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https://issues.apache.org/jira/browse/CASSANDRA-8494?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14264714#comment-14264714
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T Jake Luciani commented on CASSANDRA-8494:
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I'm not suggesting we change the ring early, just that we include pending 
ranges when we do read requests.  But you are right, if node A proxies to 
joining node B how do we keep B from sending back to A. 

Perhaps we can have B broadcast gossip the ranges it's completed and A would 
only send to B when it sees there is data for that range.

If B dies along the way everything was still pending so nothing bad happens.

> incremental bootstrap
> ---------------------
>
>                 Key: CASSANDRA-8494
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-8494
>             Project: Cassandra
>          Issue Type: New Feature
>          Components: Core
>            Reporter: Jon Haddad
>            Assignee: Yuki Morishita
>            Priority: Minor
>              Labels: density
>             Fix For: 3.0
>
>
> Current bootstrapping involves (to my knowledge) picking tokens and streaming 
> data before the node is available for requests.  This can be problematic with 
> "fat nodes", since it may require 20TB of data to be streamed over before the 
> machine can be useful.  This can result in a massive window of time before 
> the machine can do anything useful.
> As a potential approach to mitigate the huge window of time before a node is 
> available, I suggest modifying the bootstrap process to only acquire a single 
> initial token before being marked UP.  This would likely be a configuration 
> parameter "incremental_bootstrap" or something similar.
> After the node is bootstrapped with this one token, it could go into UP 
> state, and could then acquire additional tokens (one or a handful at a time), 
> which would be streamed over while the node is active and serving requests.  
> The benefit here is that with the default 256 tokens a node could become an 
> active part of the cluster with less than 1% of it's final data streamed over.



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