diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index 0c35c666805dd560af74e8c2dfd26a0e3a535ba9..94ba22306afbddce6cbd98dbaadae7e0445d3a1a 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -48,6 +48,35 @@ from py4j.java_collections import ListConverter, MapConverter
 __all__ = ["RDD"]
 
 
+# TODO: for Python 3.3+, PYTHONHASHSEED should be reset to disable randomized
+# hash for string
+def portable_hash(x):
+    """
+    This function returns consistant hash code for builtin types, especially
+    for None and tuple with None.
+
+    The algrithm is similar to that one used by CPython 2.7
+
+    >>> portable_hash(None)
+    0
+    >>> portable_hash((None, 1))
+    219750521
+    """
+    if x is None:
+        return 0
+    if isinstance(x, tuple):
+        h = 0x345678
+        for i in x:
+            h ^= portable_hash(i)
+            h *= 1000003
+            h &= 0xffffffff
+        h ^= len(x)
+        if h == -1:
+            h = -2
+        return h
+    return hash(x)
+
+
 def _extract_concise_traceback():
     """
     This function returns the traceback info for a callsite, returns a dict
@@ -1164,7 +1193,9 @@ class RDD(object):
         return python_right_outer_join(self, other, numPartitions)
 
     # TODO: add option to control map-side combining
-    def partitionBy(self, numPartitions, partitionFunc=None):
+    # portable_hash is used as default, because builtin hash of None is different
+    # cross machines.
+    def partitionBy(self, numPartitions, partitionFunc=portable_hash):
         """
         Return a copy of the RDD partitioned using the specified partitioner.
 
@@ -1176,8 +1207,6 @@ class RDD(object):
         if numPartitions is None:
             numPartitions = self._defaultReducePartitions()
 
-        if partitionFunc is None:
-            partitionFunc = lambda x: 0 if x is None else hash(x)
         # Transferring O(n) objects to Java is too expensive.  Instead, we'll
         # form the hash buckets in Python, transferring O(numPartitions) objects
         # to Java.  Each object is a (splitNumber, [objects]) pair.