Published August 2023
We often get asked: “Can a Kafka consumer listen to multiple topics?” The short answer is: Yes, a Kafka consumer can listen to (or subscribe to) multiple topics.
In this post we discuss examples where consumers would listen to multiple topics versus only one. And we address concerns about potential impacts on Kafka’s performance and hardware requirements.
For more context, check out our previous post on the limit to how many topics a Kafka implementation can support.
Understanding Kafka Consumers
A Kafka consumer is any application or process that processes data from Kafka topics. Consumers subscribe to topics, and Kafka ensures that each message within a topic is delivered to all subscribed consumers in a scalable and parallel manner.
Check out our posts about Kafka Consumer Groups and Kafka Topics for additional context.
Can a Kafka Consumer Listen to Multiple Topics?
Yes, a Kafka consumer can listen to (and subscribe to) more than one topic. This capability is one of Kafka’s strengths, making it incredibly versatile in various use cases. Read about various Kafka use cases here.
When designing your Kafka-based data architecture, the ability for consumers to listen to multiple topics becomes an invaluable asset.
Examples of Subscribing to Multiple Topics
Data Aggregation and Analytics.
Let’s start with the example of a data analytics platform. This platform analyzes data from many sources. Some example data sources are website clicks, user interactions, and social media feeds.
These sources get split amongst topics. The architecture can either:
- use separate consumers for each topic
- use a consolidated consumer that listens to multiple topics
Either approach can work. However, using a consolidated consumer simplifies the data processing pipeline and reduces overhead.
Microservices Communication.
Let’s next consider a microservice architecture. In a microservices architecture, different services communicate through Kafka to exchange information.
Each microservice might be responsible for specific functionalities. In that case they might need to subscribe to multiple topics to access relevant data. By doing so, microservices remain loosely coupled, facilitating scalability and maintainability.
Below is an example code snippet for a consumer subscribing to multiple topics.
import org.apache.kafka.clients.consumer.*;
import java.util.Arrays;
public class MicroserviceConsumer {
public static void main(String[] args) {
Properties properties = new Properties();
properties.put("bootstrap.servers", "kafka-broker:9092");
properties.put("group.id", "microservice_group");
properties.put("enable.auto.commit", "true");
properties.put("auto.commit.interval.ms", "1000");
properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(properties);
consumer.subscribe(Arrays.asList("orders", "inventory", "payments"));
while (true) {
ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
for (ConsumerRecord<String, String> record : records) {
// Process the record data here
processRecord(record);
}
}
}
}
Subscribing to Multiple Topics: Impact on Kafka and Hardware
Does having consumers listen to multiple topics slow down Kafka’s performance? Yes, there is an impact, and it is manageable with proper design and configuration.
When consumers listen to multiple topics, they may generate a higher load on the Kafka cluster. This is especially true if the topics have high message rates.
This additional load can be addressed by adding brokers, optimizing consumer groups, and adding hardware.
- Kafka is horizontally scalable. Horizontal scalability refers to the ability to add more brokers to the cluster. This structure helps in accommodating higher workloads.
- Optimizing the consumer group and Kafka brokers can further improve performance. Learn about Kafka broker optimization.
- The need for extra hardware will depend on the number of consumers and message throughput. Establishing effective monitoring will help determine hardware needs. Read about setting up Kafka monitoring with open source tools here.
Consumers Subscribing to Multiple Kafka Topics
A Kafka consumer can subscribe to multiple topics. This structure offers flexibility and efficiency in various use cases.
Listening to multiple topics may impact Kafka’s performance. These challenges can be addressed with proper cluster configuration and by adding hardware.
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