Akka Cluster原理与应用

  

Akka集群原理

Akka集群支持去中心化的基于P2P的集群服务，没有单点故障（SPOF）问题，它主要是通过Gossip协议来实现。对于集群成员的状态，Akka提供了一种故障检测机制，能够自动发现出现故障而离开集群的成员节点，通过事件驱动的方式，将状态传播到整个集群的其它成员节点。

  • 状态转移与故障检测

Akka内部为集群成员定义了一组有限状态（6种状态），并给出了一个状态转移矩阵，代码如下所示：

  private[cluster] val allowedTransitions: Map[MemberStatus, Set[MemberStatus]] =
    Map(
      Joining -> Set(Up, Down, Removed),
      Up -> Set(Leaving, Down, Removed),
      Leaving -> Set(Exiting, Down, Removed),
      Down -> Set(Removed),
      Exiting -> Set(Removed, Down),
      Removed -> Set.empty[MemberStatus])
}

Akka集群中的每个成员节点，都有可能处于上面的一种状态，在发生某些事件以后，会发生状态转移。需要注意的是，除了Down和Removed状态以外，节点处于其它任何一个状态时都有可能变成Down状态，即节点故障而无法提供服务，而在变成Down状态之前有一个虚拟的Unreachable状态，因为在Gossip收敛过程中，是无法到达或者经由Unreachable状态的节点，这个状态是由Akka实现的故障探测器（Failure Detector）来检测到的。处于Down状态的节点如果想要再次加入Akka集群，需要重新启动，并进入Joining状态，然后才能进行后续状态的转移变化。Akka集群成员节点状态及其转移情况，如下图所示：
akka-node-state-transition
我们说明一下Akka中的故障检测机制。在Akka中，集群中每一个成员节点M会被集群中的其他另一组节点（默认是5个）G监控，这一组节点G并不是整个集群中的其他所有节点，只是整个集群全部节点的一个子集，组G中的节点会检测节点M是否处于Unreachable状态，这是通过发送心跳来确认节点M是否可达，如果不可达则组G中的节点会将节点M的Unreachable状态向集群中组G之外的其它节点传播，最终使得集群中的每个成员节点都知道节点M故障。

  • Akka事件集合

节点状态发生转移会触发某个事件，我们可以根据不同类型的事件来进行相应的处理，为了能够详细捕获到各种事件，我们先看一下Akka定义的事件集合，如图所示：
akka-events
通常，在基于Akka Cluster的应用中实现Actor时，可以重写Actor的preStart方法，通过Cluster来订阅集群事件，代码示例如下所示：

  val cluster = Cluster(context.system)

  override def preStart(): Unit = {
    cluster.subscribe(self, initialStateMode = InitialStateAsEvents,
      classOf[MemberUp], classOf[MemberRemoved], classOf[UnreachableMember])
  }

例如，对于MemberUp事件，我们可以获取到对应Actor的引用ActorRef，然后通过与其进行消息交换，一起协同完成特定任务。

  • Akka成员角色（Node Role）

Akka支持在每个成员节点加入集群的时候，设置成员自己的角色。通过角色划分，可以将使用Akka集群处理业务的系统划分为多个处理逻辑独立的子系统，每个子系统处理自己的业务逻辑，而且，划分得到的多个子系统都处于一个统一的Akka集群中。因此，每个子系统也具备了Akka集群所具有的特性，如故障检测、状态转移、状态传播等等。

Akka集群应用实践

我们基于Akka实现了一个简单的模拟日志实时处理的集群系统，可以从任何数据源输入数据，如文件、消息中间件Kafka、数据库，还可以是一个远程调用请求，我们收集数据，然数据经过一个拦截器层，最后解析处理数据为特定格式，最后数据写入Kafka。具体实现逻辑如下图所示：
akka-event-processing-cluster
上图中，我们将日志实时处理系统分为3个子系统，通过Akka的Role来进行划分，3个角色分别为collector、interceptor、processor，3个子系统中的节点都是整个Akka集群的成员。整个集群系统中的数据流向是：collector接收数据（或者直接对接特定数据源而产生数据），我们这里模式发送Nginx日志记录行，将数据发送到interceptor；interceptor收到collector发送的日志记录行，解析出请求的真是IP地址，拦截在黑名单IP列表中的请求，如果IP地址不在黑名单，则发送给processor去处理；processor对整个日志记录行进行处理，最后保存到Kakfa中。
我们抽象出用来订阅集群事件相关的逻辑，实现抽象类为ClusterRoledWorker，代码如下所示：

