Reducer

The MapReduce framework uses partitions to make sure that all the records with the same key always go to the same reducer. The reducer receives the list of values for the key and thus can easily perform aggregated operations such as count and sum, as follows:

import org.apache.Hadoop.io.IntWritable;
import org.apache.Hadoop.io.Text;
import org.apache.Hadoop.mapreduce.Reducer;

import java.io.IOException;

public class WordcountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context)
            throws IOException, InterruptedException {

        int count = 0;
        for (IntWritable current : values) {
            count += current.get();

        }
        context.write(key, new IntWritable(count));
    }

}