Merge remote-tracking branch 'upstream/master' into spark-1403

bin/load-spark-env.sh

@@ -30,6 +30,9 @@ if [ -z "$SPARK_ENV_LOADED" ]; then
   use_conf_dir=${SPARK_CONF_DIR:-"$parent_dir/conf"}
 
   if [ -f "${use_conf_dir}/spark-env.sh" ]; then
+    # Promote all variable declarations to environment (exported) variables
+    set -a
     . "${use_conf_dir}/spark-env.sh"
+    set +a
   fi
 fi

bin/spark-shell

@@ -127,7 +127,7 @@ function set_spark_log_conf(){
 
 function set_spark_master(){
     if ! [[ "$1" =~ $ARG_FLAG_PATTERN ]]; then
-        MASTER="$1"
+        export MASTER="$1"
     else
         out_error "wrong format for $2"
     fi
@@ -145,7 +145,7 @@ function resolve_spark_master(){
     fi
 
     if [ -z "$MASTER" ]; then
-        MASTER="$DEFAULT_MASTER"
+        export MASTER="$DEFAULT_MASTER"
     fi
 
 }

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

@@ -37,6 +37,7 @@ import org.apache.mesos.MesosNativeLibrary
 
 import org.apache.spark.broadcast.Broadcast
 import org.apache.spark.deploy.{LocalSparkCluster, SparkHadoopUtil}
+import org.apache.spark.input.WholeTextFileInputFormat
 import org.apache.spark.partial.{ApproximateEvaluator, PartialResult}
 import org.apache.spark.rdd._
 import org.apache.spark.scheduler._
@@ -371,6 +372,39 @@ class SparkContext(
       minSplits).map(pair => pair._2.toString)
   }
 
+  /**
+   * Read a directory of text files from HDFS, a local file system (available on all nodes), or any
+   * Hadoop-supported file system URI. Each file is read as a single record and returned in a
+   * key-value pair, where the key is the path of each file, the value is the content of each file.
+   *
+   * <p> For example, if you have the following files:
+   * {{{
+   *   hdfs://a-hdfs-path/part-00000
+   *   hdfs://a-hdfs-path/part-00001
+   *   ...
+   *   hdfs://a-hdfs-path/part-nnnnn
+   * }}}
+   *
+   * Do `val rdd = sparkContext.wholeTextFile("hdfs://a-hdfs-path")`,
+   *
+   * <p> then `rdd` contains
+   * {{{
+   *   (a-hdfs-path/part-00000, its content)
+   *   (a-hdfs-path/part-00001, its content)
+   *   ...
+   *   (a-hdfs-path/part-nnnnn, its content)
+   * }}}
+   *
+   * @note Small files are perferred, large file is also allowable, but may cause bad performance.
+   */
+  def wholeTextFiles(path: String): RDD[(String, String)] = {
+    newAPIHadoopFile(
+      path,
+      classOf[WholeTextFileInputFormat],
+      classOf[String],
+      classOf[String])
+  }
+
   /**
    * Get an RDD for a Hadoop-readable dataset from a Hadoop JobConf given its InputFormat and other
    * necessary info (e.g. file name for a filesystem-based dataset, table name for HyperTable),

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

@@ -154,6 +154,34 @@ class JavaSparkContext(val sc: SparkContext) extends JavaSparkContextVarargsWork
    */
   def textFile(path: String, minSplits: Int): JavaRDD[String] = sc.textFile(path, minSplits)
 
