diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
index c25cee74bc91f..1d79bed6cc0ee 100644
--- a/core/src/main/scala/org/apache/spark/SparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -933,7 +933,6 @@ class SparkContext(config: SparkConf) extends Logging {
   def stop() {
     postApplicationEnd()
     ui.stop()
-    eventLogger.foreach(_.stop())
     // Do this only if not stopped already - best case effort.
     // prevent NPE if stopped more than once.
     val dagSchedulerCopy = dagScheduler
@@ -942,13 +941,14 @@ class SparkContext(config: SparkConf) extends Logging {
       metadataCleaner.cancel()
       cleaner.foreach(_.stop())
       dagSchedulerCopy.stop()
-      listenerBus.stop()
       taskScheduler = null
       // TODO: Cache.stop()?
       env.stop()
       SparkEnv.set(null)
       ShuffleMapTask.clearCache()
       ResultTask.clearCache()
+      listenerBus.stop()
+      eventLogger.foreach(_.stop())
       logInfo("Successfully stopped SparkContext")
     } else {
       logInfo("SparkContext already stopped")
diff --git a/core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala b/core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala
index ebc6eb8fb0fd4..ef13b26a6c047 100644
--- a/core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala
+++ b/core/src/main/scala/org/apache/spark/scheduler/LiveListenerBus.scala
@@ -36,6 +36,22 @@ private[spark] class LiveListenerBus extends SparkListenerBus with Logging {
   private val eventQueue = new LinkedBlockingQueue[SparkListenerEvent](EVENT_QUEUE_CAPACITY)
   private var queueFullErrorMessageLogged = false
   private var started = false
+  private val listenerThread = new Thread("SparkListenerBus") {
+    setDaemon(true)
+    override def run() {
+      while (true) {
+        val event = eventQueue.take
+        if (event == SparkListenerShutdown) {
+          // Get out of the while loop and shutdown the daemon thread
+          return
+        }
+        postToAll(event)
+      }
+    }
+  }
+
+  // Exposed for testing
+  @volatile private[spark] var stopCalled = false
 
   /**
    * Start sending events to attached listeners.
@@ -48,20 +64,8 @@ private[spark] class LiveListenerBus extends SparkListenerBus with Logging {
     if (started) {
       throw new IllegalStateException("Listener bus already started!")
     }
+    listenerThread.start()
     started = true
-    new Thread("SparkListenerBus") {
-      setDaemon(true)
-      override def run() {
-        while (true) {
-          val event = eventQueue.take
-          if (event == SparkListenerShutdown) {
-            // Get out of the while loop and shutdown the daemon thread
-            return
-          }
-          postToAll(event)
-        }
-      }
-    }.start()
   }
 
   def post(event: SparkListenerEvent, blocking: Boolean = false) {
@@ -98,9 +102,11 @@ private[spark] class LiveListenerBus extends SparkListenerBus with Logging {
   }
 
   def stop() {
+    stopCalled = true
     if (!started) {
       throw new IllegalStateException("Attempted to stop a listener bus that has not yet started!")
     }
     post(SparkListenerShutdown)
+    listenerThread.join()
   }
 }
diff --git a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
index 7c843772bc2e0..dc704e07a81de 100644
--- a/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
+++ b/core/src/test/scala/org/apache/spark/scheduler/SparkListenerSuite.scala
@@ -17,6 +17,8 @@
 
 package org.apache.spark.scheduler
 
+import java.util.concurrent.Semaphore
+
 import scala.collection.mutable
 
 import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite}
@@ -72,6 +74,49 @@ class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatc
     }
   }
 
+  test("bus.stop() waits for the event queue to completely drain") {
+    @volatile var drained = false
+
+    // Tells the listener to stop blocking
+    val listenerWait = new Semaphore(1)
+
+    // When stop has returned
+    val stopReturned = new Semaphore(1)
+
+    class BlockingListener extends SparkListener {
+      override def onJobEnd(jobEnd: SparkListenerJobEnd) = {
+        listenerWait.acquire()
+        drained = true
+      }
+    }
+
+    val bus = new LiveListenerBus
+    val blockingListener = new BlockingListener
+
+    bus.addListener(blockingListener)
+    bus.start()
+    bus.post(SparkListenerJobEnd(0, JobSucceeded))
+
+    // the queue should not drain immediately
+    assert(!drained)
+
+    new Thread("ListenerBusStopper") {
+      override def run() {
+        // stop() will block until notify() is called below
+        bus.stop()
+        stopReturned.release(1)
+      }
+    }.start()
+
+    while (!bus.stopCalled) {
+      Thread.sleep(10)
+    }
+
+    listenerWait.release()
+    stopReturned.acquire()
+    assert(drained)
+  }
+
   test("basic creation of StageInfo") {
     val listener = new SaveStageAndTaskInfo
     sc.addSparkListener(listener)
diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
index e698b9bf376e1..038afbcba80a3 100644
--- a/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/SparkHdfsLR.scala
@@ -73,6 +73,6 @@ object SparkHdfsLR {
     }
 
