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From vanzin <...@git.apache.org>
Subject [GitHub] spark pull request #19468: [SPARK-18278] [Scheduler] Spark on Kubernetes - B...
Date Tue, 17 Oct 2017 21:29:47 GMT
Github user vanzin commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19468#discussion_r145260359
  
    --- Diff: resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackendSuite.scala
---
    @@ -0,0 +1,378 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +package org.apache.spark.scheduler.cluster.k8s
    +
    +import java.util.concurrent.{ExecutorService, ScheduledExecutorService, TimeUnit}
    +
    +import scala.collection.JavaConverters._
    +import scala.concurrent.Future
    +
    +import io.fabric8.kubernetes.api.model.{DoneablePod, Pod, PodBuilder, PodList}
    +import io.fabric8.kubernetes.client.{KubernetesClient, Watch, Watcher}
    +import io.fabric8.kubernetes.client.Watcher.Action
    +import io.fabric8.kubernetes.client.dsl.{FilterWatchListDeletable, MixedOperation, NonNamespaceOperation,
PodResource}
    +import org.mockito.{AdditionalAnswers, ArgumentCaptor, Mock, MockitoAnnotations}
    +import org.mockito.Matchers.{any, eq => mockitoEq}
    +import org.mockito.Mockito.{mock => _, _}
    +import org.scalatest.BeforeAndAfter
    +import org.scalatest.mock.MockitoSugar._
    +
    +import org.apache.spark.{SparkConf, SparkContext, SparkFunSuite}
    +import org.apache.spark.deploy.k8s.config._
    +import org.apache.spark.deploy.k8s.constants._
    +import org.apache.spark.rpc._
    +import org.apache.spark.scheduler.{ExecutorExited, LiveListenerBus, SlaveLost, TaskSchedulerImpl}
    +import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.{RegisterExecutor,
RemoveExecutor}
    +import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
    +
    +private[spark] class KubernetesClusterSchedulerBackendSuite
    +    extends SparkFunSuite with BeforeAndAfter {
    +
    +  private val APP_ID = "test-spark-app"
    +  private val DRIVER_POD_NAME = "spark-driver-pod"
    +  private val NAMESPACE = "test-namespace"
    +  private val SPARK_DRIVER_HOST = "localhost"
    +  private val SPARK_DRIVER_PORT = 7077
    +  private val POD_ALLOCATION_INTERVAL = 60L
    +  private val DRIVER_URL = RpcEndpointAddress(
    +      SPARK_DRIVER_HOST, SPARK_DRIVER_PORT, CoarseGrainedSchedulerBackend.ENDPOINT_NAME).toString
    +  private val FIRST_EXECUTOR_POD = new PodBuilder()
    +    .withNewMetadata()
    +      .withName("pod1")
    +      .endMetadata()
    +    .withNewSpec()
    +      .withNodeName("node1")
    +      .endSpec()
    +    .withNewStatus()
    +      .withHostIP("192.168.99.100")
    +      .endStatus()
    +    .build()
    +  private val SECOND_EXECUTOR_POD = new PodBuilder()
    +    .withNewMetadata()
    +      .withName("pod2")
    +      .endMetadata()
    +    .withNewSpec()
    +      .withNodeName("node2")
    +      .endSpec()
    +    .withNewStatus()
    +      .withHostIP("192.168.99.101")
    +      .endStatus()
    +    .build()
    +
    +  private type PODS = MixedOperation[Pod, PodList, DoneablePod, PodResource[Pod, DoneablePod]]
    +  private type LABELLED_PODS = FilterWatchListDeletable[
    +      Pod, PodList, java.lang.Boolean, Watch, Watcher[Pod]]
    +  private type IN_NAMESPACE_PODS = NonNamespaceOperation[
    +      Pod, PodList, DoneablePod, PodResource[Pod, DoneablePod]]
    +
    +  @Mock
    +  private var sparkContext: SparkContext = _
    +
    +  @Mock
    +  private var listenerBus: LiveListenerBus = _
    +
