Apache kafka Kafka消费者没有从分区中获得一条消息

我只是注意到，当我在一个分区中生成一条消息时，我的消费者并没有收到它。只有在我向同一分区中生成更多消息之后，消费者才会收到它们。我的

fetch.min.bytes

设置为1

是否存在其他可能影响此处的配置

每个分区都有一个专用的使用者

相关部件的消费者代码。我的消费者为

configs['stream']

定义的不同主题启动多个线程。使用原始消费品gem的分叉。我添加了一个批量消费方法。以及以管理方式关闭消费者的方法

key = configs['app_key']
consumer = Rdkafka::Config.new(config(configs)).consumer
topic = "#{topic_prefix}#{app_env}_#{configs['stream']}"
consumer.subscribe(topic)

logger.info "#{rand}| Starting consumer for #{key} with topic #{topic}"
begin
  retry_counter = 0
  retries_started_at = nil
  current_assignment = nil
  partitions = []
  consumer.each_batch(configs['max_messages_per_partition'] || 5, 100, rand) do |messages|
    partitions = messages.collect {|m| m.partition}.uniq.sort
    logger.info "#{rand}| Batch started. Received #{messages.length} messages from partitions #{partitions} for app #{key}"
    current_assignment = consumer.assignment.to_h
    values = messages.collect {|m| JSON.parse(m.payload)}
    skip_commit = false
    begin
      values.each_slice((values.length / ((retry_counter * 2) + 1).to_f).ceil) do |slice|
        logger.info "#{rand}| Sending #{slice.length} messages to lambda"
        result = invoke_lambda(key, slice)
        if result.status_code != 200 || result.function_error
          logger.info "#{rand}| Batch finished with error #{result.function_error}"
          raise LambdaError, result.function_error.to_s
        end
      end
    rescue LambdaError => e
      logger.warn "#{rand}| #{e}"
      if consumer.running? && current_assignment == consumer.assignment.to_h
        retry_counter += 1
        retries_started_at ||= Time.now
        if retry_counter <= 5 && Time.now - retries_started_at < 600
          logger.warn "#{rand}| Retrying from: #{e.cause}, app_key: #{key}"
          Rollbar.warning("Retrying from: #{e.cause}", app_key: key, thread: rand, partitions: partitions.join(', '))
          sleep 5
          retry if consumer.running? && current_assignment == consumer.assignment.to_h
        else
          raise e # Raise to exit the retry loop so that consumers are rebalanced.
        end
      end
      skip_commit = true
    end
    retry_counter = 0
    retries_started_at = nil
    if skip_commit
      logger.info "#{rand}| Commit skipped"
    else
      consumer.commit
      logger.info "#{rand}| Batch finished"
    end
  end
  consumer.close
  logger.info "#{rand}| Stopped #{key}"
rescue Rdkafka::RdkafkaError => e
  logger.warn "#{rand}| #{e}"
  logger.info "#{rand}| assignment: #{consumer.assignment.to_h}"
  if e.to_s.index('No offset stored')
    retry
  else
    raise e
  end
end

生产者代码使用

更新：看起来消息的数量与此无关。我刚刚在一个分区中生成了100多条消息，而消费者还没有开始使用这些消息

---

更新2：它在晚上没有开始使用这些消息。但是当我今天早上在同一个分区中生成一组新消息时，它醒来并开始使用我刚才生成的新消息。它跳过了昨晚生成的消息。

我认为问题在于分区有一段时间没有收到消息，而且显然没有保存偏移量。获取偏移量时，将其设置为默认的最大值。在我设置了

auto.offset.reset:“minimable”之后，我还没有看到会跳过消息的问题。
请向制作人说明代码生成不是问题。我可以通过卡夫卡管理工具验证每次生成消息时结束偏移量都在增加。什么管理工具？请再次显示所有相关代码。您没有提供任何上下文来重现您的问题，只有一个属性在消息传递中不是真正确定的。管理工具是Cloudkarafka的Kafka Manager。我为相关部分添加了生产者代码和消费者代码。
def config(app_config)
  {
      "bootstrap.servers": brokers,
      "group.id": app_configs['app_key'],
      "enable.auto.commit": false,
      "enable.partition.eof": false,
      "log.connection.close": false,
      "session.timeout.ms": 30*1000,
      "fetch.message.max.bytes": ['sources'].include?(app_configs['stream']) ? 102400 : 10240,
      "queued.max.messages.kbytes": ['sources'].include?(app_configs['stream']) ? 250 : 25,
      "queued.min.messages": (app_configs['max_messages_per_partition'] || 5) * 10,
      "fetch.min.bytes": 1,
      "partition.assignment.strategy": 'roundrobin'
  }
end

def to_kafka(stream_name, data, batch_size)
  stream_name_with_env = "#{Rails.env}_#{stream_name}"
  topic = [Rails.application.secrets.kafka_topic_prefix, stream_name_with_env].compact.join
  partitions_count = KAFKA.partitions_for(topic)
  Rails.logger.info "Partition count for #{topic}: #{partitions_count}"
  if @job.active? && @job.partition.blank?
    @job.connect_to_partition
  end
  partition = @job.partition&.number.to_i % partitions_count
  producer = KAFKA.producer 
  if data.is_a?(Array)
    data.each_slice(batch_size) do |slice|
      producer.produce(JSON.generate(slice), topic: topic, partition: partition)
    end
  else
    producer.produce(JSON.generate(data), topic: topic, partition: partition)
  end
  producer.deliver_messages
  Rails.logger.info "records sent to topic #{topic} partition #{partition}"
  producer.shutdown
end