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https://issues.apache.org/jira/browse/KAFKA-6144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17002584#comment-17002584
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ASF GitHub Bot commented on KAFKA-6144:
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vinothchandar commented on pull request #7868: [WIP] KAFKA-6144: Allow state
stores to serve stale reads during rebalance
URL: https://github.com/apache/kafka/pull/7868
KIP-535 Implementation
*Summary of testing strategy*
- [ ] Unit tests for standby metadata
- [ ] Integration test for querying standbys, during rebalance
- [ ] Local testing
- [ ] Unit tests around APIs used for allLocalOffsetLags() API
- [ ] Integration test for lag APIs
### Committer Checklist (excluded from commit message)
- [ ] Verify design and implementation
- [ ] Verify test coverage and CI build status
- [ ] Verify documentation (including upgrade notes)
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> Allow serving interactive queries from in-sync Standbys
> -------------------------------------------------------
>
> Key: KAFKA-6144
> URL: https://issues.apache.org/jira/browse/KAFKA-6144
> Project: Kafka
> Issue Type: New Feature
> Components: streams
> Reporter: Antony Stubbs
> Assignee: Navinder Brar
> Priority: Major
> Labels: kip-535
> Attachments: image-2019-10-09-20-33-37-423.png,
> image-2019-10-09-20-47-38-096.png
>
>
> Currently when expanding the KS cluster, the new node's partitions will be
> unavailable during the rebalance, which for large states can take a very long
> time, or for small state stores even more than a few ms can be a deal-breaker
> for micro service use cases.
> One workaround is to allow stale data to be read from the state stores when
> use case allows. Adding the use case from KAFKA-8994 as it is more
> descriptive.
> "Consider the following scenario in a three node Streams cluster with node A,
> node S and node R, executing a stateful sub-topology/topic group with 1
> partition and `_num.standby.replicas=1_`
> * *t0*: A is the active instance owning the partition, B is the standby that
> keeps replicating the A's state into its local disk, R just routes streams
> IQs to active instance using StreamsMetadata
> * *t1*: IQs pick node R as router, R forwards query to A, A responds back to
> R which reverse forwards back the results.
> * *t2:* Active A instance is killed and rebalance begins. IQs start failing
> to A
> * *t3*: Rebalance assignment happens and standby B is now promoted as active
> instance. IQs continue to fail
> * *t4*: B fully catches up to changelog tail and rewinds offsets to A's last
> commit position, IQs continue to fail
> * *t5*: IQs to R, get routed to B, which is now ready to serve results. IQs
> start succeeding again
>
> Depending on Kafka consumer group session/heartbeat timeouts, step t2,t3 can
> take few seconds (~10 seconds based on defaults values). Depending on how
> laggy the standby B was prior to A being killed, t4 can take few
> seconds-minutes.
> While this behavior favors consistency over availability at all times, the
> long unavailability window might be undesirable for certain classes of
> applications (e.g simple caches or dashboards).
> This issue aims to also expose information about standby B to R, during each
> rebalance such that the queries can be routed by an application to a standby
> to serve stale reads, choosing availability over consistency."
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