【hadoop2.6.0】通过代码运行程序流程

之前跑了一下hadoop里面自带的例子，现在顺一下如何通过源代码来运行程序。

我懒得装eclipse,就全部用命令行了。

整体参考官网上的：http://hadoop.apache.org/docs/r2.6.0/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html#Example:_WordCount_v1.0

 

注意：所有的代码都放在hadoop的根文件夹下面，否则会提示找不到主类！ 

 

①写源代码，  保存为WordCount.java

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;



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();

    Job job = Job.getInstance(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(args[0]));

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

    System.exit(job.waitForCompletion(true) ? 0 : 1);

  }

}

 

②把源代码编译打包成jar文件

$ bin/hadoop com.sun.tools.javac.Main WordCount.java 

$ jar cf wc.jar WordCount*.class

这样就生成了jar文件

 

③运行文件

假设已经有一些文件上传到了/user/kzy/input2/hadoop 文件夹， 已经有/user/kzy/output文件夹，那么下面的语句令输出都放在新建的wc文件夹里

bin/hadoop jar wc.jar WordCount /user/kzy/input2/hadoop /user/kzy/output/wc