edu.umd.cloud9.examples.BigramCount.java Source code

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/*
 * 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;

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.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;

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.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import org.apache.log4j.Logger;

/**
 * <p>
 * Simple bigram count demo. This Hadoop Tool counts bigrams 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 BigramCount extends Configured implements Tool {
    private static final Logger sLogger = Logger.getLogger(BigramCount.class);

    /**
     *  Mapper: emits (token + " " + token, 1) for every bigram occurrence
     *
     */
    private static class MyMapper extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {

        /**
         *  Store an IntWritable with a value of 1, which will be mapped 
         *  to each bigram found in the test
         */
        private final static IntWritable one = new IntWritable(1);
        /**
         * reuse objects to save overhead of object creation
         */
        //variable to hold bigram
        private Text bigram = new Text();

        /**
         * 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 (Text) to its count (IntWritable)
         */
        public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> 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
            Text previous_word = new Text();

            //variable to hold current word
            Text current_word = new Text();

            //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.set(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);
                }

                //update the previous word as the current word
                previous_word.set(current_word);
            }
        }
    }

    /**
     * Reducer: sums up all the counts
     *
     */
    private static class MyReducer extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {

        /**
         *  Stores the sum of counts for a bigram
         */
        private final static IntWritable SumValue = new IntWritable();

        /**
         *  @param key The Text bigram 
         *  @param values An iterator over the values associated with this word
         *  @param output Map from each bigram (Text) to its count (IntWritable)
         *  @param reporter Used to report progress
         */
        public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> 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);
        }
    }

    /**
     * Creates an instance of this tool.
     */
    public BigramCount() {
    }

    /**
     *  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: BigramCount");
        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(BigramCount.class);
        conf.setJobName("BigramCount");

        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(Text.class);
        conf.setOutputValueClass(IntWritable.class);

        conf.setMapperClass(MyMapper.class);
        conf.setCombinerClass(MyReducer.class);
        conf.setReducerClass(MyReducer.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 BigramCount(), args);
        System.exit(res);
    }
}