Merge remote-tracking branch 'apache/master' into SPARK-3530

Author: mengxr

core/src/main/resources/org/apache/spark/ui/static/additional-metrics.js

@@ -39,6 +39,8 @@ $(function() {
         var column = "table ." + $(this).attr("name");
         $(column).hide();
     });
+    // Stripe table rows after rows have been hidden to ensure correct striping.
+    stripeTables();
 
     $("input:checkbox").click(function() {
         var column = "table ." + $(this).attr("name");

core/src/main/resources/org/apache/spark/ui/static/table.js

@@ -28,8 +28,3 @@ function stripeTables() {
         });
     });
 }
-
-/* Stripe all tables after pages finish loading. */
-$(function() {
-    stripeTables();
-});

core/src/main/scala/org/apache/spark/SecurityManager.scala

@@ -343,15 +343,7 @@ private[spark] class SecurityManager(sparkConf: SparkConf) extends Logging with
    */
   def getSecretKey(): String = secretKey
 
-  override def getSaslUser(appId: String): String = {
-    val myAppId = sparkConf.getAppId
-    require(appId == myAppId, s"SASL appId $appId did not match my appId ${myAppId}")
-    getSaslUser()
-  }
-
-  override def getSecretKey(appId: String): String = {
-    val myAppId = sparkConf.getAppId
-    require(appId == myAppId, s"SASL appId $appId did not match my appId ${myAppId}")
-    getSecretKey()
-  }
+  // Default SecurityManager only has a single secret key, so ignore appId.
+  override def getSaslUser(appId: String): String = getSaslUser()
+  override def getSecretKey(appId: String): String = getSecretKey()
 }

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -560,6 +560,8 @@ class SparkContext(config: SparkConf) extends SparkStatusAPI with Logging {
 
 
   /**
+   * :: Experimental ::
+   *
    * Get an RDD for a Hadoop-readable dataset as PortableDataStream for each file
    * (useful for binary data)
    *
@@ -602,6 +604,8 @@ class SparkContext(config: SparkConf) extends SparkStatusAPI with Logging {
   }
 
   /**
+   * :: Experimental ::
+   *
    * Load data from a flat binary file, assuming the length of each record is constant.
    *
    * @param path Directory to the input data files

core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala

@@ -21,18 +21,14 @@ import java.io.Closeable
 import java.util
 import java.util.{Map => JMap}
 
-import java.io.DataInputStream
-
-import org.apache.hadoop.io.{BytesWritable, LongWritable}
-import org.apache.spark.input.{PortableDataStream, FixedLengthBinaryInputFormat}
-
 import scala.collection.JavaConversions
 import scala.collection.JavaConversions._
 import scala.language.implicitConversions
 import scala.reflect.ClassTag
 
 import com.google.common.base.Optional
 import org.apache.hadoop.conf.Configuration
+import org.apache.spark.input.PortableDataStream
 import org.apache.hadoop.mapred.{InputFormat, JobConf}
 import org.apache.hadoop.mapreduce.{InputFormat => NewInputFormat}
 
@@ -286,6 +282,8 @@ class JavaSparkContext(val sc: SparkContext)
     new JavaPairRDD(sc.binaryFiles(path, minPartitions))
 
   /**
+   * :: Experimental ::
+   *
    * Read a directory of binary files from HDFS, a local file system (available on all nodes),
    * or any Hadoop-supported file system URI as a byte array. Each file is read as a single
    * record and returned in a key-value pair, where the key is the path of each file,
@@ -312,15 +310,19 @@ class JavaSparkContext(val sc: SparkContext)
    *
    * @note Small files are preferred; very large files but may cause bad performance.
    */
+  @Experimental
   def binaryFiles(path: String): JavaPairRDD[String, PortableDataStream] =
     new JavaPairRDD(sc.binaryFiles(path, defaultMinPartitions))
 
   /**
+   * :: Experimental ::
+   *
    * Load data from a flat binary file, assuming the length of each record is constant.
    *
    * @param path Directory to the input data files
    * @return An RDD of data with values, represented as byte arrays
    */
+  @Experimental
   def binaryRecords(path: String, recordLength: Int): JavaRDD[Array[Byte]] = {
     new JavaRDD(sc.binaryRecords(path, recordLength))
   }

core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala

@@ -21,6 +21,8 @@ import java.io._
 import java.net._
 import java.util.{List => JList, ArrayList => JArrayList, Map => JMap, Collections}
 
