fe75ff8bea
## What changes were proposed in this pull request?
Seems like we used to generate PySpark API documentation by Epydoc almost at the very first place (see 85b8f2c64f
).
This fixes an actual issue:
Before:
![Screen Shot 2019-07-05 at 8 20 01 PM](https://user-images.githubusercontent.com/6477701/60720491-e9879180-9f65-11e9-9562-100830a456cd.png)
After:
![Screen Shot 2019-07-05 at 8 20 05 PM](https://user-images.githubusercontent.com/6477701/60720495-ec828200-9f65-11e9-8277-8f689e292cb0.png)
It seems apparently a bug within `epytext` plugin during the conversion between`param` and `:param` syntax. See also [Epydoc syntax](http://epydoc.sourceforge.net/manual-epytext.html).
Actually, Epydoc syntax violates [PEP-257](https://www.python.org/dev/peps/pep-0257/) IIRC and blocks us to enable some rules for doctest linter as well.
We should remove this legacy away and I guess Spark 3 is good timing to do it.
## How was this patch tested?
Manually built the doc and check each.
I had to manually find the Epydoc syntax by `git grep -r "{L"`, for instance.
Closes #25060 from HyukjinKwon/SPARK-28206.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Xiangrui Meng <meng@databricks.com>
302 lines
9.3 KiB
Python
302 lines
9.3 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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>>> a = sc.accumulator(1)
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>>> a.value
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1
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>>> a.value = 2
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>>> a.value
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2
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>>> a += 5
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>>> a.value
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7
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>>> sc.accumulator(1.0).value
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1.0
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>>> sc.accumulator(1j).value
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1j
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>>> rdd = sc.parallelize([1,2,3])
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>>> def f(x):
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... global a
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... a += x
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>>> rdd.foreach(f)
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>>> a.value
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13
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>>> b = sc.accumulator(0)
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>>> def g(x):
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... b.add(x)
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>>> rdd.foreach(g)
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>>> b.value
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6
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>>> from pyspark.accumulators import AccumulatorParam
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>>> class VectorAccumulatorParam(AccumulatorParam):
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... def zero(self, value):
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... return [0.0] * len(value)
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... def addInPlace(self, val1, val2):
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... for i in range(len(val1)):
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... val1[i] += val2[i]
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... return val1
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>>> va = sc.accumulator([1.0, 2.0, 3.0], VectorAccumulatorParam())
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>>> va.value
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[1.0, 2.0, 3.0]
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>>> def g(x):
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... global va
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... va += [x] * 3
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>>> rdd.foreach(g)
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>>> va.value
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[7.0, 8.0, 9.0]
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>>> rdd.map(lambda x: a.value).collect() # doctest: +IGNORE_EXCEPTION_DETAIL
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Traceback (most recent call last):
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...
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Py4JJavaError:...
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>>> def h(x):
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... global a
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... a.value = 7
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>>> rdd.foreach(h) # doctest: +IGNORE_EXCEPTION_DETAIL
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Traceback (most recent call last):
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...
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Py4JJavaError:...
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>>> sc.accumulator([1.0, 2.0, 3.0]) # doctest: +IGNORE_EXCEPTION_DETAIL
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Traceback (most recent call last):
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...
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TypeError:...
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"""
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import sys
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import select
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import struct
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if sys.version < '3':
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import SocketServer
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else:
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import socketserver as SocketServer
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import threading
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from pyspark.serializers import read_int, PickleSerializer
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__all__ = ['Accumulator', 'AccumulatorParam']
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pickleSer = PickleSerializer()
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# Holds accumulators registered on the current machine, keyed by ID. This is then used to send
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# the local accumulator updates back to the driver program at the end of a task.
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_accumulatorRegistry = {}
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def _deserialize_accumulator(aid, zero_value, accum_param):
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from pyspark.accumulators import _accumulatorRegistry
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# If this certain accumulator was deserialized, don't overwrite it.
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if aid in _accumulatorRegistry:
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return _accumulatorRegistry[aid]
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else:
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accum = Accumulator(aid, zero_value, accum_param)
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accum._deserialized = True
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_accumulatorRegistry[aid] = accum
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return accum
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class Accumulator(object):
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"""
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A shared variable that can be accumulated, i.e., has a commutative and associative "add"
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operation. Worker tasks on a Spark cluster can add values to an Accumulator with the `+=`
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operator, but only the driver program is allowed to access its value, using `value`.
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Updates from the workers get propagated automatically to the driver program.
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While :class:`SparkContext` supports accumulators for primitive data types like :class:`int` and
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:class:`float`, users can also define accumulators for custom types by providing a custom
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:class:`AccumulatorParam` object. Refer to the doctest of this module for an example.
