Github user mridulm commented on a diff in the pull request: https://github.com/apache/spark/pull/19468#discussion_r146980311 --- Diff: resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackend.scala --- @@ -0,0 +1,440 @@ +/* + * 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 scala.collection.JavaConverters._ +import scala.collection.mutable +import scala.concurrent.{ExecutionContext, Future} + +import io.fabric8.kubernetes.api.model._ +import io.fabric8.kubernetes.client.{KubernetesClient, KubernetesClientException, Watcher} +import io.fabric8.kubernetes.client.Watcher.Action + +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 +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 + // Indexed by executor IDs and guarded by RUNNING_EXECUTOR_PODS_LOCK. + private val runningExecutorsToPods = new mutable.HashMap[String, Pod] + // Indexed by executor pod names and guarded by RUNNING_EXECUTOR_PODS_LOCK. + private val runningPodsToExecutors = new mutable.HashMap[String, String] + 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 = try { + kubernetesClient.pods() + .inNamespace(kubernetesNamespace) + .withName(kubernetesDriverPodName) + .get() + } catch { + case throwable: Throwable => + logError(s"Executor cannot find driver pod.", throwable) + throw new SparkException(s"Executor cannot find driver pod", throwable) + } + + 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 = getInitialTargetExecutorNumber() + + private val podAllocationInterval = conf.get(KUBERNETES_ALLOCATION_BATCH_DELAY) + require(podAllocationInterval > 0, s"Allocation batch delay " + + s"${KUBERNETES_ALLOCATION_BATCH_DELAY} " + + s"is ${podAllocationInterval}, should be a positive integer") + + private val podAllocationSize = conf.get(KUBERNETES_ALLOCATION_BATCH_SIZE) + require(podAllocationSize > 0, s"Allocation batch size " + + s"${KUBERNETES_ALLOCATION_BATCH_SIZE} " + + s"is ${podAllocationSize}, should be a positive integer") + + 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() + RUNNING_EXECUTOR_PODS_LOCK.synchronized { + if (totalRegisteredExecutors.get() < runningExecutorsToPods.size) { + logDebug("Waiting for pending executors before scaling") --- End diff -- Btw, these variables can be modified from underneath this `synchronized` block, right ? If yes, better to copy them to local variables and work with them.
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