spark/examples/JavaSparkPi.java

0001 /*
0002  * Licensed to the Apache Software Foundation (ASF) under one or more
0003  * contributor license agreements.  See the NOTICE file distributed with
0004  * this work for additional information regarding copyright ownership.
0005  * The ASF licenses this file to You under the Apache License, Version 2.0
0006  * (the "License"); you may not use this file except in compliance with
0007  * the License.  You may obtain a copy of the License at
0008  *
0009  *    http://www.apache.org/licenses/LICENSE-2.0
0010  *
0011  * Unless required by applicable law or agreed to in writing, software
0012  * distributed under the License is distributed on an "AS IS" BASIS,
0013  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
0014  * See the License for the specific language governing permissions and
0015  * limitations under the License.
0016  */
0017
0018 package org.apache.spark.examples;
0019
0020 import org.apache.spark.api.java.JavaRDD;
0021 import org.apache.spark.api.java.JavaSparkContext;
0022 import org.apache.spark.sql.SparkSession;
0023
0024 import java.util.ArrayList;
0025 import java.util.List;
0026
0027 /**
0028  * Computes an approximation to pi
0029  * Usage: JavaSparkPi [partitions]
0030  */
0031 public final class JavaSparkPi {
0032
0033   public static void main(String[] args) throws Exception {
0034     SparkSession spark = SparkSession
0035       .builder()
0036       .appName("JavaSparkPi")
0037       .getOrCreate();
0038
0039     JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());
0040
0041     int slices = (args.length == 1) ? Integer.parseInt(args[0]) : 2;
0042     int n = 100000 * slices;
0043     List<Integer> l = new ArrayList<>(n);
0044     for (int i = 0; i < n; i++) {
0045       l.add(i);
0046     }
0047
0048     JavaRDD<Integer> dataSet = jsc.parallelize(l, slices);
0049
0050     int count = dataSet.map(integer -> {
0051       double x = Math.random() * 2 - 1;
0052       double y = Math.random() * 2 - 1;
0053       return (x * x + y * y <= 1) ? 1 : 0;
0054     }).reduce((integer, integer2) -> integer + integer2);
0055
0056     System.out.println("Pi is roughly " + 4.0 * count / n);
0057
0058     spark.stop();
0059   }
0060 }