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

    https://github.com/apache/spark/pull/21366#discussion_r191866216
  
    --- Diff: 
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala
 ---
    @@ -0,0 +1,120 @@
    +/*
    + * 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.atomic.{AtomicInteger, AtomicLong}
    +
    +import io.fabric8.kubernetes.api.model.{Pod, PodBuilder}
    +import io.fabric8.kubernetes.client.KubernetesClient
    +import scala.collection.mutable
    +
    +import org.apache.spark.{SparkConf, SparkException}
    +import org.apache.spark.deploy.k8s.Config._
    +import org.apache.spark.deploy.k8s.Constants._
    +import org.apache.spark.deploy.k8s.KubernetesConf
    +import org.apache.spark.internal.Logging
    +
    +private[spark] class ExecutorPodsAllocator(
    +    conf: SparkConf,
    +    executorBuilder: KubernetesExecutorBuilder,
    +    kubernetesClient: KubernetesClient,
    +    eventQueue: ExecutorPodsEventQueue) extends Logging {
    +
    +  private val EXECUTOR_ID_COUNTER = new AtomicLong(0L)
    +
    +  private val totalExpectedExecutors = new AtomicInteger(0)
    +
    +  private val podAllocationSize = 
conf.get(KUBERNETES_ALLOCATION_BATCH_SIZE)
    +
    +  private val podAllocationDelay = 
conf.get(KUBERNETES_ALLOCATION_BATCH_DELAY)
    +
    +  private val kubernetesDriverPodName = conf
    +    .get(KUBERNETES_DRIVER_POD_NAME)
    +    .getOrElse(throw new SparkException("Must specify the driver pod 
name"))
    +
    +  private val driverPod = kubernetesClient.pods()
    +    .withName(kubernetesDriverPodName)
    +    .get()
    +
    +  // Use sets of ids instead of counters to be able to handle duplicate 
events.
    +
    +  // Executor IDs that have been requested from Kubernetes but are not 
running yet.
    +  private val pendingExecutors = mutable.Set.empty[Long]
    +
    +  // We could use CoarseGrainedSchedulerBackend#totalRegisteredExecutors 
here for tallying the
    +  // executors that are running. But, here we choose instead to maintain 
all state within this
    +  // class from the persecptive of the k8s API. Therefore whether or not 
this scheduler loop
    +  // believes an executor is running is dictated by the K8s API rather 
than Spark's RPC events.
    +  // We may need to consider where these perspectives may differ and which 
perspective should
    +  // take precedence.
    +  private val runningExecutors = mutable.Set.empty[Long]
    +
    +  def start(applicationId: String): Unit = {
    +    eventQueue.addSubscriber(podAllocationDelay) { updatedPods =>
    +      processUpdatedPodEvents(applicationId, updatedPods)
    +    }
    +  }
    +
    +  def setTotalExpectedExecutors(total: Int): Unit = 
totalExpectedExecutors.set(total)
    +
    +  private def processUpdatedPodEvents(applicationId: String, updatedPods: 
Seq[Pod]): Unit = {
    +    updatedPods.foreach { updatedPod =>
    +      val execId = 
updatedPod.getMetadata.getLabels.get(SPARK_EXECUTOR_ID_LABEL).toLong
    +      val phase = updatedPod.getStatus.getPhase.toLowerCase
    +      phase match {
    +        case "running" =>
    +          pendingExecutors -= execId
    +          runningExecutors += execId
    +        case "failed" | "succeeded" | "error" =>
    +          pendingExecutors -= execId
    +          runningExecutors -= execId
    +      }
    +    }
    +
    +    val currentRunningExecutors = runningExecutors.size
    +    val currentTotalExpectedExecutors = totalExpectedExecutors.get
    +    if (pendingExecutors.isEmpty && currentRunningExecutors < 
currentTotalExpectedExecutors) {
    +      val numExecutorsToAllocate = math.min(
    +        currentTotalExpectedExecutors - currentRunningExecutors, 
podAllocationSize)
    +      logInfo(s"Going to request $numExecutorsToAllocate executors from 
Kubernetes.")
    +      val newExecutorIds = mutable.Buffer.empty[Long]
    +      val podsToAllocate = mutable.Buffer.empty[Pod]
    +      for ( _ <- 0 until numExecutorsToAllocate) {
    +        val newExecutorId = EXECUTOR_ID_COUNTER.incrementAndGet()
    +        val executorConf = KubernetesConf.createExecutorConf(
    +          conf,
    +          newExecutorId.toString,
    +          applicationId,
    +          driverPod)
    +        val executorPod = executorBuilder.buildFromFeatures(executorConf)
    +        val podWithAttachedContainer = new PodBuilder(executorPod.pod)
    +          .editOrNewSpec()
    +          .addToContainers(executorPod.container)
    +          .endSpec()
    +          .build()
    +        kubernetesClient.pods().create(podWithAttachedContainer)
    +        pendingExecutors += newExecutorId
    +      }
    +    } else if (currentRunningExecutors == currentTotalExpectedExecutors) {
    --- End diff --
    
    `>=` to be more defensive?


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