permap.WordCount.java Source code

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Here is the source code for permap.WordCount.java

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package permap;

///**
// *  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.
// */

import java.io.IOException;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map;
import java.util.StringTokenizer;
import java.util.regex.Pattern;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

    /*
    The condition to check the counts for the real word.I have developed a RegularExpression(Regex)
     to determine the counts of the real? words starting with m,n,o,p,q,M,N,O,P,Q
    */
    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {

        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();

        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            HashMap<String, Integer> hmap = new HashMap<String, Integer>();
            while (itr.hasMoreTokens()) {
                word.set(itr.nextToken());
                String wordToString = word.toString();
                if (Pattern.matches("[m-qM-Q].*$", wordToString)) {
                    if (hmap.containsKey(wordToString))
                        hmap.put(wordToString, hmap.get(wordToString) + 1);
                    else
                        hmap.put(wordToString, 1);
                }
            }
            Iterator it = hmap.entrySet().iterator();
            while (it.hasNext()) {
                Map.Entry<String, Integer> keyValuePair = (Map.Entry<String, Integer>) it.next();
                IntWritable valueaccepted = new IntWritable(keyValuePair.getValue());
                Text texttoremove = new Text(keyValuePair.getKey());
                context.write(texttoremove, valueaccepted);
                it.remove(); // avoids a ConcurrentModificationException

            }

        }

    }

    /*A custom Partioner that assigns words that start with a specific alphabet to the given Reduced task.
    The problem statement says the reduce task 0 should contain words that start either with m or M.
    I have implemented the same approach.I have done so by taking the CharAt(0) the first position of 
    the value converted toString() and then checking against the accepted values*/

    public static class WordPartitioner extends Partitioner<Text, IntWritable> {
        @Override
        public int getPartition(Text key, IntWritable value, int numReduceTasks) {

            String val = key.toString();
            if (val.charAt(0) == 'm' || val.charAt(0) == 'M')
                return 0;

            if (val.charAt(0) == 'n' || val.charAt(0) == 'N')
                return 1;

            if (val.charAt(0) == 'o' || val.charAt(0) == 'O')
                return 2;

            if (val.charAt(0) == 'p' || val.charAt(0) == 'P')
                return 3;

            if (val.charAt(0) == 'q' || val.charAt(0) == 'Q')
                return 4;

            else
                return -1;

        }
    }

    public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
        private IntWritable result = new IntWritable();

        public void reduce(Text key, Iterable<IntWritable> values, Context context)
                throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length != 2) {
            System.err.println("Usage: wordcount <in> <out>");
            System.exit(2);
        }
        Job job = new Job(conf, "word count");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(TokenizerMapper.class);
        job.setPartitionerClass(WordPartitioner.class);
        // job.setCombinerClass(IntSumReducer.class);
        job.setReducerClass(IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

}