Github user rmetzger commented on a diff in the pull request:
https://github.com/apache/incubator-flink/pull/78#discussion_r15434359
--- Diff:
flink-examples/flink-java-examples/src/main/java/org/apache/flink/example/java/pi/PiEstimation.java
---
@@ -0,0 +1,127 @@
+/**
+ * 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.
+ */
+
+package org.apache.flink.example.java.pi;
+
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.flink.api.java.DataSet;
+import org.apache.flink.api.java.ExecutionEnvironment;
+import org.apache.flink.api.java.functions.*;
+
+
+/**
+ * Estimates the value of Pi using the Monte Carlo method.
+ * The area of a circle is Pi * R^2, R being the radius of the circle
+ * The area of a square is 4 * R^2, where the length of the square's edge
is 2*R.
+ *
+ * Thus Pi = 4 * (area of circle / area of square).
+ *
+ * The idea is to find a way to estimate the circle to square area ratio.
+ * The Monte Carlo method suggests collecting random points (within the
square)
+ * ```
+ * x = Math.random() * 2 - 1
+ * y = Math.random() * 2 - 1
+ * ```
+ * then counting the number of points that fall within the circle
+ * ```
+ * x * x + y * y < 1
+ * ```
+ */
+public class PiEstimation {
+
+ static int n;
+
+ public static void main(String[] args) throws Exception {
+
+ int blocks = (args.length == 1) ? Integer.parseInt(args[0]) : 2;
+ n = 100000 * blocks;
+ List<Integer> l = new ArrayList<Integer>(n);
+ for (int i = 0; i < n; i++) {
+ l.add(1);
+ }
+
+ //Sets up the execution environment
+ final ExecutionEnvironment env =
ExecutionEnvironment.getExecutionEnvironment();
+ DataSet<Integer> dataSet = env.fromCollection(l);
+
+
+ DataSet<Double> count = dataSet
+ .filter(new PiFilter())
+ .setParallelism(blocks)
+ .reduce(new PiReducer())
+ .map(new PiMapper());
+
+ System.out.println("We estimate Pi to be:");
+ count.print();
+
+ env.execute();
+ }
+
+
+
//*************************************************************************
+ // USER FUNCTIONS
+
//*************************************************************************
+
+ // FilterFunction that filters out all Integers smaller than zero.
+
+ /**
+ * PiFilter randomly emits points that fall within a square of edge 2*x
= 2*y = 2.
+ * It calculates the distance to the center of a virtually centered
circle of radius x = y = 1
+ * If the distance is less than 1, then and only then does it return a
value (in this case 1, a list's value)
+ */
+ public static class PiFilter extends FilterFunction<Integer> {
+ private static final long serialVersionUID = 1L;
+
+ @Override
+ public boolean filter(Integer value) throws Exception{
+ double x = Math.random() * 2 - 1;
+ double y = Math.random() * 2 - 1;
+ return (x * x + y * y) < 1;
+ }
+ }
+
+
+ /**
+ * PiReducer takes over the filter. It goes through the selected 1s and
returns the sum.
+ */
+ public static final class PiReducer extends ReduceFunction<Integer>{
+ private static final long serialVersionUID = 1L;
+
+ @Override
+ public Integer reduce(Integer value1, Integer value2) throws
Exception {
+ return value1 + value2;
+ }
+ }
+
+
+ /**
+ * The PiMapper's role is to apply one final operation on the count
thus returning the estimated Pi value.
+ */
+ public static final class PiMapper extends MapFunction<Integer,Double> {
+ private static final long serialVersionUID = 1L;
+
+ @Override
+ public Double map(Integer intSum) throws Exception {
+ return intSum*4.0 / n;
--- End diff --
I think `n` will be 0 if you run the Job in a distributed environment on a
cluster.
You'll probably have to pass it either as a configuration value or via the
constructor of the class.
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