Open Deegue opened 9 months ago
When we use ray.init(runtime_env={"env_vars":"xxx"}), executors cannot get "env_vars" while it is critical for executors in many scenarios.
ray.init(runtime_env={"env_vars":"xxx"})
It is because RayAppMaster will raise a new job which is separated from the worker pod of RayDPSparkMaster.
RayAppMaster
RayDPSparkMaster
I'm running in to this also. Would like to be able to run experiments with different dependent libraries (and send them to the workers with an env_var) without having to change the base image of my ray cluster.
When we use
ray.init(runtime_env={"env_vars":"xxx"})
, executors cannot get "env_vars" while it is critical for executors in many scenarios.It is because
RayAppMaster
will raise a new job which is separated from the worker pod ofRayDPSparkMaster
.