Github user squito commented on a diff in the pull request: https://github.com/apache/spark/pull/19041#discussion_r179179616 --- Diff: core/src/test/scala/org/apache/spark/scheduler/CacheRecoveryIntegrationSuite.scala --- @@ -0,0 +1,149 @@ +/* + * 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 + +import scala.util.Try + +import org.scalatest.{BeforeAndAfterAll, BeforeAndAfterEach, Matchers} +import org.scalatest.concurrent.Eventually +import org.scalatest.time.{Seconds, Span} + +import org.apache.spark.{SparkConf, SparkContext, SparkException, SparkFunSuite, TestUtils} +import org.apache.spark.internal.config._ +import org.apache.spark.network.TransportContext +import org.apache.spark.network.netty.SparkTransportConf +import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler +import org.apache.spark.rdd.RDD +import org.apache.spark.storage._ + +/** + * This is an integration test for the cache recovery feature using a local spark cluster. It + * extends the unit tests in CacheRecoveryManagerSuite which mocks a lot of cluster infrastructure. + */ +class CacheRecoveryIntegrationSuite extends SparkFunSuite + with Matchers + with BeforeAndAfterEach + with BeforeAndAfterAll + with Eventually { + + private var conf: SparkConf = makeBaseConf() + private val transportConf = SparkTransportConf.fromSparkConf(conf, "shuffle", numUsableCores = 4) + private val rpcHandler = new ExternalShuffleBlockHandler(transportConf, null) + private val transportContext = new TransportContext(transportConf, rpcHandler) + private val shuffleService = transportContext.createServer() + private var sc: SparkContext = _ + + private def makeBaseConf() = new SparkConf() + .setAppName("test") + .setMaster("local-cluster[4, 1, 512]") + .set("spark.dynamicAllocation.enabled", "true") + .set("spark.dynamicAllocation.executorIdleTimeout", "1s") // always + .set("spark.dynamicAllocation.cachedExecutorIdleTimeout", "1s") + .set(EXECUTOR_MEMORY.key, "512m") + .set(SHUFFLE_SERVICE_ENABLED.key, "true") + .set(DYN_ALLOCATION_CACHE_RECOVERY.key, "true") + .set(DYN_ALLOCATION_CACHE_RECOVERY_TIMEOUT.key, "500s") + .set(EXECUTOR_INSTANCES.key, "1") + .set(DYN_ALLOCATION_INITIAL_EXECUTORS.key, "4") + .set(DYN_ALLOCATION_MIN_EXECUTORS.key, "3") + + override def beforeEach(): Unit = { + conf = makeBaseConf() + conf.set("spark.shuffle.service.port", shuffleService.getPort.toString) + } + + override def afterEach(): Unit = { + sc.stop() + conf = null + } + + override def afterAll(): Unit = { + shuffleService.close() + } + + private def getLocations( + sc: SparkContext, + rdd: RDD[_]): Map[BlockId, Map[BlockManagerId, BlockStatus]] = { + import scala.collection.breakOut + val blockIds: Array[BlockId] = rdd.partitions.map(p => RDDBlockId(rdd.id, p.index)) + blockIds.map { id => + id -> Try(sc.env.blockManager.master.getBlockStatus(id)).getOrElse(Map.empty) + }(breakOut) + } + + test("cached data is replicated before dynamic de-allocation") { + sc = new SparkContext(conf) + TestUtils.waitUntilExecutorsUp(sc, 4, 60000) + + val rdd = sc.parallelize(1 to 1000, 4).map(_ * 4).cache() + rdd.reduce(_ + _) shouldBe 2002000 + sc.getExecutorIds().size shouldBe 4 + getLocations(sc, rdd).forall { case (_, map) => map.nonEmpty } shouldBe true + + eventually(timeout(Span(5, Seconds)), interval(Span(1, Seconds))) { + sc.getExecutorIds().size shouldBe 3 + getLocations(sc, rdd).forall { case (_, map) => map.nonEmpty } shouldBe true + } + } + + test("dont fail if a bunch of executors are shut down at once") { + conf.set("spark.dynamicAllocation.minExecutors", "1") + sc = new SparkContext(conf) + TestUtils.waitUntilExecutorsUp(sc, 2, 60000) + + val rdd = sc.parallelize(1 to 1000, 4).map(_ * 4).cache() + rdd.reduce(_ + _) shouldBe 2002000 + sc.getExecutorIds().size shouldBe 4 --- End diff -- though there are 4 tasks, they could run on fewer executors before dynamic allocation spins them all up. This could become a flaky tests. I think you should change the `waitUntilExecutorsUp` to be 4
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