hadoop 自学指南二之开发环境搭建

一、前言

从一个简单的程序观察hadoop 的运行过程

二、window 下hadoop 的开发环境搭建

环境准备：
hadoop 1.2.1
eclipse Version: Mars Release (4.5.0)
hadoop-eclipse-plugin-1.2.1(网上有许多，不再重复提供）
hadoop-eclipse-plugin-1.2.1放到dropins 启动eclipse

根据自己的情况填写



advanced parameters:这里要改一下

出现



代表成功了

问题ps： 一直有listening.....请检查插件版本与hadoop 版本是否一致
插件安装没有成功,原因可以是eclipse版本过旧，你到官网下载最新的版本

三、hadoop 运行过程

下面是hadoop-example的一个经典程序hello word,是wordCount

package hadoop.v3;

import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

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.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
import org.hai.hdfs.utils.HDFSUtils;

/**
* hadoop 的 hello word
* @author : chenhaipeng
* @date : 2015年9月5日 下午8:38:13
*/
public class WordCount {

//Map
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);
}

}
}

//reduce
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 deletedir(String path){
try {
HDFSUtils.DeleteHDFSFile(path);
} catch (IOException e) {
e.printStackTrace();
}
}

public static void main(String[] args) throws Exception {
JobConf conf  = new JobConf(WordCount.class);
conf.setJobName("mywordcount");

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]));
deletedir(args[1]);
FileOutputFormat.setOutputPath(conf, new Path(args[1]));

JobClient.runJob(conf);

}

}

输入为：
Mary had a little lamb

its fleece very white as snow

and everywhere that Mary went

the lamb was sure to go

查看输出结果如下 ：



进入http://hai:50030/jobtracker.jsp 发现根本就没有运行这个job,但结果有输出，什么鬼？
参巧hadoop 自学指南-hadoop 的各种问题汇总