[SPARK-32091][CORE] Ignore timeout error when remove blocks on the lost executor

core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedClusterMessage.scala

@@ -132,4 +132,6 @@ private[spark] object CoarseGrainedClusterMessages {
   // Used internally by executors to shut themselves down.
   case object Shutdown extends CoarseGrainedClusterMessage
 
+  // The message to check whether the executor is alive or not.
+  case class IsExecutorAlive(executorId: String) extends CoarseGrainedClusterMessage
 }

core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala

@@ -285,6 +285,9 @@ class CoarseGrainedSchedulerBackend(scheduler: TaskSchedulerImpl, val rpcEnv: Rp
           Option(delegationTokens.get()),
           rp)
         context.reply(reply)
+
+      case IsExecutorAlive(executorId) => context.reply(isExecutorActive(executorId))
+
       case e =>
         logError(s"Received unexpected ask ${e}")
     }

core/src/main/scala/org/apache/spark/storage/BlockManagerMaster.scala

@@ -36,6 +36,7 @@ class BlockManagerMaster(
   extends Logging {
 
   val timeout = RpcUtils.askRpcTimeout(conf)
+  private val infinite = RpcUtils.infiniteTimeout
 
   /** Remove a dead executor from the driver endpoint. This is only called on the driver side. */
   def removeExecutor(execId: String): Unit = {
@@ -142,8 +143,8 @@ class BlockManagerMaster(
       logWarning(s"Failed to remove RDD $rddId - ${e.getMessage}", e)
     )(ThreadUtils.sameThread)
     if (blocking) {
-      timeout.awaitResult(future)
-    }
+      // the underlying Futures will timeout anyway, so it's safe to use infinite here
+      infinite.awaitResult(future)    }
   }
 
   /** Remove all blocks belonging to the given shuffle. */
@@ -153,8 +154,8 @@ class BlockManagerMaster(
       logWarning(s"Failed to remove shuffle $shuffleId - ${e.getMessage}", e)
     )(ThreadUtils.sameThread)
     if (blocking) {
-      timeout.awaitResult(future)
-    }
+      // the underlying Futures will timeout anyway, so it's safe to use infinite here
+      infinite.awaitResult(future)    }
   }
 
   /** Remove all blocks belonging to the given broadcast. */
@@ -166,8 +167,8 @@ class BlockManagerMaster(
         s" with removeFromMaster = $removeFromMaster - ${e.getMessage}", e)
     )(ThreadUtils.sameThread)
     if (blocking) {
-      timeout.awaitResult(future)
-    }
+      // the underlying Futures will timeout anyway, so it's safe to use infinite here
+      infinite.awaitResult(future)    }
   }
 
   /**

core/src/main/scala/org/apache/spark/storage/BlockManagerMasterEndpoint.scala

@@ -23,17 +23,19 @@ import java.util.concurrent.TimeUnit
 
 import scala.collection.JavaConverters._
 import scala.collection.mutable
-import scala.concurrent.{ExecutionContext, Future}
+import scala.concurrent.{ExecutionContext, Future, TimeoutException}
 import scala.util.Random
+import scala.util.control.NonFatal
 
 import com.google.common.cache.CacheBuilder
 
 import org.apache.spark.SparkConf
 import org.apache.spark.annotation.DeveloperApi
 import org.apache.spark.internal.{config, Logging}
 import org.apache.spark.network.shuffle.ExternalBlockStoreClient
-import org.apache.spark.rpc.{IsolatedRpcEndpoint, RpcCallContext, RpcEndpointRef, RpcEnv}
+import org.apache.spark.rpc.{IsolatedRpcEndpoint, RpcCallContext, RpcEndpointAddress, RpcEndpointRef, RpcEnv}
 import org.apache.spark.scheduler._
+import org.apache.spark.scheduler.cluster.{CoarseGrainedClusterMessages, CoarseGrainedSchedulerBackend}
 import org.apache.spark.storage.BlockManagerMessages._
 import org.apache.spark.util.{RpcUtils, ThreadUtils, Utils}
 
@@ -95,6 +97,9 @@ class BlockManagerMasterEndpoint(
   private val externalShuffleServiceRddFetchEnabled: Boolean = externalBlockStoreClient.isDefined
   private val externalShuffleServicePort: Int = StorageUtils.externalShuffleServicePort(conf)
 
