Merge branch 'master' into avro-hadoop2

bin/utils.sh

@@ -26,14 +26,14 @@ function gatherSparkSubmitOpts() {
     exit 1
   fi
 
-  # NOTE: If you add or remove spark-sumbmit options,
+  # NOTE: If you add or remove spark-submit options,
   # modify NOT ONLY this script but also SparkSubmitArgument.scala
   SUBMISSION_OPTS=()
   APPLICATION_OPTS=()
   while (($#)); do
     case "$1" in
-      --master | --deploy-mode | --class | --name | --jars | --py-files | --files | \
-      --conf | --properties-file | --driver-memory | --driver-java-options | \
+      --master | --deploy-mode | --class | --name | --jars | --packages | --py-files | --files | \
+      --conf | --repositories | --properties-file | --driver-memory | --driver-java-options | \
       --driver-library-path | --driver-class-path | --executor-memory | --driver-cores | \
       --total-executor-cores | --executor-cores | --queue | --num-executors | --archives)
         if [[ $# -lt 2 ]]; then

bin/windows-utils.cmd

@@ -32,7 +32,7 @@ SET opts="\<--master\> \<--deploy-mode\> \<--class\> \<--name\> \<--jars\> \<--p
 SET opts="%opts:~1,-1% \<--conf\> \<--properties-file\> \<--driver-memory\> \<--driver-java-options\>"
 SET opts="%opts:~1,-1% \<--driver-library-path\> \<--driver-class-path\> \<--executor-memory\>"
 SET opts="%opts:~1,-1% \<--driver-cores\> \<--total-executor-cores\> \<--executor-cores\> \<--queue\>"
-SET opts="%opts:~1,-1% \<--num-executors\> \<--archives\>"
+SET opts="%opts:~1,-1% \<--num-executors\> \<--archives\> \<--packages\> \<--repositories\>"
 
 echo %1 | findstr %opts% >nul
 if %ERRORLEVEL% equ 0 (

core/pom.xml

@@ -241,6 +241,17 @@
       <artifactId>derby</artifactId>
       <scope>test</scope>
     </dependency>
+    <dependency>
+      <groupId>org.apache.ivy</groupId>
+      <artifactId>ivy</artifactId>
+      <version>${ivy.version}</version>
+    </dependency>
+    <dependency>
+      <groupId>oro</groupId>
+      <!-- oro is needed by ivy, but only listed as an optional dependency, so we include it. -->
+      <artifactId>oro</artifactId>
+      <version>${oro.version}</version>
+    </dependency>
     <dependency>
       <groupId>org.tachyonproject</groupId>
       <artifactId>tachyon-client</artifactId>

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

@@ -657,6 +657,9 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
    *
    * Load data from a flat binary file, assuming the length of each record is constant.
    *
+   * '''Note:''' We ensure that the byte array for each record in the resulting RDD
+   * has the provided record length.
+   *
    * @param path Directory to the input data files
    * @param recordLength The length at which to split the records
    * @return An RDD of data with values, represented as byte arrays
@@ -671,7 +674,11 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
       classOf[LongWritable],
       classOf[BytesWritable],
       conf=conf)
-    val data = br.map{ case (k, v) => v.getBytes}
+    val data = br.map { case (k, v) =>
+      val bytes = v.getBytes
+      assert(bytes.length == recordLength, "Byte array does not have correct length")
+      bytes
+    }
     data
   }
 
@@ -1224,7 +1231,19 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
                   null
               }
             } else {
-              env.httpFileServer.addJar(new File(uri.getPath))
+              try {
+                env.httpFileServer.addJar(new File(uri.getPath))
+              } catch {
+                case exc: FileNotFoundException =>
+                  logError(s"Jar not found at $path")
+                  null
+                case e: Exception =>
+                  // For now just log an error but allow to go through so spark examples work.
+                  // The spark examples don't really need the jar distributed since its also
+                  // the app jar.
+                  logError("Error adding jar (" + e + "), was the --addJars option used?")
+                  null
+              }
             }
           // A JAR file which exists locally on every worker node
           case "local" =>
@@ -1749,8 +1768,14 @@ object SparkContext extends Logging {
   @deprecated("Replaced by implicit functions in the RDD companion object. This is " +
     "kept here only for backward compatibility.", "1.3.0")
   def rddToSequenceFileRDDFunctions[K <% Writable: ClassTag, V <% Writable: ClassTag](
-      rdd: RDD[(K, V)]) =
+      rdd: RDD[(K, V)]) = {
+    val kf = implicitly[K => Writable]
+    val vf = implicitly[V => Writable]
+    // Set the Writable class to null and `SequenceFileRDDFunctions` will use Reflection to get it
+    implicit val keyWritableFactory = new WritableFactory[K](_ => null, kf)
+    implicit val valueWritableFactory = new WritableFactory[V](_ => null, vf)
     RDD.rddToSequenceFileRDDFunctions(rdd)
+  }
 
