Github user liyinan926 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19468#discussion_r150959150
  
    --- Diff: 
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackend.scala
 ---
    @@ -0,0 +1,427 @@
    +/*
    + * 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.io.Closeable
    +import java.net.InetAddress
    +import java.util.concurrent.{ConcurrentHashMap, ExecutorService, 
ScheduledExecutorService, TimeUnit}
    +import java.util.concurrent.atomic.{AtomicInteger, AtomicLong, 
AtomicReference}
    +import javax.annotation.concurrent.GuardedBy
    +
    +import io.fabric8.kubernetes.api.model._
    +import io.fabric8.kubernetes.client.{KubernetesClient, 
KubernetesClientException, Watcher}
    +import io.fabric8.kubernetes.client.Watcher.Action
    +import scala.collection.JavaConverters._
    +import scala.collection.mutable
    +import scala.concurrent.{ExecutionContext, Future}
    +
    +import org.apache.spark.SparkException
    +import org.apache.spark.deploy.k8s.config._
    +import org.apache.spark.deploy.k8s.constants._
    +import org.apache.spark.rpc.{RpcAddress, RpcEndpointAddress, RpcEnv}
    +import org.apache.spark.scheduler.{ExecutorExited, SlaveLost, 
TaskSchedulerImpl}
    +import org.apache.spark.scheduler.cluster.{CoarseGrainedSchedulerBackend, 
SchedulerBackendUtils}
    +import org.apache.spark.util.Utils
    +
    +private[spark] class KubernetesClusterSchedulerBackend(
    +    scheduler: TaskSchedulerImpl,
    +    rpcEnv: RpcEnv,
    +    executorPodFactory: ExecutorPodFactory,
    +    kubernetesClient: KubernetesClient,
    +    allocatorExecutor: ScheduledExecutorService,
    +    requestExecutorsService: ExecutorService)
    +  extends CoarseGrainedSchedulerBackend(scheduler, rpcEnv) {
    +
    +  import KubernetesClusterSchedulerBackend._
    +
    +  private val EXECUTOR_ID_COUNTER = new AtomicLong(0L)
    +  private val RUNNING_EXECUTOR_PODS_LOCK = new Object
    +  @GuardedBy("RUNNING_EXECUTOR_PODS_LOCK")
    +  private val runningExecutorsToPods = new mutable.HashMap[String, Pod]
    +  private val executorPodsByIPs = new ConcurrentHashMap[String, Pod]()
    +  private val podsWithKnownExitReasons = new ConcurrentHashMap[String, 
ExecutorExited]()
    +  private val disconnectedPodsByExecutorIdPendingRemoval = new 
ConcurrentHashMap[String, Pod]()
    +
    +  private val kubernetesNamespace = conf.get(KUBERNETES_NAMESPACE)
    +
    +  private val kubernetesDriverPodName = conf
    +    .get(KUBERNETES_DRIVER_POD_NAME)
    +    .getOrElse(throw new SparkException("Must specify the driver pod 
name"))
    +  private implicit val requestExecutorContext = 
ExecutionContext.fromExecutorService(
    +    requestExecutorsService)
    +
    +  private val driverPod = kubernetesClient.pods()
    +    .inNamespace(kubernetesNamespace)
    +    .withName(kubernetesDriverPodName)
    +    .get()
    +
    +  override val minRegisteredRatio =
    +    if 
(conf.getOption("spark.scheduler.minRegisteredResourcesRatio").isEmpty) {
    +      0.8
    +    } else {
    +      super.minRegisteredRatio
    +    }
    +
    +  private val executorWatchResource = new AtomicReference[Closeable]
    +  protected val totalExpectedExecutors = new AtomicInteger(0)
    +
    +  private val driverUrl = RpcEndpointAddress(
    +    conf.get("spark.driver.host"),
    +    conf.getInt("spark.driver.port", DEFAULT_DRIVER_PORT),
    +    CoarseGrainedSchedulerBackend.ENDPOINT_NAME).toString
    +
    +  private val initialExecutors = 
SchedulerBackendUtils.getInitialTargetExecutorNumber(conf)
    +
    +  private val podAllocationInterval = 
conf.get(KUBERNETES_ALLOCATION_BATCH_DELAY)
    +
    +  private val podAllocationSize = 
conf.get(KUBERNETES_ALLOCATION_BATCH_SIZE)
    +
    +  private val allocatorRunnable = new Runnable {
    +
    +    // Maintains a map of executor id to count of checks performed to 
learn the loss reason
    +    // for an executor.
    +    private val executorReasonCheckAttemptCounts = new 
mutable.HashMap[String, Int]
    +
    +    override def run(): Unit = {
    +      handleDisconnectedExecutors()
    +      val executorsToAllocate = mutable.Map[String, Pod]()
    +      val currentTotalRegisteredExecutors = totalRegisteredExecutors.get
    +      val currentTotalExpectedExecutors = totalExpectedExecutors.get
    +      val currentNodeToLocalTaskCount = getNodesWithLocalTaskCounts
    +      if (currentTotalRegisteredExecutors < runningExecutorsToPods.size) {
    +        logDebug("Waiting for pending executors before scaling")
    +      } else if (currentTotalExpectedExecutors <= 
runningExecutorsToPods.size) {
    +        logDebug("Maximum allowed executor limit reached. Not scaling up 
further.")
    +      } else {
    +        for (i <- 0 until math.min(
    +          currentTotalExpectedExecutors - runningExecutorsToPods.size, 
podAllocationSize)) {
    +          val executorId = EXECUTOR_ID_COUNTER.incrementAndGet().toString
    +          val executorPod = executorPodFactory.createExecutorPod(
    +            executorId,
    +            applicationId(),
    +            driverUrl,
    +            conf.getExecutorEnv,
    +            driverPod,
    +            currentNodeToLocalTaskCount)
    +          
require(executorPod.getMetadata.getLabels.containsKey(SPARK_EXECUTOR_ID_LABEL),
    +            s"Illegal internal state for pod with name 
${executorPod.getMetadata.getName} - all" +
    +              s" executor pods must contain the label 
$SPARK_EXECUTOR_ID_LABEL.")
    +          val resolvedExecutorIdLabel = 
executorPod.getMetadata.getLabels.get(
    +            SPARK_EXECUTOR_ID_LABEL)
    +          require(resolvedExecutorIdLabel == executorId,
    --- End diff --
    
    If this is purely for preventing future changes from potentially breaking 
it, why cannot we verify that the contract is held in integration tests so the 
integration tests will fail if the contract is indeed broken?


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