Consuming Messages from Kafka Topics

Apache Kafka is a distributed streaming platform that enables the building of real-time data pipelines and streaming applications. It provides a high-throughput, fault-tolerant, and scalable messaging system for handling large volumes of data.

In this article, we will discuss how to consume messages from Kafka topics using various programming languages and frameworks.

Kafka Consumer API

Kafka provides a powerful and flexible Consumer API for consuming messages from Kafka topics. The Consumer API allows developers to read data from Kafka in a pull-based fashion, where consumers actively fetch messages from the Kafka broker.

To consume messages from a Kafka topic, you need to follow these steps:

1. Create a configuration object that specifies the Kafka broker's address, the consumer group, and other necessary properties.
2. Create an instance of the KafkaConsumer class, passing the configuration object as a parameter.
3. Use the subscribe method to specify the topic(s) to consume messages from.
4. Start a loop to continuously poll the Kafka broker for new messages.
5. Process each received message and perform any necessary business logic.

Here's an example of consuming messages from a Kafka topic using the Java client:

import org.apache.kafka.clients.consumer.*;

Properties props = new Properties();
props.put("bootstrap.servers", "kafka-server:9092");
props.put("group.id", "my-consumer-group");
props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
consumer.subscribe(Collections.singletonList("my-topic"));

while (true) {
    ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
    for (ConsumerRecord<String, String> record : records) {
        System.out.println("Received message: " + record.value());
        // Process the message here
    }
}

Kafka Connect

Kafka Connect is a feature in Kafka that simplifies the integration of Kafka with external systems. It provides a set of connectors for various data sources and sinks, allowing easy ingestion and egress of data into and out of Kafka.

Kafka Connect provides a high-level abstraction for consuming messages from Kafka topics. You can configure a Kafka Connect source connector to read messages from a Kafka topic and write them to an external system.

To consume messages from Kafka topics using Kafka Connect, you need to follow these steps:

1. Install and configure Kafka Connect on your system.
2. Create and configure a source connector that defines the Kafka topic to consume from and the destination system to write the messages to.
3. Start Kafka Connect and let it handle the consumption of messages from the Kafka topic.

Here's an example of a Kafka Connect source connector configuration file:

name=my-source-connector
connector.class=io.confluent.connect.kafka.KafkaSourceConnector
tasks.max=1
kafka.topic=my-topic
key.converter=org.apache.kafka.connect.storage.StringConverter
value.converter=org.apache.kafka.connect.storage.StringConverter
transforms=MessageTransform
transforms.MessageTransform.type=org.example.custom.transforms.MessageTransform

Conclusion

Consuming messages from Kafka topics is a fundamental task in building real-time data processing systems. It allows applications to receive and process data in a scalable and fault-tolerant manner.

In this article, we explored two approaches to consume messages from Kafka topics: using the Kafka Consumer API and Kafka Connect. Both approaches provide flexible and efficient ways to integrate Kafka with your applications or external systems.

Whether you are writing a custom consumer program or leveraging Kafka Connect's connectors, Kafka provides powerful tools to consume messages from topics and unlock the full potential of real-time data processing.