Java tutorial
/** * 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 com.test; import java.io.IOException; import java.math.BigDecimal; import java.util.Iterator; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.BooleanWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.SequenceFile; import org.apache.hadoop.io.Writable; import org.apache.hadoop.io.WritableComparable; import org.apache.hadoop.io.SequenceFile.CompressionType; import org.apache.hadoop.mapred.FileInputFormat; import org.apache.hadoop.mapred.FileOutputFormat; import org.apache.hadoop.mapred.JobClient; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.MapReduceBase; import org.apache.hadoop.mapred.Mapper; import org.apache.hadoop.mapred.OutputCollector; import org.apache.hadoop.mapred.Reducer; import org.apache.hadoop.mapred.Reporter; import org.apache.hadoop.mapred.SequenceFileInputFormat; import org.apache.hadoop.mapred.SequenceFileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.apache.log4j.Logger; import org.apache.log4j.Level; /** * A Map-reduce program to estimate the value of Pi * using quasi-Monte Carlo method. * * Mapper: * Generate points in a unit square * and then count points inside/outside of the inscribed circle of the square. * * Reducer: * Accumulate points inside/outside results from the mappers. * * Let numTotal = numInside + numOutside. * The fraction numInside/numTotal is a rational approximation of * the value (Area of the circle)/(Area of the square), * where the area of the inscribed circle is Pi/4 * and the area of unit square is 1. * Then, Pi is estimated value to be 4(numInside/numTotal). */ public class PiEstimatorKrb extends Configured implements Tool { /** tmp directory for input/output */ private static final Logger sLogger = Logger.getLogger(PiEstimatorKrb.class); /** static private Path TMP_DIR = new Path( PiEstimatorKrb.class.getSimpleName() + "/" + "_TMP_" + randNum); */ public static Path TMP_DIR; public PiEstimatorKrb(String path) { TMP_DIR = new Path(path); } /** 2-dimensional Halton sequence {H(i)}, * where H(i) is a 2-dimensional point and i >= 1 is the index. * Halton sequence is used to generate sample points for Pi estimation. */ private static class HaltonSequence { /** Bases */ static final int[] P = { 2, 3 }; /** Maximum number of digits allowed */ static final int[] K = { 63, 40 }; private long index; private double[] x; private double[][] q; private int[][] d; /** Initialize to H(startindex), * so the sequence begins with H(startindex+1). */ HaltonSequence(long startindex) { index = startindex; x = new double[K.length]; q = new double[K.length][]; d = new int[K.length][]; for (int i = 0; i < K.length; i++) { q[i] = new double[K[i]]; d[i] = new int[K[i]]; } for (int i = 0; i < K.length; i++) { long k = index; x[i] = 0; for (int j = 0; j < K[i]; j++) { q[i][j] = (j == 0 ? 1.0 : q[i][j - 1]) / P[i]; d[i][j] = (int) (k % P[i]); k = (k - d[i][j]) / P[i]; x[i] += d[i][j] * q[i][j]; } } } /** Compute next point. * Assume the current point is H(index). * Compute H(index+1). * * @return a 2-dimensional point with coordinates in [0,1)^2 */ double[] nextPoint() { index++; for (int i = 0; i < K.length; i++) { for (int j = 0; j < K[i]; j++) { d[i][j]++; x[i] += q[i][j]; if (d[i][j] < P[i]) { break; } d[i][j] = 0; x[i] -= (j == 0 ? 1.0 : q[i][j - 1]); } } return x; } } /** * Mapper class for Pi estimation. * Generate points in a unit square * and then count points inside/outside of the inscribed circle of the square. */ public static class PiMapper extends MapReduceBase implements Mapper<LongWritable, LongWritable, BooleanWritable, LongWritable> { /** Map method. * @param offset samples starting from the (offset+1)th sample. * @param size the number of samples for this map * @param out output {ture->numInside, false->numOutside} * @param reporter */ public void map(LongWritable offset, LongWritable size, OutputCollector<BooleanWritable, LongWritable> out, Reporter reporter) throws IOException { final HaltonSequence haltonsequence = new HaltonSequence(offset.get()); long numInside = 0L; long numOutside = 0L; for (long i = 0; i < size.get();) { //generate points in a unit square final double[] point = haltonsequence.nextPoint(); //count points inside/outside of the inscribed circle of the square final double x = point[0] - 0.5; final double y = point[1] - 0.5; if (x * x + y * y > 0.25) { numOutside++; } else { numInside++; } //report status i++; if (i % 1000 == 0) { reporter.setStatus("Generated " + i + " samples."); } } //output map results out.collect(new BooleanWritable(true), new LongWritable(numInside)); out.collect(new BooleanWritable(false), new LongWritable(numOutside)); } } /** * Reducer class for Pi estimation. * Accumulate points inside/outside results from the mappers. */ public static class PiReducer extends MapReduceBase implements Reducer<BooleanWritable, LongWritable, WritableComparable<?