本文演示如何在Eclipse中开发一个Map/Reduce项目： 1、环境说明 Hadoop2.2.0 Eclipse?Juno SR2 Hadoop2.x-eclipse-plugin 插件的编译安装配置的过程参考：http://www.micmiu.com/bigdata/hadoop/hadoop2-x-eclipse-plugin-build-install/ 2、新建MR工程 依次
本文演示如何在Eclipse中开发一个Map/Reduce项目： 1、环境说明
- Hadoop2.2.0
- Eclipse?Juno SR2
- Hadoop2.x-eclipse-plugin 插件的编译安装配置的过程参考：http://www.micmiu.com/bigdata/hadoop/hadoop2-x-eclipse-plugin-build-install/
依次点击 File →?New →?Ohter... ?选择 “Map/Reduce Project”，然后输入项目名称:micmiu_MRDemo，创建新项目:
3、创建Mapper和Reducer
依次点击?File →?New →?Ohter... 选择Mapper，自动继承Mapper
创建Reducer的过程同Mapper，具体的业务逻辑自己实现即可。
本文就以官方自带的WordCount为例进行测试：
package com.micmiu.mr;
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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);
}
//conf.set("fs.defaultFS", "hdfs://192.168.6.77:9000");
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、准备测试数据micmiu-01.txt：
Hi Michael welcome to Hadoop more see micmiu.com
micmiu-02.txt：
Hi Michael welcome to BigData more see micmiu.com
micmiu-03.txt：
Hi Michael welcome to Spark more see micmiu.com
把 micmiu 打头的三个文件上传到hdfs：
micmiu-mbp:Downloads micmiu$ hdfs dfs -copyFromLocal micmiu-*.txt /user/micmiu/test/input micmiu-mbp:Downloads micmiu$ hdfs dfs -ls /user/micmiu/test/input Found 3 items -rw-r--r-- 1 micmiu supergroup 50 2014-04-15 14:53 /user/micmiu/test/input/micmiu-01.txt -rw-r--r-- 1 micmiu supergroup 50 2014-04-15 14:53 /user/micmiu/test/input/micmiu-02.txt -rw-r--r-- 1 micmiu supergroup 49 2014-04-15 14:53 /user/micmiu/test/input/micmiu-03.txt micmiu-mbp:Downloads micmiu$5、配置运行参数
Run As →?Run Configurations… ，在Arguments中配置运行参数，例如程序的输入参数：
6、运行
Run As -> Run on Hadoop ，执行完成后可以看到如下信息：
到此Eclipse中调用Hadoop2x本地伪分布式模式执行MR演示成功。
ps：调用集群环境MR运行一直失败，暂时没有找到原因。
—————– ?EOF?@Michael Sun?—————–
原文地址：eclipse中开发Hadoop2.x的Map/Reduce项目, 感谢原作者分享。