package org.shirdrn.scala.akka.cluster

import akka.actor._
import akka.cluster.ClusterEvent.{InitialStateAsEvents, MemberEvent, MemberUp, UnreachableMember}
import akka.cluster.{Cluster, Member}

abstract class ClusterRoledWorker extends Actor with ActorLogging {

  // 创建一个Cluster实例
  val cluster = Cluster(context.system) 
  // 用来缓存下游注册过来的子系统ActorRef
  var workers = IndexedSeq.empty[ActorRef] 

  override def preStart(): Unit = {
    // 订阅集群事件
    cluster.subscribe(self, initialStateMode = InitialStateAsEvents,
      classOf[MemberUp], classOf[UnreachableMember], classOf[MemberEvent])
  }

  override def postStop(): Unit = cluster.unsubscribe(self)

  /**
   * 下游子系统节点发送注册消息
   */
  def register(member: Member, createPath: (Member) => ActorPath): Unit = { 
    val actorPath = createPath(member)
    log.info("Actor path: " + actorPath)
    val actorSelection = context.actorSelection(actorPath)
    actorSelection ! Registration
  }
}

另外，定义了一些case class作为消息，方便在各个Actor之间进行发送/接收，代码如下所示：

package org.shirdrn.scala.akka.cluster

object Registration extends Serializable

trait EventMessage extends Serializable
case class RawNginxRecord(sourceHost: String, line: String) extends EventMessage
case class NginxRecord(sourceHost: String, eventCode: String, line: String) extends EventMessage
case class FilteredRecord(sourceHost: String, eventCode: String, line: String, logDate: String, realIp: String) extends EventMessage

Akka Cluster使用一个配置文件，用来指定一些有关Actor的配置，我们使用的配置文件为application.conf，配置内容如下所示：

akka {
  loglevel = INFO
  stdout-loglevel = INFO
  event-handlers = ["akka.event.Logging$DefaultLogger"]

  actor {
    provider = "akka.cluster.ClusterActorRefProvider"
  }

  remote {
    enabled-transports = ["akka.remote.netty.tcp"]
    log-remote-lifecycle-events = off
    netty.tcp {
      hostname = "127.0.0.1"
      port = 0
    }
  }
  cluster {
    seed-nodes = [
      "akka.tcp://event-cluster-system@127.0.0.1:2751",
      "akka.tcp://event-cluster-system@127.0.0.1:2752",
      "akka.tcp://event-cluster-system@127.0.0.1:2753"
    ]
    seed-node-timeout = 60s
    auto-down-unreachable-after = 10s
  }
}

上述配置中，我们创建的Akka Cluster的名称为event-cluster-system，初始指定了3个seed节点，实际上这3个节点是我们实现的collector角色的节点，用来收集数据。
下面，我们依次说明collector、interceptor、processor这3中角色的集群节点的处理逻辑：

  • collector实现

我们实现的collector实现类为EventCollector，它是一个Actor，该实现类继承自ClusterRoledWorker抽象类，具体实现代码如下所示：

package org.shirdrn.scala.akka.cluster

import akka.actor._
import akka.cluster.ClusterEvent._
import com.typesafe.config.ConfigFactory

import scala.concurrent.ExecutionContext
import scala.concurrent.duration._
import scala.concurrent.forkjoin.ForkJoinPool

class EventCollector extends ClusterRoledWorker {

  @volatile var recordCounter : Int = 0

  def receive = {
    case MemberUp(member) =>
      log.info("Member is Up: {}", member.address)
    case UnreachableMember(member) =>
      log.info("Member detected as Unreachable: {}", member)
    case MemberRemoved(member, previousStatus) =>
      log.info("Member is Removed: {} after {}", member.address, previousStatus)
    case _: MemberEvent => // ignore

