如何捕获java.net.ConnectException：Akka steram拒绝连接？

时间：2019-04-21 13:14:49

标签： scala apache-kafka akka-stream alpakka

我有一个kafka用户，其外观如下：

import akka.actor.ActorSystem
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ConsumerSettings, Subscriptions}
import akka.stream.ActorMaterializer
import akka.stream.scaladsl.Sink
import org.apache.kafka.clients.consumer.ConsumerConfig
import org.apache.kafka.common.serialization.StringDeserializer

import scala.util.{Failure, Success}

object App {
  def main(args: Array[String]): Unit = {


    implicit val system = ActorSystem("SAP-SENDER")
    implicit val executor = system.dispatcher
    implicit val materilizer = ActorMaterializer()

    val config = system.settings.config.getConfig("akka.kafka.consumer")

    val consumerSettings: ConsumerSettings[String, String] =
      ConsumerSettings(config, new StringDeserializer, new StringDeserializer)
        .withBootstrapServers("localhost:9003")
        .withGroupId("SAPSENDER")
        .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest")

    Consumer
      .plainSource(
        consumerSettings,
        Subscriptions.topics("TEST-TOPIC")
      )
      .runWith(Sink.foreach(println))
      .onComplete{
        case Success(_) => println("Goood")
        case Failure(ex) =>
          println(s"I am failed ==============> ${ex.getMessage}")
          system.terminate()
      }

  }
}

kafka服务器未激活，我只想终止使用者。它总是尝试连接并显示以下消息：

19:03:47.342 [SAP-SENDER-akka.kafka.default-dispatcher-15] DEBUG org.apache.kafka.clients.consumer.KafkaConsumer - [Consumer clientId=consumer-1, groupId=SAPSENDER] Pausing partitions []
19:03:47.342 [SAP-SENDER-akka.kafka.default-dispatcher-15] DEBUG org.apache.kafka.clients.consumer.internals.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=SAPSENDER] No broker available to send FindCoordinator request
19:03:47.342 [SAP-SENDER-akka.kafka.default-dispatcher-15] DEBUG org.apache.kafka.clients.NetworkClient - [Consumer clientId=consumer-1, groupId=SAPSENDER] Give up sending metadata request since no node is available
19:03:47.342 [SAP-SENDER-akka.kafka.default-dispatcher-15] DEBUG org.apache.kafka.clients.consumer.internals.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=SAPSENDER] Coordinator discovery failed, refreshing metadata
19:03:47.342 [SAP-SENDER-akka.kafka.default-dispatcher-15] DEBUG org.apache.kafka.clients.NetworkClient - [Consumer clientId=consumer-1, groupId=SAPSENDER] Give up sending metadata request since no node is available
19:03:47.412 [SAP-SENDER-akka.kafka.default-dispatcher-17] DEBUG org.apache.kafka.clients.consumer.KafkaConsumer - [Consumer clientId=consumer-1, groupId=SAPSENDER] Pausing partitions []
19:03:47.412 [SAP-SENDER-akka.kafka.default-dispatcher-17] DEBUG org.apache.kafka.clients.consumer.internals.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=SAPSENDER] No broker available to send FindCoordinator request
19:03:47.412 [SAP-SENDER-akka.kafka.default-dispatcher-17] DEBUG org.apache.kafka.clients.NetworkClient - [Consumer clientId=consumer-1, groupId=SAPSENDER] Give up sending metadata request since no node is available
19:03:47.412 [SAP-SENDER-akka.kafka.default-dispatcher-17] DEBUG org.apache.kafka.clients.consumer.internals.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=SAPSENDER] Coordinator discovery failed, refreshing metadata
19:03:47.412 [SAP-SENDER-akka.kafka.default-dispatcher-17] DEBUG org.apache.kafka.clients.NetworkClient - [Consumer clientId=consumer-1, groupId=SAPSENDER] Give up sending metadata request since no node is available
19:03:47.478 [SAP-SENDER-akka.kafka.default-dispatcher-20] DEBUG org.apache.kafka.clients.consumer.KafkaConsumer - [Consumer clientId=consumer-1, groupId=SAPSENDER] Pausing partitions []

