Kafka - Rewind Consumer Offsets

January 31, 2017

Reading time ~9 minutes

One of the most important features from Apache Kafka is how it manages Multiple Consumers. Each consumer group has a current offset, that determine at what point in a topic this consumer group has consume messages. So, each consumer group can manage its offset independently, by partition.

This offers the possibility to rollback in time and reprocess messages from the beginning of a topic and regenerate the current status of the system.

But how to do it (programmatically)?


Source code: https://github.com/jeqo/post-kafka-rewind-consumer-offset **

Basic Concepts

Topics and Offsets

First thing to understand to achieve Consumer Rewind, is: rewind over what? Because topics are divided into partitions. Records sent from Producers are balanced between them, so each partition has its own offset index.

Each record has its own offset that will be used by consumers to define which messages has been consumed from the log.

Consumers and Consumer Groups

Once we understand that topics have partitions and offsets by partition we can now understand how consumers and consumer groups work.

Consumers are grouped by group.id. This property identify you as a consumer group, so the broker knows which was the last record you have consumed by offset, by partition.

This partitions allows parallelism, because members from a consumer group can consume records from partitions independently, in parallel.

Before continue, let’s check a simple Kafka Producer implemented with Java:

KafkaSimpleProducer.java:

public static void main(String[] args) {
    ...
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

    Producer<String, String> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 100)
            .boxed()
            .map(number -> new ProducerRecord<>(
                    "topic-1",
                    number.toString(),
                    number.toString()))
            .map(record -> producer.send(record))
            .forEach(result -> printMetadata(result));
    producer.close();
}

This will create 100 records in topic topic-1, with offsets from 0-99

From Command-Line

In this first scenario, we will see how to manage offsets from command-line so it will give us an idea of how to implement it in our application.

When you’re working from the terminal, you can use kafka-console-consumer without group.id, a new group.id is generated using: console-consumer-${new Random().nextInt(100000)}. So unless you use the same group.id afterwards, it would be as you create a new consumer group each time.

By default, when you connect to a topic as a consumer, you go to the latest offset, so you won’t see any new message until new records arrive after you connect.

In this case, going back to the beginning of the topic will as easy as add --from-beginning option to the command line:

But, what happen if you use group.id property, it will only work the first time, but offset gets commited to cluster:

So, how to go back to the beginning?

We can use --offset option to with three alternatives:

--offset <String: consume offset>        The offset id to consume from (a non-  
                                           negative number), or 'earliest'      
                                           which means from beginning, or       
                                           'latest' which means from end        
                                           (default: latest)

From Java Clients

So, from command-line is pretty easy to go back in time in the log. But how to do it from your application?

If you’re using Kafka Consumers in your applications, you have to options (with Java):

Long story short: If you need stateful and stream processing capabilities, go with Kafka Streams. If you need simple one-by-one consumption of messages by topics, go with Kafka Consumer.

At this moment this are the options to rewind offsets with these APIs:

  • Kafka Consumer API support go back to the beginning of the topic, go back to a specific offset, and go back to a specific offset by timestamps.

  • Kafka Streams API only support to go back to the earliest offset of the input topics, and is well explained by Matthias J. Sax in his post [1].

So I will focus in options available in Kafka Consumer.

A simple Consumer will look something like this:

public static void main(String[] args) {
    Properties props = new Properties();
    props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    props.put(ConsumerConfig.GROUP_ID_CONFIG, "test");
    props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true");
    props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");
    props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer");

    KafkaConsumer<String, String> consumer = new KafkaConsumer<>(props);
    consumer.subscribe(Arrays.asList("topic-1"));

    while (true) {
        ConsumerRecords<String, String> records = consumer.poll(100);

        for (ConsumerRecord<String, String> record : records)
            System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
    }
}

This will poll by 100ms for records and print them out. In this case it should print 100 records.

Now let’s check how to rewind offsets in different scenarios. Consumer API has add #seek operations to achieve this behavior. I will show a naive way to use these operations using flags but it shows the point:

Rewind to earliest offset

The most common options is to go back to the beginning of the topic, that not always will be offset=0. This will depends on the retention policy option that will be clean up old records based on time or size; but this also deserves its own post.

To go to the beginning we can use #seekToBeginning(topicPartition) operation to go back to earliest offset:

boolean flag = true;

while (true) {
    ConsumerRecords<String, String> records = consumer.poll(100);

    if (flag) {
        consumer.seekToBeginning(
            Stream.of(new TopicPartition("topic-1", 0)).collect(toList()));
        flag = false;
    }

    for (ConsumerRecord<String, String> record : records)
        //Consume record
}

Once the seek to beginnning is done, it will reprocess all records from topic=topic-1 and partition=0.

Rewind to specific offset

If we can recognized the specific record (by partition) from where we need to reprocess all the log, we can use #seek(topicPartition, offset) directly.

boolean flag = true;

while (true) {
    ConsumerRecords<String, String> records = consumer.poll(100);

    if(flag) {
        consumer.seek(new TopicPartition("topic-1", 0), 90);
        flag = false;
    }

    for (ConsumerRecord<String, String> record : records)
        System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
}

In this case, we will consume from record with offset=90from topic=topic-1 and partition=0.


NOTE: It could be cumbersome to map all offsets in case that you have several partitions. Thats why addition of timestamps helps a lot with this. ***

Rewind to offset by timestamps

What if you don’t know exactly the offset id to go back to, but you know you want to go back 1 hour or 10 min?

For these, since release 0.10.1.0, there are a couple of improvements [2] [3] were added and a new operation was added to Kafka Consumer API: #offsetsForTimes.

Here is how to use it:

boolean flag = true;

while (true) {
    ConsumerRecords<String, String> records = consumer.poll(100);

    if(flag) {
        Map<TopicPartition, Long> query = new HashMap<>();
        query.put(
                new TopicPartition("simple-topic-1", 0),
                Instant.now().minus(10, MINUTES).toEpochMilli());

        Map<TopicPartition, OffsetAndTimestamp> result = consumer.offsetsForTimes(query);

        result.entrySet()
                .stream()
                .forEach(entry -> consumer.seek(entry.getKey(), entry.getValue().offset()));

        flag = false;
    }

    for (ConsumerRecord<String, String> record : records)
        System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
}

In this case, we are using a query first to get the offset inside a timestamp (10 minutes ago) and then using that offset to go back with #seek operation.

As you can see, for each operation I have to define the specific topic partition to go back to, so this can get tricky if you have more than one partition, so I would recommend to use #offsetsForTimes in those cases to get an aligned result and avoid inconsistencies in your consumers.

In the source code, I’ve added the steps to get partitions by topic that will help us to reproduce this steps when you have several topics.


References

  1. https://www.confluent.io/blog/data-reprocessing-with-kafka-streams-resetting-a-streams-application/

  2. https://cwiki.apache.org/confluence/display/KAFKA/KIP-32+-+Add+timestamps+to+Kafka+message

  3. https://cwiki.apache.org/confluence/display/KAFKA/KIP-33+-+Add+a+time+based+log+index

  4. https://cwiki.apache.org/confluence/display/KAFKA/FAQ#FAQ-HowcanIrewindtheoffsetintheconsumer



Published originally here: https://jeqo.github.io/post/2017-01-31-kafka-rewind-consumers-offset/


Jorge is part of the middleware team at Sysco and an Oracle ACE Associate . He has developed business solutions based on Oracle Fusion Middleware technologies since 2010. Also he is certified as SOA Architect and Implementation Specialist at BPM, SOA and WebLogic products.

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