distributed
https://github.com/dask/distributed
Python
A distributed task scheduler for Dask
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- Issues
- "TypeError: h5py objects cannot be pickled" when applying map_blocks to dask array constructed from HDF5 dataset
- Remove IP lookup from `inproc` protocol
- While registering a scheduler plugin get TypeError: PooledRPCCall.__getattr__.<locals>.send_recv_from_rpc() takes 0 positional arguments but 1 was given
- Multiple semaphores render scheduler unresponsive and crash entire cluster
- Add keyword to allow disabling config forwarding in SSHCluster
- Priorities are ignored when stealing tasks
- Increasing value of `OMP_NUM_THREADS` reduces performance even when controlling for `n_workers` and `threads_per_worker`
- Restructure cudf spill metrics and test
- Add config to control default direct_to_worker value
- `Client.compute` doesn't materialize delayed chunk of persisted array if provided as a dict value
- Docs
- Python not yet supported