>, Writable> { private long numInside = 0; private long numOutside = 0; private JobConf conf; //configuration for accessing the file system /** Store job configuration. */ @Override public void configure(JobConf job) { conf = job; } /** * Accumulate number of points inside/outside results from the mappers. * @param isInside Is the points inside? * @param values An iterator to a list of point counts * @param output dummy, not used here. * @param reporter */ public void reduce(BooleanWritable isInside, Iterator<LongWritable> values, OutputCollector<WritableComparable<?>, Writable> output, Reporter reporter) throws IOException { if (isInside.get()) { for (; values.hasNext(); numInside += values.next().get()) ; } else { for (; values.hasNext(); numOutside += values.next().get()) ; } } /** * Reduce task done, write output to a file. */ @Override public void close() throws IOException { //write output to a file Path outDir = FileOutputFormat.getOutputPath(conf); Path outFile = new Path(outDir, "reduce-out"); FileSystem fileSys = FileSystem.get(conf); SequenceFile.Writer writer = SequenceFile.createWriter(fileSys, conf, outFile, LongWritable.class, LongWritable.class, CompressionType.NONE); writer.append(new LongWritable(numInside), new LongWritable(numOutside)); writer.close(); } } /** * Run a map/reduce job for estimating Pi. * * @return the estimated value of Pi */ public static BigDecimal estimate(int numMaps, long numPoints, JobConf jobConf) throws IOException { //setup job conf jobConf.setJobName(PiEstimatorKrb.class.getSimpleName()); jobConf.setInputFormat(SequenceFileInputFormat.class); jobConf.setOutputKeyClass(BooleanWritable.class); jobConf.setOutputValueClass(LongWritable.class); jobConf.setOutputFormat(SequenceFileOutputFormat.class); jobConf.setMapperClass(PiMapper.class); jobConf.setNumMapTasks(numMaps); jobConf.setReducerClass(PiReducer.class); jobConf.setNumReduceTasks(1); // turn off speculative execution, because DFS doesn't handle // multiple writers to the same file. jobConf.setSpeculativeExecution(false); //setup input/output directories final Path inDir = new Path(TMP_DIR, "in"); final Path outDir = new Path(TMP_DIR, "out"); FileInputFormat.setInputPaths(jobConf, inDir); FileOutputFormat.setOutputPath(jobConf, outDir); final FileSystem fs = FileSystem.get(jobConf); if (fs.exists(TMP_DIR)) { throw new IOException( "Tmp directory " + fs.makeQualified(TMP_DIR) + " already exists. Please remove it first."); } if (!fs.mkdirs(inDir)) { throw new IOException("Cannot create input directory " + inDir); } try { //generate an input file for each map task for (int i = 0; i < numMaps; ++i) { final Path file = new Path(inDir, "part" + i); final LongWritable offset = new LongWritable(i * numPoints); final LongWritable size = new LongWritable(numPoints); final SequenceFile.Writer writer = SequenceFile.createWriter(fs, jobConf, file, LongWritable.class, LongWritable.class, CompressionType.NONE); try { writer.append(offset, size); } finally { writer.close(); } sLogger.info("Wrote input for Map #" + i); } //start a map/reduce job sLogger.info("Starting Job"); final long startTime = System.currentTimeMillis(); if (System.getenv("HADOOP_TOKEN_FILE_LOCATION") != null) { jobConf.set("mapreduce.job.credentials.binary", System.getenv("HADOOP_TOKEN_FILE_LOCATION")); } JobClient.runJob(jobConf); final double duration = (System.currentTimeMillis() - startTime) / 1000.0; sLogger.info("Job Finished in " + duration + " seconds"); //read outputs Path inFile = new Path(outDir, "reduce-out"); LongWritable numInside = new LongWritable(); LongWritable numOutside = new LongWritable(); SequenceFile.Reader reader = new SequenceFile.Reader(fs, inFile, jobConf); try { reader.next(numInside, numOutside); } finally { reader.close(); } //compute estimated value return BigDecimal.valueOf(4).setScale(20).multiply(BigDecimal.valueOf(numInside.get())) .divide(BigDecimal.valueOf(numMaps)).divide(BigDecimal.valueOf(numPoints)); } finally { fs.delete(TMP_DIR, true); } } /** * Parse arguments and then runs a map/reduce job. * Print output in standard out. * * @return a non-zero if there is an error. Otherwise, return 0. */ public int run(String[] args) throws Exception { sLogger.setLevel(Level.DEBUG); if (args.length != 3) { System.err.println("Usage: " + getClass().getName() + " <tmpDir> <nMaps> <nSamples>"); ToolRunner.printGenericCommandUsage(System.err); return -1; } final String tmpDir = args[0]; final int nMaps = Integer.parseInt(args[1]); final long nSamples = Long.parseLong(args[2]); sLogger.info("Number of Maps = " + nMaps); sLogger.info("Samples per Map = " + nSamples); sLogger.info("Temp location = " + TMP_DIR); final JobConf jobConf = new JobConf(getConf(), getClass()); sLogger.info("Estimated value of Pi is " + estimate(nMaps, nSamples, jobConf)); return 0; } /** * main method for running it as a stand alone command. */ public static void main(String[] argv) throws Exception { System.exit(ToolRunner.run(null, new PiEstimatorKrb(argv[0]), argv)); } }