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https://issues.apache.org/jira/browse/FLINK-36863?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Rui Fan resolved FLINK-36863.
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Fix Version/s: kubernetes-operator-1.11.0
Resolution: Fixed
Merged to main(1.11.0) via: 6e16bac00caf631ac6f54cdd8f06c67bfdd82255
> Use the maximum parallelism in the past scale-down.interval window when
> scaling down
> ------------------------------------------------------------------------------------
>
> Key: FLINK-36863
> URL: https://issues.apache.org/jira/browse/FLINK-36863
> Project: Flink
> Issue Type: Bug
> Components: Autoscaler
> Reporter: Rui Fan
> Assignee: Rui Fan
> Priority: Major
> Labels: pull-request-available
> Fix For: kubernetes-operator-1.11.0
>
>
> FLINK-36535 uses the maximum parallelism since the scale down trigger when
> scaling down. Because VertexDelayedScaleDownInfo only stored the
> maxRecommendedParallelism [1].
> It's better to use the maximum parallelism in the {color:#de350b}past
> scale-down.interval window{color}.
> h1. Reason:
> Assuming current parallelism is 100, and scale down interval is 1 hour,
> what's difference between them?
> Following is the recommended parallelism at the different time:
> * 2024-12-09 00:00:00 -> 99 (trigger scale down)
> * 2024-12-09 00:30:00 -> 90
> * 2024-12-09 01:00:00 -> 80
> * 2024-12-09 01:30:00 -> 70
> * 2024-12-09 02:00:00 -> 60
> * 2024-12-09 02:30:00 -> 50
> * 2024-12-09 03:00:00 -> 40
> For the current code in the main branch, the 99 will be as the final
> parallelism at 2024-12-09 03:10:00 since we take the
> maxRecommendedParallelism from VertexDelayedScaleDownInfo.
> But it has a bug here: 99 is closer with current parallelism (100), so the
> recommended parallelism is always within the utilization range. So job or
> task never scale down.
> But we should use 50 as the final parallelism at 2024-12-09 03:10:00, because
> 50 is the max parallelism in the past 1 hour. And 50 is not within the
> utilization range, scale down could be executed.
> h1. Approach:
> VertexDelayedScaleDownInfo maintain all recommended parallelisms at each time
> within the past scale-down.interval window period.
> * Evicts the recommended parallelism before the scale-down.interval window.
> * The max parallelism within the window range as the final parallelism.
> Note: It is a scenario that calculates the max value within a sliding window.
> * It is similar with leetcode 239: Sliding Window Maximum [2].
> * If latest parallelism is greater than the past parallelism, the past
> parallelism never be the max value, so we could evict all smaller parallelism
> in the past.
> * We only need to maintain a list with monotonically decreasing parallelism
> within the past window.
> * The first parallelism is the final parallelism.
> h1. Note:
> This proposal is exactly what FLINK-36535 change1 expects. But I was not
> aware of this bug during my development. Sorry for that. :(
> * {color:#de350b}Change1{color}: Using the maximum parallelism within the
> window instead of the latest parallelism when scaling down.
>
> [1]
> [https://github.com/apache/flink-kubernetes-operator/blob/d9e8cce85499f26ac0129a2f2d13a083d68b5c21/flink-autoscaler/src/main/java/org/apache/flink/autoscaler/DelayedScaleDown.java#L42]
> [2] [https://leetcode.com/problems/sliding-window-maximum/description/]
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