diff --git a/python/pyspark/mllib/regression.py b/python/pyspark/mllib/regression.py
index 5ddbbee4babdd..e438694dccdb8 100644
--- a/python/pyspark/mllib/regression.py
+++ b/python/pyspark/mllib/regression.py
@@ -19,6 +19,7 @@
 from numpy import array
 
 from pyspark import RDD
+from pyspark.streaming.dstream import DStream
 from pyspark.mllib.common import callMLlibFunc, _py2java, _java2py, inherit_doc
 from pyspark.mllib.linalg import SparseVector, Vectors, _convert_to_vector
 from pyspark.mllib.util import Saveable, Loader
@@ -570,6 +571,47 @@ def train(cls, data, isotonic=True):
         return IsotonicRegressionModel(boundaries.toArray(), predictions.toArray(), isotonic)
 
 
+@inherit_doc
+class StreamingLinearRegressionWithSGD(LinearRegressionModel):
+
+    def _validate_dstream(self, dstream):
+        if not isinstance(dstream, DStream):
+            raise TypeError(
+                "dstream should be a DStream object, got %s" % type(dstream))
+        if not self.latestModel:
+            raise ValueError(
+                "Model must be intialized using setInitialWeights")
+
+    def __init__(self, stepSize, numIterations, miniBatchFraction):
+        self.stepSize = stepSize
+        self.numIterations = numIterations
+        self.miniBatchFraction = miniBatchFraction
+        self.latestModel = None
+
+    def setInitialWeights(self, initialWeights):
+        initialWeights = _convert_to_vector(initialWeights)
+        self.latestModel = LinearRegressionModel(initialWeights, 0)
+
+    def trainOn(self, dstream):
+        self._validate_dstream(dstream)
+
+        def update(rdd):
+            if rdd:
+                self.latestModel = LinearRegressionWithSGD.train(
+                    rdd, self.numIteration, self.stepSize,
+                    self.miniBatchFraction, self.latestModel.weights)
+
+        dstream.foreachRDD(update)
+
+    def predictOn(self, dstream):
+        self._validate_dstream(dstream)
+        return dstream.map(self.latestModel.predict)
+
+    def predictOnValues(self, dstream):
+        self._validate_dstream(dstream)
+        return dstream.mapValues(self.latestModel.predict)
+
+
 def _test():
     import doctest
     from pyspark import SparkContext