source: sample/WordCount.java @ 9

/**
 * Program: WordCount.java
 * Editor: Waue Chen 
 * From :  NCHC. Taiwn
 * Last Update Date: 06/13/2008
 */

/**
 * Purpose : 
 *  Store the result of WordCount.java from Hbase to Hadoop file system 
 * 
 * HowToUse : 
 *  Make sure Hadoop file system is running correctly.
 *  Put text file on the directory "/local_src/input" 
 *  You can use the instruction to upload "/local_src/input" to HDFS input dir
 *    $ bin/hadoop dfs -put /local_src/input input
 *  Then modify the $filepath parameter in construtor to be correct and run this code.
 *  
 * 
 * Check Result:
 *  inspect http://localhost:50070 by web explorer
 */
package tw.org.nchc.code;

import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

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.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;


public class WordCount {
  private String filepath;
  private String outputPath;
  
  public WordCount(){
    filepath = "/user/waue/input/";
    outputPath = "counts1";
  }
  public WordCount(String path,String output){
    filepath = path;
    outputPath = output;
  }
  // mapper: emits (token, 1) for every word occurrence
  private static class MapClass extends MapReduceBase implements
      Mapper<LongWritable, Text, Text, IntWritable> {

    // reuse objects to save overhead of object creation
    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value,
        OutputCollector<Text, IntWritable> output, Reporter reporter)
        throws IOException {
      String line = ((Text) value).toString();
      StringTokenizer itr = new StringTokenizer(line);
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        output.collect(word, one);
      }
    }
  }

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

    // reuse objects
    private final static IntWritable SumValue = new IntWritable();

    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);
    }
  }

  
  /**
   * Runs the demo.
   */
  public static void main(String[] args) throws IOException {
    WordCount wc = new WordCount();
    
    int mapTasks = 1;
    int reduceTasks = 1;
    JobConf conf = new JobConf(WordCount.class);
    conf.setJobName("wordcount");

    conf.setNumMapTasks(mapTasks);
    conf.setNumReduceTasks(reduceTasks);

    conf.setInputPath(new Path(wc.filepath));
    conf.setOutputKeyClass(Text.class);
    conf.setOutputValueClass(IntWritable.class);
    conf.setOutputPath(new Path(wc.outputPath));

    conf.setMapperClass(MapClass.class);
    conf.setCombinerClass(ReduceClass.class);
    conf.setReducerClass(ReduceClass.class);
    
    // Delete the output directory if it exists already
    Path outputDir = new Path(wc.outputPath);
    FileSystem.get(conf).delete(outputDir);

    JobClient.runJob(conf);
  }
}