리뷰 Dataflow를 사용한 서버리스 데이터 분석: 부 입력(Python)개

Matthieu C. · 거의 3년 전에 리뷰됨

Zana O. · 거의 3년 전에 리뷰됨

Allam V. · 거의 3년 전에 리뷰됨

Sudarsan S. · 거의 3년 전에 리뷰됨

Amine K. · 거의 3년 전에 리뷰됨

Ben S. · 거의 3년 전에 리뷰됨

OMKAR B. · 거의 3년 전에 리뷰됨

ok

Sovers S. · 거의 3년 전에 리뷰됨

gnanaarasan j. · 거의 3년 전에 리뷰됨

Executing the pipeline on the cloud (Task 4, step 4) often results in the pipeline failing due to a ZONE_RESOURCE_POOL_EXHAUSTED error, and the instructions don't account for this error. The error can (probably) be suppressed right away by changing the region/zone of the job (by editing JavaProjectsThatNeedHelp.py, the relevant parameter is `'--region=us-central1',` at around line 155, and if you want to specify the zone you can add another parameter beside it called `'--worker_zone=<zone>'` — the zone MUST BE contained within the specified region), but it seems like changing to any region beside `us-central1` prevents the lab from counting the objective as completed. Alternatively, you can just wait and try again another time. I really think this lab should check whether the pipeline has been successfully run regardless of region, because an unlucky learner could end up hitting the resource pool exhausted error several times in a row and potentially be locked out of the lab while trying to debug it. I ran the lab 3 times before succeeding in `us-central1`. It also seems like people in other regions are persistently having another type of error, `'us-central1' violates constraint 'constraints/gcp.resourceLocations'`. If the lab accounted for work being done in different regions (and included some guidance about these potential errors), both of these issues would be easy to resolve. There are loads of people reporting the same issues in the reviews for this lab, the Java version of the lab, the Coursera forums for a Coursera course using this lab, and there is a GitHub issue about this on the training-data-analyst repo.

Nicholas C. · 거의 3년 전에 리뷰됨

自分の進め方が悪かったのか、最後の[進行状況を確認]押しても完了できなかった GCSのバケットにはファイルが作成されており、ローカル・クラウドそれぞれで更新がかかっていた "error": { "code": 400, "message": "(5b4cea77a6d05a9d): 'us-central1' violates constraint 'constraints/gcp.resourceLocations' on the resource 'projects/qwiklabs-gcp-02-54459e55a7fd'.", "status": "FAILED_PRECONDITION"

Yuhei K. · 거의 3년 전에 리뷰됨

ayushi p. · 거의 3년 전에 리뷰됨

santhosh k. · 거의 3년 전에 리뷰됨

Nikola K. · 거의 3년 전에 리뷰됨

Startup of the worker pool in zone us-central1-f failed to bring up any of the desired 1 workers. Tried changin region task check fails

Jason K. · 거의 3년 전에 리뷰됨

Startup of the worker pool in zone us-central1-f failed to bring up any of the desired 1 workers. Tried changin region task check fails

Jason K. · 거의 3년 전에 리뷰됨

Task 4. step 4. results in the following error: > Startup of the worker pool in zone us-central1-a failed to bring up any of the desired 1 workers. Please refer to https://cloud.google.com/dataflow/docs/guides/common-errors#worker-pool-failure for help troubleshooting. ZONE_RESOURCE_POOL_EXHAUSTED: Instance 'javahelpjob-07271209-mht6-harness-g9r5' creation failed: The zone 'projects/qwiklabs-gcp-03-4743b84e1c9a/zones/us-central1-a' does not have enough resources available to fulfill the request. Try a different zone, or try again later. I have attempted changing the zone of the Dataflow job being run, and this can resolve the previous error, but the objective "Execute the pipeline" does not consider the task completed (presumably because I have deviated from the instructions, which do not account for such an error). I am not sure how to proceed. I have successfully executed the pipeline 3 times. The lab does not mark it complete. To successfully execute the pipeline and not get that error, I have to change the region/zone of the pipeline. The lab only marks the job complete if it has been done in the hardcoded region `us-central1`, and this leads to the error. I am not the only person having this issue, and it seems to be persistent, as I have found support requests on the Coursera forums going back *several months* about this lab and error. https://www.coursera.org/learn/batch-data-pipelines-gcp/discussions/weeks/4 Here are a few example threads: Lab (Practicing Pipeline Side Inputs) - error with DataFlowRunner option https://www.coursera.org/learn/batch-data-pipelines-gcp/discussions/forums/mYGuD7njEeyBoBL7F1DbTw/threads/riLq7yn-Ee6fqw5g8_UaQQ Serverless Data Analysis with Dataflow: Side Inputs both Phytom [sic] and Java DataFlow Job error https://www.coursera.org/learn/batch-data-pipelines-gcp/discussions/forums/mYGuD7njEeyBoBL7F1DbTw/threads/_NywZCggEe6qcgp0u5G9Fw Serverless Data Analysis with Dataflow: Side Inputs (Python) https://www.coursera.org/learn/batch-data-pipelines-gcp/discussions/forums/mYGuD7njEeyBoBL7F1DbTw/threads/kwqhqs4mEe2Rxw5vmkBsRw Here is a GitHub issue about this from June https://github.com/GoogleCloudPlatform/training-data-analyst/issues/2322 I spoke to Qwiklabs chat support about this issue, whether I could have the lab marked as complete, and they advised I wait and try again later. I am not sure what else I can really do, but I'm not confident that waiting will resolve this issue, considering it appears to have been going on for months. My lab timed out while I was attempting to troubleshoot this issue. I completed every step, and every task in the lab, carefully and multiple times, but I have not gotten any credit for it. I am not happy about this.

Nicholas C. · 거의 3년 전에 리뷰됨

Por que hay tantos errores y solo indica que siga adelante, pero no es exitoso el laboratorio

Heremar M. · 거의 3년 전에 리뷰됨

Heremar M. · 거의 3년 전에 리뷰됨

cd ~/training-data-analyst/courses/data_analysis/lab2/python nano JavaProjectsThatNeedHelp.py is not present

Trailokya B. · 거의 3년 전에 리뷰됨

Ismael R. · 거의 3년 전에 리뷰됨

Wasn't able to finish the last task because I ran into a resources for a particular zone error: The zone 'projects/qwiklabs-gcp-01-28784bd2c459/zones/us-central1-b' does not have enough resources available to fulfill the request. Try a different zone, or try again later.

Joash C. · 거의 3년 전에 리뷰됨

Eevamaija V. · 거의 3년 전에 리뷰됨

Olcay F. · 거의 3년 전에 리뷰됨

Tuomas L. · 거의 3년 전에 리뷰됨