     println("Final w: " + w)
-    System.exit(0)
+    sc.stop()
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
index ae27c57799873..a6c049e517ee0 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
@@ -30,7 +30,6 @@ import org.apache.spark.rdd.RDD
 
 /**
  * :: DeveloperApi ::
- *
  * The Java stubs necessary for the Python mllib bindings.
  */
 @DeveloperApi
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
index 5a45f12f1aa12..18658850a2f64 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/classification/NaiveBayes.scala
@@ -29,7 +29,6 @@ import org.apache.spark.rdd.RDD
 
 /**
  * :: Experimental ::
- *
  * Model for Naive Bayes Classifiers.
  *
  * @param labels list of labels
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
index 8f565eb60a60f..90cf8525df523 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
@@ -78,7 +78,6 @@ class KMeans private (
 
   /**
    * :: Experimental ::
-   *
    * Set the number of runs of the algorithm to execute in parallel. We initialize the algorithm
    * this many times with random starting conditions (configured by the initialization mode), then
    * return the best clustering found over any run. Default: 1.
@@ -398,9 +397,6 @@ object KMeans {
     MLUtils.fastSquaredDistance(v1.vector, v1.norm, v2.vector, v2.norm)
   }
 
-  /**
-   * :: Experimental ::
-   */
   @Experimental
   def main(args: Array[String]) {
     if (args.length < 4) {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala
index 89d5c03d76c42..56b8fdcda66eb 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala
@@ -34,7 +34,6 @@ case class MatrixEntry(i: Long, j: Long, value: Double)
 
 /**
  * :: Experimental ::
- *
  * Represents a matrix in coordinate format.
  *
  * @param entries matrix entries
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala
index 24c123ab7eb51..132b3af72d9ce 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala
@@ -26,7 +26,6 @@ import org.apache.spark.mllib.linalg.SingularValueDecomposition
 
 /**
  * :: Experimental ::
- *
  * Represents a row of [[org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix]].
  */
 @Experimental
@@ -34,7 +33,6 @@ case class IndexedRow(index: Long, vector: Vector)
 
 /**
  * :: Experimental ::
- *
  * Represents a row-oriented [[org.apache.spark.mllib.linalg.distributed.DistributedMatrix]] with
  * indexed rows.
  *
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
index 8d32c1a6dbba1..f65f43dd3007b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
@@ -30,7 +30,6 @@ import org.apache.spark.Logging
 
 /**
  * :: Experimental ::
- *
  * Represents a row-oriented distributed Matrix with no meaningful row indices.
  *
  * @param rows rows stored as an RDD[Vector]
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
index 1176dc9dbc08d..679842f831c2a 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.linalg.{Vectors, Vector}
 
 /**
  * :: DeveloperApi ::
- *
  * Class used to compute the gradient for a loss function, given a single data point.
  */
 @DeveloperApi
@@ -56,7 +55,6 @@ abstract class Gradient extends Serializable {
 
 /**
  * :: DeveloperApi ::
- *
  * Compute gradient and loss for a logistic loss function, as used in binary classification.
  * See also the documentation for the precise formulation.
  */
@@ -100,7 +98,6 @@ class LogisticGradient extends Gradient {
 
 /**
  * :: DeveloperApi ::
- *
  * Compute gradient and loss for a Least-squared loss function, as used in linear regression.
  * This is correct for the averaged least squares loss function (mean squared error)
  *              L = 1/n ||A weights-y||^2
@@ -135,7 +132,6 @@ class LeastSquaresGradient extends Gradient {
 
 /**
  * :: DeveloperApi ::
- *
  * Compute gradient and loss for a Hinge loss function, as used in SVM binary classification.
  * See also the documentation for the precise formulation.
  * NOTE: This assumes that the labels are {0,1}
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala
index 04267d967dcad..f60417f21d4b9 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/GradientDescent.scala
@@ -28,7 +28,6 @@ import org.apache.spark.mllib.linalg.{Vectors, Vector}
 
