akka 原理（终于有人把AkkaCluster原理与应用讲明白了）
akka 原理（终于有人把AkkaCluster原理与应用讲明白了）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。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：通常，在基于Akka Cluster的应用中实现Actor时，可以重
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：
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：
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：
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×tamp=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×tamp=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×tamp=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×tamp=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×tamp=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×tamp=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×tamp=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×tamp=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"}
（原创 时延军 ，链接：http://shiyanjun.cn）
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