    case Registration => {
      // watch发送注册消息的interceptor，如果对应的Actor终止了，会发送一个Terminated消息
      context watch sender
      workers = workers :+ sender
      log.info("Interceptor registered: " + sender)
      log.info("Registered interceptors: " + workers.size)
    }
    case Terminated(interceptingActorRef) =>
      // interceptor终止，更新缓存的ActorRef
      workers = workers.filterNot(_ == interceptingActorRef)
    case RawNginxRecord(sourceHost, line) => {
      // 构造NginxRecord消息，发送到下游interceptor
      val eventCode = "eventcode=(\\d+)".r.findFirstIn(line).get
      log.info("Raw message: eventCode=" + eventCode + ", sourceHost=" + sourceHost + ", line=" + line)
      recordCounter += 1
      if(workers.size > 0) {
        // 模拟Roudrobin方式，将日志记录消息发送给下游一组interceptor中的一个
        val interceptorIndex = (if(recordCounter < 0) 0 else recordCounter) % workers.size
        workers(interceptorIndex) ! NginxRecord(sourceHost, eventCode, line)
        log.info("Details: interceptorIndex=" + interceptorIndex + ", interceptors=" + workers.size)
      }
    }
  }

}

/**
 * 用来模拟发送日志记录消息的Actor
 */
class EventClientActor extends Actor with ActorLogging {

  implicit val ec: ExecutionContext = ExecutionContext.fromExecutor(new ForkJoinPool())

  def receive = {
    case _=>
  }

  val events = Map(
    "2751" -> List(
      """10.10.2.72 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000lAOX&udid=25371384b2eb1a5dc5643e14626ecbd4&sessionid=25371384b2eb1a5dc5643e14626ecbd41440152875362&imsi=460002830862833&operator=1&network=1&timestamp=1440152954&action=14&eventcode=300039&page=200002& HTTP/1.0" "-" 204 0 "-" "Dalvik/1.6.0 (Linux; U; Android 4.4.4; R8207 Build/KTU84P)" "121.25.190.146"""",
      """10.10.2.8 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000VACO&udid=f6b0520cbc36fda6f63a72d91bf305c0&imsi=460012927613645&operator=2&network=1&timestamp=1440152956&action=1840&eventcode=100003&type=1&result=0& HTTP/1.0" "-" 204 0 "-" "Dalvik/1.6.0 (Linux; U; Android 4.4.2; GT-I9500 Build/KOT49H)" "61.175.219.69""""
    ),
    "2752" -> List(
      """10.10.2.72 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000gCo4&udid=636d127f4936109a22347b239a0ce73f&sessionid=636d127f4936109a22347b239a0ce73f1440150695096&imsi=460036010038180&operator=3&network=4&timestamp=1440152902&action=1566&eventcode=101010&playid=99d5a59f100cb778b64b5234a189e1f4&radioid=1100000048450&audioid=1000001535718&playtime=3& HTTP/1.0" "-" 204 0 "-" "Dalvik/1.6.0 (Linux; U; Android 4.4.4; R8205 Build/KTU84P)" "106.38.128.67"""",
      """10.10.2.72 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000kPSC&udid=2ee585cde388ac57c0e81f9a76f5b797&operator=0&network=1&timestamp=1440152968&action=6423&eventcode=100003&type=1&result=0& HTTP/1.0" "-" 204 0 "-" "Dalvik/v3.3.85 (Linux; U; Android L; P8 Build/KOT49H)" "202.103.133.112"""",
      """10.10.2.72 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000lABW&udid=face1161d739abacca913dcb82576e9d&sessionid=face1161d739abacca913dcb82576e9d1440151582673&operator=0&network=1&timestamp=1440152520&action=1911&eventcode=101010&playid=b07c241010f8691284c68186c42ab006&radioid=1100000000762&audioid=1000001751983&playtime=158& HTTP/1.0" "-" 204 0 "-" "Dalvik/1.6.0 (Linux; U; Android 4.1; H5 Build/JZO54K)" "221.232.36.250""""
    ),
    "2753" -> List(
      """10.10.2.8 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000krJw&udid=939488333889f18e2b406d2ece8f938a&sessionid=939488333889f18e2b406d2ece8f938a1440137301421&imsi=460028180045362&operator=1&network=1&timestamp=1440152947&action=1431&eventcode=300030&playid=e1fd5467085475dc4483d2795f112717&radioid=1100000001123&audioid=1000000094911&playtime=951992& HTTP/1.0" "-" 204 0 "-" "Dalvik/1.6.0 (Linux; U; Android 4.0.4; R813T Build/IMM76D)" "5.45.64.205"""",
      """10.10.2.72 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000kcpz&udid=cbc7bbb560914c374cb7a29eef8c2144&sessionid=cbc7bbb560914c374cb7a29eef8c21441440152816008&imsi=460008782944219&operator=1&network=1&timestamp=1440152873&action=360&eventcode=200003&page=200003&radioid=1100000046018& HTTP/1.0" "-" 204 0 "-" "Dalvik/v3.3.85 (Linux; U; Android 4.4.2; MX4S Build/KOT49H)" "119.128.106.232"""",
      """10.10.2.8 [21/Aug/2015:18:29:19 +0800] "GET /t.gif?installid=0000juRL&udid=3f9a5ffa69a5cd5f0754d2ba98c0aeb2&imsi=460023744091238&operator=1&network=1&timestamp=1440152957&action=78&eventcode=100003&type=1&result=0& HTTP/1.0" "-" 204 0 "-" "Dalvik/v3.3.85 (Linux; U; Android 4.4.3; S?MSUNG. Build/KOT49H)" "223.153.72.78""""
    )
  )

