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初学Hadoop之WordCount分词统计

时间:2015-05-05 10:24:24      阅读:113      评论:0      收藏:0      [点我收藏+]

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1、WordCount源码

  将源码文件WordCount.java放到Hadoop2.6.0文件夹中。

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、编译源码

$ bin/hadoop com.sun.tools.javac.Main WordCount.java  #将WordCount.java编译成三个.class文件
$ jar cf wc.jar WordCount*.class #将三个.class文件打包成jar文件

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3、运行

  新建input文件夹,用于存放需要统计的文本。

cd /opt/hadoop-2.6.0
mkdir input

  复制hadoop-2.6.0文件夹下的txt文件到input文件夹下。

cp *.txt /opt/hadoop-2.6.0/input

 

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  运行命令。

bin/hadoop jar wc.jar WordCount /opt/hadoop-2.6.0/input /opt/hadoop-2.6.0/output #自动生成output文件夹,用于存放分词统计结果。

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4、查看结果

bin/hdfs dfs -cat /opt/hadoop-2.6.0/output/part-r-00000

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  至此,WordCount分词统计运行成功,Hadoop环境搭建成功。

初学Hadoop之WordCount分词统计

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原文地址:http://www.cnblogs.com/hehaiyang/p/4478233.html

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