diff --git a/python/pyspark/streaming/context.py b/python/pyspark/streaming/context.py
index a647c9ec734df..00a1ec6f31fec 100644
--- a/python/pyspark/streaming/context.py
+++ b/python/pyspark/streaming/context.py
@@ -184,7 +184,7 @@ def _check_serialzers(self, rdds):
                 # reset them to sc.serializer
                 rdds[i] = rdds[i].map(lambda x: x, preservesPartitioning=True)
 
-    def queueStream(self, queue, oneAtATime=False, default=None):
+    def queueStream(self, queue, oneAtATime=True, default=None):
         """
         Create an input stream from an queue of RDDs or list. In each batch,
         it will process either one or all of the RDDs returned by the queue.
@@ -200,9 +200,12 @@ def queueStream(self, queue, oneAtATime=False, default=None):
         self._check_serialzers(rdds)
         jrdds = ListConverter().convert([r._jrdd for r in rdds],
                                         SparkContext._gateway._gateway_client)
-        jdstream = self._jvm.PythonDataInputStream(self._jssc, jrdds, oneAtATime,
-                                                   default and default._jrdd)
-        return DStream(jdstream.asJavaDStream(), self, rdds[0]._jrdd_deserializer)
+        queue = self._jvm.PythonDStream.toRDDQueue(jrdds)
+        if default:
+            jdstream = self._jssc.queueStream(queue, oneAtATime, default._jrdd)
+        else:
+            jdstream = self._jssc.queueStream(queue, oneAtATime)
+        return DStream(jdstream, self, rdds[0]._jrdd_deserializer)
 
     def transform(self, dstreams, transformFunc):
         """
diff --git a/streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala
index c0a1aa71840a5..d7dd0a0c5c88b 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/api/python/PythonDStream.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.streaming.api.python
 
 import java.util.{ArrayList => JArrayList}
+import scala.collection.JavaConversions._
 
 import org.apache.spark.rdd.RDD
 import org.apache.spark.api.java._
@@ -65,6 +66,16 @@ abstract class PythonDStream(parent: DStream[_]) extends DStream[Array[Byte]] (p
   val asJavaDStream  = JavaDStream.fromDStream(this)
 }
 
+object PythonDStream {
+
+  // convert list of RDD into queue of RDDs, for ssc.queueStream()
+  def toRDDQueue(rdds: JArrayList[JavaRDD[Array[Byte]]]): java.util.Queue[JavaRDD[Array[Byte]]] = {
+    val queue = new java.util.LinkedList[JavaRDD[Array[Byte]]]
+    rdds.forall(queue.add(_))
+    queue
+  }
+}
+
 /**
  * Transformed DStream in Python.
  *
@@ -243,46 +254,4 @@ class PythonForeachDStream(
   ) {
 
   this.register()
-}
-
-
-/**
- * similar to QueueInputStream
- */
-class PythonDataInputStream(
-    ssc_ : JavaStreamingContext,
-    inputRDDs: JArrayList[JavaRDD[Array[Byte]]],
-    oneAtAtime: Boolean,
-    defaultRDD: JavaRDD[Array[Byte]]
-  ) extends InputDStream[Array[Byte]](JavaStreamingContext.toStreamingContext(ssc_)) {
-
-  val emptyRDD = if (defaultRDD != null) {
-    Some(defaultRDD.rdd)
-  } else {
-    Some(ssc.sparkContext.emptyRDD[Array[Byte]])
-  }
-
-  def start() {}
-
-  def stop() {}
-
-  def compute(validTime: Time): Option[RDD[Array[Byte]]] = {
-    val index = ((validTime - zeroTime) / slideDuration - 1).toInt
-    if (oneAtAtime) {
-      if (index == 0) {
-        val rdds = inputRDDs.toArray.map(_.asInstanceOf[JavaRDD[Array[Byte]]].rdd).toSeq
-        Some(ssc.sparkContext.union(rdds))
-      } else {
-        emptyRDD
-      }
-    } else {
-      if (index < inputRDDs.size()) {
-        Some(inputRDDs.get(index).rdd)
-      } else {
-        emptyRDD
-      }
-    }
-  }
-
-  val asJavaDStream  = JavaDStream.fromDStream(this)
-}
+}
\ No newline at end of file