使用eclipse開發MapReduce

1.增長插件
將插件hadoop-eclipse-plugin-1.0.4.jar放入/usr/lib/eclipse/plugins目錄下
（完成後從新啓動eclipse）[插件存放路徑視eclipse存放位置而定]
2.配置hadoop的安裝路徑
eclipse中
window—preferences，在左邊欄中找到Hadoop Map/Reduce，將hadoop的目錄設置爲hadoop的安裝目錄
3.創建MapRedece工程
建立一個MapReduce Project，點擊eclipse主菜單上的File—New—Project，在彈出的對話框中選擇MapReduce Project，以後輸入Project的名
4.創建MapReduce程序
就和創建普通的java程序是同樣的

package com.sun.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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class WordCount {
    public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {
        private final static IntWritable one = new IntWritable(1);
        private Text word = new Text();
        public void map(LongWritable key, Text value, Context context) 
            throws IOException, InterruptedException{
                String line = value.toString();
                StringTokenizer tokenizer = new StringTokenizer(line);
                while (tokenizer.hasMoreTokens()) {
                    word.set(tokenizer.nextToken());
                    context.write(word, one);
                }
            }
    }
    public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {

        @Override
            public void reduce(Text key, Iterable<IntWritable> values, Context context)
            throws IOException, InterruptedException {
                // TODO Auto-generated method stub
                int sum = 0;
                for (IntWritable val : values)
                    sum += val.get();
                context.write(key, new IntWritable(sum));
            }
    }
    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();

        Job job = new Job(conf, "wordcount");
        job.setJarByClass(WordCount.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);

        job.setInputFormatClass(TextInputFormat.class);
        job.setOutputFormatClass(TextOutputFormat.class);

        FileInputFormat.addInputPath(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        job.waitForCompletion(true);

    }
}

5.執行程序
執行程序時要附加必定的參數
點擊Run-run configurations ，在Arguments中填寫參數，參數分別爲輸入文件的目錄 輸出文件的目錄
例如/home/asheng/hadoop/in /home/asheng/hadoop/out(in目錄下應該放置須要分析的文件，out目錄不須要手工創建)
設置完成後點擊Run便可，經過控制檯能夠觀察運行狀態，具體的運行結果在out目錄下