+  private lazy val driverEndpoint =
+    RpcUtils.makeDriverRef(CoarseGrainedSchedulerBackend.ENDPOINT_NAME, conf, rpcEnv)
+
   override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
     case RegisterBlockManager(id, localDirs, maxOnHeapMemSize, maxOffHeapMemSize, slaveEndpoint) =>
       context.reply(register(id, localDirs, maxOnHeapMemSize, maxOffHeapMemSize, slaveEndpoint))
@@ -168,6 +173,37 @@ class BlockManagerMasterEndpoint(
       stop()
   }
 
+  private def handleFailure[T](
+      blockType: String,
+      blockId: String,
+      bmId: BlockManagerId,
+      defaultValue: T): PartialFunction[Throwable, T] = {
+    case e: IOException =>
+      logWarning(s"Error trying to remove $blockType $blockId" +
+        s" from block manager $bmId", e)
+      defaultValue
+
+    case t: TimeoutException =>
+      val executorId = bmId.executorId
+      val isAlive = try {
+        driverEndpoint.askSync[Boolean](CoarseGrainedClusterMessages.IsExecutorAlive(executorId))
+      } catch {
+        // ignore the non-fatal error from driverEndpoint since the caller doesn't really
+        // care about the return result of removing blocks. And so we could avoid breaking
+        // down the whole application.
+        case NonFatal(e) =>
+          logError(s"Fail to know the executor $executorId is alive or not.", e)
+          false
+      }
+      if (!isAlive) {
+        logWarning(s"Error trying to remove $blockType $blockId. " +
+          s"The executor $executorId may have been lost.", t)
+        defaultValue
+      } else {
+        throw t
+      }
+  }
+
   private def removeRdd(rddId: Int): Future[Seq[Int]] = {
     // First remove the metadata for the given RDD, and then asynchronously remove the blocks
     // from the slaves.
@@ -207,10 +243,8 @@ class BlockManagerMasterEndpoint(
     }
     val removeRddFromExecutorsFutures = blockManagerInfo.values.map { bmInfo =>
       bmInfo.slaveEndpoint.ask[Int](removeMsg).recover {
-        case e: IOException =>
-          logWarning(s"Error trying to remove RDD ${removeMsg.rddId} " +
-            s"from block manager ${bmInfo.blockManagerId}", e)
-          0 // zero blocks were removed
+        // use 0 as default value means no blocks were removed
+        handleFailure("RDD", rddId.toString, bmInfo.blockManagerId, 0)
       }
     }.toSeq
 
@@ -235,7 +269,10 @@ class BlockManagerMasterEndpoint(
     val removeMsg = RemoveShuffle(shuffleId)
     Future.sequence(
       blockManagerInfo.values.map { bm =>
-        bm.slaveEndpoint.ask[Boolean](removeMsg)
+        bm.slaveEndpoint.ask[Boolean](removeMsg).recover {
+          // use false as default value means no shuffle data were removed
+          handleFailure("shuffle", shuffleId.toString, bm.blockManagerId, false)
+        }
       }.toSeq
     )
   }
@@ -252,10 +289,8 @@ class BlockManagerMasterEndpoint(
     }
     val futures = requiredBlockManagers.map { bm =>
       bm.slaveEndpoint.ask[Int](removeMsg).recover {
-        case e: IOException =>
-          logWarning(s"Error trying to remove broadcast $broadcastId from block manager " +
-            s"${bm.blockManagerId}", e)
-          0 // zero blocks were removed
+        // use 0 as default value means no blocks were removed
+        handleFailure("broadcast", broadcastId.toString, bm.blockManagerId, 0)
       }
     }.toSeq
 
@@ -350,11 +385,14 @@ class BlockManagerMasterEndpoint(
     if (locations != null) {
       locations.foreach { blockManagerId: BlockManagerId =>
         val blockManager = blockManagerInfo.get(blockManagerId)
-        if (blockManager.isDefined) {
+        blockManager.foreach { bm =>
           // Remove the block from the slave's BlockManager.
           // Doesn't actually wait for a confirmation and the message might get lost.
           // If message loss becomes frequent, we should add retry logic here.
-          blockManager.get.slaveEndpoint.ask[Boolean](RemoveBlock(blockId))
+          bm.slaveEndpoint.ask[Boolean](RemoveBlock(blockId)).recover {
+            // use false as default value means no blocks were removed
+            handleFailure("block", blockId.toString, bm.blockManagerId, false)
+          }
         }
       }
     }

core/src/main/scala/org/apache/spark/util/RpcUtils.scala

@@ -17,6 +17,8 @@
 
 package org.apache.spark.util
 
+import scala.concurrent.duration._
+
 import org.apache.spark.SparkConf
 import org.apache.spark.internal.config
 import org.apache.spark.internal.config.Network._
@@ -54,6 +56,13 @@ private[spark] object RpcUtils {
     RpcTimeout(conf, Seq(RPC_LOOKUP_TIMEOUT.key, NETWORK_TIMEOUT.key), "120s")
   }
 