 /**
  * :: DeveloperApi ::
- *
  * Class used to solve an optimization problem using Gradient Descent.
  * @param gradient Gradient function to be used.
  * @param updater Updater to be used to update weights after every iteration.
@@ -113,7 +112,6 @@ class GradientDescent(private var gradient: Gradient, private var updater: Updat
 
 /**
  * :: DeveloperApi ::
- *
  * Top-level method to run gradient descent.
  */
 @DeveloperApi
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Optimizer.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Optimizer.scala
index 0a313f3104b14..e41d9bbe18c37 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Optimizer.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Optimizer.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.linalg.Vector
 
 /**
  * :: DeveloperApi ::
- *
  * Trait for optimization problem solvers.
  */
 @DeveloperApi
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Updater.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Updater.scala
index e67816796c6b1..3ed3a5b9b3843 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Updater.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Updater.scala
@@ -26,7 +26,6 @@ import org.apache.spark.mllib.linalg.{Vectors, Vector}
 
 /**
  * :: DeveloperApi ::
- *
  * Class used to perform steps (weight update) using Gradient Descent methods.
  *
  * For general minimization problems, or for regularized problems of the form
@@ -64,7 +63,6 @@ abstract class Updater extends Serializable {
 
 /**
  * :: DeveloperApi ::
- *
  * A simple updater for gradient descent *without* any regularization.
  * Uses a step-size decreasing with the square root of the number of iterations.
  */
@@ -86,7 +84,6 @@ class SimpleUpdater extends Updater {
 
 /**
  * :: DeveloperApi ::
- *
  * Updater for L1 regularized problems.
  *          R(w) = ||w||_1
  * Uses a step-size decreasing with the square root of the number of iterations.
@@ -131,7 +128,6 @@ class L1Updater extends Updater {
 
 /**
  * :: DeveloperApi ::
- *
  * Updater for L2 regularized problems.
  *          R(w) = 1/2 ||w||^2
  * Uses a step-size decreasing with the square root of the number of iterations.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
index 60cbb1c1e1d86..5cc47de8ffdfc 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala
@@ -140,7 +140,6 @@ class ALS private (
 
   /**
    * :: Experimental ::
-   *
    * Sets the constant used in computing confidence in implicit ALS. Default: 1.0.
    */
   @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
index e05224fc7caf2..471546cd82c7d 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala
@@ -70,7 +70,6 @@ class MatrixFactorizationModel(
 
   /**
    * :: DeveloperApi ::
-   *
    * Predict the rating of many users for many products.
    * This is a Java stub for python predictAll()
    *
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
index c24f5afb99686..3bd0017aa196a 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/regression/GeneralizedLinearAlgorithm.scala
@@ -103,7 +103,6 @@ abstract class GeneralizedLinearAlgorithm[M <: GeneralizedLinearModel]
 
   /**
    * :: Experimental ::
-   *
    * Set if the algorithm should validate data before training. Default true.
    */
   @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
index c8a966cd5f5a8..3019447ce4cd9 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala
@@ -35,7 +35,6 @@ import org.apache.spark.mllib.linalg.{Vector, Vectors}
 
 /**
  * :: Experimental ::
- *
  * A class that implements a decision tree algorithm for classification and regression. It
  * supports both continuous and categorical features.
  * @param strategy The configuration parameters for the tree algorithm which specify the type
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Algo.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Algo.scala
index 017f84f3b9e8b..79a01f58319e8 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Algo.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Algo.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.Experimental
 
 /**
  * :: Experimental ::
- *
  * Enum to select the algorithm for the decision tree
  */
 @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/FeatureType.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/FeatureType.scala
index c0254c32c2dce..f4c877232750f 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/FeatureType.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/FeatureType.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.Experimental
 
 /**
  * :: Experimental ::
- *
  * Enum to describe whether a feature is "continuous" or "categorical"
  */
 @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/QuantileStrategy.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/QuantileStrategy.scala
index b3e8b224beeaa..7da976e55a722 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/QuantileStrategy.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/QuantileStrategy.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.Experimental
 
 /**
  * :: Experimental ::
- *
  * Enum for selecting the quantile calculation strategy
  */
 @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala
index 482faaa9e7256..8767aca47cd5a 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.tree.configuration.QuantileStrategy._
 
 /**
  * :: Experimental ::
- *
  * Stores all the configuration options for tree construction
  * @param algo classification or regression
  * @param impurity criterion used for information gain calculation
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Entropy.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Entropy.scala
index 55c43f2fcf9c5..60f43e9278d2a 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Entropy.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Entropy.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental}
 
