Created
February 16, 2017 03:36
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from __future__ import print_function | |
# | |
# 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. | |
# | |
import sys | |
from random import random | |
from operator import add | |
from pyspark.sql import SparkSession | |
if __name__ == "__main__": | |
""" | |
Usage: pi [partitions] | |
""" | |
spark = SparkSession\ | |
.builder\ | |
.appName("PythonPi")\ | |
.getOrCreate() | |
partitions = int(sys.argv[1]) if len(sys.argv) > 1 else 2 | |
n = 100000 * partitions | |
def f(_): | |
x = random() * 2 - 1 | |
y = random() * 2 - 1 | |
return 1 if x ** 2 + y ** 2 <= 1 else 0 | |
count = spark.sparkContext.parallelize(range(1, n + 1), partitions).map(f).reduce(add) | |
print("Pi is roughly %f" % (4.0 * count / n)) | |
spark.stop() |
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