   @deprecated("Replaced by implicit functions in the RDD companion object. This is " +
     "kept here only for backward compatibility.", "1.3.0")
@@ -1767,20 +1792,35 @@ object SparkContext extends Logging {
   def numericRDDToDoubleRDDFunctions[T](rdd: RDD[T])(implicit num: Numeric[T]) =
     RDD.numericRDDToDoubleRDDFunctions(rdd)
 
-  // Implicit conversions to common Writable types, for saveAsSequenceFile
+  // The following deprecated functions have already been moved to `object WritableFactory` to
+  // make the compiler find them automatically. They are still kept here for backward compatibility.
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def intToIntWritable(i: Int): IntWritable = new IntWritable(i)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def longToLongWritable(l: Long): LongWritable = new LongWritable(l)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def floatToFloatWritable(f: Float): FloatWritable = new FloatWritable(f)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def doubleToDoubleWritable(d: Double): DoubleWritable = new DoubleWritable(d)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def boolToBoolWritable (b: Boolean): BooleanWritable = new BooleanWritable(b)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def bytesToBytesWritable (aob: Array[Byte]): BytesWritable = new BytesWritable(aob)
 
+  @deprecated("Replaced by implicit functions in the WritableFactory companion object. This is " +
+    "kept here only for backward compatibility.", "1.3.0")
   implicit def stringToText(s: String): Text = new Text(s)
 
   private implicit def arrayToArrayWritable[T <% Writable: ClassTag](arr: Traversable[T])
@@ -2070,7 +2110,7 @@ object WritableConverter {
     new WritableConverter[T](_ => wClass, x => convert(x.asInstanceOf[W]))
   }
 
-  // The following implicit functions were in SparkContext before 1.2 and users had to
+  // The following implicit functions were in SparkContext before 1.3 and users had to
   // `import SparkContext._` to enable them. Now we move them here to make the compiler find
   // them automatically. However, we still keep the old functions in SparkContext for backward
   // compatibility and forward to the following functions directly.
@@ -2103,3 +2143,46 @@ object WritableConverter {
   implicit def writableWritableConverter[T <: Writable](): WritableConverter[T] =
     new WritableConverter[T](_.runtimeClass.asInstanceOf[Class[T]], _.asInstanceOf[T])
 }
+
+/**
+ * A class encapsulating how to convert some type T to Writable. It stores both the Writable class
+ * corresponding to T (e.g. IntWritable for Int) and a function for doing the conversion.
+ * The Writable class will be used in `SequenceFileRDDFunctions`.
+ */
+private[spark] class WritableFactory[T](
+    val writableClass: ClassTag[T] => Class[_ <: Writable],
+    val convert: T => Writable) extends Serializable
+
+object WritableFactory {
+
+  private[spark] def simpleWritableFactory[T: ClassTag, W <: Writable : ClassTag](convert: T => W)
+    : WritableFactory[T] = {
+    val writableClass = implicitly[ClassTag[W]].runtimeClass.asInstanceOf[Class[W]]
+    new WritableFactory[T](_ => writableClass, convert)
+  }
+
+  implicit def intWritableFactory: WritableFactory[Int] =
+    simpleWritableFactory(new IntWritable(_))
+
+  implicit def longWritableFactory: WritableFactory[Long] =
+    simpleWritableFactory(new LongWritable(_))
+
+  implicit def floatWritableFactory: WritableFactory[Float] =
+    simpleWritableFactory(new FloatWritable(_))
+
+  implicit def doubleWritableFactory: WritableFactory[Double] =
+    simpleWritableFactory(new DoubleWritable(_))
+
+  implicit def booleanWritableFactory: WritableFactory[Boolean] =
+    simpleWritableFactory(new BooleanWritable(_))
+
+  implicit def bytesWritableFactory: WritableFactory[Array[Byte]] =
+    simpleWritableFactory(new BytesWritable(_))
+
+  implicit def stringWritableFactory: WritableFactory[String] =
+    simpleWritableFactory(new Text(_))
+
+  implicit def writableWritableFactory[T <: Writable: ClassTag]: WritableFactory[T] =
+    simpleWritableFactory(w => w)
+
+}

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

@@ -107,7 +107,6 @@ private[python] class WritableToDoubleArrayConverter extends Converter[Any, Arra
  * given directory (probably a temp directory)
  */
 object WriteInputFormatTestDataGenerator {
-  import SparkContext._
 
   def main(args: Array[String]) {
     val path = args(0)