 /**
  * :: Experimental ::
- *
  * Class for calculating [[http://en.wikipedia.org/wiki/Binary_entropy_function entropy]] during
  * binary classification.
  */
@@ -32,7 +31,6 @@ object Entropy extends Impurity {
 
   /**
    * :: DeveloperApi ::
-   *
    * entropy calculation
    * @param c0 count of instances with label 0
    * @param c1 count of instances with label 1
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Gini.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Gini.scala
index c923b8e8f4cf1..c51d76d9b4c5b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Gini.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Gini.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental}
 
 /**
  * :: Experimental ::
- *
  * Class for calculating the
  * [[http://en.wikipedia.org/wiki/Decision_tree_learning#Gini_impurity Gini impurity]]
  * during binary classification.
@@ -31,7 +30,6 @@ object Gini extends Impurity {
 
   /**
    * :: DeveloperApi ::
-   *
    * Gini coefficient calculation
    * @param c0 count of instances with label 0
    * @param c1 count of instances with label 1
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Impurity.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Impurity.scala
index f407796596c6c..8eab247cf0932 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Impurity.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Impurity.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental}
 
 /**
  * :: Experimental ::
- *
  * Trait for calculating information gain.
  */
 @Experimental
@@ -29,7 +28,6 @@ trait Impurity extends Serializable {
 
   /**
    * :: DeveloperApi ::
-   *
    * information calculation for binary classification
    * @param c0 count of instances with label 0
    * @param c1 count of instances with label 1
@@ -40,7 +38,6 @@ trait Impurity extends Serializable {
 
   /**
    * :: DeveloperApi ::
-   *
    * information calculation for regression
    * @param count number of instances
    * @param sum sum of labels
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Variance.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Variance.scala
index 2c64644f4ed0f..47d07122af30f 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Variance.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/impurity/Variance.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.{DeveloperApi, Experimental}
 
 /**
  * :: Experimental ::
- *
  * Class for calculating variance during regression
  */
 @Experimental
@@ -31,7 +30,6 @@ object Variance extends Impurity {
 
   /**
    * :: DeveloperApi ::
-   *
    * variance calculation
    * @param count number of instances
    * @param sum sum of labels
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
index 0f76f4a049057..bf692ca8c4bd7 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/DecisionTreeModel.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.linalg.Vector
 
 /**
  * :: Experimental ::
- *
  * Model to store the decision tree parameters
  * @param topNode root node
  * @param algo algorithm type -- classification or regression
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/InformationGainStats.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/InformationGainStats.scala
index d36b58e92ced6..cc8a24cce9614 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/InformationGainStats.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/InformationGainStats.scala
@@ -21,7 +21,6 @@ import org.apache.spark.annotation.DeveloperApi
 
 /**
  * :: DeveloperApi ::
- *
  * Information gain statistics for each split
  * @param gain information gain value
  * @param impurity current node impurity
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Node.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Node.scala
index 339972141498c..682f213f411a7 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Node.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Node.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.linalg.Vector
 
 /**
  * :: DeveloperApi ::
- *
  * Node in a decision tree
  * @param id integer node id
  * @param predict predicted value at the node
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Split.scala b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Split.scala
index 8bbb343079b49..d7ffd386c05ee 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Split.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/tree/model/Split.scala
@@ -22,7 +22,6 @@ import org.apache.spark.mllib.tree.configuration.FeatureType.FeatureType
 
 /**
  * :: DeveloperApi ::
- *
  * Split applied to a feature
  * @param feature feature index
  * @param threshold threshold for continuous feature
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/DataValidators.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/DataValidators.scala
index 230c409e1be33..45f95482a1def 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/DataValidators.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/DataValidators.scala
@@ -24,7 +24,6 @@ import org.apache.spark.mllib.regression.LabeledPoint
 
 /**
  * :: DeveloperApi ::
- *
  * A collection of methods used to validate data before applying ML algorithms.
  */
 @DeveloperApi
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/KMeansDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/KMeansDataGenerator.scala
index e693d13703987..6eaebaf7dba9f 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/KMeansDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/KMeansDataGenerator.scala
@@ -25,7 +25,6 @@ import org.apache.spark.rdd.RDD
 
