distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- Worker plugin can not be registered on worker unless its entire package source uploaded on server
- Improve structure of event logging
- PubSub functionality kills stream-based connections due to race conditions
- Client.map() keys as a list breaks Dask queue system
- Support collective style tasks
- [QST][Bug?] Can I fit/evaluate many XGBoost models on the same cluster?
- RecursionError when using PerformanceReport context manager
- Race condition in scatter->dereference->scatter
- `RuntimeError` when sending graph with `dask.array.ufunc.ufunc`s to scheduler and importing the wrapped `numpy` function
- Data loss during p2p shuffle
- Docs
- Python not yet supported