Github user foxish commented on a diff in the pull request:
https://github.com/apache/spark/pull/19468#discussion_r149172795
--- Diff:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterSchedulerBackend.scala
---
@@ -0,0 +1,425 @@
+/*
+ * 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)
+ 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()
+ 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),
--- End diff --
This lgtm as is. Getting the info from the pod itself makes sense.
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