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The specific upgrade path is described below. Note that this will be different depending on whether you have a plain consumer app or a Streams app, and make sure to follow the appropriate one.
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From the user's perspective, the upgrade path of leveraging new protocols is just the same as switching to a new assignor. For example, assuming the current version of Kafka consumer is 2.2 and "range" assignor is specified in the config. The upgrade path would be:
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The key point behind this two rolling bounce is that, we want to avoid the situation where leader is on old byte-code and only recognize "eager", but due to compatibility would still be able to deserialize the new protocol data from newer versioned members, and hence just go ahead and do the assignment while new versioned members did not revoke their partitions before joining the group. Note the difference with KIP-415 here: since on consumer we do not have the luxury to leverage on list of built-in assignors since it is user-customizable and hence would be black box to the consumer coordinator, we'd need two rolling bounces instead of one rolling bounce to complete the upgrade, whereas Connect only need one rolling bounce.
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These changes should all be fairly transparent to Streams apps, as there are no semantics only improved rebalancing performance. However, users using Interactive Queries (IQ) or implementing a StateListener will notice that Streams spends less time in the REBALANCING state, as we will not transition to that until the end of the rebalance. This means all owned stores will remain open for IQ while the rebalance is in progress, and Streams will continue to restore active tasks if there are any that are not yet running, and will process standbys if there aren't.
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Allow Consumer to Return Records in Rebalance
As summarized in
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a further optimization would be to allow consumers to still return messages
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belong to its owned partitions even when it is within a rebalance.
In order to do this, we'd need to allow the consumer#commit API to throw RebalanceInProgressException if it is committing offset while a rebalance is undergoing.
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/** * ... * * @throws org.apache.kafka.common.errors.RebalanceInProgressException if the consumer instance is in the middle of a rebalance * so it is not yet determined which partitions would be assigned to the consumer. In such cases you can first * complete the rebalance by calling {@link #poll(Duration)} and commit can be reconsidered afterwards. * NOTE when you reconsider committing after the rebalance, the assigned partitions may have changed, * and also for those partitions that are still assigned their fetch positions may have changed too * if more records are returned from the {@link #poll(Duration)} call. * ... */ @Override public void commitSync() { commitSync(Duration.ofMillis(defaultApiTimeoutMs)); } |
With this optimization (implemented in 2.5.0) consumer groups can continue to process some records even while a rebalance is in progress. This means that in addition to processing standby and restoring tasks during a rebalance, Streams apps will be able to make progress on running active tasks.
Looking into the Future: Heartbeat Communicated Protocol
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