    +  @Mock
    +  private var taskSchedulerImpl: TaskSchedulerImpl = _
    +
    +  @Mock
    +  private var allocatorExecutor: ScheduledExecutorService = _
    +
    +  @Mock
    +  private var requestExecutorsService: ExecutorService = _
    +
    +  @Mock
    +  private var executorPodFactory: ExecutorPodFactory = _
    +
    +  @Mock
    +  private var kubernetesClient: KubernetesClient = _
    +
    +  @Mock
    +  private var podOperations: PODS = _
    +
    +  @Mock
    +  private var podsWithLabelOperations: LABELLED_PODS = _
    +
    +  @Mock
    +  private var podsInNamespace: IN_NAMESPACE_PODS = _
    +
    +  @Mock
    +  private var podsWithDriverName: PodResource[Pod, DoneablePod] = _
    +
    +  @Mock
    +  private var rpcEnv: RpcEnv = _
    +
    +  @Mock
    +  private var driverEndpointRef: RpcEndpointRef = _
    +
    +  @Mock
    +  private var executorPodsWatch: Watch = _
    +
    +  private var sparkConf: SparkConf = _
    +  private var executorPodsWatcherArgument: ArgumentCaptor[Watcher[Pod]] = _
    +  private var allocatorRunnable: ArgumentCaptor[Runnable] = _
    +  private var requestExecutorRunnable: ArgumentCaptor[Runnable] = _
    +  private var driverEndpoint: ArgumentCaptor[RpcEndpoint] = _
    +
    +  private val driverPod = new PodBuilder()
    +    .withNewMetadata()
    +      .withName(DRIVER_POD_NAME)
    +      .addToLabels(SPARK_APP_ID_LABEL, APP_ID)
    +      .addToLabels(SPARK_ROLE_LABEL, SPARK_POD_DRIVER_ROLE)
    +      .endMetadata()
    +    .build()
    +
    +  before {
    +    MockitoAnnotations.initMocks(this)
    +    sparkConf = new SparkConf()
    +        .set("spark.app.id", APP_ID)
    +        .set(KUBERNETES_DRIVER_POD_NAME, DRIVER_POD_NAME)
    +        .set(KUBERNETES_NAMESPACE, NAMESPACE)
    +        .set("spark.driver.host", SPARK_DRIVER_HOST)
    +        .set("spark.driver.port", SPARK_DRIVER_PORT.toString)
    +        .set(KUBERNETES_ALLOCATION_BATCH_DELAY, POD_ALLOCATION_INTERVAL)
    +    executorPodsWatcherArgument = ArgumentCaptor.forClass(classOf[Watcher[Pod]])
    +    allocatorRunnable = ArgumentCaptor.forClass(classOf[Runnable])
    +    requestExecutorRunnable = ArgumentCaptor.forClass(classOf[Runnable])
    +    driverEndpoint = ArgumentCaptor.forClass(classOf[RpcEndpoint])
    +    when(sparkContext.conf).thenReturn(sparkConf)
    +    when(sparkContext.listenerBus).thenReturn(listenerBus)
    +    when(taskSchedulerImpl.sc).thenReturn(sparkContext)
    +    when(kubernetesClient.pods()).thenReturn(podOperations)
    +    when(podOperations.withLabel(SPARK_APP_ID_LABEL, APP_ID)).thenReturn(podsWithLabelOperations)
    +    when(podsWithLabelOperations.watch(executorPodsWatcherArgument.capture()))
    +        .thenReturn(executorPodsWatch)
    +    when(podOperations.inNamespace(NAMESPACE)).thenReturn(podsInNamespace)
    +    when(podsInNamespace.withName(DRIVER_POD_NAME)).thenReturn(podsWithDriverName)
    +    when(podsWithDriverName.get()).thenReturn(driverPod)
    +    when(allocatorExecutor.scheduleWithFixedDelay(
    +        allocatorRunnable.capture(),
    +        mockitoEq(0L),
    +        mockitoEq(POD_ALLOCATION_INTERVAL),
    +        mockitoEq(TimeUnit.SECONDS))).thenReturn(null)
    +    // Creating Futures in Scala backed by a Java executor service resolves to running
    +    // ExecutorService#execute (as opposed to submit)
    +    doNothing().when(requestExecutorsService).execute(requestExecutorRunnable.capture())
    +    when(rpcEnv.setupEndpoint(
    +        mockitoEq(CoarseGrainedSchedulerBackend.ENDPOINT_NAME), driverEndpoint.capture()))
