eclipse 运行WordCount(附源码)

1.下载hadoop插件(hadoop下载包里好像有这个插件)java

hadoop-eclipse-plugin-2.7.1分享连接  https://pan.baidu.com/s/1sldBu9napache

放到eclipse/plugins文件夹下,重启eclipseapp

2.window  -> preferences  点击肯定  找到 hadoop map/reduce 在右窗口填上hadoop安装地址eclipse

3.出现一个和控制台同样位置的map/reduce location ,右击空白处 选择new hadoop locationoop

loaction name填上名字,Map/Reduce (V2) Master的端口填mapred-site.xml端口 。DFS Master填core-site.xml 肯定。host都是填localhost。this

4.File-->New-->Other-->Map/Reduce Project 建立文件 取名   新建java文件代码以下spa

5.源代码以下插件

package com.filex;
 
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.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Mapper.Context;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.Reducer.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;

public class WordCount
{
  public static void main(String[] args)
    throws Exception
  {
    Configuration conf = new Configuration();

    Job job = new Job(conf);
    job.setJarByClass(WordCount.class);
    job.setJobName("wordcount");

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

    job.setMapperClass(WordCountMap.class);
    job.setReducerClass(WordCountReduce.class);

    job.setInputFormatClass(TextInputFormat.class);
    job.setOutputFormatClass(TextOutputFormat.class);
/////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////
    //下面的两句代码,其中参数意义
    //hdfs://localhost:9000/in   表示须要计数的文件夹    计算命令行下:hadoop fs -ls /in  出现的文件
    //hdfs://localhost:9000/output 表示储存结果的文件夹(不要建立,同时以前不要存在这个文件夹)
    //new Path(arg[0]) new Path(arg[1])也能够使用命令行传参的方式传入两个文件夹(不能够直接运行)
    //  
    FileInputFormat.addInputPath(job, new Path("hdfs://localhost:9000/in"));
    FileOutputFormat.setOutputPath(job, new Path("hdfs://localhost:9000/output"));
    job.waitForCompletion(true);
  }

  public static class WordCountMap extends Mapper<LongWritable, Text, Text, IntWritable>
  {
    private final IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException
    {
      String line = value.toString();
      StringTokenizer token = new StringTokenizer(line);
      while (token.hasMoreTokens()) {
        this.word.set(token.nextToken());
        context.write(this.word, this.one);
      }
    }
  }

  public static class WordCountReduce extends Reducer<Text, IntWritable, Text, IntWritable>
  {
    public void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context)
      throws IOException, InterruptedException
    {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      context.write(key, new IntWritable(sum));
    }
  }
}

ps:注意一下注释部分,须要确认你须要计算的文件命令行

6.直接运行 或者导出code

7.若是导出,运行命令:

hadoop  jar      .jar路径                运行的类(含包路径)    类的参数 

hadoop   jar   /home/user/xxx.jar  com.filex.WordCount                (输入输出文件已经设置好)

hadoop   jar   /home/user/xxx.jar  com.filex.WordCount      in put     ( 输入输出文件未设置好)。

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