[SPARK-9602] remove "Akka/Actor" words from comments
https://issues.apache.org/jira/browse/SPARK-9602 Although we have hidden Akka behind RPC interface, I found that the Akka/Actor-related comments are still spreading everywhere. To make it consistent, we shall remove "actor"/"akka" words from the comments... Author: CodingCat <zhunansjtu@gmail.com> Closes #7936 from CodingCat/SPARK-9602 and squashes the following commits: e8296a3 [CodingCat] remove actor words from comments
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CodingCat
Reynold Xin
parent
ab8ee1a3b9
commit
9d668b7368
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@ -794,7 +794,7 @@ private class PythonAccumulatorParam(@transient serverHost: String, serverPort:
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/**
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* We try to reuse a single Socket to transfer accumulator updates, as they are all added
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* by the DAGScheduler's single-threaded actor anyway.
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* by the DAGScheduler's single-threaded RpcEndpoint anyway.
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*/
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@transient var socket: Socket = _
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@ -73,12 +73,8 @@ class LocalSparkCluster(
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def stop() {
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logInfo("Shutting down local Spark cluster.")
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// Stop the workers before the master so they don't get upset that it disconnected
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// TODO: In Akka 2.1.x, ActorSystem.awaitTermination hangs when you have remote actors!
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// This is unfortunate, but for now we just comment it out.
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workerRpcEnvs.foreach(_.shutdown())
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// workerActorSystems.foreach(_.awaitTermination())
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masterRpcEnvs.foreach(_.shutdown())
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// masterActorSystems.foreach(_.awaitTermination())
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masterRpcEnvs.clear()
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workerRpcEnvs.clear()
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}
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@ -257,7 +257,7 @@ private[spark] class AppClient(
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}
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def start() {
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// Just launch an actor; it will call back into the listener.
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// Just launch an rpcEndpoint; it will call back into the listener.
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endpoint = rpcEnv.setupEndpoint("AppClient", new ClientEndpoint(rpcEnv))
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}
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@ -26,7 +26,7 @@ import org.apache.spark.annotation.DeveloperApi
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*/
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@DeveloperApi
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trait LeaderElectionAgent {
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val masterActor: LeaderElectable
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val masterInstance: LeaderElectable
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def stop() {} // to avoid noops in implementations.
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}
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@ -37,7 +37,7 @@ trait LeaderElectable {
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}
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/** Single-node implementation of LeaderElectionAgent -- we're initially and always the leader. */
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private[spark] class MonarchyLeaderAgent(val masterActor: LeaderElectable)
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private[spark] class MonarchyLeaderAgent(val masterInstance: LeaderElectable)
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extends LeaderElectionAgent {
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masterActor.electedLeader()
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masterInstance.electedLeader()
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}
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@ -38,5 +38,5 @@ private[master] object MasterMessages {
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case object BoundPortsRequest
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case class BoundPortsResponse(actorPort: Int, webUIPort: Int, restPort: Option[Int])
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case class BoundPortsResponse(rpcEndpointPort: Int, webUIPort: Int, restPort: Option[Int])
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}
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@ -22,7 +22,7 @@ import org.apache.curator.framework.CuratorFramework
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import org.apache.curator.framework.recipes.leader.{LeaderLatchListener, LeaderLatch}
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import org.apache.spark.deploy.SparkCuratorUtil
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private[master] class ZooKeeperLeaderElectionAgent(val masterActor: LeaderElectable,
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private[master] class ZooKeeperLeaderElectionAgent(val masterInstance: LeaderElectable,
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conf: SparkConf) extends LeaderLatchListener with LeaderElectionAgent with Logging {
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val WORKING_DIR = conf.get("spark.deploy.zookeeper.dir", "/spark") + "/leader_election"
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@ -73,10 +73,10 @@ private[master] class ZooKeeperLeaderElectionAgent(val masterActor: LeaderElecta
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private def updateLeadershipStatus(isLeader: Boolean) {
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if (isLeader && status == LeadershipStatus.NOT_LEADER) {
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status = LeadershipStatus.LEADER
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masterActor.electedLeader()
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masterInstance.electedLeader()
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} else if (!isLeader && status == LeadershipStatus.LEADER) {
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status = LeadershipStatus.NOT_LEADER
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masterActor.revokedLeadership()
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masterInstance.revokedLeadership()
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}
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}
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@ -228,7 +228,7 @@ private[deploy] class Worker(
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/**
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* Re-register with the master because a network failure or a master failure has occurred.
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* If the re-registration attempt threshold is exceeded, the worker exits with error.
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* Note that for thread-safety this should only be called from the actor.
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* Note that for thread-safety this should only be called from the rpcEndpoint.
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*/
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private def reregisterWithMaster(): Unit = {
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Utils.tryOrExit {
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@ -365,7 +365,8 @@ private[deploy] class Worker(
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if (connected) { sendToMaster(Heartbeat(workerId, self)) }
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case WorkDirCleanup =>
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// Spin up a separate thread (in a future) to do the dir cleanup; don't tie up worker actor
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// Spin up a separate thread (in a future) to do the dir cleanup; don't tie up worker
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// rpcEndpoint.
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// Copy ids so that it can be used in the cleanup thread.
