798ed22c28
Retire Epydoc, use Sphinx to generate API docs. Refine Sphinx docs, also convert some docstrings into Sphinx style. It looks like:  Author: Davies Liu <davies.liu@gmail.com> Closes #2689 from davies/docs and squashes the following commits: bf4a0a5 [Davies Liu] fix links 3fb1572 [Davies Liu] fix _static in jekyll 65a287e [Davies Liu] fix scripts and logo 8524042 [Davies Liu] Merge branch 'master' of github.com:apache/spark into docs d5b874a [Davies Liu] Merge branch 'master' of github.com:apache/spark into docs 4bc1c3c [Davies Liu] refactor 746d0b6 [Davies Liu] @param -> :param 240b393 [Davies Liu] replace epydoc with sphinx doc
66 lines
2.5 KiB
Python
66 lines
2.5 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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"""
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PySpark is the Python API for Spark.
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Public classes:
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- :class:`SparkContext`:
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Main entry point for Spark functionality.
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- L{RDD}
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A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
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- L{Broadcast}
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A broadcast variable that gets reused across tasks.
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- L{Accumulator}
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An "add-only" shared variable that tasks can only add values to.
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- L{SparkConf}
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For configuring Spark.
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- L{SparkFiles}
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Access files shipped with jobs.
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- L{StorageLevel}
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Finer-grained cache persistence levels.
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"""
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# The following block allows us to import python's random instead of mllib.random for scripts in
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# mllib that depend on top level pyspark packages, which transitively depend on python's random.
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# Since Python's import logic looks for modules in the current package first, we eliminate
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# mllib.random as a candidate for C{import random} by removing the first search path, the script's
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# location, in order to force the loader to look in Python's top-level modules for C{random}.
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import sys
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s = sys.path.pop(0)
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import random
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sys.path.insert(0, s)
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from pyspark.conf import SparkConf
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from pyspark.context import SparkContext
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from pyspark.rdd import RDD
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from pyspark.files import SparkFiles
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from pyspark.storagelevel import StorageLevel
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from pyspark.accumulators import Accumulator, AccumulatorParam
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from pyspark.broadcast import Broadcast
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from pyspark.serializers import MarshalSerializer, PickleSerializer
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# for back compatibility
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from pyspark.sql import SQLContext, HiveContext, SchemaRDD, Row
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__all__ = [
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"SparkConf", "SparkContext", "SparkFiles", "RDD", "StorageLevel", "Broadcast",
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"Accumulator", "AccumulatorParam", "MarshalSerializer", "PickleSerializer",
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]
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