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hadoop2.5.0单节点下MR运行WordCount

时间:2014-09-03 19:45:17      阅读:270      评论:0      收藏:0      [点我收藏+]

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参考:http://hadoop.apache.org/docs/r2.5.0/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html

Maven和WordCount代码:

   <dependencies>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.4.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-mapreduce-client-core</artifactId>
            <version>2.4.1</version>
        </dependency>
    </dependencies>
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);
  }
}
export JAVA_HOME=/usr/java/default
export PATH=$JAVA_HOME/bin:$PATH
export HADOOP_CLASSPATH=$JAVA_HOME/lib/tools.jar

运行Shell:

$ bin/hadoop com.sun.tools.javac.Main WordCount.java
$ jar cf wc.jar WordCount*.clas

假设:

    /user/joe/wordcount/input - input directory in HDFS
    /user/joe/wordcount/output - output directory in HDFS

以下目录和文件没有的话先创建:

$ bin/hdfs dfs -ls /user/joe/wordcount/input/
/user/joe/wordcount/input/file01
/user/joe/wordcount/input/file02
$ bin/hdfs dfs -cat /user/joe/wordcount/input/file01
Hello World Bye World

$ bin/hdfs dfs -cat /user/joe/wordcount/input/file02
Hello Hadoop Goodbye Hadoop

运行:

$ bin/hadoop jar wc.jar WordCount /user/joe/wordcount/input /user/joe/wordcount/output

输出:

$ bin/hdfs dfs -cat /user/joe/wordcount/output/part-r-00000

Bye 1
Goodbye 1
Hadoop 2
Hello 2
World 2

 

hadoop2.5.0单节点下MR运行WordCount

标签:style   blog   http   color   os   io   java   ar   for   

原文地址:http://www.cnblogs.com/spacewalk/p/3954336.html

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