Consuming-messages.md

Consumers should inherit from the ApplicationConsumer. You need to define a #consume method that will execute your business logic code against a batch of messages.

Karafka fetches and consumes messages in batches by default.

Consuming messages

Karafka framework has a long-running server process responsible for fetching and consuming messages.

To start the Karafka server process, use the following CLI command:

bundle exec karafka server

In batches

Data fetched from Kafka is accessible using the #messages method. The returned object is an enumerable containing received data and additional information that can be useful during the processing.

To access the payload of your messages, you can use the #payload method available for each received message:

class EventsConsumer < ApplicationConsumer
  def consume
    # Print all the payloads one after another
    messages.each do |message|
      puts message.payload
    end
  end
end

You can also access all the payloads together to elevate things like batch DB operations available for some of the ORMs:

class EventsConsumer < ApplicationConsumer
  def consume
    # Insert all the events at once with a single query
    Event.insert_all messages.payloads
  end
end

One at a time

While we encourage you to process data in batches to elevate in-memory computation and many DBs batch APIs, you may want to process messages one at a time.

You can achieve this by defining a base consumer with such a capability:

class SingleMessageBaseConsumer < Karafka::BaseConsumer
  attr_reader :message

  def consume
    messages.each do |message|
      @message = message
      consume_one
    
      mark_as_consumed(message)
    end
  end
end

class Consumer < SingleMessageBaseConsumer
  def consume_one
    puts "I received following message: #{message.payload}"
  end
end

Accessing topic details

If, in any case, your logic is dependent on some routing details, you can access them from the consumer using the #topic method. You could use it, for example, in case you want to perform a different logic within a single consumer based on the topic from which your messages come:

class UsersConsumer < ApplicationConsumer
  def consume
    send(:"topic_#{topic.name}")
  end

  def topic_a
    # do something
  end

  def topic_b
    # do something else if it's a "b" topic
  end
end

If you're interested in all the details that are stored in the topic, you can extract all of them at once, by using the #to_h method:

class UsersConsumer < ApplicationConsumer
  def consume
    puts topic.to_h #=> { name: 'x', ... }
  end
end

Consuming from earliest or latest offset

Karafka, by default, will start consuming messages from the earliest it can reach. You can, however configure it to start consuming from the latest message by setting the initial_offset value:

# This will start from the earliest (default)
class KarafkaApp < Karafka::App
  setup do |config|
    config.initial_offset = 'earliest'
  end
end

# This will make Karafka start consuming from the latest message on a given topic
class KarafkaApp < Karafka::App
  setup do |config|
    config.initial_offset = 'latest'
  end
end

!!! note ""

This setting applies only to the first execution of a Karafka process. All following executions will pick up from the last offset where the process ended previously.

Detecting revocation midway

When working with a distributed system like Kafka, partitions of a topic can be distributed among different consumers in a consumer group for processing. However, there might be cases where a partition needs to be taken away from a consumer and reassigned to another consumer. This is referred to as a partition revocation.

Partition revocation can be voluntary, where the consumer willingly gives up the partition after it is done processing the current batch, or it can be involuntary. An involuntary partition revocation is typically due to a rebalance triggered by consumer group changes or a failure in the consumer, which causes it to become unresponsive. It is important to remember that involuntary revocations can occur during data processing. You may not want to continue processing messages when you know the partition has been taken away. This is where the #revoked? method is beneficial.

By monitoring the status of the #revoked? method, your application can detect that your process no longer owns a partition you are operating on. In such scenarios, you can choose to stop any ongoing, expensive processing. This can help you save resources and limit the number of potential reprocessings.

def consume
  messages.each do |message|
    Message.create!(message)

    mark_as_consumed(message)

    return if revoked?
  end
end

It is worth, however, keeping in mind that under normal operating conditions, Karafka will complete all ongoing processing before a rebalance occurs. This includes finishing the processing of all messages already fetched. Karafka has built-in mechanisms to handle voluntary partition revocations and rebalances, ensuring that no messages are lost or unprocessed during such events. Hence #revoked? is especially useful for involuntary revocations.

In most cases, especially if you do not use Long-Running Jobs, the Karafka default offset management strategy should be more than enough. It ensures that after batch processing as well as upon rebalances, before partition reassignment, all the offsets are committed. In a healthy system with stable deployment procedures and without frequent short-lived consumer generations, the number of re-processings should be close to zero.

!!! note ""

You do **not** need to mark the message as consumed for the `#revoked?` method result to change.

!!! note ""

When using the [Long-Running Jobs](Pro-Long-Running-Jobs) feature, `#revoked?` result also changes independently from marking messages.

Consumer persistence

Karafka consumer instances are persistent by default. This means that a single consumer instance will "live" as long as a given process instance consumes a given topic partition. This means you can elevate in-memory processing and buffering to achieve better performance.

Karafka consumer instance for a given topic partition will be re-created in case a given partition is lost and re-assigned.

!!! note ""

If you decide to utilize such techniques, you may be better with manual offset management.

# A consumer that will buffer messages in memory until it reaches 1000 of them. Then it will flush
# and commit the offset.
class EventsConsumer < ApplicationConsumer
  # Flush every 1000 messages
  MAX_BUFFER_SIZE = 1_000

  def initialize
    @buffer = []
  end

  def consume
    # Print all the payloads one after another
    @buffer += messages.payloads

    return if @buffer.size < MAX_BUFFER_SIZE

    flush
  end

  private

  def flush
    Event.insert_all @buffer

    mark_as_consumed @buffer.last

    @buffer.clear!
  end
end

Shutdown and partition revocation handlers

Karafka consumer, aside from the #consume method, allows you to define two additional methods that you can use to free any resources that you may be using upon certain events. Those are:

• #revoked - will be executed when there is a rebalance resulting in the given partition being revoked from the current process.
• #shutdown - will be executed when the Karafka process is being shutdown.

class LogsConsumer < ApplicationConsumer
  def initialize
    @log = File.open('log.txt', 'a')
  end

  def consume
    messages.each do |message|
      @log << message.raw_payload
    end
  end

  def shutdown
    @log.close
  end

  def revoked
    @log.close
  end
end

Please note that when using #shutdown with the filtering API or Delayed Topics, there are scenarios where #shutdown and #revoked may be invoked without prior #consume running and the #messages batch may be empty.

Inline API based consumption

Karafka Pro provides the Iterator API that allows you to subscribe to topics and to perform lookups from Rake tasks, custom scripts, Rails console, or any other Ruby processes.

# Note: you still need to configure your settings using `karafka.rb`

# Select all the events of user with id 5 from last 10 000 messages of
# each partition of the topic `users_events`

user_5_events = []

iterator = ::Karafka::Pro::Iterator.new(
  { 'users_events' => -1000 }
)

iterator.each do |message|
  # Cast to integer because headers are always string
  next unless message.headers['user-id'].to_i == 5

  user_5_events << message
end

puts "There were #{user_5_events.count} messages"

You can read more about it here.