

aulia s. · 已于 almost 5 years前审核

Finished

aulia s. · 已于 almost 5 years前审核

Lab is broken and outdated. There is no more version 1.3 image and copying just the .py file is not enough - it requires the entire .* of the directory. This was good enough for all tasks, except for the "demonstrate failure" one - the way GCP works now does not cause OOM Errors anymore (even when I tried getting the number of partitions to extreme - it tells me about 22TiB memory and maxes on 12 GB allocated, but still keeps on running chunk by chunk.) Trying to override driver setting didn't help either and, since the lab itself was expecting a very specific failure, neither did failing the job differently (by referring it to a non-existing file.)

Aleksandr Z. · 已于 almost 5 years前审核

Arthur M. · 已于 almost 5 years前审核

Karthick K. · 已于 almost 5 years前审核

super

Yogee P. · 已于 almost 5 years前审核

LEUNG, C. · 已于 almost 5 years前审核

très bien fait

Koniba J. · 已于 almost 5 years前审核

one of the tasks took about 45 minutes to fail which is waste of time

翔中 張. · 已于 almost 5 years前审核

sibatyu9793 s. · 已于 almost 5 years前审核

Demetrius T. · 已于 almost 5 years前审核