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- #!/usr/bin/env python
- # Licensed to Cloudera, Inc. under one
- # or more contributor license agreements. See the NOTICE file
- # distributed with this work for additional information
- # regarding copyright ownership. Cloudera, Inc. 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.
- import pyspark
- import random
- if not 'sc' in globals():
- sc = pyspark.SparkContext()
- NUM_SAMPLES = 1000
- def sample(p):
- x,y = random.random(),random.random()
- return 1 if x*x + y*y < 1 else 0
- count = sc.parallelize(xrange(0, NUM_SAMPLES)) \
- .map(sample) \
- .reduce(lambda a, b: a + b)
- print "Pi is roughly %f" % (4.0 * count / NUM_SAMPLES)
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