+  /**
+   * Read a directory of text files from HDFS, a local file system (available on all nodes), or any
+   * Hadoop-supported file system URI. Each file is read as a single record and returned in a
+   * key-value pair, where the key is the path of each file, the value is the content of each file.
+   *
+   * <p> For example, if you have the following files:
+   * {{{
+   *   hdfs://a-hdfs-path/part-00000
+   *   hdfs://a-hdfs-path/part-00001
+   *   ...
+   *   hdfs://a-hdfs-path/part-nnnnn
+   * }}}
+   *
+   * Do `JavaPairRDD<String, String> rdd = sparkContext.wholeTextFiles("hdfs://a-hdfs-path")`,
+   *
+   * <p> then `rdd` contains
+   * {{{
+   *   (a-hdfs-path/part-00000, its content)
+   *   (a-hdfs-path/part-00001, its content)
+   *   ...
+   *   (a-hdfs-path/part-nnnnn, its content)
+   * }}}
+   *
+   * @note Small files are perferred, large file is also allowable, but may cause bad performance.
+   */
+  def wholeTextFiles(path: String): JavaPairRDD[String, String] =
+    new JavaPairRDD(sc.wholeTextFiles(path))
+
   /** Get an RDD for a Hadoop SequenceFile with given key and value types.
     *
     * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each

core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala

@@ -79,20 +79,23 @@ object SparkSubmit {
       printErrorAndExit("master must start with yarn, mesos, spark, or local")
     }
 
-    // Because "yarn-standalone" and "yarn-client" encapsulate both the master
+    // Because "yarn-cluster" and "yarn-client" encapsulate both the master
     // and deploy mode, we have some logic to infer the master and deploy mode
     // from each other if only one is specified, or exit early if they are at odds.
-    if (appArgs.deployMode == null && appArgs.master == "yarn-standalone") {
+    if (appArgs.deployMode == null &&
+        (appArgs.master == "yarn-standalone" || appArgs.master == "yarn-cluster")) {
       appArgs.deployMode = "cluster"
     }
     if (appArgs.deployMode == "cluster" && appArgs.master == "yarn-client") {
       printErrorAndExit("Deploy mode \"cluster\" and master \"yarn-client\" are not compatible")
     }
-    if (appArgs.deployMode == "client" && appArgs.master == "yarn-standalone") {
-      printErrorAndExit("Deploy mode \"client\" and master \"yarn-standalone\" are not compatible")
+    if (appArgs.deployMode == "client" &&
+        (appArgs.master == "yarn-standalone" || appArgs.master == "yarn-cluster")) {
+      printErrorAndExit("Deploy mode \"client\" and master \"" + appArgs.master
+        + "\" are not compatible")
     }
     if (appArgs.deployMode == "cluster" && appArgs.master.startsWith("yarn")) {
-      appArgs.master = "yarn-standalone"
+      appArgs.master = "yarn-cluster"
     }
     if (appArgs.deployMode != "cluster" && appArgs.master.startsWith("yarn")) {
       appArgs.master = "yarn-client"

core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala

@@ -171,7 +171,7 @@ private[spark] class SparkSubmitArguments(args: Array[String]) {
       outStream.println("Unknown/unsupported param " + unknownParam)
     }
     outStream.println(
-      """Usage: spark-submit <primary binary> [options]
+      """Usage: spark-submit <app jar> [options]
         |Options:
         |  --master MASTER_URL         spark://host:port, mesos://host:port, yarn, or local.
         |  --deploy-mode DEPLOY_MODE   Mode to deploy the app in, either 'client' or 'cluster'.

core/src/main/scala/org/apache/spark/input/WholeTextFileInputFormat.scala

@@ -0,0 +1,47 @@
+/*
+ * 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.input
+
+import org.apache.hadoop.fs.Path
+import org.apache.hadoop.mapreduce.InputSplit
+import org.apache.hadoop.mapreduce.JobContext
+import org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat
+import org.apache.hadoop.mapreduce.RecordReader
+import org.apache.hadoop.mapreduce.TaskAttemptContext
+import org.apache.hadoop.mapreduce.lib.input.CombineFileRecordReader
+import org.apache.hadoop.mapreduce.lib.input.CombineFileSplit
+
+/**
+ * A [[org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat CombineFileInputFormat]] for
+ * reading whole text files. Each file is read as key-value pair, where the key is the file path and
+ * the value is the entire content of file.
+ */
+
+private[spark] class WholeTextFileInputFormat extends CombineFileInputFormat[String, String] {
+  override protected def isSplitable(context: JobContext, file: Path): Boolean = false
+
+  override def createRecordReader(
+      split: InputSplit,
+      context: TaskAttemptContext): RecordReader[String, String] = {
+
+    new CombineFileRecordReader[String, String](
+      split.asInstanceOf[CombineFileSplit],
+      context,
+      classOf[WholeTextFileRecordReader])
+  }
+}