    +        .thenReturn(driverEndpointRef)
    +    when(driverEndpointRef.ask[Boolean]
    +      (any(classOf[Any]))
    +      (any())).thenReturn(mock[Future[Boolean]])
    +  }
    +
    +  test("Basic lifecycle expectations when starting and stopping the scheduler.") {
    +    val scheduler = newSchedulerBackend()
    +    scheduler.start()
    +    assert(executorPodsWatcherArgument.getValue != null)
    +    assert(allocatorRunnable.getValue != null)
    +    scheduler.stop()
    +    verify(executorPodsWatch).close()
    +  }
    +
    +  test("Static allocation should request executors upon first allocator run.") {
    +    sparkConf
    +        .set(KUBERNETES_ALLOCATION_BATCH_SIZE, 2)
    +        .set(org.apache.spark.internal.config.EXECUTOR_INSTANCES, 2)
    +    val scheduler = newSchedulerBackend()
    +    scheduler.start()
    +    requestExecutorRunnable.getValue.run()
    +    expectPodCreationWithId(1, FIRST_EXECUTOR_POD)
    +    expectPodCreationWithId(2, SECOND_EXECUTOR_POD)
    +    when(podOperations.create(any(classOf[Pod]))).thenAnswer(AdditionalAnswers.returnsFirstArg())
    +    allocatorRunnable.getValue.run()
    +    verify(podOperations).create(FIRST_EXECUTOR_POD)
    +    verify(podOperations).create(SECOND_EXECUTOR_POD)
    +  }
    +
    +  test("Killing executors deletes the executor pods") {
    +    sparkConf
    +        .set(KUBERNETES_ALLOCATION_BATCH_SIZE, 2)
    +        .set(org.apache.spark.internal.config.EXECUTOR_INSTANCES, 2)
    +    val scheduler = newSchedulerBackend()
    +    scheduler.start()
    +    requestExecutorRunnable.getValue.run()
    +    expectPodCreationWithId(1, FIRST_EXECUTOR_POD)
    +    expectPodCreationWithId(2, SECOND_EXECUTOR_POD)
    +    when(podOperations.create(any(classOf[Pod])))
    +        .thenAnswer(AdditionalAnswers.returnsFirstArg())
    +    allocatorRunnable.getValue.run()
    +    scheduler.doKillExecutors(Seq("2"))
    +    requestExecutorRunnable.getAllValues.asScala.last.run()
    +    verify(podOperations).delete(SECOND_EXECUTOR_POD)
    +    verify(podOperations, never()).delete(FIRST_EXECUTOR_POD)
    +  }
    +
    +  test("Executors should be requested in batches.") {
    +    sparkConf
    +        .set(KUBERNETES_ALLOCATION_BATCH_SIZE, 1)
    +        .set(org.apache.spark.internal.config.EXECUTOR_INSTANCES, 2)
    +    val scheduler = newSchedulerBackend()
    +    scheduler.start()
    +    requestExecutorRunnable.getValue.run()
    +    when(podOperations.create(any(classOf[Pod])))
    +      .thenAnswer(AdditionalAnswers.returnsFirstArg())
    +    expectPodCreationWithId(1, FIRST_EXECUTOR_POD)
    +    expectPodCreationWithId(2, SECOND_EXECUTOR_POD)
    +    allocatorRunnable.getValue.run()
    +    verify(podOperations).create(FIRST_EXECUTOR_POD)
    +    verify(podOperations, never()).create(SECOND_EXECUTOR_POD)
    +    val registerFirstExecutorMessage = RegisterExecutor(
    +        "1", mock[RpcEndpointRef], "localhost", 1, Map.empty[String, String])
    +    when(taskSchedulerImpl.resourceOffers(any())).thenReturn(Seq.empty)
    +    driverEndpoint.getValue.receiveAndReply(mock[RpcCallContext])
    +        .apply(registerFirstExecutorMessage)
    +    allocatorRunnable.getValue.run()
    +    verify(podOperations).create(SECOND_EXECUTOR_POD)
    +  }
    +
    +  test("Deleting executors and then running an allocator pass after finding the loss
reason" +
    --- End diff --
    
    shorter test name?


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