[SPARK-1065] [PySpark] improve supporting for large broadcast

Passing large object by py4j is very slow (cost much memory), so pass broadcast objects via files (similar to parallelize()).

Add an option to keep object in driver (it's False by default) to save memory in driver.

Author: Davies Liu <davies.liu@gmail.com>

Closes #1912 from davies/broadcast and squashes the following commits:

e06df4a [Davies Liu] load broadcast from disk in driver automatically
db3f232 [Davies Liu] fix serialization of accumulator
631a827 [Davies Liu] Merge branch 'master' into broadcast
c7baa8c [Davies Liu] compress serrialized broadcast and command
9a7161f [Davies Liu] fix doc tests
e93cf4b [Davies Liu] address comments: add test
6226189 [Davies Liu] improve large broadcast

6 files changed, 73 insertions, 21 deletions

diff --git a/python/pyspark/broadcast.py b/python/pyspark/broadcast.py
index f3e64989ed..675a2fcd2f 100644
--- a/python/pyspark/broadcast.py
+++ b/python/pyspark/broadcast.py
@@ -21,18 +21,16 @@
 >>> b = sc.broadcast([1, 2, 3, 4, 5])
 >>> b.value
 [1, 2, 3, 4, 5]
-
->>> from pyspark.broadcast import _broadcastRegistry
->>> _broadcastRegistry[b.bid] = b
->>> from cPickle import dumps, loads
->>> loads(dumps(b)).value
-[1, 2, 3, 4, 5]
-
 >>> sc.parallelize([0, 0]).flatMap(lambda x: b.value).collect()
 [1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
+>>> b.unpersist()
 
 >>> large_broadcast = sc.broadcast(list(range(10000)))
 """
+import os
+
+from pyspark.serializers import CompressedSerializer, PickleSerializer
+
 # Holds broadcasted data received from Java, keyed by its id.
 _broadcastRegistry = {}
 
@@ -52,17 +50,38 @@ class Broadcast(object):
     Access its value through C{.value}.
     """
 
-    def __init__(self, bid, value, java_broadcast=None, pickle_registry=None):
+    def __init__(self, bid, value, java_broadcast=None,
+                 pickle_registry=None, path=None):
         """
         Should not be called directly by users -- use
         L{SparkContext.broadcast()<pyspark.context.SparkContext.broadcast>}
         instead.
         """
-        self.value = value
         self.bid = bid
+        if path is None:
+            self.value = value
         self._jbroadcast = java_broadcast
         self._pickle_registry = pickle_registry
+        self.path = path
+
+    def unpersist(self, blocking=False):
+        self._jbroadcast.unpersist(blocking)
+        os.unlink(self.path)
 
     def __reduce__(self):
         self._pickle_registry.add(self)
         return (_from_id, (self.bid, ))
+
+    def __getattr__(self, item):
+        if item == 'value' and self.path is not None:
+            ser = CompressedSerializer(PickleSerializer())
+            value = ser.load_stream(open(self.path)).next()
+            self.value = value
+            return value
+
+        raise AttributeError(item)
+
+
+if __name__ == "__main__":
+    import doctest
+    doctest.testmod()
diff --git a/python/pyspark/context.py b/python/pyspark/context.py
index 6c04923881..a90870ed3a 100644
--- a/python/pyspark/context.py
+++ b/python/pyspark/context.py
@@ -29,7 +29,7 @@ from pyspark.conf import SparkConf
 from pyspark.files import SparkFiles
 from pyspark.java_gateway import launch_gateway
 from pyspark.serializers import PickleSerializer, BatchedSerializer, UTF8Deserializer, \
-    PairDeserializer
+    PairDeserializer, CompressedSerializer
 from pyspark.storagelevel import StorageLevel
 from pyspark import rdd
 from pyspark.rdd import RDD
@@ -566,13 +566,19 @@ class SparkContext(object):
         """
         Broadcast a read-only variable to the cluster, returning a
         L{Broadcast<pyspark.broadcast.Broadcast>}
-        object for reading it in distributed functions. The variable will be
-        sent to each cluster only once.
+        object for reading it in distributed functions. The variable will
+        be sent to each cluster only once.
+
+        :keep: Keep the `value` in driver or not.
         """
-        pickleSer = PickleSerializer()
-        pickled = pickleSer.dumps(value)
-        jbroadcast = self._jsc.broadcast(bytearray(pickled))
-        return Broadcast(jbroadcast.id(), value, jbroadcast, self._pickled_broadcast_vars)
+        ser = CompressedSerializer(PickleSerializer())
+        # pass large object by py4j is very slow and need much memory
+        tempFile = NamedTemporaryFile(delete=False, dir=self._temp_dir)
+        ser.dump_stream([value], tempFile)
+        tempFile.close()
+        jbroadcast = self._jvm.PythonRDD.readBroadcastFromFile(self._jsc, tempFile.name)
+        return Broadcast(jbroadcast.id(), None, jbroadcast,
+                         self._pickled_broadcast_vars, tempFile.name)
 
