In Apache Kafka, a consumer is a crucial component that reads messages from a topic. By default, Kafka is designed to handle high throughput, meaning that a consumer typically reads batches of messages. However, there are scenarios where an application might need to process messages one at a time. This can be particularly useful in cases where each message requires significant processing time or when message ordering is critical.

Understanding the Consumer Configuration

To configure a Kafka Consumer to read a single message at a time, you'll need to adjust several properties in the consumer configuration:

1. max.poll.records: This setting controls the maximum number of records the consumer will fetch in one call to poll(). Setting this to 1 ensures that the consumer fetches one message at a time.
2. fetch.min.bytes: This property sets the minimum amount of data that the broker should return for a fetch request. If set to 1, the broker responds as soon as it has at least one byte of data or the fetch.wait.max.ms is reached.
3. fetch.max.wait.ms: This setting specifies the maximum amount of time the broker will wait before responding to a fetch request if there isn’t sufficient data to meet the fetch.min.bytes requirement.

Example Configuration in Java

Here is how you might set up a Kafka consumer in Java to read one message at a time:

1Properties props = new Properties();
2props.put("bootstrap.servers", "localhost:9092");
3props.put("group.id", "test");
4props.put("enable.auto.commit", "false");
5props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
6props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
7props.put("max.poll.records", "1");
8props.put("fetch.min.bytes", "1");
9props.put("fetch.max.wait.ms", "500");
10
11KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);

Consuming Messages

After configuring the consumer, the next step is to subscribe to the topic and start consuming messages:

1consumer.subscribe(Arrays.asList("topic_name"));
2
3while (true) {
4    ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(1000));
5    for (ConsumerRecord<String, String> record : records) {
6        System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
7        // Process each record
8    }
9    consumer.commitSync(); // commits the offset of record to Kafka
10}

In this loop, the consumer reads messages one at a time, processes them, and commits the offset right after each message is processed. This approach ensures that each message is processed individually.

Trade-offs

There are several benefits of consuming one message at a time, including:

• Fine-grained Processing: Allows detailed processing logic to be applied to each message.
• Simpler Error Handling: Easier to manage and recover from errors when messages are processed individually.

However, this method also comes with drawbacks:

• Lower Throughput: Consuming messages one-by-one can significantly reduce the consumer's throughput.
• Increased Latency: More round trips to the server can increase latency.

Summary Table

Conclusion

Configuring a Kafka consumer to read single messages at a time can be beneficial for specific use cases, particularly those involving complex processing or strict ordering requirements. While this setup ensures meticulous message handling, it also poses challenges such as reduced throughput and potential increase in latency. It's essential to weigh the benefits against the drawbacks and consider the specific needs of your application when deciding how to consume messages from Kafka.