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https://issues.apache.org/jira/browse/HDDS-8494?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated HDDS-8494:
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Labels: pull-request-available (was: )
> Adjust replication queue limits for decommissioning nodes
> ---------------------------------------------------------
>
> Key: HDDS-8494
> URL: https://issues.apache.org/jira/browse/HDDS-8494
> Project: Apache Ozone
> Issue Type: Sub-task
> Components: Ozone Datanode, SCM
> Reporter: Stephen O'Donnell
> Assignee: Attila Doroszlai
> Priority: Major
> Labels: pull-request-available
>
> When a node hosting a Ratis container is decommissioned, there are generally
> 3 sources available for the container replicas. One on the decommissioning
> host, and then 2 others on somewhat random nodes across the cluster. This
> allows the decommissioning load and hence speed of decommission to be shared
> across many more nodes.
> For an EC container, the decommissioning host is likely the only source of
> the replica which needs to be copied and hence the decommission will be
> slower.
> A host which is decommissioning is generally not used for Ratis reads unless
> there are no other nodes available, but it would still be used for EC reads
> to avoid online reconstruction. As decommission progresses on the node, and
> new copies are formed, the read load will decline over time. Furthermore,
> decommissioning nodes are not used for writes, so they should be under less
> load than other cluster nodes.
> Due to the reduced load on a decommissioning host, it is possible to increase
> the number of commands queued on a decommissioning host and also increase the
> size of the executor thread pool to process the commands.
> When a datanode switches to a decommissioning state, it will adjust the size
> of the replication supervisor thread pool higher, and if the node returns to
> the In Service state, it will return to the lower thread pool limit.
> Similarly when scheduling commands, SCM can allocate more commands to the
> decommissioning host, as it should process them more quickly due to the lower
> load and increased threadpool.
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