Java tutorial
/* * Cloud9: A MapReduce Library for Hadoop * * Licensed 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 edu.umd.cloud9.examples; import java.io.IOException; import java.util.Iterator; import java.util.StringTokenizer; //added PairOfStrings package import edu.umd.cloud9.io.PairOfStrings; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; //added FloatWritable package import org.apache.hadoop.io.FloatWritable; 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.Partitioner; import org.apache.hadoop.mapred.Reducer; import org.apache.hadoop.mapred.Reporter; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; import org.apache.log4j.Logger; /** * <p> * Simple bigram relative frequency. This Hadoop Tool counts bigram relative frequency in flat text file, and * takes the following command-line arguments: * </p> * * <ul> * <li>[input-path] input path</li> * <li>[output-path] output path</li> * <li>[num-mappers] number of mappers</li> * <li>[num-reducers] number of reducers</li> * </ul> * * @author Jimmy Lin * @author Marc Sloan */ public class BigramRelativeFrequency extends Configured implements Tool { private static final Logger sLogger = Logger.getLogger(BigramRelativeFrequency.class); /** * Mapper: emits (token + " " + token, 1) for every bigram occurrence * */ private static class MyMapper extends MapReduceBase implements Mapper<LongWritable, Text, PairOfStrings, FloatWritable> { /** * Store an IntWritable with a value of 1, which will be mapped * to each bigram found in the test */ private final static FloatWritable one = new FloatWritable(1); /** * reuse objects to save overhead of object creation */ //variable to hold bigram private final static PairOfStrings bigram = new PairOfStrings(); /** * Mapping function. This takes the text input, converts it into a String which is split into * words, then each of the bigrams is mapped to the OutputCollector with a count of * one. * * @param key Input key, not used in this example * @param value A line of input Text taken from the data * @param output Map from each bigram (PairOfStrings) to its count (IntWritable) */ public void map(LongWritable key, Text value, OutputCollector<PairOfStrings, FloatWritable> output, Reporter reporter) throws IOException { //Convert input word into String and tokenize to find words String line = ((Text) value).toString(); StringTokenizer itr = new StringTokenizer(line); //variable to hold previous word String previous_word = null; //variable to hold current word String current_word; //For each bigram, map it to a count of one. Duplicate bigrams will be counted //in the reduce phase. while (itr.hasMoreTokens()) { //update the current word as the next word current_word = itr.nextToken(); //if there is a previous word before the current word if (previous_word != null) { //form bigram of previous word and current word bigram.set(previous_word, current_word); //output the bigram output.collect(bigram, one); //form bigram of previous word and current word bigram.set(previous_word, "***"); //output the bigram output.collect(bigram, one); } //update the previous word as the current word previous_word = current_word; } } } /** * Combiner: sums up all the counts * */ private static class MyCombiner extends MapReduceBase implements Reducer<PairOfStrings, FloatWritable, PairOfStrings, FloatWritable> { /** * Stores the sum of counts for a bigram */ private final static FloatWritable SumValue = new FloatWritable(); /** * @param key The Text bigram * @param values An iterator over the values associated with this word * @param output Map from each bigram (PairOfStrings) to its sum (FloatWritable) * @param reporter Used to report progress */ @Override public void reduce(PairOfStrings key, Iterator<FloatWritable> values, OutputCollector<PairOfStrings, FloatWritable> output, Reporter reporter) throws IOException { //sum up values int sum = 0; while (values.hasNext()) { sum += values.next().get(); } SumValue.set(sum); output.collect(key, SumValue); } } /** * Reducer: sums up all the counts * */ private static class MyReducer extends MapReduceBase implements Reducer<PairOfStrings, FloatWritable, PairOfStrings, FloatWritable> { /** * Stores the sum of counts for a bigram */ private final static FloatWritable SumValue = new FloatWritable(); private float each_frequency = 0.0f; /** * @param key The Text bigram * @param values An iterator over the values associated with this word * @param output Map from each bigram (PairOfStrings) to its sum (FloatWritable) * @param reporter Used to report progress */ public void reduce(PairOfStrings key, Iterator<FloatWritable> values, OutputCollector<PairOfStrings, FloatWritable> output, Reporter reporter) throws IOException { //sum up values float sum = 0.0f; while (values.hasNext()) { sum += values.next().get(); } //if the right element of the bigram equals to "***" //this will output the frequency of any word followed by the word supplied as argument if (key.getRightElement().equals("***")) { //update sum SumValue.set(sum); //output bigram and its sum output.collect(key, SumValue); //update each_frequency as the sum each_frequency = sum; //if the right element of the bigram doesn't equal to "***" //this will output frequencies for every bigram that contains the word supplied as argument } else { //set sum as the sum divided by each_frequency SumValue.set(sum / each_frequency); //output bigram and its sum output.collect(key, SumValue); } } } /** * Partitioner controls the partitioning of the keys of the intermediate map-outputs. * The key (or a subset of the key) is used to derive the partition, typically by a * hash function. The total number of partitions is the same as the number of reduce * tasks for the job. Hence this controls which of the m reduce tasks the intermediate * key (and hence the record) is sent for reduction. */ protected static class MyPartitioner extends MapReduceBase implements Partitioner<PairOfStrings, FloatWritable> { @Override public int getPartition(PairOfStrings key, FloatWritable value, int numReduceTasks) { return (key.getLeftElement().hashCode() & Integer.MAX_VALUE) % numReduceTasks; } } /** * Creates an instance of this tool. */ public BigramRelativeFrequency() { } /** * Prints argument options * @return */ private static int printUsage() { System.out.println("usage: [input-path] [output-path] [num-mappers] [num-reducers]"); ToolRunner.printGenericCommandUsage(System.out); return -1; } /** * Runs this tool. */ public int run(String[] args) throws Exception { if (args.length != 4) { printUsage(); return -1; } String inputPath = args[0]; String outputPath = args[1]; int mapTasks = Integer.parseInt(args[2]); int reduceTasks = Integer.parseInt(args[3]); sLogger.info("Tool: BigramRelativeFrequency"); sLogger.info(" - input path: " + inputPath); sLogger.info(" - output path: " + outputPath); sLogger.info(" - number of mappers: " + mapTasks); sLogger.info(" - number of reducers: " + reduceTasks); JobConf conf = new JobConf(BigramRelativeFrequency.class); conf.setJobName("BigramRelativeFrequency"); conf.setNumMapTasks(mapTasks); conf.setNumReduceTasks(reduceTasks); FileInputFormat.setInputPaths(conf, new Path(inputPath)); FileOutputFormat.setOutputPath(conf, new Path(outputPath)); FileOutputFormat.setCompressOutput(conf, false); /** * Note that these must match the Class arguments given in the mapper */ conf.setOutputKeyClass(PairOfStrings.class); conf.setOutputValueClass(FloatWritable.class); conf.setMapperClass(MyMapper.class); conf.setCombinerClass(MyCombiner.class); conf.setReducerClass(MyReducer.class); conf.setPartitionerClass(MyPartitioner.class); //Delete the output directory if it exists already Path outputDir = new Path(outputPath); FileSystem.get(outputDir.toUri(), conf).delete(outputDir, true); long startTime = System.currentTimeMillis(); JobClient.runJob(conf); sLogger.info("Job Finished in " + (System.currentTimeMillis() - startTime) / 1000.0 + " seconds"); return 0; } /** * Dispatches command-line arguments to the tool via the * <code>ToolRunner</code>. */ public static void main(String[] args) throws Exception { int res = ToolRunner.run(new Configuration(), new BigramRelativeFrequency(), args); System.exit(res); } }