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https://issues.apache.org/jira/browse/IGNITE-23572?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Alexander Lapin updated IGNITE-23572:
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Ignite Flags: (was: Docs Required,Release Notes Required)
> Change rebalance scheduling when data nodes are changed
> -------------------------------------------------------
>
> Key: IGNITE-23572
> URL: https://issues.apache.org/jira/browse/IGNITE-23572
> Project: Ignite
> Issue Type: Improvement
> Reporter: Mirza Aliev
> Assignee: Mirza Aliev
> Priority: Major
> Labels: ignite-3
> Fix For: 3.0
>
> Time Spent: 50m
> Remaining Estimate: 0h
>
> h3. Motivation
> [IEP-131|https://cwiki.apache.org/confluence/display/IGNITE/IEP-131%3A+Partition+Majority+Unavailability+Handling]
>
>
> In HA mode for scale up situations:
> # Let’s say we have [A, B, C] for the partition assignments, B and C left.
> # Raft group was narrowed in force manner to [A], and after that node B
> returned, we must enhance stable to [A, B]
> # In terms of DZ.scale up, there wasn't any change in DZ.scale up time
> window, so data nodes will be the same, so it could mean that we don’t need
> to schedule new rebalance to enhance stable assignment to [A, B], but we
> actually do need. (Note that DZ.scale down timer is quite big and wasn’t
> event passed)
> Proposed enhancements
> # Data nodes are rewritten on scale up even if they are the same
> # When we decide if we need to trigger rebalance after data nodes change, we
> calculate assignments and apply nodes aliveness check filter to those
> assignments. If we see that the actual stablePartAssignmentsKey differs from
> the filtered one, we schedule rebalance.
> # In our example, calculated assignments will be [A, B, C], we will filter
> them to [A,B] and schedule new rebalance to enhance stablePartAssignmentsKey
> h3. Definition of done
> * Corresponding approach must be implemented, so nodes that returned back
> after majority loss could be returned back to stable
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