 /**
  * :: DeveloperApi ::
- *
  * Generate test data for KMeans. This class first chooses k cluster centers
  * from a d-dimensional Gaussian distribution scaled by factor r and then creates a Gaussian
  * cluster with scale 1 around each center.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala
index 140ff92869176..c8e160d00c2d6 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/LinearDataGenerator.scala
@@ -30,7 +30,6 @@ import org.apache.spark.mllib.regression.LabeledPoint
 
 /**
  * :: DeveloperApi ::
- *
  * Generate sample data used for Linear Data. This class generates
  * uniformly random values for every feature and adds Gaussian noise with mean `eps` to the
  * response variable `Y`.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/LogisticRegressionDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/LogisticRegressionDataGenerator.scala
index ca06b9ad58538..c82cd8fd4641c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/LogisticRegressionDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/LogisticRegressionDataGenerator.scala
@@ -27,7 +27,6 @@ import org.apache.spark.mllib.linalg.Vectors
 
 /**
  * :: DeveloperApi ::
- *
  * Generate test data for LogisticRegression. This class chooses positive labels
  * with probability `probOne` and scales features for positive examples by `eps`.
  */
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
index 3bd86d6813375..3f413faca6bb4 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MFDataGenerator.scala
@@ -27,29 +27,28 @@ import org.apache.spark.rdd.RDD
 
 /**
  * :: DeveloperApi ::
+ * Generate RDD(s) containing data for Matrix Factorization.
  *
-* Generate RDD(s) containing data for Matrix Factorization.
-*
-* This method samples training entries according to the oversampling factor
-* 'trainSampFact', which is a multiplicative factor of the number of
-* degrees of freedom of the matrix: rank*(m+n-rank).
-*
-* It optionally samples entries for a testing matrix using
-* 'testSampFact', the percentage of the number of training entries
-* to use for testing.
-*
-* This method takes the following inputs:
-*   sparkMaster    (String) The master URL.
-*   outputPath     (String) Directory to save output.
-*   m              (Int) Number of rows in data matrix.
-*   n              (Int) Number of columns in data matrix.
-*   rank           (Int) Underlying rank of data matrix.
-*   trainSampFact  (Double) Oversampling factor.
-*   noise          (Boolean) Whether to add gaussian noise to training data.
-*   sigma          (Double) Standard deviation of added gaussian noise.
-*   test           (Boolean) Whether to create testing RDD.
-*   testSampFact   (Double) Percentage of training data to use as test data.
-*/
+ * This method samples training entries according to the oversampling factor
+ * 'trainSampFact', which is a multiplicative factor of the number of
+ * degrees of freedom of the matrix: rank*(m+n-rank).
+ *
+ * It optionally samples entries for a testing matrix using
+ * 'testSampFact', the percentage of the number of training entries
+ * to use for testing.
+ *
+ * This method takes the following inputs:
+ *   sparkMaster    (String) The master URL.
+ *   outputPath     (String) Directory to save output.
+ *   m              (Int) Number of rows in data matrix.
+ *   n              (Int) Number of columns in data matrix.
+ *   rank           (Int) Underlying rank of data matrix.
+ *   trainSampFact  (Double) Oversampling factor.
+ *   noise          (Boolean) Whether to add gaussian noise to training data.
+ *   sigma          (Double) Standard deviation of added gaussian noise.
+ *   test           (Boolean) Whether to create testing RDD.
+ *   testSampFact   (Double) Percentage of training data to use as test data.
+ */
 @DeveloperApi
 object MFDataGenerator {
   def main(args: Array[String]) {
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
index 7f9804deaf33f..ac2360c429e2b 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
@@ -124,7 +124,6 @@ object MLUtils {
 
   /**
    * :: Experimental ::
-   *
    * Load labeled data from a file. The data format used here is
    * <L>, <f1> <f2> ...
    * where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double.
@@ -146,7 +145,6 @@ object MLUtils {
 
   /**
    * :: Experimental ::
-   *
    * Save labeled data to a file. The data format used here is
    * <L>, <f1> <f2> ...
    * where <f1>, <f2> are feature values in Double and <L> is the corresponding label as Double.
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/SVMDataGenerator.scala b/mllib/src/main/scala/org/apache/spark/mllib/util/SVMDataGenerator.scala
index 87a6f2a0c3976..ba8190b0e07e8 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/SVMDataGenerator.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/SVMDataGenerator.scala
@@ -29,7 +29,6 @@ import org.apache.spark.mllib.regression.LabeledPoint
 
 /**
  * :: DeveloperApi ::
- *
  * Generate sample data used for SVM. This class generates uniform random values
  * for the features and adds Gaussian noise with weight 0.1 to generate labels.
  */