Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature

Author: sarutak

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

@@ -1901,7 +1901,17 @@ object SparkContext extends Logging {
 
   private[spark] val SPARK_JOB_INTERRUPT_ON_CANCEL = "spark.job.interruptOnCancel"
 
-  private[spark] val DRIVER_IDENTIFIER = "<driver>"
+  /**
+   * Executor id for the driver.  In earlier versions of Spark, this was `<driver>`, but this was
+   * changed to `driver` because the angle brackets caused escaping issues in URLs and XML (see
+   * SPARK-6716 for more details).
+   */
+  private[spark] val DRIVER_IDENTIFIER = "driver"
+
+  /**
+   * Legacy version of DRIVER_IDENTIFIER, retained for backwards-compatibility.
+   */
+  private[spark] val LEGACY_DRIVER_IDENTIFIER = "<driver>"
 
   // The following deprecated objects have already been copied to `object AccumulatorParam` to
   // make the compiler find them automatically. They are duplicate codes only for backward

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

@@ -89,7 +89,7 @@ private class ClientActor(driverArgs: ClientArguments, conf: SparkConf)
 
   /* Find out driver status then exit the JVM */
   def pollAndReportStatus(driverId: String) {
-    println(s"... waiting before polling master for driver state")
+    println("... waiting before polling master for driver state")
     Thread.sleep(5000)
     println("... polling master for driver state")
     val statusFuture = (masterActor ? RequestDriverStatus(driverId))(timeout)

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

@@ -245,7 +245,7 @@ private[deploy] class StandaloneRestClient extends Logging {
       }
     } else {
       val failMessage = Option(submitResponse.message).map { ": " + _ }.getOrElse("")
-      logError("Application submission failed" + failMessage)
+      logError(s"Application submission failed$failMessage")
     }
   }
 

core/src/main/scala/org/apache/spark/deploy/rest/StandaloneRestClient.scala

@@ -181,7 +181,7 @@ abstract class Connection(val channel: SocketChannel, val selector: Selector,
     buffer.get(bytes)
     bytes.foreach(x => print(x + " "))
     buffer.position(curPosition)
-    print(" (" + bytes.size + ")")
+    print(" (" + bytes.length + ")")
   }
 
   def printBuffer(buffer: ByteBuffer, position: Int, length: Int) {

core/src/main/scala/org/apache/spark/network/nio/Connection.scala

@@ -45,7 +45,7 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
         }
         result
       },
-      Range(0, self.partitions.size),
+      Range(0, self.partitions.length),
       (index: Int, data: Long) => totalCount.addAndGet(data),
       totalCount.get())
   }
@@ -54,8 +54,8 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
    * Returns a future for retrieving all elements of this RDD.
    */
   def collectAsync(): FutureAction[Seq[T]] = {
-    val results = new Array[Array[T]](self.partitions.size)
-    self.context.submitJob[T, Array[T], Seq[T]](self, _.toArray, Range(0, self.partitions.size),
+    val results = new Array[Array[T]](self.partitions.length)
+    self.context.submitJob[T, Array[T], Seq[T]](self, _.toArray, Range(0, self.partitions.length),
       (index, data) => results(index) = data, results.flatten.toSeq)
   }
 
@@ -111,15 +111,15 @@ class AsyncRDDActions[T: ClassTag](self: RDD[T]) extends Serializable with Loggi
    */
   def foreachAsync(f: T => Unit): FutureAction[Unit] = {
     val cleanF = self.context.clean(f)
-    self.context.submitJob[T, Unit, Unit](self, _.foreach(cleanF), Range(0, self.partitions.size),
+    self.context.submitJob[T, Unit, Unit](self, _.foreach(cleanF), Range(0, self.partitions.length),
       (index, data) => Unit, Unit)
   }
 
   /**
    * Applies a function f to each partition of this RDD.
    */
   def foreachPartitionAsync(f: Iterator[T] => Unit): FutureAction[Unit] = {
-    self.context.submitJob[T, Unit, Unit](self, f, Range(0, self.partitions.size),
+    self.context.submitJob[T, Unit, Unit](self, f, Range(0, self.partitions.length),
       (index, data) => Unit, Unit)
   }
 }

core/src/main/scala/org/apache/spark/rdd/AsyncRDDActions.scala

@@ -36,7 +36,7 @@ class BlockRDD[T: ClassTag](@transient sc: SparkContext, @transient val blockIds
 
   override def getPartitions: Array[Partition] = {
     assertValid()
-    (0 until blockIds.size).map(i => {
+    (0 until blockIds.length).map(i => {
       new BlockRDDPartition(blockIds(i), i).asInstanceOf[Partition]
     }).toArray
   }

core/src/main/scala/org/apache/spark/rdd/BlockRDD.scala

@@ -53,11 +53,11 @@ class CartesianRDD[T: ClassTag, U: ClassTag](
   extends RDD[Pair[T, U]](sc, Nil)
   with Serializable {
 
-  val numPartitionsInRdd2 = rdd2.partitions.size
+  val numPartitionsInRdd2 = rdd2.partitions.length
 
   override def getPartitions: Array[Partition] = {
     // create the cross product split
-    val array = new Array[Partition](rdd1.partitions.size * rdd2.partitions.size)
+    val array = new Array[Partition](rdd1.partitions.length * rdd2.partitions.length)
     for (s1 <- rdd1.partitions; s2 <- rdd2.partitions) {
       val idx = s1.index * numPartitionsInRdd2 + s2.index
       array(idx) = new CartesianPartition(idx, rdd1, rdd2, s1.index, s2.index)

core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala

@@ -49,7 +49,7 @@ class CheckpointRDD[T: ClassTag](sc: SparkContext, val checkpointPath: String)
     if (fs.exists(cpath)) {
       val dirContents = fs.listStatus(cpath).map(_.getPath)
       val partitionFiles = dirContents.filter(_.getName.startsWith("part-")).map(_.toString).sorted
-      val numPart =  partitionFiles.size
+      val numPart =  partitionFiles.length
       if (numPart > 0 && (! partitionFiles(0).endsWith(CheckpointRDD.splitIdToFile(0)) ||
           ! partitionFiles(numPart-1).endsWith(CheckpointRDD.splitIdToFile(numPart-1)))) {
         throw new SparkException("Invalid checkpoint directory: " + checkpointPath)

core/src/main/scala/org/apache/spark/rdd/CheckpointRDD.scala

@@ -99,7 +99,7 @@ class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part:
 
   override def getPartitions: Array[Partition] = {
     val array = new Array[Partition](part.numPartitions)
-    for (i <- 0 until array.size) {
+    for (i <- 0 until array.length) {
       // Each CoGroupPartition will have a dependency per contributing RDD
       array(i) = new CoGroupPartition(i, rdds.zipWithIndex.map { case (rdd, j) =>
         // Assume each RDD contributed a single dependency, and get it
@@ -120,7 +120,7 @@ class CoGroupedRDD[K](@transient var rdds: Seq[RDD[_ <: Product2[K, _]]], part:
     val sparkConf = SparkEnv.get.conf
     val externalSorting = sparkConf.getBoolean("spark.shuffle.spill", true)
     val split = s.asInstanceOf[CoGroupPartition]
-    val numRdds = split.deps.size
+    val numRdds = split.deps.length
 
     // A list of (rdd iterator, dependency number) pairs
     val rddIterators = new ArrayBuffer[(Iterator[Product2[K, Any]], Int)]