What is the Consumer Group in Apache Kafka?

In Apache Kafka, consumers can consume data from Kafka topics partitions individually, but for horizontal scalability purposes, it is recommended to consume Kafka topics as a group.

A consumer group is a group of consumers that work together to consume and process messages from one or more topics in parallel. Each consumer group consists of one or more consumer instances, and each consumer instance can consume one or more partitions of a topic.

Kafka Consumer Group ID

In order for indicating to Kafka consumers that they are part of the same specific group, we must specify the consumer-side setting group.id.

It is important to note that each topic partition is only assigned to one consumer within a consumer group, but a consumer from a consumer group can be assigned multiple partitions.

Case I: If there are fewer consumers than the number of partitions of a topic, then some consumers will have multiple partitions.

Case II: If there are more consumers than the number of partitions of a topic, then some consumers will remain inactive as shown below.

Case III: Multiple consumer groups

Benefits of having a consumer group

Consumer groups allow multiple consumers to work together to process messages from a topic. This can help to increase the throughput and performance of the Kafka system.

Consumer groups also provide fault tolerance and high availability. If a consumer instance fails or is shut down, the partitions it was consuming are automatically reassigned to other consumer instances in the same consumer group. This allows the remaining consumers to continue processing messages from the topic without any interruption.

Who manages the consumer group?

In Apache Kafka, the consumer group is managed by the Kafka broker. The partition assignment is handled automatically by the Kafka broker. When a new consumer instance joins a consumer group or an existing consumer instance leaves a consumer group, the broker automatically handles the partition reassignment process using a rebalancing algorithm to ensure that the partitions are evenly distributed among the active consumer instances in the group.

Overall, consumer groups are a powerful feature of Apache Kafka that allows multiple consumers to work together to consume and process messages from a topic in a fault-tolerant and scalable way.

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