ec1adecbb7
Using Sphinx to generate API docs for PySpark.
requirement: Sphinx
```
$ cd python/docs/
$ make html
```
The generated API docs will be located at python/docs/_build/html/index.html
It can co-exists with those generated by Epydoc.
This is the first working version, after merging in, then we can continue to improve it and replace the epydoc finally.
Author: Davies Liu <davies.liu@gmail.com>
Closes #2292 from davies/sphinx and squashes the following commits:
425a3b1 [Davies Liu] cleanup
1573298 [Davies Liu] move docs to python/docs/
5fe3903 [Davies Liu] Merge branch 'master' into sphinx
9468ab0 [Davies Liu] fix makefile
b408f38 [Davies Liu] address all comments
e2ccb1b [Davies Liu] update name and version
9081ead [Davies Liu] generate PySpark API docs using Sphinx
95 lines
2.8 KiB
Python
95 lines
2.8 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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"""
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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(list(range(10000)))
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"""
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import os
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from pyspark.serializers import CompressedSerializer, PickleSerializer
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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
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L{SparkContext.broadcast()<pyspark.context.SparkContext.broadcast>}.
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Access its value through C{.value}.
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"""
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def __init__(self, bid, value, java_broadcast=None,
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pickle_registry=None, path=None):
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"""
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Should not be called directly by users -- use
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L{SparkContext.broadcast()<pyspark.context.SparkContext.broadcast>}
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instead.
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"""
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self.bid = bid
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if path is None:
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self._value = value
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self._jbroadcast = java_broadcast
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self._pickle_registry = pickle_registry
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self.path = path
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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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ser = CompressedSerializer(PickleSerializer())
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self._value = ser.load_stream(open(self.path)).next()
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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.
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"""
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self._jbroadcast.unpersist(blocking)
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os.unlink(self.path)
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def __reduce__(self):
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self._pickle_registry.add(self)
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return (_from_id, (self.bid, ))
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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