dbfc7aa4d0
## What changes were proposed in this pull request? For large objects, pickle does not raise useful error messages. However, we can wrap them to be slightly more user friendly: Example 1: ``` def run(): import numpy.random as nr b = nr.bytes(8 * 1000000000) sc.parallelize(range(1000), 1000).map(lambda x: len(b)).count() run() ``` Before: ``` error: 'i' format requires -2147483648 <= number <= 2147483647 ``` After: ``` pickle.PicklingError: Object too large to serialize: 'i' format requires -2147483648 <= number <= 2147483647 ``` Example 2: ``` def run(): import numpy.random as nr b = sc.broadcast(nr.bytes(8 * 1000000000)) sc.parallelize(range(1000), 1000).map(lambda x: len(b.value)).count() run() ``` Before: ``` SystemError: error return without exception set ``` After: ``` cPickle.PicklingError: Could not serialize broadcast: SystemError: error return without exception set ``` ## How was this patch tested? Manually tried out these cases cc davies Author: Eric Liang <ekl@databricks.com> Closes #15026 from ericl/spark-17472.
145 lines
4.5 KiB
Python
145 lines
4.5 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import os
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import sys
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import gc
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from tempfile import NamedTemporaryFile
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from pyspark.cloudpickle import print_exec
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if sys.version < '3':
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import cPickle as pickle
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else:
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import pickle
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unicode = str
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__all__ = ['Broadcast']
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# Holds broadcasted data received from Java, keyed by its id.
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_broadcastRegistry = {}
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def _from_id(bid):
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from pyspark.broadcast import _broadcastRegistry
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if bid not in _broadcastRegistry:
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raise Exception("Broadcast variable '%s' not loaded!" % bid)
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return _broadcastRegistry[bid]
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class Broadcast(object):
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"""
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A broadcast variable created with L{SparkContext.broadcast()}.
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Access its value through C{.value}.
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Examples:
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>>> from pyspark.context import SparkContext
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>>> sc = SparkContext('local', 'test')
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>>> b = sc.broadcast([1, 2, 3, 4, 5])
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>>> b.value
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[1, 2, 3, 4, 5]
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>>> sc.parallelize([0, 0]).flatMap(lambda x: b.value).collect()
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[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
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>>> b.unpersist()
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>>> large_broadcast = sc.broadcast(range(10000))
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"""
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def __init__(self, sc=None, value=None, pickle_registry=None, path=None):
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"""
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Should not be called directly by users -- use L{SparkContext.broadcast()}
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instead.
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"""
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if sc is not None:
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f = NamedTemporaryFile(delete=False, dir=sc._temp_dir)
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self._path = self.dump(value, f)
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self._jbroadcast = sc._jvm.PythonRDD.readBroadcastFromFile(sc._jsc, self._path)
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self._pickle_registry = pickle_registry
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else:
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self._jbroadcast = None
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self._path = path
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def dump(self, value, f):
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try:
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pickle.dump(value, f, 2)
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except pickle.PickleError:
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raise
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except Exception as e:
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msg = "Could not serialize broadcast: " + e.__class__.__name__ + ": " + e.message
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print_exec(sys.stderr)
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raise pickle.PicklingError(msg)
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f.close()
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return f.name
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def load(self, path):
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with open(path, 'rb', 1 << 20) as f:
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# pickle.load() may create lots of objects, disable GC
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# temporary for better performance
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gc.disable()
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try:
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return pickle.load(f)
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finally:
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gc.enable()
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@property
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def value(self):
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""" Return the broadcasted value
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"""
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if not hasattr(self, "_value") and self._path is not None:
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self._value = self.load(self._path)
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return self._value
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def unpersist(self, blocking=False):
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"""
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Delete cached copies of this broadcast on the executors. If the
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broadcast is used after this is called, it will need to be
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re-sent to each executor.
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:param blocking: Whether to block until unpersisting has completed
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"""
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if self._jbroadcast is None:
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raise Exception("Broadcast can only be unpersisted in driver")
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self._jbroadcast.unpersist(blocking)
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def destroy(self):
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"""
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Destroy all data and metadata related to this broadcast variable.
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Use this with caution; once a broadcast variable has been destroyed,
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it cannot be used again. This method blocks until destroy has
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completed.
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"""
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if self._jbroadcast is None:
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raise Exception("Broadcast can only be destroyed in driver")
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self._jbroadcast.destroy()
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os.unlink(self._path)
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def __reduce__(self):
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if self._jbroadcast is None:
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raise Exception("Broadcast can only be serialized in driver")
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self._pickle_registry.add(self)
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return _from_id, (self._jbroadcast.id(),)
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if __name__ == "__main__":
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import doctest
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(failure_count, test_count) = doctest.testmod()
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if failure_count:
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exit(-1)
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