pearu commented on PR #50923: URL: https://github.com/apache/arrow/pull/50923#issuecomment-6520942636
> > Sorry for late response. numba-cuda is in [maintenance mode](https://github.com/NVIDIA/numba-cuda/issues/902) now and we will unlikely fix this, I am afraid. > > Here's a more radical suggestion: how about we deprecate Numba-CUDA support in PyArrow and then remove it? The code has almost not been touched since 2018 when it was [first written by @pearu](https://github.com/apache/arrow/pull/2732) , and we don't seem to get any user feedback or reports about it (the only reason we are noticing problems is because of our own CI). > > I don't think anyone cares at this point. Or it just works :) In any case, I agree that users should switch to the NVIDIA/numba-cuda-mlir approach (`numba_cuda_mlir.cuda` instead of `numba.cuda`) or use standard protocols such as DLPack or `__cuda_array_interface__`. For the export direction, CudaBuffer would need to implement these. I looked for downstream users of `from_numba`/`to_numba` and found almost none. dora-rs was the only real user and dropped them in Aug 2026 (dora-rs/dora#3249). Other `pyarrow.cuda` users, like heavyai, rely only on the IPC and record-batch APIs. So deprecating and removing the `numba` methods seems fine, as long as the rest of `pyarrow.cuda` stays. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