core/src/main/scala/org/apache/spark/input/WholeTextFileRecordReader.scala

@@ -0,0 +1,72 @@
+/*
+ * 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.input
+
+import com.google.common.io.{ByteStreams, Closeables}
+
+import org.apache.hadoop.io.Text
+import org.apache.hadoop.mapreduce.InputSplit
+import org.apache.hadoop.mapreduce.lib.input.CombineFileSplit
+import org.apache.hadoop.mapreduce.RecordReader
+import org.apache.hadoop.mapreduce.TaskAttemptContext
+
+/**
+ * A [[org.apache.hadoop.mapreduce.RecordReader RecordReader]] for reading a single whole text file
+ * out in a key-value pair, where the key is the file path and the value is the entire content of
+ * the file.
+ */
+private[spark] class WholeTextFileRecordReader(
+    split: CombineFileSplit,
+    context: TaskAttemptContext,
+    index: Integer)
+  extends RecordReader[String, String] {
+
+  private val path = split.getPath(index)
+  private val fs = path.getFileSystem(context.getConfiguration)
+
+  // True means the current file has been processed, then skip it.
+  private var processed = false
+
+  private val key = path.toString
+  private var value: String = null
+
+  override def initialize(split: InputSplit, context: TaskAttemptContext) = {}
+
+  override def close() = {}
+
+  override def getProgress = if (processed) 1.0f else 0.0f
+
+  override def getCurrentKey = key
+
+  override def getCurrentValue = value
+
+  override def nextKeyValue = {
+    if (!processed) {
+      val fileIn = fs.open(path)
+      val innerBuffer = ByteStreams.toByteArray(fileIn)
+
+      value = new Text(innerBuffer).toString
+      Closeables.close(fileIn, false)
+
+      processed = true
+      true
+    } else {
+      false
+    }
+  }
+}

core/src/test/java/org/apache/spark/JavaAPISuite.java

@@ -17,9 +17,7 @@
 
 package org.apache.spark;
 
-import java.io.File;
-import java.io.IOException;
-import java.io.Serializable;
+import java.io.*;
 import java.util.*;
 
 import scala.Tuple2;
@@ -599,6 +597,32 @@ public void textFiles() throws IOException {
     Assert.assertEquals(expected, readRDD.collect());
   }
 
+  @Test
+  public void wholeTextFiles() throws IOException {
+    byte[] content1 = "spark is easy to use.\n".getBytes();
+    byte[] content2 = "spark is also easy to use.\n".getBytes();
+
+    File tempDir = Files.createTempDir();
+    String tempDirName = tempDir.getAbsolutePath();
+    DataOutputStream ds = new DataOutputStream(new FileOutputStream(tempDirName + "/part-00000"));
+    ds.write(content1);
+    ds.close();
+    ds = new DataOutputStream(new FileOutputStream(tempDirName + "/part-00001"));
+    ds.write(content2);
+    ds.close();
+
+    HashMap<String, String> container = new HashMap<String, String>();
+    container.put(tempDirName+"/part-00000", new Text(content1).toString());
+    container.put(tempDirName+"/part-00001", new Text(content2).toString());
+
+    JavaPairRDD<String, String> readRDD = sc.wholeTextFiles(tempDirName);
+    List<Tuple2<String, String>> result = readRDD.collect();
+
+    for (Tuple2<String, String> res : result) {
+      Assert.assertEquals(res._2(), container.get(res._1()));
+    }
+  }
+
   @Test
   public void textFilesCompressed() throws IOException {
     File tempDir = Files.createTempDir();