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#
# 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.
#
"""
Randomly generated RDDs.
"""
import sys
from pyspark import SparkContext
from pyspark.mllib.random import RandomRDDs
if __name__ == "__main__":
if len(sys.argv) not in [1, 2]:
print >> sys.stderr, "Usage: random_rdd_generation"
exit(-1)
sc = SparkContext(appName="PythonRandomRDDGeneration")
numExamples = 10000 # number of examples to generate
fraction = 0.1 # fraction of data to sample
# Example: RandomRDDs.normalRDD
normalRDD = RandomRDDs.normalRDD(sc, numExamples)
print 'Generated RDD of %d examples sampled from the standard normal distribution'\
% normalRDD.count()
print ' First 5 samples:'
for sample in normalRDD.take(5):
print ' ' + str(sample)
print
# Example: RandomRDDs.normalVectorRDD
normalVectorRDD = RandomRDDs.normalVectorRDD(sc, numRows=numExamples, numCols=2)
print 'Generated RDD of %d examples of length-2 vectors.' % normalVectorRDD.count()
print ' First 5 samples:'
for sample in normalVectorRDD.take(5):
print ' ' + str(sample)
print
sc.stop()
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