I am new to Ray. I am trying to create a private cluster on-prem.
I installed ray on host1 and started as master, host2 joined a node.
I can connect to the cluster from master (host1) without any problem and could use all the resources from master and worker. But when I try to connect from python from worker node, it takes a long time to connect
ray.init(address='***')
2021-07-09 14:14:06,484 INFO worker.py:735 -- Connecting to existing Ray cluster at address:
In [3]: /worker/lib/python3.9/site-packages/jupyter_console/ptshell.py:783: UserWarning: The kernel did not respond to an is_complete_request. Setting `use_kernel_is_complete` to False.
warn('The kernel did not respond to an is_complete_request. '
The kernel stops responding. Can I only run the job from master node?
This has been addressed here, but I just want to make sure if I am using it correctly.
I found out 10001 is the port. I could connect from the workers successfully, does ray support connecting from arbitrary servers, I could connect to redis from arbitrary machines but not as ray client?
Creating a on-prem cluster for every day data pipelines. It’s so trivial to parallelize them for any general purpose python lib. Spark cluster is little hard to setup (yarn/mesos)