+import org.apache.spark.input.PortableDataStream
+
 import scala.collection.JavaConversions._
 import scala.collection.mutable
 import scala.language.existentials
@@ -395,22 +397,33 @@ private[spark] object PythonRDD extends Logging {
           newIter.asInstanceOf[Iterator[String]].foreach { str =>
             writeUTF(str, dataOut)
           }
-        case pair: Tuple2[_, _] =>
-          pair._1 match {
-            case bytePair: Array[Byte] =>
-              newIter.asInstanceOf[Iterator[Tuple2[Array[Byte], Array[Byte]]]].foreach { pair =>
-                dataOut.writeInt(pair._1.length)
-                dataOut.write(pair._1)
-                dataOut.writeInt(pair._2.length)
-                dataOut.write(pair._2)
-              }
-            case stringPair: String =>
-              newIter.asInstanceOf[Iterator[Tuple2[String, String]]].foreach { pair =>
-                writeUTF(pair._1, dataOut)
-                writeUTF(pair._2, dataOut)
-              }
-            case other =>
-              throw new SparkException("Unexpected Tuple2 element type " + pair._1.getClass)
+        case stream: PortableDataStream =>
+          newIter.asInstanceOf[Iterator[PortableDataStream]].foreach { stream =>
+            val bytes = stream.toArray()
+            dataOut.writeInt(bytes.length)
+            dataOut.write(bytes)
+          }
+        case (key: String, stream: PortableDataStream) =>
+          newIter.asInstanceOf[Iterator[(String, PortableDataStream)]].foreach {
+            case (key, stream) =>
+              writeUTF(key, dataOut)
+              val bytes = stream.toArray()
+              dataOut.writeInt(bytes.length)
+              dataOut.write(bytes)
+          }
+        case (key: String, value: String) =>
+          newIter.asInstanceOf[Iterator[(String, String)]].foreach {
+            case (key, value) =>
+              writeUTF(key, dataOut)
+              writeUTF(value, dataOut)
+          }
+        case (key: Array[Byte], value: Array[Byte]) =>
+          newIter.asInstanceOf[Iterator[(Array[Byte], Array[Byte])]].foreach {
+            case (key, value) =>
+              dataOut.writeInt(key.length)
+              dataOut.write(key)
+              dataOut.writeInt(value.length)
+              dataOut.write(value)
           }
         case other =>
           throw new SparkException("Unexpected element type " + first.getClass)

core/src/main/scala/org/apache/spark/deploy/worker/StandaloneWorkerShuffleService.scala

@@ -0,0 +1,66 @@
+/*
+ * 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.deploy.worker
+
+import org.apache.spark.{Logging, SparkConf, SecurityManager}
+import org.apache.spark.network.TransportContext
+import org.apache.spark.network.netty.SparkTransportConf
+import org.apache.spark.network.sasl.SaslRpcHandler
+import org.apache.spark.network.server.TransportServer
+import org.apache.spark.network.shuffle.ExternalShuffleBlockHandler
+
+/**
+ * Provides a server from which Executors can read shuffle files (rather than reading directly from
+ * each other), to provide uninterrupted access to the files in the face of executors being turned
+ * off or killed.
+ *
+ * Optionally requires SASL authentication in order to read. See [[SecurityManager]].
+ */
+private[worker]
+class StandaloneWorkerShuffleService(sparkConf: SparkConf, securityManager: SecurityManager)
+  extends Logging {
+
+  private val enabled = sparkConf.getBoolean("spark.shuffle.service.enabled", false)
+  private val port = sparkConf.getInt("spark.shuffle.service.port", 7337)
+  private val useSasl: Boolean = securityManager.isAuthenticationEnabled()
+
+  private val transportConf = SparkTransportConf.fromSparkConf(sparkConf)
+  private val blockHandler = new ExternalShuffleBlockHandler()
+  private val transportContext: TransportContext = {
+    val handler = if (useSasl) new SaslRpcHandler(blockHandler, securityManager) else blockHandler
+    new TransportContext(transportConf, handler)
+  }
+
+  private var server: TransportServer = _
+
+  /** Starts the external shuffle service if the user has configured us to. */
+  def startIfEnabled() {
+    if (enabled) {
+      require(server == null, "Shuffle server already started")
+      logInfo(s"Starting shuffle service on port $port with useSasl = $useSasl")
+      server = transportContext.createServer(port)
+    }
+  }
+
+  def stop() {
+    if (enabled && server != null) {
+      server.close()
+      server = null
+    }
+  }
+}

core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala

@@ -111,6 +111,9 @@ private[spark] class Worker(
   val drivers = new HashMap[String, DriverRunner]
   val finishedDrivers = new HashMap[String, DriverRunner]
 
