Kafka offsets

In Apache Kafka, offsets are used to track the progress of a consumer group as it consumes messages from Kafka topics. Each partition of a Kafka topic has its own set of offsets, which indicate the last message that was successfully processed by the consumer group for that partition.

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Kafka offsets serve several important purposes:

1. Guarantees ordering: Kafka guarantees that messages within a partition are delivered in the order they were produced. Kafka offsets allow consumers to process messages in order, even if they are processed by different instances of the same consumer group.
2. Enables fault-tolerance: Kafka offsets allow consumers to recover from failures and continue processing messages from where they left off. When a consumer fails, another consumer instance can take over processing messages from the last committed offset, ensuring that no messages are lost.
3. Provides replayability: Kafka offsets allow consumers to replay messages from any point in time. By resetting the offset to an earlier point in time, consumers can reprocess messages that were previously processed or were missed due to failures.
4. Enables scalability: Kafka offsets allow multiple instances of a consumer group to process messages from the same Kafka topic in parallel. Each instance of the consumer group is assigned a subset of partitions to process, and Kafka offsets to ensure that each instance processes a unique set of messages.

To use Kafka offsets, consumers can either manually manage offsets by calling the KafkaConsumer.commitSync() or KafkaConsumer.commitAsync() methods to commit offsets to Kafka, or use the automatic offset management feature in Kafka.

Automatic offset management is enabled by default in Kafka and allows Kafka to manage offsets on behalf of consumers. When a consumer reads messages from Kafka, it periodically commits the last processed offset to Kafka using a background thread. This ensures that the consumer group always picks up where it left off, even if a consumer instance fails.

Piggybacking in Kafka offsets

In Kafka, piggybacking refers to the practice of adding extra information to a Kafka message that is unrelated to the primary purpose of the message. One example of piggybacking in Kafka is adding additional metadata to Kafka offsets.

Kafka offsets are used to track the progress of a consumer group as it consumes messages from Kafka topics. Each partition of a Kafka topic has its own set of offsets, which indicate the last message that was successfully processed by the consumer group for that partition.

In some cases, it can be useful to add additional metadata to the Kafka offsets. For example, you might want to add information about the consumer group that processed the message, the timestamp when the message was processed, or any custom metadata that is relevant to your use case.

To piggyback additional metadata onto Kafka offsets, you can use a technique called offset metadata. Offset metadata is a field in the Kafka offset that can be used to store any additional information that is relevant to your use case. You can set the offset metadata field when committing offsets using the KafkaConsumer.commitSync() or KafkaConsumer.commitAsync() methods.

Here is an example of how to piggyback metadata onto Kafka offsets using offset metadata:

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

// Subscribe to a Kafka topic
consumer.subscribe(Collections.singletonList("my-topic"));

while (true) {
  // Poll for new Kafka messages
  ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));

  for (ConsumerRecord<String, String> record : records) {
    // Process the Kafka message
    processRecord(record);

    // Commit the Kafka offset with metadata
    Map<TopicPartition, OffsetAndMetadata> offsets = new HashMap<>();
    offsets.put(new TopicPartition(record.topic(), record.partition()), new OffsetAndMetadata(record.offset(), "my-custom-metadata"));
    consumer.commitSync(offsets);
  }
}

In this example, the consumer reads messages from a Kafka topic and processes each message using the processRecord() method. After processing each message, the consumer commits the offset with the additional metadata "my-custom-metadata" using the commitSync() method.

By piggybacking metadata onto Kafka offsets, you can add additional information to Kafka messages without having to modify the message payload itself. This can be useful for tracking the progress of a consumer group or adding custom metadata to Kafka offsets.

Overall, Kafka offsets are a critical component of building reliable and scalable event-driven systems with Kafka. By using offsets to track the progress of a consumer group, you can guarantee ordering, enable fault-tolerance, provide replayability, and enable scalability.

References

Inbuilt Consumer Offset Management

https://www.conduktor.io/kafka/kafka-consumer-groups-and-consumer-offsets/