spark-instrumented-optimizer/python/pyspark/__init__.py
Davies Liu ce0333f9a0 [SPARK-4348] [PySpark] [MLlib] rename random.py to rand.py
This PR rename random.py to rand.py to avoid the side affects of conflict with random module, but still keep the same interface as before.

```
>>> from pyspark.mllib.random import RandomRDDs
```

```
$ pydoc pyspark.mllib.random
Help on module random in pyspark.mllib:
NAME
    random - Python package for random data generation.

FILE
    /Users/davies/work/spark/python/pyspark/mllib/rand.py

CLASSES
    __builtin__.object
        pyspark.mllib.random.RandomRDDs

    class RandomRDDs(__builtin__.object)
     |  Generator methods for creating RDDs comprised of i.i.d samples from
     |  some distribution.
     |
     |  Static methods defined here:
     |
     |  normalRDD(sc, size, numPartitions=None, seed=None)
```

cc mengxr

reference link: http://xion.org.pl/2012/05/06/hacking-python-imports/

Author: Davies Liu <davies@databricks.com>

Closes #3216 from davies/random and squashes the following commits:

7ac4e8b [Davies Liu] rename random.py to rand.py
2014-11-13 10:24:54 -08:00

56 lines
1.9 KiB
Python

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# 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
# the License. You may obtain a copy of the License at
#
# 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.
#
"""
PySpark is the Python API for Spark.
Public classes:
- :class:`SparkContext`:
Main entry point for Spark functionality.
- L{RDD}
A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
- L{Broadcast}
A broadcast variable that gets reused across tasks.
- L{Accumulator}
An "add-only" shared variable that tasks can only add values to.
- L{SparkConf}
For configuring Spark.
- L{SparkFiles}
Access files shipped with jobs.
- L{StorageLevel}
Finer-grained cache persistence levels.
"""
from pyspark.conf import SparkConf
from pyspark.context import SparkContext
from pyspark.rdd import RDD
from pyspark.files import SparkFiles
from pyspark.storagelevel import StorageLevel
from pyspark.accumulators import Accumulator, AccumulatorParam
from pyspark.broadcast import Broadcast
from pyspark.serializers import MarshalSerializer, PickleSerializer
# for back compatibility
from pyspark.sql import SQLContext, HiveContext, SchemaRDD, Row
__all__ = [
"SparkConf", "SparkContext", "SparkFiles", "RDD", "StorageLevel", "Broadcast",
"Accumulator", "AccumulatorParam", "MarshalSerializer", "PickleSerializer",
]