[
https://issues.apache.org/jira/browse/FLINK-31215?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17693923#comment-17693923
]
Gaurav Miglani commented on FLINK-31215:
----------------------------------------
[~gyfora]
can you assigned it to me, i want to work on it
> Backpropagate processing rate limits from non-scalable bottlenecks to
> upstream operators
> ----------------------------------------------------------------------------------------
>
> Key: FLINK-31215
> URL: https://issues.apache.org/jira/browse/FLINK-31215
> Project: Flink
> Issue Type: New Feature
> Components: Autoscaler, Kubernetes Operator
> Reporter: Gyula Fora
> Priority: Major
>
> The current algorithm scales operators based on input data rates by
> propagating it forward through the graph.
> However there are cases where a certain operators processing capacity is
> limited either because it has a set maxParallelism or the users excludes it
> from scaling (or otherwise the capacity doesnt increase with scaling).
> In these cases it doesn't make sense to scale upstream operators to the
> target data rate if the job is going to be bottlenecked by a downstream
> operator. But instead we should backpropagate the limit based on the
> non-scalable bottleneck.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
