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https://issues.apache.org/jira/browse/SOLR-15588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Megan Carey updated SOLR-15588:
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Description:
This is a stopgap replica placement strategy that randomly selects a node in
the cluster (as long as no other replicas of that shard already live on that
node), to be made available in 8x for users that need a performant option until
they can upgrade to 9.0.
This has proven to be a valuable strategy for my use case, as it allows for
really fast replica placement (-> fast collection creation, fast rebalancing,
etc.), but it does not explicitly respect Autoscaling policies, so should be
used wisely.
was:
While this might be particularly interesting to users of 8x, it can also be
made available in 9+: a replica placement strategy that randomly selects a node
in the cluster (as long as no other replicas of that shard already live on that
node).
This has proven to be a valuable strategy for my use case, as it allows for
really fast replica placement (-> fast collection creation, fast rebalancing,
etc.), but it does not explicitly respect Autoscaling policies, so should be
used wisely.
> Implement random replica placement strategy
> -------------------------------------------
>
> Key: SOLR-15588
> URL: https://issues.apache.org/jira/browse/SOLR-15588
> Project: Solr
> Issue Type: New Feature
> Security Level: Public(Default Security Level. Issues are Public)
> Components: SolrCloud
> Affects Versions: main (9.0), 8x
> Reporter: Megan Carey
> Priority: Minor
>
> This is a stopgap replica placement strategy that randomly selects a node in
> the cluster (as long as no other replicas of that shard already live on that
> node), to be made available in 8x for users that need a performant option
> until they can upgrade to 9.0.
> This has proven to be a valuable strategy for my use case, as it allows for
> really fast replica placement (-> fast collection creation, fast rebalancing,
> etc.), but it does not explicitly respect Autoscaling policies, so should be
> used wisely.
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