Class: Kafka::Consumer

Inherits:
Object
  • Object
show all
Defined in:
lib/kafka/consumer.rb

Overview

A client that consumes messages from a Kafka cluster in coordination with other clients.

A Consumer subscribes to one or more Kafka topics; all consumers with the same *group id* then agree on who should read from the individual topic partitions. When group members join or leave, the group synchronizes, making sure that all partitions are assigned to a single member, and that all members have some partitions to read from.

## Example

A simple producer that simply writes the messages it consumes to the console.

require "kafka"

kafka = Kafka.new(["kafka1:9092", "kafka2:9092"])

# Create a new Consumer instance in the group `my-group`:
consumer = kafka.consumer(group_id: "my-group")

# Subscribe to a Kafka topic:
consumer.subscribe("messages")

# Loop forever, reading in messages from all topics that have been
# subscribed to.
consumer.each_message do |message|
  puts message.topic
  puts message.partition
  puts message.key
  puts message.headers
  puts message.value
  puts message.offset
end

Instance Method Summary collapse

Constructor Details

#initialize(cluster:, logger:, instrumenter:, group:, fetcher:, offset_manager:, session_timeout:, heartbeat:) ⇒ Consumer

Returns a new instance of Consumer.



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# File 'lib/kafka/consumer.rb', line 47

def initialize(cluster:, logger:, instrumenter:, group:, fetcher:, offset_manager:, session_timeout:, heartbeat:)
  @cluster = cluster
  @logger = TaggedLogger.new(logger)
  @instrumenter = instrumenter
  @group = group
  @offset_manager = offset_manager
  @session_timeout = session_timeout
  @fetcher = fetcher
  @heartbeat = heartbeat

  @pauses = Hash.new {|h, k|
    h[k] = Hash.new {|h2, k2|
      h2[k2] = Pause.new
    }
  }

  # Whether or not the consumer is currently consuming messages.
  @running = false

  # Hash containing offsets for each topic and partition that has the
  # automatically_mark_as_processed feature disabled. Offset manager is only active
  # when everything is suppose to happen automatically. Otherwise we need to keep track of the
  # offset manually in memory for all the time
  # The key structure for this equals an array with topic and partition [topic, partition]
  # The value is equal to the offset of the last message we've received
  # @note It won't be updated in case user marks message as processed, because for the case
  #   when user commits message other than last in a batch, this would make ruby-kafka refetch
  #   some already consumed messages
  @current_offsets = Hash.new { |h, k| h[k] = {} }
end

Instance Method Details

#commit_offsetsObject



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# File 'lib/kafka/consumer.rb', line 373

def commit_offsets
  @offset_manager.commit_offsets
end

#each_batch(min_bytes: 1, max_bytes: 10485760, max_wait_time: 1, automatically_mark_as_processed: true) {|batch| ... } ⇒ nil

Fetches and enumerates the messages in the topics that the consumer group subscribes to.

Each batch of messages is yielded to the provided block. If the block returns without raising an exception, the batch will be considered successfully processed. At regular intervals the offset of the most recent successfully processed message batch in each partition will be committed to the Kafka offset store. If the consumer crashes or leaves the group, the group member that is tasked with taking over processing of these partitions will resume at the last committed offsets.

Parameters:

  • min_bytes (Integer) (defaults to: 1)

    the minimum number of bytes to read before returning messages from each broker; if ‘max_wait_time` is reached, this is ignored.

  • max_bytes (Integer) (defaults to: 10485760)

    the maximum number of bytes to read before returning messages from each broker.

  • max_wait_time (Integer, Float) (defaults to: 1)

    the maximum duration of time to wait before returning messages from each broker, in seconds.

  • automatically_mark_as_processed (Boolean) (defaults to: true)

    whether to automatically mark a batch’s messages as successfully processed when the block returns without an exception. Once marked successful, the offsets of processed messages can be committed to Kafka.

Yield Parameters:

Returns:

  • (nil)

Raises:

  • (Kafka::ProcessingError)

    if there was an error processing a batch. The original exception will be returned by calling ‘#cause` on the ProcessingError instance.



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# File 'lib/kafka/consumer.rb', line 292

def each_batch(min_bytes: 1, max_bytes: 10485760, max_wait_time: 1, automatically_mark_as_processed: true)
  @fetcher.configure(
    min_bytes: min_bytes,
    max_bytes: max_bytes,
    max_wait_time: max_wait_time,
  )

  consumer_loop do
    batches = fetch_batches

    batches.each do |batch|
      unless batch.empty?
        raw_messages = batch.messages
        batch.messages = raw_messages.reject(&:is_control_record)

        notification = {
          topic: batch.topic,
          partition: batch.partition,
          last_offset: batch.last_offset,
          offset_lag: batch.offset_lag,
          highwater_mark_offset: batch.highwater_mark_offset,
          message_count: batch.messages.count,
        }

        # Instrument an event immediately so that subscribers don't have to wait until
        # the block is completed.
        @instrumenter.instrument("start_process_batch.consumer", notification)