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"""
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def __init__(self, aid, value, accum_param):
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"""Create a new Accumulator with a given initial value and AccumulatorParam object"""
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from pyspark.accumulators import _accumulatorRegistry
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self.aid = aid
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self.accum_param = accum_param
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self._value = value
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self._deserialized = False
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_accumulatorRegistry[aid] = self
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def __reduce__(self):
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"""Custom serialization; saves the zero value from our AccumulatorParam"""
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param = self.accum_param
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return (_deserialize_accumulator, (self.aid, param.zero(self._value), param))
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@property
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def value(self):
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"""Get the accumulator's value; only usable in driver program"""
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if self._deserialized:
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raise Exception("Accumulator.value cannot be accessed inside tasks")
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return self._value
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@value.setter
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def value(self, value):
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"""Sets the accumulator's value; only usable in driver program"""
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if self._deserialized:
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raise Exception("Accumulator.value cannot be accessed inside tasks")
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self._value = value
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def add(self, term):
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"""Adds a term to this accumulator's value"""
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self._value = self.accum_param.addInPlace(self._value, term)
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def __iadd__(self, term):
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"""The += operator; adds a term to this accumulator's value"""
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self.add(term)
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return self
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def __str__(self):
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return str(self._value)
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def __repr__(self):
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return "Accumulator<id=%i, value=%s>" % (self.aid, self._value)
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class AccumulatorParam(object):
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"""
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Helper object that defines how to accumulate values of a given type.
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"""
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def zero(self, value):
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"""
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Provide a "zero value" for the type, compatible in dimensions with the
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provided `value` (e.g., a zero vector)
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"""
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raise NotImplementedError
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def addInPlace(self, value1, value2):
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"""
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Add two values of the accumulator's data type, returning a new value;
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for efficiency, can also update `value1` in place and return it.
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"""
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raise NotImplementedError
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class AddingAccumulatorParam(AccumulatorParam):
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"""
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An AccumulatorParam that uses the + operators to add values. Designed for simple types
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such as integers, floats, and lists. Requires the zero value for the underlying type
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as a parameter.
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"""
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def __init__(self, zero_value):
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self.zero_value = zero_value
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def zero(self, value):
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return self.zero_value
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def addInPlace(self, value1, value2):
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value1 += value2
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return value1
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# Singleton accumulator params for some standard types
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INT_ACCUMULATOR_PARAM = AddingAccumulatorParam(0)
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FLOAT_ACCUMULATOR_PARAM = AddingAccumulatorParam(0.0)
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COMPLEX_ACCUMULATOR_PARAM = AddingAccumulatorParam(0.0j)
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class _UpdateRequestHandler(SocketServer.StreamRequestHandler):
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"""
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This handler will keep polling updates from the same socket until the
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server is shutdown.
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"""
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def handle(self):
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from pyspark.accumulators import _accumulatorRegistry
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auth_token = self.server.auth_token
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def poll(func):
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while not self.server.server_shutdown:
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# Poll every 1 second for new data -- don't block in case of shutdown.
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r, _, _ = select.select([self.rfile], [], [], 1)
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if self.rfile in r:
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if func():
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break
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def accum_updates():
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num_updates = read_int(self.rfile)
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for _ in range(num_updates):
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(aid, update) = pickleSer._read_with_length(self.rfile)
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_accumulatorRegistry[aid] += update
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# Write a byte in acknowledgement
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self.wfile.write(struct.pack("!b", 1))
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return False
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def authenticate_and_accum_updates():
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received_token = self.rfile.read(len(auth_token))
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if isinstance(received_token, bytes):
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received_token = received_token.decode("utf-8")
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if (received_token == auth_token):
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accum_updates()
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# we've authenticated, we can break out of the first loop now
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return True
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else:
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raise Exception(
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"The value of the provided token to the AccumulatorServer is not correct.")
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# first we keep polling till we've received the authentication token
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poll(authenticate_and_accum_updates)
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# now we've authenticated, don't need to check for the token anymore
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poll(accum_updates)
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class AccumulatorServer(SocketServer.TCPServer):
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def __init__(self, server_address, RequestHandlerClass, auth_token):
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SocketServer.TCPServer.__init__(self, server_address, RequestHandlerClass)
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self.auth_token = auth_token
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"""
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A simple TCP server that intercepts shutdown() in order to interrupt
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our continuous polling on the handler.
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"""
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server_shutdown = False
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def shutdown(self):
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self.server_shutdown = True
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SocketServer.TCPServer.shutdown(self)
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self.server_close()
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def _start_update_server(auth_token):
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"""Start a TCP server to receive accumulator updates in a daemon thread, and returns it"""
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server = AccumulatorServer(("localhost", 0), _UpdateRequestHandler, auth_token)
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thread = threading.Thread(target=server.serve_forever)
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thread.daemon = True
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thread.start()
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return server
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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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sys.exit(-1)
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