Remove Pickle-wrapping of Java objects in PySpark.

If we support custom serializers, the Python
worker will know what type of input to expect,
so we won't need to wrap Tuple2 and Strings into
pickled tuples and strings.

1 files changed, 7 insertions, 4 deletions

diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index 7019fb8bee..d3c4d13a1e 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -54,6 +54,7 @@ class RDD(object):
         self.is_checkpointed = False
         self.ctx = ctx
         self._partitionFunc = None
+        self._stage_input_is_pairs = False
 
     @property
     def context(self):
@@ -344,6 +345,7 @@ class RDD(object):
                     yield pair
             else:
                 yield pair
+        java_cartesian._stage_input_is_pairs = True
         return java_cartesian.flatMap(unpack_batches)
 
     def groupBy(self, f, numPartitions=None):
@@ -391,8 +393,8 @@ class RDD(object):
         """
         Return a list that contains all of the elements in this RDD.
         """
-        picklesInJava = self._jrdd.collect().iterator()
-        return list(self._collect_iterator_through_file(picklesInJava))
+        bytesInJava = self._jrdd.collect().iterator()
+        return list(self._collect_iterator_through_file(bytesInJava))
 
     def _collect_iterator_through_file(self, iterator):
         # Transferring lots of data through Py4J can be slow because
@@ -400,7 +402,7 @@ class RDD(object):
         # file and read it back.
         tempFile = NamedTemporaryFile(delete=False, dir=self.ctx._temp_dir)
         tempFile.close()
-        self.ctx._writeIteratorToPickleFile(iterator, tempFile.name)
+        self.ctx._writeToFile(iterator, tempFile.name)
         # Read the data into Python and deserialize it:
         with open(tempFile.name, 'rb') as tempFile:
             for item in read_from_pickle_file(tempFile):
@@ -941,6 +943,7 @@ class PipelinedRDD(RDD):
             self.func = func
             self.preservesPartitioning = preservesPartitioning
             self._prev_jrdd = prev._jrdd
+        self._stage_input_is_pairs = prev._stage_input_is_pairs
         self.is_cached = False
         self.is_checkpointed = False
         self.ctx = prev.ctx
@@ -959,7 +962,7 @@ class PipelinedRDD(RDD):
             def batched_func(split, iterator):
                 return batched(oldfunc(split, iterator), batchSize)
             func = batched_func
-        cmds = [func, self._bypass_serializer]
+        cmds = [func, self._bypass_serializer, self._stage_input_is_pairs]
         pipe_command = ' '.join(b64enc(cloudpickle.dumps(f)) for f in cmds)
         broadcast_vars = ListConverter().convert(
             [x._jbroadcast for x in self.ctx._pickled_broadcast_vars],