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Status

Current stateUnder DiscussionAccepted

Discussion thread: here

JIRA:

Jira
serverASF JIRA
serverId5aa69414-a9e9-3523-82ec-879b028fb15b
keyKAFKA-9525

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

...

Code Block
languagejava
Consumer {
	   /**
     * Alert the consumer to trigger a new rebalance by rejoining the group. This is a nonblocking call that forces
     * @see KafkaConsumer#enforceRebalance() the consumer to trigger a new rebalance on the next {@link #poll(Duration)} call. Note that this API does not
     */
	void enforceRebalance();
}

KafkaConsumer {
   /**
	* Alert the consumer to trigger a new rebalance by rejoining the group. You should itself initiate the rebalance, so you must still call {@link #poll(Duration)}. If a rebalance is already in
     * progress this call will be a no-op. If you wish to force an additional rebalance you must complete the current
     * one by calling poll before retrying this API.
     * <p>
     * You do not need to call this during normal processing,
	* as the consumer group will manage itself
     * automatically and rebalance when necessary. However there may be situations where 
	* the application wishes to
     * trigger a rebalance that would otherwise not occur,. forFor example, if some condition hasexternal and changedinvisible that
	* has implications for the ideal partition assignment.
	* <p>
	* If a rebalance is already in progress, an exception will be thrown so you can choose to retry or not once the current rebalance completes.
	* 
	* @throws java.lang.IllegalStateException if the consumerto
     * the Consumer and its group changes in a way that would affect the userdata encoded in the
     * {@link org.apache.kafka.clients.consumer.ConsumerPartitionAssignor.Subscription Subscription}, the Consumer
     * will not be notified and no rebalance will occur. This API can be used to force the group to rebalance so that
     * the assignor can perform a partition reassignment based on the latest userdata. If your assignor does not use group subscription

     * this userdata, or you do not use a custom
     * @throws{@link org.apache.kafka.commonclients.errors.RebalanceInProgressException if a rebalance is already in progress
	* @throws org.apache.kafka.common.errors.CoordinatorNotAvailableException if the coordinator is unknown/unavailable
	* @throws org.apache.kafka.common.KafkaException for any other unrecoverable errors (e.g. rebalance callback errors)
	*/ 
	publicconsumer.ConsumerPartitionAssignor ConsumerPartitionAssignor}, you should not
     * use this API.
     *
     * @throws java.lang.IllegalStateException if the consumer does not use group subscription
     */
    void enforceRebalance() {}
}

Proposed Changes

This KIP proposes to add an API that will immediately trigger a rebalance (as in Consumer#unsubscribe) request a rebalance without revoking all currently owned partitions. Both static and dynamic members will attempt to rejoin the group. The intended It is a nonblocking call that does not itself initiate the rebalance (as in consumer.unsubscribe()) but instead just marks the consumer as needing to rejoin. A rebalance will then be triggered on the next poll() call.

The behavior is fairly straightforward overall, but there are some edge cases to consider:

...

Clearly, the behavior of this API in the case on an ongoing rebalance is application-dependent. We should throw a RebalanceInProgressException to alert the user and allow them to choose how to handle this case.However it seems best to leave it up to the user to determine whether or not to retry based on the results of the completed rebalance by checking the assignment received. 

The consumer is not part of an active group

If the consumer is not part of an active group, either because it dropped out or it has not yet joined the group, we should already be attempting to rejoin. Continue on with triggering the rebalance.

The coordinator is unknown/unavailable

...

But if we are not yet in the REBALANCING state (above case), then we have not yet sent out the metadata and so the next rebalance should include whatever update caused the app to want to force a rebalance. In this case we just return "true".

example usage:

Let's say your app has some heavy initialization to do before it is ready to start processing partitions from certain topics (call it topic A), while other topics (topic B) can be processed right away. You want to avoid assigning any of the topic A partitions to a new member until it's ready to work on them, so your assignor will need to include whether the member is initialized or not in the userdata. This way the  assignor can make sure a member that has just joined will only receive partitions from topic B, allowing other members of the group to continue making progress on the partitions of topic A until the newer member is ready for them. In the example processing loop below, each member will check some system condition to determine whether it is ready to receive partitions from topic A and trigger a rebalance if so. By using this new API, in combination with a cooperative assignor, the app can actually continue to poll and process records while the rebalance goes on in the background.

Code Block
languagejava
titleMyApp.java
mainProcessingLoop() {
	if (justCompletedInitialization) {
		needsRebalance = true;
		justCompletedInitialization = false;
	}

	if (needsRebalance) {
		consumer.enforceRebalance() 
	}
	
	records = consumer.poll();

	// check the assignment in case you need to retry, eg if a rebalance was already in progress was enforceRebalance was called
	if (receivedFinalAssignment()) {
		needsRebalance = false;
	}
	...
	// do something
}

Compatibility, Deprecation, and Migration Plan

N/AWe will be adding a new method to the Consumer interface, and as such any new implementations should override this method. No default implementation will be provided so existing Consumer implementations that wish to upgrade should be extended and recompiled.

Rejected Alternatives

Instead of adding this directly to the consumer client, we could have added this to the admin client as in

...

On the one hand, triggering a rebalance seems like an administrative action and thus more appropriate for the admin client than the consumer. However this API is not intended to be an operational one, but instead a way for consumers to proactively communicate with the group and efficiently channel updates relevant to their assignment. I'm also not sure whether this would even be possible to implement without broker-side changes.

Another idea that was debated was whether to make this a blocking call, where the consumer will actually initiate the rebalance (ie send out a JoinGroup) and then potentially wait up to some provided timeout for it to complete. On the surface this seems to offer the simpler approach: the rebalance will be triggered by this single API, and users can choose to wait on the rebalance to complete or fall back to a nonblocking call by setting the timeout to zero. However, the same thing can be achieved by just calling poll afterwards (with whatever timeout). This makes the enforceRebalance API much cleaner and easier to reason about, as all the edge case (eg coordinator unavailable/unknown) and error handling (for example if the rebalance callback throws an error) can remain part of poll, and the user need only worry about whether they want to retry in the case a rebalance was already ongoing. This also keeps the implementation clean, by keeping all actual rebalancing within the scope of poll and just setting a flag to rejoin.

Furthermore, some use cases (such as the current design plan of KIP-441) will involve calling this new API at some regular, periodic basis. For those cases a more straightforward solution might be to simply add a "rebalance.interval" config that allows users to specify some interval at which to automatically trigger periodic rebalances. However this does not fit all use cases: some, such as version probing or a more advanced, heuristic-driven KIP-441 design, require triggering of a rebalance in response to specific system changes. The chosen design is intended to allow users to trigger a reassignment based on conditions external/unknown to the consumer (and not for example as a way to resolve temporary imbalances due to membership changes).