@dongjoon-hyun @yangwwei Thanks! @Mich Thanks for testing it, I'm not very professional with GKE,
I'm also not quite sure if it is different in configurations, internal network, scheduler implementations itself VS upstream K8S. As far as I know, different K8S vendors also maintain their own optimizations in their downstream product. But you can see some basic integration test results based on upstream K8S on x86/arm64: - x86: https://github.com/apache/spark/pull/35422#issuecomment-1035901775 - Arm64: https://github.com/apache/spark/pull/35422#issuecomment-1037039764 As can be seen from the results, for a single job, there is no big difference between default scheduler and volcano. Also custom schedulers such as Volcano, Yunikorn are more for the overall situation for multiple jobs and the utilization of the entire K8S cluster.
