| # |
| # 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() |