Hi all,
I have question about kafka-streams, particularly in-memory state-store
(/org.apache.kafka.streams.state.internals.InMemoryKeyValueStore/).
I believe that topology is irrelevant here, but let's say I have one
source topic with single partition
feeding data into one statefull processor associated to single in-memory
state store.
This results in topology with single task.
This topology is run in 2 application instances:
- First instance (A) runs the task in active mode
- Second instance (B) runs the task as standby
Our use-case is low-latency processing, hence we need to keep rebalance
downtime as low as possible (ideally few hundreds milliseconds).
Let's say that we kill instance A, which triggers rebalance and B takes
over the processing.
We found that, when task on B transitions from STANDBY into ACTIVE mode,
it closes in-memory state-store and effectively throws
away any state read from changelog while it was in STANDBY. No
checkpoints nor state is preserved.
Subsequently in ACTIVE mode, it reads again changelog with
restore-consumer. Depending on the size of the changelog this operation
can take few minutes during which no processing is done. This happens
despite of B having up-to-date standby-replica,
which is really counterintuitive. What is the reason for this behavior ?
Note that we initially used persistent RocksDB state-store, but we had
simillar issues with latency (only this time it was due to RocksDB
compaction I believe), so we prefer in-memory solution.
If this question is more appropriate for developer mailing list, please
let me know.
Thanks and Regards,
Igor