+  /**
+   * Infinite timeout is used internally, so there's no actual timeout property controls it.
+   * Therefore, we use "infinite" without any specific reason as its timeout property. And
+   * its timeout property should never be accessed since infinite means we never timeout.
+   */
+  val infiniteTimeout = new RpcTimeout(Long.MaxValue.nanos, "infinite")
+
   private val MAX_MESSAGE_SIZE_IN_MB = Int.MaxValue / 1024 / 1024
 
   /** Returns the configured max message size for messages in bytes. */

core/src/test/scala/org/apache/spark/storage/BlockManagerSuite.scala

@@ -23,7 +23,7 @@ import java.nio.ByteBuffer
 import scala.collection.JavaConverters._
 import scala.collection.mutable
 import scala.collection.mutable.ArrayBuffer
-import scala.concurrent.Future
+import scala.concurrent.{Future, TimeoutException}
 import scala.concurrent.duration._
 import scala.language.implicitConversions
 import scala.reflect.ClassTag
@@ -49,8 +49,9 @@ import org.apache.spark.network.netty.{NettyBlockTransferService, SparkTransport
 import org.apache.spark.network.server.{NoOpRpcHandler, TransportServer, TransportServerBootstrap}
 import org.apache.spark.network.shuffle.{BlockFetchingListener, DownloadFileManager, ExecutorDiskUtils, ExternalBlockStoreClient}
 import org.apache.spark.network.shuffle.protocol.{BlockTransferMessage, RegisterExecutor}
-import org.apache.spark.rpc.RpcEnv
+import org.apache.spark.rpc.{RpcCallContext, RpcEndpoint, RpcEnv}
 import org.apache.spark.scheduler.{LiveListenerBus, SparkListenerBlockUpdated}
+import org.apache.spark.scheduler.cluster.{CoarseGrainedClusterMessages, CoarseGrainedSchedulerBackend}
 import org.apache.spark.security.{CryptoStreamUtils, EncryptionFunSuite}
 import org.apache.spark.serializer.{JavaSerializer, KryoSerializer, SerializerManager}
 import org.apache.spark.shuffle.sort.SortShuffleManager
@@ -93,6 +94,7 @@ class BlockManagerSuite extends SparkFunSuite with Matchers with BeforeAndAfterE
       .set(MEMORY_STORAGE_FRACTION, 0.999)
       .set(Kryo.KRYO_SERIALIZER_BUFFER_SIZE.key, "1m")
       .set(STORAGE_UNROLL_MEMORY_THRESHOLD, 512L)
+      .set(Network.RPC_ASK_TIMEOUT, "5s")
   }
 
   private def makeBlockManager(
@@ -137,8 +139,10 @@ class BlockManagerSuite extends SparkFunSuite with Matchers with BeforeAndAfterE
     conf = new SparkConf(false)
     init(conf)
 
-    rpcEnv = RpcEnv.create("test", "localhost", 0, conf, securityMgr)
+    rpcEnv = RpcEnv.create("test", conf.get(config.DRIVER_HOST_ADDRESS),
+      conf.get(config.DRIVER_PORT), conf, securityMgr)
     conf.set(DRIVER_PORT, rpcEnv.address.port)
+    conf.set(DRIVER_HOST_ADDRESS, rpcEnv.address.host)
 
     // Mock SparkContext to reduce the memory usage of tests. It's fine since the only reason we
     // need to create a SparkContext is to initialize LiveListenerBus.
@@ -177,6 +181,95 @@ class BlockManagerSuite extends SparkFunSuite with Matchers with BeforeAndAfterE
     blockManager.stop()
   }
 