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val appIds = executors.values.map(_.appId).toSet
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val cleanupFuture = concurrent.future {
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@ -684,7 +685,7 @@ private[deploy] object Worker extends Logging {
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workerNumber: Option[Int] = None,
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conf: SparkConf = new SparkConf): RpcEnv = {
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// The LocalSparkCluster runs multiple local sparkWorkerX actor systems
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// The LocalSparkCluster runs multiple local sparkWorkerX RPC Environments
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val systemName = SYSTEM_NAME + workerNumber.map(_.toString).getOrElse("")
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val securityMgr = new SecurityManager(conf)
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val rpcEnv = RpcEnv.create(systemName, host, port, conf, securityMgr)
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@ -43,7 +43,7 @@ private[spark] class WorkerWatcher(override val rpcEnv: RpcEnv, workerUrl: Strin
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private[deploy] def setTesting(testing: Boolean) = isTesting = testing
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private var isTesting = false
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// Lets us filter events only from the worker's actor system
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// Lets filter events only from the worker's rpc system
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private val expectedAddress = RpcAddress.fromURIString(workerUrl)
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private def isWorker(address: RpcAddress) = expectedAddress == address
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@ -62,7 +62,7 @@ private[spark] class WorkerWatcher(override val rpcEnv: RpcEnv, workerUrl: Strin
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override def onDisconnected(remoteAddress: RpcAddress): Unit = {
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if (isWorker(remoteAddress)) {
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// This log message will never be seen
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logError(s"Lost connection to worker actor $workerUrl. Exiting.")
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logError(s"Lost connection to worker rpc endpoint $workerUrl. Exiting.")
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exitNonZero()
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}
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}
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@ -100,7 +100,7 @@ private[spark] abstract class RpcEndpointRef(@transient conf: SparkConf)
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val future = ask[T](message, timeout)
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val result = timeout.awaitResult(future)
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if (result == null) {
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throw new SparkException("Actor returned null")
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throw new SparkException("RpcEndpoint returned null")
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}
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return result
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} catch {
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@ -162,7 +162,7 @@ private[spark] class OutputCommitCoordinator(conf: SparkConf, isDriver: Boolean)
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private[spark] object OutputCommitCoordinator {
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// This actor is used only for RPC
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// This endpoint is used only for RPC
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private[spark] class OutputCommitCoordinatorEndpoint(
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override val rpcEnv: RpcEnv, outputCommitCoordinator: OutputCommitCoordinator)
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extends RpcEndpoint with Logging {
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@ -22,7 +22,7 @@ import org.apache.spark.rpc.{RpcEndpointRef, RpcAddress}
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/**
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* Grouping of data for an executor used by CoarseGrainedSchedulerBackend.
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*
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* @param executorEndpoint The ActorRef representing this executor
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* @param executorEndpoint The RpcEndpointRef representing this executor
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* @param executorAddress The network address of this executor
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* @param executorHost The hostname that this executor is running on
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* @param freeCores The current number of cores available for work on the executor
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@ -22,10 +22,10 @@ import java.util.concurrent.atomic.AtomicInteger
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/**
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* A util used to get a unique generation ID. This is a wrapper around Java's
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* AtomicInteger. An example usage is in BlockManager, where each BlockManager
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* instance would start an Akka actor and we use this utility to assign the Akka
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* actors unique names.
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* instance would start an RpcEndpoint and we use this utility to assign the RpcEndpoints'
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* unique names.
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*/
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private[spark] class IdGenerator {
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private var id = new AtomicInteger
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private val id = new AtomicInteger
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def next: Int = id.incrementAndGet
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}
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@ -99,7 +99,7 @@ object CustomPersistenceEngine {
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@volatile var lastInstance: Option[CustomPersistenceEngine] = None
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}
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class CustomLeaderElectionAgent(val masterActor: LeaderElectable) extends LeaderElectionAgent {
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masterActor.electedLeader()
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class CustomLeaderElectionAgent(val masterInstance: LeaderElectable) extends LeaderElectionAgent {
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masterInstance.electedLeader()
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}
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@ -38,12 +38,11 @@ class WorkerWatcherSuite extends SparkFunSuite {
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val conf = new SparkConf()
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val rpcEnv = RpcEnv.create("test", "localhost", 12345, conf, new SecurityManager(conf))
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val targetWorkerUrl = rpcEnv.uriOf("test", RpcAddress("1.2.3.4", 1234), "Worker")
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val otherAddress = "akka://test@4.3.2.1:1234/user/OtherActor"
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val otherAkkaAddress = RpcAddress("4.3.2.1", 1234)
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val otherRpcAddress = RpcAddress("4.3.2.1", 1234)
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val workerWatcher = new WorkerWatcher(rpcEnv, targetWorkerUrl)
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workerWatcher.setTesting(testing = true)
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rpcEnv.setupEndpoint("worker-watcher", workerWatcher)
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workerWatcher.onDisconnected(otherAkkaAddress)
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workerWatcher.onDisconnected(otherRpcAddress)
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assert(!workerWatcher.isShutDown)
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rpcEnv.shutdown()
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}
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@ -182,7 +182,7 @@ object MimaExcludes {
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ProblemFilters.exclude[IncompatibleResultTypeProblem](
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"org.apache.spark.broadcast.TorrentBroadcastFactory.newBroadcast"),
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ProblemFilters.exclude[MissingClassProblem](
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"org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorActor")
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"org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint")
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) ++ Seq(
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// SPARK-4655 - Making Stage an Abstract class broke binary compatility even though
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// the stage class is defined as private[spark]
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@ -981,7 +981,7 @@ class SparkILoop(
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// which spins off a separate thread, then print the prompt and try
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// our best to look ready. The interlocking lazy vals tend to
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// inter-deadlock, so we break the cycle with a single asynchronous
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// message to an actor.
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// message to an rpcEndpoint.
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if (isAsync) {
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intp initialize initializedCallback()
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createAsyncListener() // listens for signal to run postInitialization
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