What does "Rebalancing" mean in Apache Kafka context?

I am a new user to Kafka and have been trialling it for about 2-3 weeks now. I believe at the moment I have a good understand of how Kafka works for the most part, but after attempting to fit the API for my own Kafka consumer (this is obscure but I'm following the guidelines for the new KafkaConsumer that is supposed to be available for v 0.9, which is out on the 'trunk' repo atm) I've had latency issues consuming from a topic if I have multiple consumers with the same groupID.

In this setup, my console consistently logs issues regarding a 'rebalance triggering'. Do rebalances occur when I add new consumers to a consumer group and are they triggered in order to figure out which consumer instance in the same groupID will get which partitions or are rebalances used for something else entirely?

I also came across this passage from https://cwiki.apache.org/confluence/display/KAFKA/Kafka+0.9+Consumer+Rewrite+Design and I just can't seem to understand it, so if someone could help me make sense of it that would be much appreciated:

> Rebalancing is the process where a group of consumer instances > (belonging to the same group) co-ordinate to own a mutually exclusive > set of partitions of topics that the group is subscribed to. At the > end of a successful rebalance operation for a consumer group, every > partition for all subscribed topics will be owned by a single consumer > instance within the group. The way rebalancing works is as follows. > Every broker is elected as the coordinator for a subset of the > consumer groups. The co-ordinator broker for a group is responsible > for orchestrating a rebalance operation on consumer group membership > changes or partition changes for the subscribed topics. It is also > responsible for communicating the resulting partition ownership > configuration to all consumers of the group undergoing a rebalance > operation.

When a new consumer joins a consumer group the set of consumers attempt to "rebalance" the load to assign partitions to each consumer. If the set of consumers changes while this assignment is taking place the rebalance will fail and retry. This setting controls the maximum number of attempts before giving up.

the command for this is: rebalance.max.retries and is set to 4 by default.

also, it might be happening if the following is true:

ZooKeeper session timeout. If the consumer fails to send a heartbeat to ZooKeeper for this period of time it is considered dead and a rebalance will occur.

Hope this helps!

Rebalance is the re-assignment of partition ownership among consumers within a given consumer group. Remember that every consumer in a consumer group is assigned one or more topic partitions exclusively.

A Rebalance happens when:

• a consumer JOINS the group
• a consumer SHUTS DOWN cleanly
• a consumer is considered DEAD by the group coordinator. This may happen after a crash or when the consumer is busy with a long-running processing, which means that no heartbeats has been sent in the meanwhile by the consumer to the group coordinator within the configured session interval
• new partitions are added

Being a group coordinator (one of the brokers in the cluster) and a group leader (the first consumer that joins a group) designated for a consumer group, Rebalance can be more or less described as follows:

• the leader receives a list of all consumers in the group from the group coordinator (this will include all consumers that sent a heartbeat recently and which are therefore considered alive) and is responsible for assigning a subset of partitions to each consumer.
• After deciding on the partition assignment (Kafka has a couple built-in partition assignment policies), the group leader sends the list of assignments to the group coordinator, which sends this information to all the consumers.

This applies to Kafka 0.9, but I'm quite sure for newer versions is still valid.

Consumer rebalance decide which consumer is responsible for which subset of all available partitions for some topic(s). For example, you might have a topic with 20 partitions and 10 consumers; at the end of a rebalance, you might expect each consumer to be reading from 2 partitions. If you shut down 10 of those consumers, you might expect each consumer to have 1 partition after a rebalance has completed. Consumer rebalance is a dynamic partition assignment that can handle automatically by Kafka.

A Group Coordinator is one of the brokers responsible to communicate with consumers to achieve rebalances between consumers.In earlier version Zookeeper stored metadata details but the latest version, it stores on brokers. The consumer coordinators receive heartbeat and polling from all consumers of the consumer groups so be aware of each consumer's heartbeat and manager their offset on partitions.

Group Leader: One of a consumer Group work as group leader which is chosen by the Group coordinator and will responsible for making partition assignment decision on behalf of all consumers in a group.

