Hadoop之Mapreduce 程序

package com.gylhaut.hadoop.senior.mapreduce;

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.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/**
 * Shift +Alt +S 快捷键用法
 *
 */
public class WordCount {
	// step 1：Map Class
	public static class WordCountMapper extends
			Mapper<LongWritable, Text, Text, IntWritable> {
		private final static IntWritable one = new IntWritable(1);
		private Text word = new Text();

		@Override
		public void map(LongWritable key, Text value, Context context)
				throws IOException, InterruptedException {
			StringTokenizer itr = new StringTokenizer(value.toString());
			while (itr.hasMoreTokens()) {
				word.set(itr.nextToken());
				context.write(word, one);
			}
		}
	}

	// step 2: Reduce Class
	public static class WordCountReducer extends
			Reducer<Text, IntWritable, Text, IntWritable> {
		private IntWritable result = new IntWritable();

		@Override
		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);
		}
	}

	// step 3: Driver, component job
	public int run(String[] args) throws Exception {
		// 1.get configuration
		Configuration configuration = new Configuration();
		// 2:create job
		Job job = Job.getInstance(configuration, this.getClass()
				.getSimpleName());
		// run jar
		job.setJarByClass(this.getClass());
		// 3.set job
		// input ->map ->reduce->output
		// 3.1 input
		Path inPath = new Path(args[0]);
		FileInputFormat.addInputPath(job, inPath);
		// 3.2 map
		job.setMapperClass(WordCountMapper.class);
		// 设置map 输出类型
		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(IntWritable.class);
		// 3.3 reduce
		job.setReducerClass(WordCountReducer.class);
		// 设置reduce 输出类型
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);
		// 3.4 output
		Path outPath = new Path(args[1]);
		FileOutputFormat.setOutputPath(job, outPath);
		// 4.submit job
		boolean isSuccess = job.waitForCompletion(true);

		return isSuccess ? 0 : 1;

	}

	public static void main(String[] args) throws Exception {
		int status = new WordCount().run(args);
		System.exit(status);
	}
}