distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- Adding futures into a `Queue` disables `resources` argument in `submit` function.
- Client submit with workers doesn’t handle new joining workers correctly
- Improve error message when spilling runs out of disk
- Memory leak when using slurm
- Dask order uses task_spec
- Remove ``defaults`` conda channel from CI
- `Client.compute(df)` operates on larger task graphs than `df.compute()`
- Propagate reason to client-side `FutureCancelledError` when closing the scheduler
- test_jupyter_cli seems to be timing out regularly on main on all jobs
- Remove data spilling that acts on `target` threshold
- Docs
- Python not yet supported