        @instrumenter.instrument("process_batch.consumer", notification) do
          begin
            yield batch
            @current_offsets[batch.topic][batch.partition] = batch.last_offset unless batch.unknown_last_offset?
          rescue => e
            offset_range = (batch.first_offset..batch.last_offset || batch.highwater_mark_offset)
            location = "#{batch.topic}/#{batch.partition} in offset range #{offset_range}"
            backtrace = e.backtrace.join("\n")

            @logger.error "Exception raised when processing #{location} -- #{e.class}: #{e}\n#{backtrace}"

            raise ProcessingError.new(batch.topic, batch.partition, offset_range)
          ensure
            batch.messages = raw_messages
          end
        end
        mark_message_as_processed(batch.messages.last) if automatically_mark_as_processed

        # We've successfully processed a batch from the partition, so we can clear
        # the pause.
        pause_for(batch.topic, batch.partition).reset!
      end

      @offset_manager.commit_offsets_if_necessary

      trigger_heartbeat

      return if shutting_down?
    end

    # We may not have received any messages, but it's still a good idea to
    # commit offsets if we've processed messages in the last set of batches.
    # This also ensures the offsets are retained if we haven't read any messages
    # since the offset retention period has elapsed.
    @offset_manager.commit_offsets_if_necessary
  end
end

#each_message(min_bytes: 1, max_bytes: 10485760, max_wait_time: 1, automatically_mark_as_processed: true) {|message| ... } ⇒ nil

Fetches and enumerates the messages in the topics that the consumer group subscribes to.

Each message is yielded to the provided block. If the block returns without raising an exception, the message will be considered successfully processed. At regular intervals the offset of the most recent successfully processed message in each partition will be committed to the Kafka offset store. If the consumer crashes or leaves the group, the group member that is tasked with taking over processing of these partitions will resume at the last committed offsets.

Parameters:

  • min_bytes (Integer) (defaults to: 1)

    the minimum number of bytes to read before returning messages from each broker; if ‘max_wait_time` is reached, this is ignored.

  • max_bytes (Integer) (defaults to: 10485760)

    the maximum number of bytes to read before returning messages from each broker.

  • max_wait_time (Integer, Float) (defaults to: 1)

    the maximum duration of time to wait before returning messages from each broker, in seconds.

  • automatically_mark_as_processed (Boolean) (defaults to: true)

    whether to automatically mark a message as successfully processed when the block returns without an exception. Once marked successful, the offsets of processed messages can be committed to Kafka.

Yield Parameters:

Returns:

  • (nil)

Raises:

  • (Kafka::ProcessingError)

    if there was an error processing a message. The original exception will be returned by calling ‘#cause` on the ProcessingError instance.



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# File 'lib/kafka/consumer.rb', line 204

def each_message(min_bytes: 1, max_bytes: 10485760, max_wait_time: 1, automatically_mark_as_processed: true)
  @fetcher.configure(
    min_bytes: min_bytes,
    max_bytes: max_bytes,
    max_wait_time: max_wait_time,
  )

  consumer_loop do
    batches = fetch_batches

    batches.each do |batch|
      batch.messages.each do |message|
        notification = {
          topic: message.topic,
          partition: message.partition,
          offset: message.offset,
          offset_lag: batch.highwater_mark_offset - message.offset - 1,
          create_time: message.create_time,
          key: message.key,
          value: message.value,
          headers: message.headers
        }

        # Instrument an event immediately so that subscribers don't have to wait until
        # the block is completed.
        @instrumenter.instrument("start_process_message.consumer", notification)

        @instrumenter.instrument("process_message.consumer", notification) do
          begin
            yield message unless message.is_control_record
            @current_offsets[message.topic][message.partition] = message.offset
          rescue => e
            location = "#{message.topic}/#{message.partition} at offset #{message.offset}"
            backtrace = e.backtrace.join("\n")
            @logger.error "Exception raised when processing #{location} -- #{e.class}: #{e}\n#{backtrace}"

            raise ProcessingError.new(message.topic, message.partition, message.offset)
          end
        end

        mark_message_as_processed(message) if automatically_mark_as_processed
        @offset_manager.commit_offsets_if_necessary

        trigger_heartbeat

        return if shutting_down?
      end

      # We've successfully processed a batch from the partition, so we can clear
      # the pause.
      pause_for(batch.topic, batch.partition).reset!
    end

    # We may not have received any messages, but it's still a good idea to
    # commit offsets if we've processed messages in the last set of batches.
    # This also ensures the offsets are retained if we haven't read any messages
    # since the offset retention period has elapsed.
    @offset_manager.commit_offsets_if_necessary
  end
end

#mark_message_as_processed(message) ⇒ Object



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# File 'lib/kafka/consumer.rb', line 377

def mark_message_as_processed(message)
  @offset_manager.mark_as_processed(message.topic, message.partition, message.offset)
end

#pause(topic, partition, timeout: nil, max_timeout: nil, exponential_backoff: false) ⇒ nil

Pause processing of a specific topic partition.

