问题
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.
回答1:
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 heartbeat to ZooKeeper for this period of time it is considered dead and a rebalance will occur.
Hope this helps!
回答2:
Every consumer in a consumer group is assigned one or more topic partitions exclusively, and Rebalance is the re-assignment of partition ownership among consumers.
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.
回答3:
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 partitions after a rebalance has completed. Consumer rebalance is dynamic partition assignment which can handle automatically by Kafka.
A Group Coordinator is one of broker responsible to communicate with consumers to achieve rebalances between consumer.In earlier version Zookeeper stored metadata details but latest version it store on brokers.Consumer coordinator receive heartbeat and polling from all consumers of consumer group so he aware about each consumer heartbeat and manager their offset on partitions.
Group Leader: One of consumer of Consumer Group work as group leader which is chosen by Group coordinator and will responsible for making partition assignment decision on behalf of all consumers in a group.
Rebalance Scenario:
- Consumer Group subscribes to any topics
- A Consumer instance could not able to send heart beat with session.heart.beat time interval.
Consumer long process exceed poll timeout
Consumer of Consumer group through exception
New partition added.
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 leaves a group. The Group Leader receive a list of all active consumer from the Group Coordinator. Group Leader decide partition(s) assigned to each consumer by using PartitionAssigner. Once Group Leader finalize partition assignment it send assignments list to Group Coordinator which send back these information to all consumer. Group only send applicable partitions to their consumer not other consumer assigned partitions. Only Group Leader aware about all consumer and its assigned partitions. After the rebalance is complete, consumers start sending Heartbeat to Group Coordinator that its alive. Consumers send a OffsetFetch request to the Group Coordinator to get last committed offsets for their assigned partitions. Consumers start consuming messaged for newly assigned partition.
State Management
While rebalancing, Group coordinator set its state to Rebalance and wait all consumer to re-join the group.
When the Group start 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 new assigne partition they moved to stable stage.
Static Membership
Thies rebalancing is quite heavy operation as it required to stop all consumer and wait to get 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 consumer state will persist and on Rebalance the same assignment will get apply. It uses new group.instance.id to persist member identity. So even in worst case scenario member id get reshuffle to assigne new partition but still same consumer instance id will get 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:
https://www.confluent.io/blog/kafka-rebalance-protocol-static-membership
https://cwiki.apache.org/confluence/display/KAFKA/KIP-345%3A+Introduce+static+membership+protocol+to+reduce+consumer+rebalances
来源：https://stackoverflow.com/questions/30988002/what-does-rebalancing-mean-in-apache-kafka-context