spark-instrumented-optimizer/python/pyspark/broadcast.py
Davies Liu 6cf507685e [SPARK-4548] []SPARK-4517] improve performance of python broadcast
Re-implement the Python broadcast using file:

1) serialize the python object using cPickle, write into disks.
2) Create a wrapper in JVM (for the dumped file), it read data from during serialization
3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors
4) During deserialization, writing the data into disk.
5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access.

It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor).

Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2):

         name |   1.1   | 1.2 with this patch |  improvement
---------|--------|---------|--------
      python-broadcast-w-bytes  |	25.20  |	9.33   |	170.13% |
        python-broadcast-w-set	  |     4.13	   |    4.50  |	-8.35%  |

Testing with 100 tasks (16 CPUs):

         name |   1.1   | 1.2 with this patch |  improvement
---------|--------|---------|--------
     python-broadcast-w-bytes	| 38.16	| 8.40	 | 353.98%
        python-broadcast-w-set	| 23.29	| 9.59 |	142.80%

Author: Davies Liu <davies@databricks.com>

Closes #3417 from davies/pybroadcast and squashes the following commits:

50a58e0 [Davies Liu] address comments
b98de1d [Davies Liu] disable gc while unpickle
e5ee6b9 [Davies Liu] support large string
09303b8 [Davies Liu] read all data into memory
dde02dd [Davies Liu] improve performance of python broadcast
2014-11-24 17:17:03 -08:00

128 lines
3.9 KiB
Python

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import cPickle
import gc
from tempfile import NamedTemporaryFile
__all__ = ['Broadcast']
# Holds broadcasted data received from Java, keyed by its id.
_broadcastRegistry = {}
def _from_id(bid):
from pyspark.broadcast import _broadcastRegistry
if bid not in _broadcastRegistry:
raise Exception("Broadcast variable '%s' not loaded!" % bid)
return _broadcastRegistry[bid]
class Broadcast(object):
"""
A broadcast variable created with L{SparkContext.broadcast()}.
Access its value through C{.value}.
Examples:
>>> from pyspark.context import SparkContext
>>> sc = SparkContext('local', 'test')
>>> b = sc.broadcast([1, 2, 3, 4, 5])
>>> 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(range(10000))
"""
def __init__(self, sc=None, value=None, pickle_registry=None, path=None):
"""
Should not be called directly by users -- use L{SparkContext.broadcast()}
instead.
"""
if sc is not None:
f = NamedTemporaryFile(delete=False, dir=sc._temp_dir)
self._path = self.dump(value, f)
self._jbroadcast = sc._jvm.PythonRDD.readBroadcastFromFile(sc._jsc, self._path)
self._pickle_registry = pickle_registry
else:
self._jbroadcast = None
self._path = path
def dump(self, value, f):
if isinstance(value, basestring):
if isinstance(value, unicode):
f.write('U')
value = value.encode('utf8')
else:
f.write('S')
f.write(value)
else:
f.write('P')
cPickle.dump(value, f, 2)
f.close()
return f.name
def load(self, path):
with open(path, 'rb', 1 << 20) as f:
flag = f.read(1)
data = f.read()
if flag == 'P':
# cPickle.loads() may create lots of objects, disable GC
# temporary for better performance
gc.disable()
try:
return cPickle.loads(data)
finally:
gc.enable()
else:
return data.decode('utf8') if flag == 'U' else data
@property
def value(self):
""" Return the broadcasted value
"""
if not hasattr(self, "_value") and self._path is not None:
self._value = self.load(self._path)
return self._value
def unpersist(self, blocking=False):
"""
Delete cached copies of this broadcast on the executors.
"""
if self._jbroadcast is None:
raise Exception("Broadcast can only be unpersisted in driver")
self._jbroadcast.unpersist(blocking)
os.unlink(self._path)
def __reduce__(self):
if self._jbroadcast is None:
raise Exception("Broadcast can only be serialized in driver")
self._pickle_registry.add(self)
return _from_id, (self._jbroadcast.id(),)
if __name__ == "__main__":
import doctest
doctest.testmod()