distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- Enable Client.wait_for_workers to optionally also wait when removing workers
- ENH: impure tasks?
- Cluster-level resources
- `dask.distributed.Lock` always async
- Allow client wait_for_workers to wait for an absolute number of workers
- Future submit()/result() takes very long time to complete with 8MB Python object
- Add worker config options to config system
- `tornado`'s `call_later`, `add_callback`, etc. prevent garbage collection of otherwise released objects
- `DequeHandler` prevents garbage collection of `Worker` instances and others
- Ease memory pressure by deprioritizing root tasks?
- Docs
- Python not yet supported