WeichenXu123 opened a new pull request, #41357:
URL: https://github.com/apache/spark/pull/41357
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### What changes were proposed in this pull request?
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Add `copyFromLocalToFS` API.
The API copies a provided local file to provided destination path on hadoop
FS.
The implementation of the API reuses `AddArtifact` proto message, and it
fill the Artifact path as `forward_to_fs/{destination_path}` , and in spark
connect server backend, when handling artifact requests, if receiving an
artifact request with path starting with `forward_to_fs`, it saves the artifact
data to the provided `destination_path` on HadoopFS.
### Why are the changes needed?
In new distributed spark ML module (designed to support spark connect and
support local inference)
We need to save ML model to hadoop file system as its raw file format and
saved as provided file name, the reason is:
We often submit a spark application to spark cluster for running the
training model job, we need to save trained model to hadoop file system before
the spark application completes.
But we want to support local model inference, that means if we save the
model by current spark DataFrame writer (e.g. parquet format), when loading
model we have to rely on the spark service. But we hope we can load model
without spark service. So we want the model being saved as the original binary
format that our ML code can handle.
### Does this PR introduce _any_ user-facing change?
Yes
Add `copyFromLocalToFS` API:
```
def copyFromLocalToFS(self, local_path: str, dest_path: str) -> None:
"""
copy file from local to FS.
Parameters
----------
local_path: str
Path to a local file (Directory is not supported yet).
The path can be either absolute path or relative path.
dest_path: str
The FS path to the destination the file will be copied to.
.. versionadded:: 3.5.0
"""
```
### How was this patch tested?
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Unit tests.
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