distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- Check plugin registration status
- remove *NUM_THREADS env variables from default config
- Fix apparent race condition between message processing and `Cluster.scheduler_info`
- 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`
- Memory leak when submitting futures
- Repeated calls to `memory_color` take around 12% of CPU time of scheduler
- Docs
- Python not yet supported