Akka是一种消息驱动运算模式，它实现跨JVM程序运算的方式是通过能跨JVM的消息系统来调动分布在不同JVM上ActorSystem中的Actor进行运算，前题是Akka的地址系统可以支持跨JVM定位。Akka的消息系统最高境界可以实现所谓的Actor位置透明化，这样在Akka编程中就无须关注Actor具体在哪个JVM上运行，分布式Actor编程从方式上跟普通Actor编程就不会有什么区别了。Akka的Remoting是一种点对点的跨JVM消息通道，让一个JVM上ActorSystem中的某个Actor可以连接另一个JVM上ActorSystem中的另一个Actor。两个JVM上的ActorSystem之间只需具备TCP网络连接功能就可以实现Akka Remoting了。Akka-Remoting还没有实现完全的位置透明化，因为用户还必须在代码里或者配置文件里指明目标Actor的具体地址。
Akka-Remoting提供了两种Actor之间的沟通方法：
1、远程查找：通过路径Path查找在远程机上已经创建存在的Actor，获取ActorRef后进行沟通
2、远程创建：在远程机上直接创建Actor作为沟通对象
Akka-Remoting的主要应用应该是把一些任务部署到远程机上去运算。发起方（Local JVM）在这里面的主要作用是任务分配，有点像Akka-Router。我们可以用下面的例子来示范：模拟一个计算器，可以进行连续的加减乘除，保留累计结果。我们会把这个计算器部署到远程机上，然后从本机与之沟通分配运算任务及获取运算结果。这个计算器就是个简单的Actor：
import akka.actor._
object Calculator {
sealed trait MathOps
case class Num(dnum: Double) extends MathOps
case class Add(dnum: Double) extends MathOps
case class Sub(dnum: Double) extends MathOps
case class Mul(dnum: Double) extends MathOps
case class Div(dnum: Double) extends MathOps
sealed trait CalcOps
case object Clear extends CalcOps
case object GetResult extends CalcOps
}
class Calcultor extends Actor {
import Calculator._
var result: Double = 0.0 //internal state
override def receive: Receive = {
case Num(d) => result = d
case Add(d) => result += d
case Sub(d) => result -= d
case Mul(d) => result *= d
case Div(d) => result = result / d
case Clear => result = 0.0
case GetResult =>
sender() ! s"Result of calculation is: $result"
}
}
就是一个简单的Actor实现，跟Remoting没什么关系。
下面我们会在一个远程机上部署这个Calculator Actor。 先看看这个示范的项目结构：remoteLookup/build.sbt
lazy val commonSettings = seq (
name := "RemoteLookupDemo",
version := "1.0",
scalaVersion := "2.11.8",
libraryDependencies := Seq(
"com.typesafe.akka" %% "akka-actor" % "2.5.2",
"com.typesafe.akka" %% "akka-remote" % "2.5.2"
)
) lazy val local = (project in file("."))
.settings(commonSettings)
.settings(
name := "localSystem"
).aggregate(messages,remote).dependsOn(messages) lazy val messages = (project in file("messages"))
.settings(commonSettings)
.settings(
name := "commands"
) lazy val remote = (project in file("remote"))
.settings(commonSettings)
.settings(
name := "remoteSystem"
).aggregate(messages).dependsOn(messages)
在这里我们分了三个项目：local是主项目，messages和remote是分项目（subprojects）。messages里只有OpsMessages.scala一个源文件：
package remoteLookup.messages
object Messages {
sealed trait MathOps
case class Num(dnum: Double) extends MathOps
case class Add(dnum: Double) extends MathOps
case class Sub(dnum: Double) extends MathOps
case class Mul(dnum: Double) extends MathOps
case class Div(dnum: Double) extends MathOps
sealed trait CalcOps
case object Clear extends CalcOps
case object GetResult extends CalcOps
}
我们看到：这个文件是把上面的Calculator支持的消息拆了出来。这是因为Calculator Actor会在另一个JVM remote上部署，而我们会从local JVM里向Calculator发送操作消息，所以Messages必须是local和remote共享的。这个要求我们通过dependOn(messages)实现了。现在Calculator是在remote项目里定义的：remote/Calculator.scala
package remoteLookup.remote import akka.actor._
import remoteLookup.messages.Messages._ object CalcProps {
def props = Props(new Calcultor)
} class Calcultor extends Actor with ActorLogging { var result: Double = 0.0 //internal state override def receive: Receive = {
case Num(d) => result = d
case Add(d) => result += d
case Sub(d) => result -= d
case Mul(d) => result *= d
case Div(d) =>
val _ = result.toInt / d.toInt //yield ArithmeticException
result /= d
case Clear => result = 0.0
case GetResult =>
sender() ! s"Result of calculation is: $result"
} override def preRestart(reason: Throwable, message: Option[Any]): Unit = {
log.info(s"Restarting calculator: ${reason.getMessage}")
super.preRestart(reason, message)
}
}
由于ArithmeticException默认的处理策略SupervisorStrategy是Restart，一旦输入Div(0.0)时会重启将result清零。我们可以在remote上加一个Supervisor来把异常处理策略改为Resume。
下面我们先在remote项目本地对Calculator的功能进行测试：remote/CalculatorRunner.scala
package remoteLookup.remote
import akka.actor._
import akka.pattern._
import remoteLookup.messages.Messages._ import scala.concurrent.duration._ class SupervisorActor extends Actor {
def decider: PartialFunction[Throwable,SupervisorStrategy.Directive] = {
case _: ArithmeticException => SupervisorStrategy.Resume
} override def supervisorStrategy: SupervisorStrategy =
OneForOneStrategy(maxNrOfRetries = , withinTimeRange = seconds){
decider.orElse(SupervisorStrategy.defaultDecider)
} val calcActor = context.actorOf(CalcProps.props,"calculator") override def receive: Receive = {
case msg@ _ => calcActor.forward(msg)
} } object CalculatorRunner extends App { val remoteSystem = ActorSystem("remoteSystem")
val calcActor = remoteSystem.actorOf(Props[SupervisorActor],"supervisorActor") import remoteSystem.dispatcher calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5) implicit val timeout = akka.util.Timeout( second) ((calcActor ? GetResult).mapTo[String]) foreach println
scala.io.StdIn.readLine() calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println
scala.io.StdIn.readLine() remoteSystem.terminate() }
测试运算得出以下结果：
Result of calculation is: 19.5 Result of calculation is: 113.0
[WARN] [// ::10.720] [remoteSystem-akka.actor.default-dispatcher-] [akka://remoteSystem/user/parentActor/calculator] / by zero
supervisorActor实现了它应有的功能。
下面进行远程查找示范：首先，remote需要把Calculator向外发布。这可以通过配置文件设置实现：remote/src/main/resources/application.conf
akka {
actor {
provider = remote
}
remote {
enabled-transports = ["akka.remote.netty.tcp"]
netty.tcp {
hostname = "127.0.0.1"
port =
}
log-sent-messages = on
log-received-messages = on
}
}
上面这段的意思是：所有向外公开Actor的地址前缀为：akka.tcp://remoteSystem@127.0.0.1:2552/user/???
那么Calculator的完整地址path应该就是：akka.tcp://remoteSystem@127.0.0.1:2552/user/supervisorActor/calculator
Akka-Remoting提供了两种远程查找方式：actorSelection.resolveOne方法和Identify消息确认。无论如何，local都需要进行Remoting配置: local/src/main/resources/application.conf
akka {
actor {
provider = remote
}
remote {
enabled-transports = ["akka.remote.netty.tcp"]
netty.tcp {
hostname = "127.0.0.1"
port =
}
}
}
port=0的意思是由系统自动选择任何可用的端口。现在我们完成了Remoting设置，也得到了在远程机上Calculator的具体地址，应该足够进行远程Actor沟通了。我们先用actorSelection.resolveOne示范。resolveOne源代码如下：
/**
* Resolve the [[ActorRef]] matching this selection.
* The result is returned as a Future that is completed with the [[ActorRef]]
* if such an actor exists. It is completed with failure [[ActorNotFound]] if
* no such actor exists or the identification didn't complete within the
* supplied `timeout`.
*
* Under the hood it talks to the actor to verify its existence and acquire its
* [[ActorRef]].
*/
def resolveOne()(implicit timeout: Timeout): Future[ActorRef] = {
implicit val ec = ExecutionContexts.sameThreadExecutionContext
val p = Promise[ActorRef]()
this.ask(Identify(None)) onComplete {
case Success(ActorIdentity(_, Some(ref))) ⇒ p.success(ref)
case _ ⇒ p.failure(ActorNotFound(this))
}
p.future
}
resolveOne返回Future[ActorRef]，我们可以用Future的函数组件（combinator）来操作：localAccessDemo.scala
import akka.actor._
import akka.util.Timeout
import scala.concurrent.duration._
import akka.pattern._
import remoteLookup.messages.Messages._ object LocalSelectionDemo extends App { val localSystem = ActorSystem("localSystem")
import localSystem.dispatcher val path = "akka.tcp://remoteSystem@127.0.0.1:2552/user/supervisorActor/calculator" implicit val timeout = Timeout( seconds)
for (calcActor : ActorRef <- localSystem.actorSelection(path).resolveOne()) { calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5)
((calcActor ? GetResult).mapTo[String]) foreach println calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println } scala.io.StdIn.readLine()
localSystem.terminate() }
因为resolveOne返回的是个Future[x]，我们可以用for来对嵌在Future内的x进行操作。现在remoteSystem只需要构建Calculator待用就行了：remote/CalculatorRunner.scala
package remoteLookup.remote
import akka.actor._
import akka.pattern._
import remoteLookup.messages.Messages._ import scala.concurrent.duration._ class SupervisorActor extends Actor {
def decider: PartialFunction[Throwable,SupervisorStrategy.Directive] = {
case _: ArithmeticException => SupervisorStrategy.Resume
} override def supervisorStrategy: SupervisorStrategy =
OneForOneStrategy(maxNrOfRetries = , withinTimeRange = seconds){
decider.orElse(SupervisorStrategy.defaultDecider)
} val calcActor = context.actorOf(CalcProps.props,"calculator") override def receive: Receive = {
case msg@ _ => calcActor.forward(msg)
} } object CalculatorRunner extends App { val remoteSystem = ActorSystem("remoteSystem")
val calcActor = remoteSystem.actorOf(Props[SupervisorActor],"supervisorActor")
/*
import remoteSystem.dispatcher calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5) implicit val timeout = akka.util.Timeout(1 second) ((calcActor ? GetResult).mapTo[String]) foreach println
scala.io.StdIn.readLine() calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println
*/
scala.io.StdIn.readLine()
remoteSystem.terminate() }
注意：注销的操作转移到了localSelectionDemo里。
先运行remote项目：
INFO] [// ::37.955] [main] [akka.remote.Remoting] Starting remoting
[INFO] [// ::38.091] [main] [akka.remote.Remoting] Remoting started; listening on addresses :[akka.tcp://remoteSystem@127.0.0.1:2552]
[INFO] [// ::38.092] [main] [akka.remote.Remoting] Remoting now listens on addresses: [akka.tcp://remoteSystem@127.0.0.1:2552]
remoteSystem开始监视配置的公开地址。
用sbt run 运行local：
Result of calculation is: 19.5
Result of calculation is: 113.0
结果正确。supervisorActor的SupervisorStrategy起到了应有的作用。
remote项目输出显示也能证明：
[INFO] [// ::37.955] [main] [akka.remote.Remoting] Starting remoting
[INFO] [// ::38.091] [main] [akka.remote.Remoting] Remoting started; listening on addresses :[akka.tcp://remoteSystem@127.0.0.1:2552]
[INFO] [// ::38.092] [main] [akka.remote.Remoting] Remoting now listens on addresses: [akka.tcp://remoteSystem@127.0.0.1:2552]
[WARN] [// ::06.330] [remoteSystem-akka.actor.default-dispatcher-] [akka://remoteSystem/user/supervisorActor/calculator] / by zero
[ERROR] [// ::34.176] [remoteSystem-akka.remote.default-remote-dispatcher-] [akka.tcp://remoteSystem@127.0.0.1:2552/system/endpointManager/reliableEndpointWriter-akka.tcp%3A%2F%2FlocalSystem%40127.0.0.1%3A60601-0/endpointWriter] AssociationError [akka.tcp://remoteSystem@127.0.0.1:2552] <- [akka.tcp://localSystem@127.0.0.1:60601]: Error [Shut down address: akka.tcp://localSystem@127.0.0.1:60601] [
akka.remote.ShutDownAssociation: Shut down address: akka.tcp://localSystem@127.0.0.1:60601
Caused by: akka.remote.transport.Transport$InvalidAssociationException: The remote system terminated the association because it is shutting down.
]
下面我们试着用Identify消息确认方式来复演上述例子。Akka是如下这样定义有关Identify消息确认的：
/**
* A message all Actors will understand, that when processed will reply with
* [[akka.actor.ActorIdentity]] containing the `ActorRef`. The `messageId`
* is returned in the `ActorIdentity` message as `correlationId`.
*/
@SerialVersionUID(1L)
final case class Identify(messageId: Any) extends AutoReceivedMessage with NotInfluenceReceiveTimeout /**
* Reply to [[akka.actor.Identify]]. Contains
* `Some(ref)` with the `ActorRef` of the actor replying to the request or
* `None` if no actor matched the request.
* The `correlationId` is taken from the `messageId` in
* the `Identify` message.
*/
@SerialVersionUID(1L)
final case class ActorIdentity(correlationId: Any, ref: Option[ActorRef]) {
if (ref.isDefined && ref.get == null) {
throw new IllegalArgumentException("ActorIdentity created with ref = Some(null) is not allowed, " +
"this could happen when serializing with Scala 2.12 and deserializing with Scala 2.11 which is not supported.")
} /**
* Java API: `ActorRef` of the actor replying to the request or
* null if no actor matched the request.
*/
@deprecated("Use getActorRef instead", "2.5.0")
def getRef: ActorRef = ref.orNull /**
* Java API: `ActorRef` of the actor replying to the request or
* not defined if no actor matched the request.
*/
def getActorRef: Optional[ActorRef] = {
import scala.compat.java8.OptionConverters._
ref.asJava
}
}
如果拿上面的例子，我们就会向远程机上的Calculator地址发送Identify(path)，而Calculator返回ActorIdentity消息，参数包括correlationId = path, ref = Calculator的ActorRef。 下面是使用示范代码：
object LocalIdentifyDemo extends App {
class RemoteCalc extends Actor with ActorLogging {
val path = "akka.tcp://remoteSystem@127.0.0.1:2552/user/supervisorActor/calculator"
context.actorSelection(path) ! Identify(path) //send req for ActorRef
import context.dispatcher
implicit val timeout = Timeout( seconds)
override def receive: Receive = {
case ActorIdentity(p,someRef) if p.equals(path) =>
someRef foreach { calcActor =>
calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5)
((calcActor ? GetResult).mapTo[String]) foreach println
calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println
}
}
}
val localSystem = ActorSystem("localSystem")
val localActor = localSystem.actorOf(Props[RemoteCalc],"localActor")
scala.io.StdIn.readLine()
localSystem.terminate()
}
Identify消息确认机制是一种Actor沟通模式，所以我们需要构建一个RemoteCalc Actor，把程序包嵌在这个Actor里面。当receive收到确认消息ActorIdentity后获取ActorRef运算程序。
查看运算结果，正确。
下面是这次示范的完整源代码：
build.sbt
lazy val commonSettings = seq (
name := "RemoteLookupDemo",
version := "1.0",
scalaVersion := "2.11.8",
libraryDependencies := Seq(
"com.typesafe.akka" %% "akka-actor" % "2.5.2",
"com.typesafe.akka" %% "akka-remote" % "2.5.2"
)
) lazy val local = (project in file("."))
.settings(commonSettings)
.settings(
name := "remoteLookupDemo"
).aggregate(messages,remote).dependsOn(messages) lazy val messages = (project in file("messages"))
.settings(commonSettings)
.settings(
name := "commands"
) lazy val remote = (project in file("remote"))
.settings(commonSettings)
.settings(
name := "remoteSystem"
).aggregate(messages).dependsOn(messages)
messages/OpsMessages.scala
package remoteLookup.messages
object Messages {
sealed trait MathOps
case class Num(dnum: Double) extends MathOps
case class Add(dnum: Double) extends MathOps
case class Sub(dnum: Double) extends MathOps
case class Mul(dnum: Double) extends MathOps
case class Div(dnum: Double) extends MathOps
sealed trait CalcOps
case object Clear extends CalcOps
case object GetResult extends CalcOps
}
remote/src/main/resources/application.conf
akka {
actor {
provider = remote
}
remote {
enabled-transports = ["akka.remote.netty.tcp"]
netty.tcp {
hostname = "127.0.0.1"
port =
}
log-sent-messages = on
log-received-messages = on
}
}
remote/Calculator.scala
package remoteLookup.remote import akka.actor._
import remoteLookup.messages.Messages._ object CalcProps {
def props = Props(new Calcultor)
} class Calcultor extends Actor with ActorLogging { var result: Double = 0.0 //internal state override def receive: Receive = {
case Num(d) => result = d
case Add(d) => result += d
case Sub(d) => result -= d
case Mul(d) => result *= d
case Div(d) =>
val _ = result.toInt / d.toInt //yield ArithmeticException
result /= d
case Clear => result = 0.0
case GetResult =>
sender() ! s"Result of calculation is: $result"
} override def preRestart(reason: Throwable, message: Option[Any]): Unit = {
log.info(s"Restarting calculator: ${reason.getMessage}")
super.preRestart(reason, message)
}
}
remote/CalculatorRunner.scala
package remoteLookup.remote
import akka.actor._
import akka.pattern._
import remoteLookup.messages.Messages._ import scala.concurrent.duration._ class SupervisorActor extends Actor {
def decider: PartialFunction[Throwable,SupervisorStrategy.Directive] = {
case _: ArithmeticException => SupervisorStrategy.Resume
} override def supervisorStrategy: SupervisorStrategy =
OneForOneStrategy(maxNrOfRetries = , withinTimeRange = seconds){
decider.orElse(SupervisorStrategy.defaultDecider)
} val calcActor = context.actorOf(CalcProps.props,"calculator") override def receive: Receive = {
case msg@ _ => calcActor.forward(msg)
} } object CalculatorRunner extends App { val remoteSystem = ActorSystem("remoteSystem")
val calcActor = remoteSystem.actorOf(Props[SupervisorActor],"supervisorActor")
/*
import remoteSystem.dispatcher calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5) implicit val timeout = akka.util.Timeout(1 second) ((calcActor ? GetResult).mapTo[String]) foreach println
scala.io.StdIn.readLine() calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println
*/
scala.io.StdIn.readLine()
remoteSystem.terminate() }
local/src/main/resources/application.conf
akka {
actor {
provider = remote
}
remote {
enabled-transports = ["akka.remote.netty.tcp"]
netty.tcp {
hostname = "127.0.0.1"
port =
}
}
}
local/localAccessDemo.scala
import akka.actor._
import akka.util.Timeout
import scala.concurrent.duration._
import akka.pattern._
import remoteLookup.messages.Messages._ object LocalSelectionDemo extends App { val localSystem = ActorSystem("localSystem")
import localSystem.dispatcher val path = "akka.tcp://remoteSystem@127.0.0.1:2552/user/supervisorActor/calculator" implicit val timeout = Timeout( seconds)
for (calcActor : ActorRef <- localSystem.actorSelection(path).resolveOne()) { calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5)
((calcActor ? GetResult).mapTo[String]) foreach println calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println } scala.io.StdIn.readLine()
localSystem.terminate() } object LocalIdentifyDemo extends App { class RemoteCalc extends Actor with ActorLogging { val path = "akka.tcp://remoteSystem@127.0.0.1:2552/user/supervisorActor/calculator" context.actorSelection(path) ! Identify(path) //semd req for ActorRef import context.dispatcher
implicit val timeout = Timeout( seconds) override def receive: Receive = {
case ActorIdentity(p,someRef) if p.equals(path) =>
someRef foreach { calcActor => calcActor ! Clear
calcActor ! Num(13.0)
calcActor ! Mul(1.5)
((calcActor ? GetResult).mapTo[String]) foreach println calcActor ! Div(0.0)
calcActor ! Div(1.5)
calcActor ! Add(100.0)
((calcActor ? GetResult).mapTo[String]) foreach println }
} } val localSystem = ActorSystem("localSystem")
val localActor = localSystem.actorOf(Props[RemoteCalc],"localActor") scala.io.StdIn.readLine()
localSystem.terminate() }