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KAFKA-2551; Update Unclean leader election docs 

Author: Manikumar reddy O <manikumar.reddy@gmail.com>

Reviewers: Ismael Juma <ismael@juma.me.uk>, Sriharsha Chintalapani <mail@harsha.io>

Closes #1054 from omkreddy/KAFKA-2551
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Manikumar reddy O 2016-03-13 20:32:47 -07:00 committed by Sriharsha Chintalapani
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@ -240,7 +240,7 @@ However a practical system needs to do something reasonable when all the replica
<li>Choose the first replica (not necessarily in the ISR) that comes back to life as the leader.
</ol>
<p>
This is a simple tradeoff between availability and consistency. If we wait for replicas in the ISR, then we will remain unavailable as long as those replicas are down. If such replicas were destroyed or their data was lost, then we are permanently down. If, on the other hand, a non-in-sync replica comes back to life and we allow it to become leader, then its log becomes the source of truth even though it is not guaranteed to have every committed message. In our current release we choose the second strategy and favor choosing a potentially inconsistent replica when all replicas in the ISR are dead. In the future, we would like to make this configurable to better support use cases where downtime is preferable to inconsistency.
This is a simple tradeoff between availability and consistency. If we wait for replicas in the ISR, then we will remain unavailable as long as those replicas are down. If such replicas were destroyed or their data was lost, then we are permanently down. If, on the other hand, a non-in-sync replica comes back to life and we allow it to become leader, then its log becomes the source of truth even though it is not guaranteed to have every committed message. By default Kafka chooses the second strategy and favor choosing a potentially inconsistent replica when all replicas in the ISR are dead. This behavior can be disabled using configuration property unclean.leader.election.enable, to support use cases where downtime is preferable to inconsistency.
<p>
This dilemma is not specific to Kafka. It exists in any quorum-based scheme. For example in a majority voting scheme, if a majority of servers suffer a permanent failure, then you must either choose to lose 100% of your data or violate consistency by taking what remains on an existing server as your new source of truth.