  val ports = Seq("2751","2752", "2753")
  val actors = scala.collection.mutable.HashMap[String, ActorRef]()

  ports.foreach { port =>
    // 创建一个Config对象
    val config = ConfigFactory.parseString("akka.remote.netty.tcp.port=" + port)
        .withFallback(ConfigFactory.parseString("akka.cluster.roles = [collector]"))
        .withFallback(ConfigFactory.load())
    // 创建一个ActorSystem实例
    val system = ActorSystem("event-cluster-system", config)
    actors(port) = system.actorOf(Props[EventCollector], name = "collectingActor")
  }

  Thread.sleep(30000)

  context.system.scheduler.schedule(0 millis, 5000 millis) {
    // 使用Akka的Scheduler，模拟定时发送日志记录消息
    ports.foreach { port =>
      events(port).foreach { line =>
        println("RAW: port=" + port + ", line=" + line)
        actors(port) ! RawNginxRecord("host.me:" + port, line)
      }
    }
  }
}

object EventClient extends App {

  val system = ActorSystem("client")
  // 创建EventClientActor实例
  val clientActorRef = system.actorOf(Props[EventClientActor], name = "clientActor")
  system.log.info("Client actor started: " + clientActorRef)
}

上面代码中，EventClientActor并不是属于我们创建的Akka集群event-cluster-system，它是一个位于集群外部的节点，它模拟向各个collector角色的节点发送消息。

  • interceptor实现

与编写collector类似，实现的interceptor的Actor实现类为EventInterceptor，代码如下所示：

package org.shirdrn.scala.akka.cluster

import akka.actor._
import akka.cluster.ClusterEvent._
import akka.cluster.Member
import akka.cluster.protobuf.msg.ClusterMessages.MemberStatus
import com.typesafe.config.ConfigFactory
import net.sf.json.JSONObject
import org.shirdrn.scala.akka.cluster.utils.DatetimeUtils

