之前习惯用hadoop streaming环境编写python程序，下面总结编辑java的eclipse环境配置总结，及一个WordCount例子运行。
一 下载eclipse安装包及hadoop插件
1去官网下载linux版本的eclipse安装包（或者在本人为了大家方便下载，上传到了csdn下载，网址：
2下载插件：hadoop-eclipse-plugin-2.6.0.jar
二 安装elicpse及hadoop插件
1 把eclipse解压到路径 /user/local/eclipse
2 把插件hadoop-eclipse-plugin-2.6.0.jar拷贝到eclipse路径：/user/local/eclipse/plugins/hadoop-eclipse-plugin-2.6.0.jar
3 启动eclipse
./user/local/eclipse/eclipse -clean
三 配置eclipse的hadoop环境
1选择 Window 菜单下的 Preference
配置hadoop路径： /usr/local/hadoop:
2 切换 Map/Reduce 开发视图。选择 Window 菜单下选择 Open Perspective -> Other-> Map/Reduce 选项即可进行切换。
3 建立与 Hadoop 集群的连接。点击 Eclipse软件右下角的 Map/Reduce Locations 面板，在面板中单击右键，选择 New Hadoop Location
4 查看效果，这样有一个好处是可视化了文件系统，要不只能输入命令查看，然而本人仍认为输入命令比较好，结合使用吧。可视化文件系统效果如下：
四 wordcount例子运行
1创建项目：点击 File 菜单，选择 New -> Project，选择 Map/Reduce Project，点击 Next，填写 Project name 为 WordCount 即可，点击 Finish 就创建好了项目。
2创建class类：接着右键点击刚创建的 WordCount 项目，选择 New -> Class；需要填写两个地方：在 Package 处填写 org.apache.hadoop.examples；在 Name 处填写 WordCount。
3填充代码：
package org.apache.hadoop.examples;
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 {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
Job job = new Job(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);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
4 运行之前终端输入以下命令，目的是通过配置文件修改默认的本地系统为hadoop文件系统和不输出一个警告；
cp /usr/local/hadoop/etc/hadoop/core-site.xml ~/workspace/WordCount/src cp /usr/local/hadoop/etc/hadoop/hdfs-site.xml ~/workspace/WordCount/src cp /usr/local/hadoop/etc/hadoop/log4j.properties ~/workspace/WordCount/src
5设置参数，输入和输出。特别指出：这个input和output实际是文件系统的路径，具体为/user/hadoop/input 和 /user/hadoop/output
6 在文件系统中的output，查看输出结果
参考：http://www.powerxing.com/hadoop-build-project-using-eclipse/ 本文图片来自这篇博客，截图太麻烦了