Windows下Eclipse安装Hadoop插件

一、下载hadoop-eclipse-plugin-2.7.3插件，并解压

二、将hadoop-eclipse-plugin-2.7.3.jar拷贝到${ECLIPSE_HOME}下的plugins文件夹，

     并重启eclipse，便可出现如下视图：

    

三、将hadoop-eclipse-plugin-2.7.3下的bin目录全部文件拷贝到window下的Hadoop目录下的bin目录中

四、同时将bin目录下的hadoop.dll拷贝到C:\windows\system32目录下

五、eclipse配置hadoop安装目录

    

六、建立Hadoop Location

    

七、运行WordCount实例

    1. 建立输入目录input，并上传数据文件input.txt，不可建立输出文件夹，否则会报错。

    

    2. 配置运行参数（以下图），最后点击run便可

        说明：input指的的文件夹，直接挂在"/"目录下，与hdfs://192.168.241.129:9000/input对应

    

3. 输入结果以下图

    

4. 附：WordCount.java源码

package com.hadoop.example;

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.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;
import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

	public static class TokenizerMapper extends
			Mapper<Object, Text, Text, IntWritable> {

		private final static IntWritable one = new IntWritable(1);
		private Text word = new Text();

		public void map(Object 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);
			}
		}
	}

	public static class IntSumReducer extends
			Reducer<Text, IntWritable, Text, IntWritable> {
		private IntWritable result = new IntWritable();

		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);
		}
	}

	public static void main(String[] args) throws Exception {
		System.setProperty("HADOOP_USER_NAME", "root");
		System.setProperty("hadoop.home.dir", "D:/install/hadoop-2.7.3");
//		System.setProperty("yarn.resourcemanager.address", "master:8032");
		System.setProperty("yarn.resourcemanager.hostname", "master");
		Configuration conf = new Configuration();
		String[] otherArgs = new GenericOptionsParser(conf, args)
				.getRemainingArgs();
		if (otherArgs.length < 2) {
			System.err.println("Usage: wordcount <in> [<in>...] <out>");
			System.exit(2);
		}
		Job job = Job.getInstance(conf, "word count");
		job.setJarByClass(WordCount.class);
		job.setMapperClass(TokenizerMapper.class);
		job.setCombinerClass(IntSumReducer.class);
		job.setReducerClass(IntSumReducer.class);
		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);
		for (int i = 0; i < otherArgs.length - 1; ++i) {
			FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
		}
		FileOutputFormat.setOutputPath(job, new Path(
				otherArgs[otherArgs.length - 1]));
		System.exit(job.waitForCompletion(true) ? 0 : 1);
	}
}

五、可打成Runnable JarFile包运行

#可运行包执行命令：hadoop jar {jar} {input} {output}
hadoop jar WordCount.jar hdfs://192.168.241.129:9000/input hdfs://192.168.241.129:9000/output