diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala
index bafff80adc54b..46ef05d9c37a1 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/DStream.scala
@@ -17,14 +17,11 @@
 
 package org.apache.spark.streaming.dstream
 
-
-import java.io._
+import java.io.{IOException, ObjectInputStream, ObjectOutputStream}
 
 import scala.deprecated
 import scala.collection.mutable.HashMap
 import scala.reflect.ClassTag
-import java.io.{IOException, ObjectInputStream, ObjectOutputStream}
-import scala.util.control.Breaks._
 
 import org.apache.spark.{Logging, SparkException}
 import org.apache.spark.rdd.{BlockRDD, RDD}
@@ -34,7 +31,6 @@ import org.apache.spark.streaming.StreamingContext._
 import org.apache.spark.streaming.scheduler.Job
 import org.apache.spark.util.MetadataCleaner
 import org.apache.spark.streaming.Duration
-import org.apache.spark.api.python.PythonRDD
 
 /**
  * A Discretized Stream (DStream), the basic abstraction in Spark Streaming, is a continuous
@@ -562,11 +558,9 @@ abstract class DStream[T: ClassTag] (
     // DStreams can't be serialized with closures, we can't proactively check 
     // it for serializability and so we pass the optional false to SparkContext.clean
 
-    // serialized python
     val cleanedF = context.sparkContext.clean(transformFunc, false)
     val realTransformFunc =  (rdds: Seq[RDD[_]], time: Time) => {
       assert(rdds.length == 1)
-      // if transformfunc is fine, it is okay
       cleanedF(rdds.head.asInstanceOf[RDD[T]], time)
     }
     new TransformedDStream[U](Seq(this), realTransformFunc)