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https://issues.apache.org/jira/browse/FLINK-30571?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated FLINK-30571:
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Labels: pull-request-available (was: )
> Compute scale parallelism based on observed scalability
> --------------------------------------------------------
>
> Key: FLINK-30571
> URL: https://issues.apache.org/jira/browse/FLINK-30571
> Project: Flink
> Issue Type: New Feature
> Components: Autoscaler, Kubernetes Operator
> Reporter: Gyula Fora
> Priority: Major
> Labels: pull-request-available
>
> When computing target parallelism for job vertices we currently assume linear
> scaling with a fixed (1) coefficient.
> This assumes that in order to double the capacity we simply double the
> parallelism.
> While linearity already might be violated by many real time workloads this
> form of strong linearity rarely holds due to the overhead of increased
> network traffic, coordination etc.
> As we can access past (parallelism, processingRate) information based on the
> scaling history we should estimate the scalability coefficient either using a
> simple or weighted linear regression.
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