它还说：

java.net.ConnectException: Connection refused
    at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
    at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
    at org.apache.kafka.common.network.PlaintextTransportLayer.finishConnect(PlaintextTransportLayer.java:50)
    at org.apache.kafka.common.network.KafkaChannel.finishConnect(KafkaChannel.java:173)
    at org.apache.kafka.common.network.Selector.pollSelectionKeys(Selector.java:515)
    at org.apache.kafka.common.network.Selector.poll(Selector.java:467)
    at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:535)
    at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:265)
    at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:236)
    at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:215)
    at org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureCoordinatorReady(AbstractCoordinator.java:231)
    at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.poll(ConsumerCoordinator.java:316)
    at org.apache.kafka.clients.consumer.KafkaConsumer.updateAssignmentMetadataIfNeeded(KafkaConsumer.java:1214)
    at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1179)
    at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:1164)
    at akka.kafka.internal.KafkaConsumerActor.poll(KafkaConsumerActor.scala:380)
    at akka.kafka.internal.KafkaConsumerActor.akka$kafka$internal$KafkaConsumerActor$$receivePoll(KafkaConsumerActor.scala:360)
    at akka.kafka.internal.KafkaConsumerActor$$anonfun$receive$1.applyOrElse(KafkaConsumerActor.scala:221)
    at akka.actor.Actor.aroundReceive(Actor.scala:539)
    at akka.actor.Actor.aroundReceive$(Actor.scala:537)
    at akka.kafka.internal.KafkaConsumerActor.akka$actor$Timers$$super$aroundReceive(KafkaConsumerActor.scala:142)
    at akka.actor.Timers.aroundReceive(Timers.scala:51)
    at akka.actor.Timers.aroundReceive$(Timers.scala:40)
    at akka.kafka.internal.KafkaConsumerActor.aroundReceive(KafkaConsumerActor.scala:142)
    at akka.actor.ActorCell.receiveMessage(ActorCell.scala:610)
    at akka.actor.ActorCell.invoke(ActorCell.scala:579)
    at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:268)
    at akka.dispatch.Mailbox.run(Mailbox.scala:229)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

如何在流中赶上ConnectException，并阻止消费者尝试连接kafka。

代码托管在https://gitlab.com/akka-samples/kafkaconsumer上。

3 个答案:

答案 0 :(得分：2)

使用Kafka Client 2.0+ Alpakka Kafka不能注意到给定地址上没有可用的Kafka经纪人。

请参见https://github.com/akka/alpakka-kafka/issues/674

答案 1 :(得分：1)

看看这个PR以及升级到kafka客户端2.0的工作，我想很多重试责任已经委派给了kafka客户端。例如，我尝试传递这些属性

val consumerSettings: ConsumerSettings[String, String] =
  ConsumerSettings(config, new StringDeserializer, new StringDeserializer)
    .withProperties(
      "reconnect.backoff.ms" -> "10000",
      "reconnect.backoff.max.ms" -> "20000"
    )
    .withBootstrapServers("localhost:9099")
    .withGroupId("SAPSENDER")
    .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest")

10秒后第二次出现该异常。我发现了这些属性here

鉴于此，我认为kafka客户端的新改编版可能缺少一项功能，因为KafkaConsumerActor并未将异常暴露给流，因此我使用您的repo尝试了各种组合，但仍然得到连续的调试流消息。

我希望这能给正确的方向一些提示，如果您解决了，请告诉我们。

答案 2 :(得分：0)

您应该监视您的流，如果有错误，请重新启动它。例如，您可以在actor内部运行流，并在actor监督下处理错误连接。

连接错误可能会持续几秒钟（也许网络不堪重负），因此您应该使用退避策略来避免重试风暴。

Akka流已经为您提供了一种使用RestartSource进行流的简单方法。参见Error Handling 

val control = new AtomicReference[Consumer.Control](Consumer.NoopControl)

val result = RestartSource
  .onFailuresWithBackoff(
    minBackoff = 3.seconds,
    maxBackoff = 30.seconds,
    randomFactor = 0.2
  ) { () =>
    Consumer
      .plainSource(consumerSettings, Subscriptions.topics(topic))
      // this is a hack to get access to the Consumer.Control
      // instances of the latest Kafka Consumer source
      .mapMaterializedValue(c => control.set(c))
      .via(businessFlow)
  }
  .runWith(Sink.seq)

control.get().shutdown()

此解决方案仅在启动流并且代理关闭时才起作用，因为当使用方尝试创建它时，使用者将引发异常。 但是，如果您成功创建了使用者，然后整个kafka集群崩溃，内部的KafkaConsumer将使用上述的reconnect.backoff.ms和reconnect.backoff.max.ms配置重新连接，并且流不会失败。

如果要限制退休人数，则应执行以下操作

val result: Future[Done] = RestartSource
  .onFailuresWithBackoff(
    minBackoff = 3.seconds,
    maxBackoff = 30.seconds,
    randomFactor = 0.2
  ) { () => // your consumer  
  }.
  .take(3) // retries limit
  .runWith(Sink.ignore)

result.onComplete {
  case _ => println("Max retries reached")
}
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