class EventInterceptor extends ClusterRoledWorker {

  @volatile var interceptedRecords : Int = 0
  val IP_PATTERN = "[^\\s]+\\s+\\[([^\\]]+)\\].+\"(\\d+\\.\\d+\\.\\d+\\.\\d+)\"".r
  val blackIpList = Array(
    "5.9.116.101", "103.42.176.138", "123.182.148.65", "5.45.64.205",
    "27.159.226.192", "76.164.228.218", "77.79.178.186", "104.200.31.117",
    "104.200.31.32", "104.200.31.238", "123.182.129.108", "220.161.98.39",
    "59.58.152.90", "117.26.221.236", "59.58.150.110", "123.180.229.156",
    "59.60.123.239", "117.26.222.6", "117.26.220.88", "59.60.124.227",
    "142.54.161.50", "59.58.148.52", "59.58.150.85", "202.105.90.142"
  ).toSet

  log.info("Black IP count: " + blackIpList.size)
  blackIpList.foreach(log.info(_))

  def receive = {
    case MemberUp(member) =>
      log.info("Member is Up: {}", member.address)
      register(member, getCollectorPath)
    case state: CurrentClusterState =>
      // 如果加入Akka集群的成员节点是Up状态，并且是collector角色，则调用register向collector进行注册
      state.members.filter(_.status == MemberStatus.Up) foreach(register(_, getCollectorPath))
    case UnreachableMember(member) =>
      log.info("Member detected as Unreachable: {}", member)
    case MemberRemoved(member, previousStatus) =>
      log.info("Member is Removed: {} after {}", member.address, previousStatus)
    case _: MemberEvent => // ignore

    case Registration => {
      context watch sender
      workers = workers :+ sender
      log.info("Processor registered: " + sender)
      log.info("Registered processors: " + workers.size)
    }
    case Terminated(processingActorRef) =>
      workers = workers.filterNot(_ == processingActorRef)
    case NginxRecord(sourceHost, eventCode, line) => {
      val (isIpInBlackList, data) = checkRecord(eventCode, line)
      if(!isIpInBlackList) {
        interceptedRecords += 1
        if(workers.size > 0) {
          val processorIndex = (if (interceptedRecords < 0) 0 else interceptedRecords) % workers.size
          workers(processorIndex) ! FilteredRecord(sourceHost, eventCode, line, data.getString("eventdate"), data.getString("realip"))
          log.info("Details: processorIndex=" + processorIndex + ", processors=" + workers.size)
        }
        log.info("Intercepted data: data=" + data)
      } else {
        log.info("Discarded: " + line)
      }
    }
  }

  def getCollectorPath(member: Member): ActorPath = {
    RootActorPath(member.address) / "user" / "collectingActor"
  }

  /**
   * 检查collector发送的消息所对应的IP是否在黑名单列表中
   */
  private def checkRecord(eventCode: String, line: String): (Boolean, JSONObject) = {
    val data: JSONObject = new JSONObject()
    var isIpInBlackList = false
    IP_PATTERN.findFirstMatchIn(line).foreach { m =>
      val rawDt = m.group(1)
      val dt = DatetimeUtils.format(rawDt)
      val realIp = m.group(2)

      data.put("eventdate", dt)
      data.put("realip", realIp)
      data.put("eventcode", eventCode)
      isIpInBlackList = blackIpList.contains(realIp)
    }
    (isIpInBlackList, data)
  }
}

object EventInterceptor extends App {

  Seq("2851","2852").foreach { port =>
    val config = ConfigFactory.parseString("akka.remote.netty.tcp.port=" + port)
      .withFallback(ConfigFactory.parseString("akka.cluster.roles = [interceptor]"))
      .withFallback(ConfigFactory.load())
    val system = ActorSystem("event-cluster-system", config)
    val processingActor = system.actorOf(Props[EventInterceptor], name = "interceptingActor")
    system.log.info("Processing Actor: " + processingActor)
  }
}