When a specific message causes the processor code to fail, it can be a good idea to simply pause the partition until the error can be resolved, allowing the rest of the partitions to continue being processed.

If the ‘timeout` argument is passed, the partition will automatically be resumed when the timeout expires. If `exponential_backoff` is enabled, each subsequent pause will cause the timeout to double until a message from the partition has been successfully processed.

Parameters:

  • topic (String)
  • partition (Integer)
  • timeout (nil, Integer) (defaults to: nil)

    the number of seconds to pause the partition for, or ‘nil` if the partition should not be automatically resumed.

  • max_timeout (nil, Integer) (defaults to: nil)

    the maximum number of seconds to pause for, or ‘nil` if no maximum should be enforced.

  • exponential_backoff (Boolean) (defaults to: false)

    whether to enable exponential backoff.

Returns:

  • (nil)


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# File 'lib/kafka/consumer.rb', line 141

def pause(topic, partition, timeout: nil, max_timeout: nil, exponential_backoff: false)
  if max_timeout && !exponential_backoff
    raise ArgumentError, "`max_timeout` only makes sense when `exponential_backoff` is enabled"
  end

  pause_for(topic, partition).pause!(
    timeout: timeout,
    max_timeout: max_timeout,
    exponential_backoff: exponential_backoff,
  )
end

#paused?(topic, partition) ⇒ Boolean

Whether the topic partition is currently paused.

Parameters:

  • topic (String)
  • partition (Integer)

Returns:

  • (Boolean)

    true if the partition is paused, false otherwise.

See Also:



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# File 'lib/kafka/consumer.rb', line 172

def paused?(topic, partition)
  pause = pause_for(topic, partition)
  pause.paused? && !pause.expired?
end

#resume(topic, partition) ⇒ nil

Resume processing of a topic partition.

Parameters:

  • topic (String)
  • partition (Integer)

Returns:

  • (nil)

See Also:



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# File 'lib/kafka/consumer.rb', line 159

def resume(topic, partition)
  pause_for(topic, partition).resume!

  # During re-balancing we might have lost the paused partition. Check if partition is still in group before seek.
  seek_to_next(topic, partition) if @group.assigned_to?(topic, partition)
end

#seek(topic, partition, offset) ⇒ nil

Move the consumer’s position in a topic partition to the specified offset.

Note that this has to be done prior to calling #each_message or #each_batch and only has an effect if the consumer is assigned the partition. Typically, you will want to do this in every consumer group member in order to make sure that the member that’s assigned the partition knows where to start.

Parameters:

  • topic (String)
  • partition (Integer)
  • offset (Integer)

Returns:

  • (nil)


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# File 'lib/kafka/consumer.rb', line 369

def seek(topic, partition, offset)
  @offset_manager.seek_to(topic, partition, offset)
end

#stopnil

Stop the consumer.

The consumer will finish any in-progress work and shut down.

Returns:

  • (nil)


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# File 'lib/kafka/consumer.rb', line 116

def stop
  @running = false
  @fetcher.stop
  @cluster.disconnect
end

#subscribe(topic_or_regex, default_offset: nil, start_from_beginning: true, max_bytes_per_partition: 1048576) ⇒ nil

Subscribes the consumer to a topic.

Typically you either want to start reading messages from the very beginning of the topic’s partitions or you simply want to wait for new messages to be written. In the former case, set ‘start_from_beginning` to true (the default); in the latter, set it to false.

Parameters:

  • topic_or_regex (String, Regexp)

    subscribe to single topic with a string or multiple topics matching a regex.

  • default_offset (Symbol) (defaults to: nil)

    whether to start from the beginning or the end of the topic’s partitions. Deprecated.

  • start_from_beginning (Boolean) (defaults to: true)

    whether to start from the beginning of the topic or just subscribe to new messages being produced. This only applies when first consuming a topic partition – once the consumer has checkpointed its progress, it will always resume from the last checkpoint.

  • max_bytes_per_partition (Integer) (defaults to: 1048576)

    the maximum amount of data fetched from a single partition at a time.

Returns:

  • (nil)


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# File 'lib/kafka/consumer.rb', line 97

def subscribe(topic_or_regex, default_offset: nil, start_from_beginning: true, max_bytes_per_partition: 1048576)
  default_offset ||= start_from_beginning ? :earliest : :latest

  if topic_or_regex.is_a?(Regexp)
    cluster_topics.select { |topic| topic =~ topic_or_regex }.each do |topic|
      subscribe_to_topic(topic, default_offset, start_from_beginning, max_bytes_per_partition)
    end
  else
    subscribe_to_topic(topic_or_regex, default_offset, start_from_beginning, max_bytes_per_partition)
  end

  nil
end

#trigger_heartbeatObject Also known as: send_heartbeat_if_necessary



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# File 'lib/kafka/consumer.rb', line 381

def trigger_heartbeat
  @heartbeat.trigger
end

#trigger_heartbeat!Object Also known as: send_heartbeat



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# File 'lib/kafka/consumer.rb', line 385

def trigger_heartbeat!
  @heartbeat.trigger!
end