+  private def setupBlockManagerMasterWithBlocks(withLost: Boolean): Unit = {
+    // set up a simple DriverEndpoint which simply adds executorIds and
+    // checks whether a certain executorId has been added before.
+    val driverEndpoint = rpcEnv.setupEndpoint(CoarseGrainedSchedulerBackend.ENDPOINT_NAME,
+      new RpcEndpoint {
+        private val executorSet = mutable.HashSet[String]()
+        override val rpcEnv: RpcEnv = this.rpcEnv
+        override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
+          case CoarseGrainedClusterMessages.RegisterExecutor(executorId, _, _, _, _, _, _, _) =>
+            executorSet += executorId
+            context.reply(true)
+          case CoarseGrainedClusterMessages.IsExecutorAlive(executorId) =>
+            context.reply(executorSet.contains(executorId))
+        }
+      }
+    )
+
+    def createAndRegisterBlockManager(timeout: Boolean): BlockManagerId = {
+      val id = if (timeout) "timeout" else "normal"
+      val bmRef = rpcEnv.setupEndpoint(s"bm-$id", new RpcEndpoint {
+        override val rpcEnv: RpcEnv = this.rpcEnv
+        private def reply[T](context: RpcCallContext, response: T): Unit = {
+          if (timeout) {
+            Thread.sleep(conf.getTimeAsMs(Network.RPC_ASK_TIMEOUT.key) + 1000)
+          }
+          context.reply(response)
+        }
+
+        override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
+          case RemoveRdd(_) => reply(context, 1)
+          case RemoveBroadcast(_, _) => reply(context, 1)
+          case RemoveShuffle(_) => reply(context, true)
+        }
+      })
+      val bmId = BlockManagerId(s"exec-$id", "localhost", 1234, None)
+      master.registerBlockManager(bmId, Array.empty, 2000, 0, bmRef)
+    }
+
+    // set up normal bm1
+    val bm1Id = createAndRegisterBlockManager(false)
+    // set up bm2, which intentionally takes more time than RPC_ASK_TIMEOUT to
+    // remove rdd/broadcast/shuffle in order to raise timeout error
+    val bm2Id = createAndRegisterBlockManager(true)
+
+    driverEndpoint.askSync[Boolean](CoarseGrainedClusterMessages.RegisterExecutor(
+      bm1Id.executorId, null, bm1Id.host, 1, Map.empty, Map.empty,
+      Map.empty, 0))
+
+    if (!withLost) {
+      driverEndpoint.askSync[Boolean](CoarseGrainedClusterMessages.RegisterExecutor(
+        bm2Id.executorId, null, bm1Id.host, 1, Map.empty, Map.empty, Map.empty, 0))
+    }
+
+    eventually(timeout(5.seconds)) {
+      // make sure both bm1 and bm2 are registered at driver side BlockManagerMaster
+      verify(master, times(2))
+        .registerBlockManager(mc.any(), mc.any(), mc.any(), mc.any(), mc.any())
+      assert(driverEndpoint.askSync[Boolean](
+        CoarseGrainedClusterMessages.IsExecutorAlive(bm1Id.executorId)))
+      assert(driverEndpoint.askSync[Boolean](
+        CoarseGrainedClusterMessages.IsExecutorAlive(bm2Id.executorId)) === !withLost)
+    }
+
+    // update RDD block info for bm1 and bm2 (Broadcast and shuffle don't report block
+    // locations to BlockManagerMaster)
+    master.updateBlockInfo(bm1Id, RDDBlockId(0, 0), StorageLevel.MEMORY_ONLY, 100, 0)
+    master.updateBlockInfo(bm2Id, RDDBlockId(0, 1), StorageLevel.MEMORY_ONLY, 100, 0)
+  }
+
+  test("SPARK-32091: count failures from active executors when remove rdd/broadcast/shuffle") {
+    setupBlockManagerMasterWithBlocks(false)
+    // fail because bm2 will timeout and it's not lost anymore
+    assert(intercept[Exception](master.removeRdd(0, true))
+      .getCause.isInstanceOf[TimeoutException])
+    assert(intercept[Exception](master.removeBroadcast(0, true, true))
+      .getCause.isInstanceOf[TimeoutException])
+    assert(intercept[Exception](master.removeShuffle(0, true))
+      .getCause.isInstanceOf[TimeoutException])
+  }
+
+  test("SPARK-32091: ignore failures from lost executors when remove rdd/broadcast/shuffle") {
+    setupBlockManagerMasterWithBlocks(true)
+    // succeed because bm1 will remove rdd/broadcast successfully and bm2 will
+    // timeout but ignored as it's lost
+    master.removeRdd(0, true)
+    master.removeBroadcast(0, true, true)
+    master.removeShuffle(0, true)
+  }
+
   test("StorageLevel object caching") {
     val level1 = StorageLevel(false, false, false, 3)
     // this should return the same object as level1