上述代码中，解析出Nginx日志记录中的IP地址，查看其是否在IP黑名单列表中，如果在内名单中则直接丢掉该记录数据。

  • processor实现

EventProcessor的实现代码，如下所示：

package org.shirdrn.scala.akka.cluster

import java.util.Properties

import akka.actor._
import akka.cluster.ClusterEvent._
import akka.cluster.Member
import akka.cluster.protobuf.msg.ClusterMessages.MemberStatus
import com.typesafe.config.ConfigFactory
import kafka.producer.{KeyedMessage, Producer, ProducerConfig}
import net.sf.json.JSONObject

class EventProcessor extends ClusterRoledWorker {

  val topic = "app_events"
  val producer = KakfaUtils.createProcuder

  def receive = {
    case MemberUp(member) =>
      log.info("Member is Up: {}", member.address)
      // 将processor注册到上游的collector中
      register(member, getProcessorPath)
    case state: CurrentClusterState =>
      state.members.filter(_.status == MemberStatus.Up).foreach(register(_, getProcessorPath))
    case UnreachableMember(member) =>
      log.info("Member detected as Unreachable: {}", member)
    case MemberRemoved(member, previousStatus) =>
      log.info("Member is Removed: {} after {}", member.address, previousStatus)
    case _: MemberEvent => // ignore

    case FilteredRecord(sourceHost, eventCode, line, nginxDate, realIp) => {
      val data = process(eventCode, line, nginxDate, realIp)
      log.info("Processed: data=" + data)
      // 将解析后的消息一JSON字符串的格式，保存到Kafka中
      producer.send(new KeyedMessage[String, String](topic, sourceHost, data.toString))
    }
  }

  def getProcessorPath(member: Member): ActorPath = {
    RootActorPath(member.address) / "user" / "interceptingActor"
  }

  private def process(eventCode: String, line: String, eventDate: String, realIp: String): JSONObject = {
    val data: JSONObject = new JSONObject()
    "[\\?|&]{1}([^=]+)=([^&]+)&".r.findAllMatchIn(line) foreach { m =>
      val key = m.group(1)
      val value = m.group(2)
      data.put(key, value)
    }
    data.put("eventdate", eventDate)
    data.put("realip", realIp)
    data
  }
}

object KakfaUtils {
  // bin/kafka-topics.sh --create -zookeeper zk1:2181,zk2:2181,zk3:2181/data-dept/kafka --replication-factor 2 --partitions 2 --topic app_events
  val props = new Properties()
  val config = Map(
    "metadata.broker.list" -> "hadoop2:9092,hadoop3:9092",
    "serializer.class" -> "kafka.serializer.StringEncoder",
    "producer.type" -> "async"
  )
  config.foreach(entry => props.put(entry._1, entry._2))
  val producerConfig = new ProducerConfig(props)

  def createProcuder() : Producer[String, String] = {
    new Producer[String, String](producerConfig)
  }
}

object EventProcessor extends App {

  // 启动了5个EventProcessor
  Seq("2951","2952", "2953", "2954", "2955") foreach { port =>
    val config = ConfigFactory.parseString("akka.remote.netty.tcp.port=" + port)
      .withFallback(ConfigFactory.parseString("akka.cluster.roles = [processor]"))
      .withFallback(ConfigFactory.load())
    val system = ActorSystem("event-cluster-system", config)
    val processingActor = system.actorOf(Props[EventProcessor], name = "processingActor")
    system.log.info("Processing Actor: " + processingActor)
  }
}

角色为processor的Actor的实现类为EventProcessor，我们在其伴生对象中创建了5个实例，分别对应不同的端口。解析的Nginx日志记录最后保存到Kafka，示例如下所示：

{"installid":"0000VACO","imsi":"460012927613645","network":"1","action":"1840","type":"1","eventdate":"2015-08-21 18:29:19","realip":"61.175.219.69"}
{"installid":"0000kcpz","sessionid":"cbc7bbb560914c374cb7a29eef8c21441440152816008","operator":"1","timestamp":"1440152873","eventcode":"200003","radioid":"1100000046018","eventdate":"2015-08-21 18:29:19","realip":"119.128.106.232"}
{"installid":"0000lAOX","sessionid":"25371384b2eb1a5dc5643e14626ecbd41440152875362","operator":"1","timestamp":"1440152954","eventcode":"300039","eventdate":"2015-08-21 18:29:19","realip":"121.25.190.146"}

参考链接

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评论(4)： “Akka Cluster原理与应用”

  2. 您好，因為圖實在太好看了，請問可以在公司內部投影片引用嗎？會附上連結跟備註

    回复

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