When working with Apache Kafka, it is common to use consumer groups to achieve parallel processing of messages from Kafka topics. Consumer groups enable multiple consumers to work together as a group and distribute the load of reading messages from topics.

What is a Kafka Topic Group?

A Kafka topic group refers to a group of consumers that work collectively to process messages from a specific Kafka topic. Each consumer within the group is assigned a subset of the partitions of the topic, allowing them to process messages in parallel.

Consumer Group Concepts

To understand Kafka topic groups, it is important to familiarize yourself with a few key concepts related to consumer groups:

1. Consumer: A consumer is an application or service that reads messages from Kafka topics. Each consumer belongs to a consumer group and is responsible for consuming messages from one or more topic partitions.

2. Consumer Group: A consumer group is a logical entity that consists of multiple consumers. Each consumer within the group is assigned to a subset of the partitions of the topic being consumed.

3. Partition: A topic in Kafka is divided into multiple partitions, which allows for parallel processing of messages. Each partition is ordered and can be consumed by only one consumer within a consumer group at a time.

4. Offset: An offset is a unique identifier that determines the position of a message within a partition. Each consumer group keeps track of the offset for each partition it is consuming, allowing for reliable message processing.

Creating a Kafka Topic Group

To create a Kafka topic group and start consuming messages from a topic, you need to take the following steps:

1. Create a Consumer Group: Define a unique identifier for your consumer group, which will be used by consumers to join the group. This identifier can be any string.

2. Assign Topics to Consumer Group: Specify the topics that the consumer group will consume messages from. Each consumer within the group will be assigned a subset of the partitions of these topics.

3. Start Consumers: Start one or more consumers using the consumer group identifier. Each consumer will be responsible for consuming messages from its assigned partitions.

Example Code in Java

Here is an example code snippet in Java that shows how to create a Kafka topic group using the KafkaConsumer API:

import org.apache.kafka.clients.consumer.KafkaConsumer;
import java.util.Properties;

public class KafkaTopicGroupExample {
    public static void main(String[] args) {
        // Configure consumer properties
        Properties props = new Properties();
        props.setProperty("bootstrap.servers", "localhost:9092");
        props.setProperty("group.id", "my-consumer-group");
        props.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

        // Create a Kafka consumer
        KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);

        // Subscribe to topics
        consumer.subscribe(Arrays.asList("my-topic"));

        // Start consuming messages
        while (true) {
            consumer.poll(100).forEach(record -> {
                System.out.println("Received message: " + record.value());
            });
        }
    }
}

Conclusion

Kafka topic groups with consumer groups provide an efficient way to process messages from Kafka topics in parallel. By assigning partitions to consumers within a group, you can achieve high throughput and scale your message processing capabilities.