MapReduce example : WordCount3

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author: Bharat (sree ram)

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 MapReduce Example : WordCount3


purpose:
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   I want to treat love, like as positive words and hate, dislike as negative words .
Now, I want to find out, number of positive words and number of negative words.

Input hdfs file:
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    mydir/comment.txt
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I like hadoop I love hadoop
I dislike java and I hate java
I love hadoop
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o/p of the program :
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  positive 3
  negative 2
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Program : WordCount3.java
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 package my.map.red.app;

 import java.io.IOException;

 import java.util.StringTokenizer;

 import org.apache.hadoop.conf.Configuration;

 import org.apache.hadoop.fs.Path;

 import org.apache.hadoop.io.Text;

 import org.apache.hadoop.io.IntWritable;

 import org.apache.hadoop.io.LongWritable;

 import org.apache.hadoop.mapreduce.Mapper;

 import org.apache.hadoop.mapreduce.Reducer;

 import org.apache.hadoop.mapreduce.Job;

 import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

 import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

 import org.apache.hadoop.util.GenericOptionsParser;

 public class WordCount3
 {
    public static class MapForWordCount extends Mapper<LongWritable, Text, Text, IntWritable>
    {
           public void map(LongWritable key, Text value, Context con) throws IOException, InterruptedException
           {
               String line = value.toString();

               StringTokenizer token = new StringTokenizer(line);

               while(token.hasMoreTokens())
               {

                  String status = new String();

                  String word = token.nextToken();

                  if (word.matches("like") || word.matches("love"))

                       status="Positive";

                  if (word.matches("dislike") || word.matches("hate"))

                        status="Negative";

                  Text outputKey = new Text(status);

                  IntWritable outputValue = new IntWritable(1);

                  if (status.matches("Positive") || status.matches("Negative"))

                      con.write(outputKey, outputValue);
               }
            } // end of map()
    } //end of Mapper Class

  /*
     output of the mapper phase :

       <Negative , <1,1>>
       <Positive, <1,1,1>>

  */
 
   public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>
   {
          public void reduce(Text status, Iterable<IntWritable> values, Context con) throws IOException, InterruptedException
          {

               int sum = 0;

               for(IntWritable value : values)
               {

                   sum += value.get();

               }

               con.write(status, new IntWritable(sum));

          } // end of reduce()
   } // end of Reducer class
/*

 output of the reducer

   Nagative 2
   Positive 3

*/

 // job definition

   public static void  main(String[] args) throws Exception
   {

           Configuration c = new Configuration();

           String[] files = new GenericOptionsParser(c, args).getRemainingArgs();

           Path input = new Path(files[0]);

           Path output = new Path(files[1]);

           Job j = new Job(c, "wordcount");

           j.setJarByClass(WordCount3.class);

           j.setMapperClass(MapForWordCount.class);

           j.setCombinerClass(ReduceForWordCount.class);

           j.setReducerClass(ReduceForWordCount.class);

           j.setOutputKeyClass(Text.class);

           j.setOutputValueClass(IntWritable.class);

           FileInputFormat.addInputPath(j, input);

           FileOutputFormat.setOutputPath(j, output);

           System.exit(j.waitForCompletion(true) ? 0:1);

   } // end of main()

} end of main class