Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/21366#discussion_r194181797
--- Diff:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsSnapshotsStoreImpl.scala
---
@@ -0,0 +1,95 @@
+/*
+ * 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 com.google.common.collect.Lists
+import io.fabric8.kubernetes.api.model.Pod
+import io.reactivex.disposables.Disposable
+import io.reactivex.functions.Consumer
+import io.reactivex.schedulers.Schedulers
+import io.reactivex.subjects.PublishSubject
+import javax.annotation.concurrent.GuardedBy
+import scala.collection.JavaConverters._
+import scala.collection.mutable
+
+import org.apache.spark.util.{ThreadUtils, Utils}
+
+private[spark] class ExecutorPodsSnapshotsStoreImpl(
+ bufferSnapshotsExecutor: ScheduledExecutorService,
+ executeSubscriptionsExecutor: ExecutorService)
+ extends ExecutorPodsSnapshotsStore {
+
+ private val SNAPSHOT_LOCK = new Object()
+
+ private val snapshotsObservable =
PublishSubject.create[ExecutorPodsSnapshot]()
+ private val observedDisposables = mutable.Buffer.empty[Disposable]
+
+ @GuardedBy("SNAPSHOT_LOCK")
+ private var currentSnapshot = ExecutorPodsSnapshot()
+
+ override def addSubscriber(
+ processBatchIntervalMillis: Long)
+ (subscriber: ExecutorPodsSnapshot => Unit): Unit = {
+ observedDisposables += snapshotsObservable
+ // Group events in the time window given by the caller. These
buffers are then sent
+ // to the caller's lambda at the given interval, with the pod
updates that occurred
+ // in that given interval.
+ .buffer(
+ processBatchIntervalMillis,
+ TimeUnit.MILLISECONDS,
+ // For testing - specifically use the given scheduled executor
service to trigger
+ // buffer boundaries. Allows us to inject a deterministic
scheduler here.
+ Schedulers.from(bufferSnapshotsExecutor))
+ // Trigger an event cycle immediately. Not strictly required to be
fully correct, but
+ // in particular the pod allocator should try to request executors
immediately instead
+ // of waiting for one pod allocation delay.
+ .startWith(Lists.newArrayList(ExecutorPodsSnapshot()))
+ // Force all triggered events - both the initial event above and the
buffered ones in
+ // the following time windows - to execute asynchronously to this
call's thread.
+ .observeOn(Schedulers.from(executeSubscriptionsExecutor))
+ .subscribe(toReactivexConsumer { snapshots:
java.util.List[ExecutorPodsSnapshot] =>
+ Utils.tryLogNonFatalError {
+ snapshots.asScala.foreach(subscriber)
+ }
+ })
+ }
+
+ override def stop(): Unit = {
+ observedDisposables.foreach(_.dispose())
+ snapshotsObservable.onComplete()
+ ThreadUtils.shutdown(bufferSnapshotsExecutor)
+ ThreadUtils.shutdown(executeSubscriptionsExecutor)
+ }
+
+ override def updatePod(updatedPod: Pod): Unit =
SNAPSHOT_LOCK.synchronized {
+ currentSnapshot = currentSnapshot.withUpdate(updatedPod)
--- End diff --
I'm pretty sure we want all snapshots. The reason is to get a more accurate
response in the lifecycle handler. If a pod enters and error state and then
someone marks it for deletion, you want to at least have the chance to capture
the error state when sending the executor removal request to the Spark
scheduler.
For the pods allocator we can do either the latest or all.
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