+  // The shuffle service is not actually started unless configured.
+  val shuffleService = new StandaloneWorkerShuffleService(conf, securityMgr)
+
   val publicAddress = {
     val envVar = System.getenv("SPARK_PUBLIC_DNS")
     if (envVar != null) envVar else host
@@ -154,6 +157,7 @@ private[spark] class Worker(
     logInfo("Spark home: " + sparkHome)
     createWorkDir()
     context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent])
+    shuffleService.startIfEnabled()
     webUi = new WorkerWebUI(this, workDir, webUiPort)
     webUi.bind()
     registerWithMaster()
@@ -419,6 +423,7 @@ private[spark] class Worker(
     registrationRetryTimer.foreach(_.cancel())
     executors.values.foreach(_.kill())
     drivers.values.foreach(_.kill())
+    shuffleService.stop()
     webUi.stop()
     metricsSystem.stop()
   }
@@ -441,7 +446,8 @@ private[spark] object Worker extends Logging {
       cores: Int,
       memory: Int,
       masterUrls: Array[String],
-      workDir: String, workerNumber: Option[Int] = None): (ActorSystem, Int) = {
+      workDir: String,
+      workerNumber: Option[Int] = None): (ActorSystem, Int) = {
 
     // The LocalSparkCluster runs multiple local sparkWorkerX actor systems
     val conf = new SparkConf

core/src/main/scala/org/apache/spark/network/netty/NettyBlockTransferService.scala

@@ -27,7 +27,7 @@ import org.apache.spark.network.client.{TransportClientBootstrap, RpcResponseCal
 import org.apache.spark.network.netty.NettyMessages.{OpenBlocks, UploadBlock}
 import org.apache.spark.network.sasl.{SaslRpcHandler, SaslClientBootstrap}
 import org.apache.spark.network.server._
-import org.apache.spark.network.shuffle.{BlockFetchingListener, OneForOneBlockFetcher}
+import org.apache.spark.network.shuffle.{RetryingBlockFetcher, BlockFetchingListener, OneForOneBlockFetcher}
 import org.apache.spark.serializer.JavaSerializer
 import org.apache.spark.storage.{BlockId, StorageLevel}
 import org.apache.spark.util.Utils
@@ -71,9 +71,22 @@ class NettyBlockTransferService(conf: SparkConf, securityManager: SecurityManage
       listener: BlockFetchingListener): Unit = {
     logTrace(s"Fetch blocks from $host:$port (executor id $execId)")
     try {
-      val client = clientFactory.createClient(host, port)
-      new OneForOneBlockFetcher(client, blockIds.toArray, listener)
-        .start(OpenBlocks(blockIds.map(BlockId.apply)))
+      val blockFetchStarter = new RetryingBlockFetcher.BlockFetchStarter {
+        override def createAndStart(blockIds: Array[String], listener: BlockFetchingListener) {
+          val client = clientFactory.createClient(host, port)
+          new OneForOneBlockFetcher(client, blockIds.toArray, listener)
+            .start(OpenBlocks(blockIds.map(BlockId.apply)))
+        }
+      }
+
+      val maxRetries = transportConf.maxIORetries()
+      if (maxRetries > 0) {
+        // Note this Fetcher will correctly handle maxRetries == 0; we avoid it just in case there's
+        // a bug in this code. We should remove the if statement once we're sure of the stability.
+        new RetryingBlockFetcher(transportConf, blockFetchStarter, blockIds, listener).start()
+      } else {
+        blockFetchStarter.createAndStart(blockIds, listener)
+      }
     } catch {
       case e: Exception =>
         logError("Exception while beginning fetchBlocks", e)

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

@@ -92,7 +92,7 @@ final class ShuffleBlockFetcherIterator(
    * Current [[FetchResult]] being processed. We track this so we can release the current buffer
    * in case of a runtime exception when processing the current buffer.
    */
-  private[this] var currentResult: FetchResult = null
+  @volatile private[this] var currentResult: FetchResult = null
 
   /**
    * Queue of fetch requests to issue; we'll pull requests off this gradually to make sure that