spark-instrumented-optimizer/python/pyspark/broadcast.py
Bryan Cutler 77cc0d67d5 [SPARK-12717][PYTHON] Adding thread-safe broadcast pickle registry
## What changes were proposed in this pull request?

When using PySpark broadcast variables in a multi-threaded environment,  `SparkContext._pickled_broadcast_vars` becomes a shared resource.  A race condition can occur when broadcast variables that are pickled from one thread get added to the shared ` _pickled_broadcast_vars` and become part of the python command from another thread.  This PR introduces a thread-safe pickled registry using thread local storage so that when python command is pickled (causing the broadcast variable to be pickled and added to the registry) each thread will have their own view of the pickle registry to retrieve and clear the broadcast variables used.

## How was this patch tested?

Added a unit test that causes this race condition using another thread.

Author: Bryan Cutler <cutlerb@gmail.com>

Closes #18695 from BryanCutler/pyspark-bcast-threadsafe-SPARK-12717.
2017-08-02 07:12:23 +09:00

166 lines
5 KiB
Python

#
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# 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
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# 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 sys
import gc
from tempfile import NamedTemporaryFile
import threading
from pyspark.cloudpickle import print_exec
from pyspark.util import _exception_message
if sys.version < '3':
import cPickle as pickle
else:
import pickle
unicode = str
__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):
try:
pickle.dump(value, f, 2)
except pickle.PickleError:
raise
except Exception as e:
msg = "Could not serialize broadcast: %s: %s" \
% (e.__class__.__name__, _exception_message(e))
print_exec(sys.stderr)
raise pickle.PicklingError(msg)
f.close()
return f.name
def load(self, path):
with open(path, 'rb', 1 << 20) as f:
# pickle.load() may create lots of objects, disable GC
# temporary for better performance
gc.disable()
try:
return pickle.load(f)
finally:
gc.enable()
@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 the
broadcast is used after this is called, it will need to be
re-sent to each executor.
:param blocking: Whether to block until unpersisting has completed
"""
if self._jbroadcast is None:
raise Exception("Broadcast can only be unpersisted in driver")
self._jbroadcast.unpersist(blocking)
def destroy(self):
"""
Destroy all data and metadata related to this broadcast variable.
Use this with caution; once a broadcast variable has been destroyed,
it cannot be used again. This method blocks until destroy has
completed.
"""
if self._jbroadcast is None:
raise Exception("Broadcast can only be destroyed in driver")
self._jbroadcast.destroy()
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(),)
class BroadcastPickleRegistry(threading.local):
""" Thread-local registry for broadcast variables that have been pickled
"""
def __init__(self):
self.__dict__.setdefault("_registry", set())
def __iter__(self):
for bcast in self._registry:
yield bcast
def add(self, bcast):
self._registry.add(bcast)
def clear(self):
self._registry.clear()
if __name__ == "__main__":
import doctest
(failure_count, test_count) = doctest.testmod()
if failure_count:
exit(-1)