在Eclipse中配置Hadoop2.6.0

1、下载并配置插件

将下载的hadoop-eclipse-plugin-2.6.0.jar 放到Eclipse的dropins目录下，重启Eclipse.

2、配置 hadoop 安装目录

• window ->preference -> hadoop Map/Reduce -> Hadoop installation directory

3、配置Map/Reduce 视图

• window ->Open Perspective -> other->Map/Reduce -> 点击“OK”
• windows → show view → other->Map/Reduce Locations-> 点击“OK”
• 控制台会多出一个“Map/Reduce Locations”的Tab页

在“Map/Reduce Locations” Tab页 点击图标<大象+>或者在空白的地方右键，选择“New Hadoop location…”，弹出对话框“New hadoop location…”，配置如下内容：将ha1改为自己的hadoop用户

注意：MR Master和DFS Master配置必须和mapred-site.xml和core-site.xml等配置文件一致

打开Project Explorer,查看HDFS文件系统。

4、新建Map/Reduce任务

File->New->project->Map/Reduce Project->Next

编写WordCount类：记得先把服务都起来

import java.io.IOException;
import java.util.*;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.util.*;
public class WordCount {
public static class Map extends MapReduceBase implements 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, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
 String line = value.toString();
 StringTokenizer tokenizer = new StringTokenizer(line);
 while (tokenizer.hasMoreTokens()) {
   word.set(tokenizer.nextToken());
   output.collect(word, one);
 }
}
}
public static class Reduce extends MapReduceBase implements Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterator<IntWritable> values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
 int sum = 0;
 while (values.hasNext()) {
   sum += values.next().get();
 }
 output.collect(key, new IntWritable(sum));
}
}
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(WordCount.class);
conf.setJobName("wordcount");

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

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

conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);

FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));

JobClient.runJob(conf);
}
}

5、配置运行时参数:右键-->Run as-->Run Confiugrations

user/ha1/input/hadoop是你上传在hdfs的文件夹（自己创建），里面放要处理的文件。ouput4放输出结果

将程序放在hadoop集群上运行：右键-->Runas -->Run on Hadoop,最终的输出结果会在HDFS相应的文件夹下显示。至此，ubuntu下hadoop-2.6.0 eclipse插件配置完成。

 

特别注意：按以上配置后，执行MR控制台没有日志详细信息。

解决方案，将hadoop-2.6.0/etc/haoop/log4j.properties 文件拷贝到 Eclipse项目下即可 （例如，将其拷贝到/home/hadoop/workspace/WordCount路径下<疑惑：在Linux文件系统中拷贝到该路径无效，但是从Eclipse视图中拷贝就有效。。且上述路径中相应的生成log4j.properties 文件>）。

 

 

http://blog.csdn.net/zythy/article/details/17397153