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https://issues.apache.org/jira/browse/FLINK-36734?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sai Sharath Dandi updated FLINK-36734:
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Description: Currently, the autoscaler algorithm tries to keep all the Job
vertices at X% utilization(default 70). However, it is impossible to keep all
the vertices at 70% utilization depending on the Job topology (Imagine a long
job topology > 10 vertices). The autoscaler algorithm should be smart enough to
set a better default utilization target depending on the topology length. 0.7 *
100 * TM_CPU / topology_length could be a good starting point (was: Currently,
the autoscaler algorithm tries to keep all the Job vertices at X%
utilization(default 70). However, it is impossible to keep all the vertices at
70% utilization depending on the Job topology (Imagine a long job topology > 10
vertices). The autoscaler algorithm should be smart enough to set a better
default utilization target depending on the topology length. 0.7 *
100/topology_length could be a good starting point)
> Potential issue in autoscaler algorithm
> ---------------------------------------
>
> Key: FLINK-36734
> URL: https://issues.apache.org/jira/browse/FLINK-36734
> Project: Flink
> Issue Type: Improvement
> Components: Autoscaler
> Reporter: Sai Sharath Dandi
> Priority: Minor
>
> Currently, the autoscaler algorithm tries to keep all the Job vertices at X%
> utilization(default 70). However, it is impossible to keep all the vertices
> at 70% utilization depending on the Job topology (Imagine a long job topology
> > 10 vertices). The autoscaler algorithm should be smart enough to set a
> better default utilization target depending on the topology length. 0.7 * 100
> * TM_CPU / topology_length could be a good starting point
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