Kumar Bharath Prabhu comments

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                                            Kumar Bharath Prabhu

Getting `concurrent.futures._base.CancelledError` from simple binary tree built from futures

Is this issue also present in dask-yarn cluster? I tried out the easy reproducible example and see the same error. If yes, would this be fixed by https://github.com/dask/distributed/pull/3643?

XGBoost 4J spark giving XGBoostError: std::bad_alloc on databricks

@jon-targaryen1995 I'm doing the exact same thing (same versions of scala, spark and xgboost4j) and I see the same error when I try to load my model. Any luck with...

Support multiple workers per VM

@jacobtomlinson I tried this on `EC2Cluster` like this: ``` ec2_cluster = EC2Cluster( env_vars=env_vars, extra_bootstrap=EC2_BOOTSTRAP_COMMANDS, filesystem_size=cluster_config["volume_size"], instance_tags=cluster_config["ec2_instance_tags"], n_workers=cluster_config["n_workers"], #worker_class="distributed.nanny.Nanny", worker_options={i: {"cls": Nanny, "options": {"nthreads": 2}} for i in range(4)}, scheduler_instance_type=cluster_config["scheduler_instance_type"], auto_shutdown=False,...

add new param to allow multiple workers in vmcluster, worker_mixin

@jacobtomlinson Thanks for the quick review. Sure, I can add tests and update docstrings. Do have a question for tests. Quickly looked at existing tests and it seems like the...