Rebalance Scenario:

1. Consumer Group subscribes to any topics

2. A Consumer instance could not able to send a heartbeat with a session.heart.beat time interval.

3. Consumer long process exceeds the poll timeout

4. Consumer of Consumer group through exception

5. New partition added.

6. Scaling Up and Down consumer. Added new consumer or remove existing consumer manually for

Consumer Rebalance

Consumer rebalance initiated when consumer requests to join a group or leave a group. The Group Leader receives a list of all active consumers from the Group Coordinator. Group Leader decides partition(s) assigned to each consumer by using PartitionAssigner. Once Group Leader finalize partition assignment it sends assignments list to Group Coordinator which send back this information to all consumer. Group only sends applicable partitions to their consumer not other consumer assigned partitions. Only the Group Leader aware of all consumers and their assigned partitions. After the rebalance is complete, consumers start sending Heartbeat to the Group Coordinator that it's alive. Consumers send an OffsetFetch request to the Group Coordinator to get the last committed offsets for their assigned partitions. Consumers start consuming messaged for newly assigned partition.

State Management

While rebalancing, the Group coordinator set its state to Rebalance and wait for all consumers to re-join the group.

When the Group starts rebalancing, the group coordinator first switches its state to rebalance so that all interacting consumers are notified to rejoin the group. Once rebalance completed Group coordinator create new generation ID and notified to all consumers and group proceed to sync stage where consumers send sync request and go to wait until group Leader finish generating new assign partition. Once consumers received a new assigned partition they moved to a stable stage.

Static Membership

This rebalancing is quite a heavy operation as it required to stop all consumers and wait to get the new assigned partition. On each rebalance always create new generation id means refresh everything. To solve this overhead Kafka 2.3+ introduced Static Membership to reduce unnecessary Rebalance. KIP-345

In Static Membership, the consumer state will persist and on Rebalance the same assignment will get apply. It uses a new group.instance.id to persist member identity. So even in the worst-case scenario member id get reshuffle to assign a new partition but still, the same consumer instance-id will get the same partition assignment

instanceId: A, memberId: 1, assignment: {0, 1, 2}
instanceId: B, memberId: 2, assignment: {3, 4, 5}
instanceId: C, memberId: 3, assignment: {6, 7, 8}

And after the restart:

instanceId: A, memberId: 4, assignment: {0, 1, 2}
instanceId: B, memberId: 2, assignment: {3, 4, 5}
instanceId: C, memberId: 3, assignment: {6, 7, 8}	

Ref:

1. https://www.confluent.io/blog/kafka-rebalance-protocol-static-membership

2. https://cwiki.apache.org/confluence/display/KAFKA/KIP-345%3A+Introduce+static+membership+protocol+to+reduce+consumer+rebalances

Consumer Group, Consumer and Partition Rebalance Kafka Consumer can consume/Subscribe to multiple topics and start receiving the messages. Kafka Consumer are typically part of consumer group. When multiple consumers are subscribed to a topic and belong to same consumer group, each consumer in the group will receive messages from a different subset of partitions in the topic.

So consumers in a consumer group share ownership of the partitions in the topics they subscribe to. When we add a new consumer to the group, it starts consuming messages from partitions previously consumed by another consumer. The same thing happen when a consumer shuts down or crashes; it leaves the group, and the partition it used to consume will be consumed by one of the remaining consumers. Reassignment of partitions to consumer also happen when the consumer group is consuming are modified like new partition are added.

"Moving partition ownership from one consumer to another is called rebalance" During a rebalance, consumers can not consumer messages so we can say that rebalance is a short window of unavailability to entire consumer group. It also leads to some other activity on consumer side like when partitions are moved from one consumer t another consumer , cosnumer lose its current state like if any data is cache then it need to refresh its cache , slowing down the overall application until consumer is setup its state again.

heartbeat.interval.ms

Consumer maintain membership in a consumer group and ownership of the partitions assigned to them is by sending heartbeats to Kafka broker designated as a group coordinator and it will be different for different consumer group. As long as consumer is sending heartbeat at a regular intervals then it is considered t be alive and continue processing messages from designated assigned partition Heartbeat are sent when consumer call the poll method ( to retrieve records from partition) and when it commit the records it has consumed.

If a consumer stop sending heartbeat for long time and its session will time out (controlled by session.timeout.ms) then group coordinator will consider it dead and as a result trigger a rebalance. If a consumer crashed and are not processing messages it will take group coordinator few seconds without heartbeat to decide it is dead and trigger rebalance. When closing a consumer cleanly , consumer will notify the group coordinator that it is leaving the group and coordinator will trigger the rebalance immediately , reducing the time of unavailability of messages.