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安装Hadoop系统 — 新建MapReduce项目

时间:2015-12-05 11:05:37      阅读:156      评论:0      收藏:0      [点我收藏+]

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1、新建MR工程

依次点击 File → New → Ohter…  选择 “Map/Reduce Project”,然后输入项目名称:mrdemo,创建新项目:
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2、(这步在以后的开发中可能会用到,但是现在不用,现在直接新建一个class文件即可)创建Mapper和Reducer
依次点击 File → New → Ohter… 选择Mapper,自动继承Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>
 
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创建Reducer的过程同Mapper,具体的业务逻辑自己实现即可。
 
3、新建一个class文件,包名为com.mrdemo,类名为WordCount,按finish。
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4、编写map函数、reduce函数和主函数。本文就以官方自带的WordCount为例进行测试(将下面的源码复制到eclipse中):
package com.mrdemo;

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);
  }
}
 
5、准备测试数据。
在hdfs中新建一个input01文件夹,然后将/home/hadoop/Documents文件夹下新建的hello文件上传到hdfs中的input01文件夹中。
测试数据:
hello world!
hello hadoop
jobtracker
maptracker
reducetracker
task
namenode
datanode
block
beautiful world
hadoop:
HDFS
MapReduce
 
hadoop@hadoop-ThinkPad:~$ hadoop fs -mkdir input01
hadoop@hadoop-ThinkPad:~$ cd /home/hadoop/Documents
hadoop@hadoop-ThinkPad:~/Documents$ hadoop fs -copyFromLocal hello input01
hdfs://localhost:9000/user/yyq/input01
hdfs://localhost:9000/user/yyq/output01
 
6、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:
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7、运行
Run As -> Run on Hadoop ,执行完成后可以看到如下信息:技术分享
到此Eclipse中调用Hadoop-1.0.3本地伪分布式模式执行MR演示成功。
参考博客:
http://www.aboutyun.com/forum.php?mod=viewthread&tid=7541&
 

安装Hadoop系统 — 新建MapReduce项目

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原文地址:http://www.cnblogs.com/yangyquin/p/5021122.html

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