Hey Gyula,
Thanks for getting back.
1) Yes, some more testing revealed the job was able to start with lower
parallelism i.e. lower than the upper bound that was set by the adaptive
scheduler.
2) I am limiting the parallelism of any job-vertex by setting
pipeline.max-parallelism to a value that ke
Hey!
Let me first answer your questions then provide some actual solution
hopefully :)
1. The adaptive scheduler would not reduce the vertex desired parallelism
in this case but it should allow the job to start depending on the
lower/upper bound resource config. There have been some changes in ho
Hello,
I am running a flink job in the application mode on k8s. It's deployed as a
FlinkDeployment and its life-cycle is managed by the flink-k8s-operator.
The autoscaler is being used with the following config
job.autoscaler.enabled: true
job.autoscaler.metrics.window: 5m
job.autoscaler.stabiliz