distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- remove *NUM_THREADS env variables from default config
- Fix apparent race condition between message processing and `Cluster.scheduler_info`
- StreamClosedError when calling client.shutdown()
- Dask may stop the instances on the middle of calculation without objective reason
- While registering a scheduler plugin get TypeError: PooledRPCCall.__getattr__.<locals>.send_recv_from_rpc() takes 0 positional arguments but 1 was given
- Priorities are ignored when stealing tasks
- Increasing value of `OMP_NUM_THREADS` reduces performance even when controlling for `n_workers` and `threads_per_worker`
- `RuntimeError: Not enough arguments provided: missing keys` in `dask.persist` with mix of `Future` and `Delayed`
- Warn (and eventually raise) when client.scatter is used with Active Memory Manager enabled
- Reuse worker to scheduler WS connection for scheduling
- Docs
- Python not yet supported