Replies: 4 comments 2 replies
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That sounds interesting, but currently we still lack native Python APIs. So for now, you have to pick one of the three interfaces (mount as a network file system, S3 gateway, HDFS) provided by JuiceFS to interact with Ray. |
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Hi @SandyXSD, thanks for the quick response! Would it work out-of-the-box if Ray clusters would support CSI? |
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Yes, it should be. |
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hi.@trahloff @SandyXSD ,Ray can run on k8s like kuberay. and JuiceFS support CSI in k8s. I think this is a feasible solution but I don't see anyone doing that.I'm trying to go in that way. |
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What would you like to be added: Support for using JuiceFS with HPC clusters like Ray.
Why is this needed:
JuiceFS is an amazing tool that makes it extremely easy to work with data that is stored on S3 but needs to be instantly available for high parallel i/o. In our case, this use case is "machine learning on satellite images".
Having this integrated into k8s via CSI is great but constraints the usecases to workloads that fit well into a k8s environment. Because of our extremely high ressource-requirements, we and many other companies that are running data processing pipelines rely on compute clusters like Ray.
Do you see any possibility in integrating JuiceFS natively into Ray?
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