/**
 * Program: WordCount.java
 * Editor: Waue Chen 
 * From :  NCHC. Taiwn
 * Last Update Date: 07/02/2008
 */

/**
 * 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);
	}
}