     def accumulator(self, value, accum_param=None):
         """
diff --git a/python/pyspark/rdd.py b/python/pyspark/rdd.py
index 3934bdda0a..240381e5ba 100644
--- a/python/pyspark/rdd.py
+++ b/python/pyspark/rdd.py
@@ -36,7 +36,7 @@ from math import sqrt, log
 
 from pyspark.serializers import NoOpSerializer, CartesianDeserializer, \
     BatchedSerializer, CloudPickleSerializer, PairDeserializer, \
-    PickleSerializer, pack_long
+    PickleSerializer, pack_long, CompressedSerializer
 from pyspark.join import python_join, python_left_outer_join, \
     python_right_outer_join, python_cogroup
 from pyspark.statcounter import StatCounter
@@ -1810,7 +1810,8 @@ class PipelinedRDD(RDD):
             self._jrdd_deserializer = NoOpSerializer()
         command = (self.func, self._prev_jrdd_deserializer,
                    self._jrdd_deserializer)
-        pickled_command = CloudPickleSerializer().dumps(command)
+        ser = CompressedSerializer(CloudPickleSerializer())
+        pickled_command = ser.dumps(command)
         broadcast_vars = ListConverter().convert(
             [x._jbroadcast for x in self.ctx._pickled_broadcast_vars],
             self.ctx._gateway._gateway_client)
diff --git a/python/pyspark/serializers.py b/python/pyspark/serializers.py
index df90cafb24..74870c0edc 100644
--- a/python/pyspark/serializers.py
+++ b/python/pyspark/serializers.py
@@ -67,6 +67,7 @@ import struct
 import sys
 import types
 import collections
+import zlib
 
 from pyspark import cloudpickle
 
@@ -403,6 +404,22 @@ class AutoSerializer(FramedSerializer):
             raise ValueError("invalid sevialization type: %s" % _type)
 
 
+class CompressedSerializer(FramedSerializer):
+    """
+    compress the serialized data
+    """
+
+    def __init__(self, serializer):
+        FramedSerializer.__init__(self)
+        self.serializer = serializer
+
+    def dumps(self, obj):
+        return zlib.compress(self.serializer.dumps(obj), 1)
+
+    def loads(self, obj):
+        return self.serializer.loads(zlib.decompress(obj))
+
+
 class UTF8Deserializer(Serializer):
 
     """
diff --git a/python/pyspark/tests.py b/python/pyspark/tests.py
index 22b51110ed..f1fece998c 100644
--- a/python/pyspark/tests.py
+++ b/python/pyspark/tests.py
@@ -323,6 +323,13 @@ class TestRDDFunctions(PySparkTestCase):
         theDoes = self.sc.parallelize([jon, jane])
         self.assertEquals([jon, jane], theDoes.collect())
 
+    def test_large_broadcast(self):
+        N = 100000
+        data = [[float(i) for i in range(300)] for i in range(N)]
+        bdata = self.sc.broadcast(data)  # 270MB
+        m = self.sc.parallelize(range(1), 1).map(lambda x: len(bdata.value)).sum()
+        self.assertEquals(N, m)
+
 
 class TestIO(PySparkTestCase):
 
diff --git a/python/pyspark/worker.py b/python/pyspark/worker.py
index 2770f63059..77a9c4a0e0 100644
--- a/python/pyspark/worker.py
+++ b/python/pyspark/worker.py
@@ -30,7 +30,8 @@ from pyspark.broadcast import Broadcast, _broadcastRegistry
 from pyspark.cloudpickle import CloudPickler
 from pyspark.files import SparkFiles
 from pyspark.serializers import write_with_length, write_int, read_long, \
-    write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer
+    write_long, read_int, SpecialLengths, UTF8Deserializer, PickleSerializer, \
+    CompressedSerializer
 
 
 pickleSer = PickleSerializer()
@@ -65,12 +66,13 @@ def main(infile, outfile):
 
         # fetch names and values of broadcast variables
         num_broadcast_variables = read_int(infile)
+        ser = CompressedSerializer(pickleSer)
         for _ in range(num_broadcast_variables):
             bid = read_long(infile)
-            value = pickleSer._read_with_length(infile)
+            value = ser._read_with_length(infile)
             _broadcastRegistry[bid] = Broadcast(bid, value)
 
-        command = pickleSer._read_with_length(infile)
+        command = ser._read_with_length(infile)
         (func, deserializer, serializer) = command
         init_time = time.time()
         iterator = deserializer.load_stream(infile)