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This repository has been archived by the owner on Feb 1, 2022. It is now read-only.
The example linked in READMEhttps://github.com/kubeflow/xgboost-operator/tree/master/config/samples/xgboost-dist shows that spawning distributed training job requires running kubectl. I want to run distributed XGBoost training as a part of bigger Kubeflow pipeline, how to achieve this? Is there a possibility to spawn distributed job from the Python code itself or from the Kubeflow Pipelines SDK?
The text was updated successfully, but these errors were encountered:
I think you can run XGBoostJob as part of Kubeflow Pipelines similar to other Kubeflow operators but I am not familiar enough with Kubeflow Pipelines to be sure. Try it out and let us know if you encounter any issues.
The example linked in
README
https://github.com/kubeflow/xgboost-operator/tree/master/config/samples/xgboost-dist shows that spawning distributed training job requires runningkubectl
. I want to run distributed XGBoost training as a part of bigger Kubeflow pipeline, how to achieve this? Is there a possibility to spawn distributed job from the Python code itself or from the Kubeflow Pipelines SDK?The text was updated successfully, but these errors were encountered: