Hadoop之MapReduce WordCount运行

搭建好Hadoop集群环境或者单机环境，并运行，MapReduce进程要起来

1. 假设已经配置了下列环境变量

export JAVA_HOME=/usr/java/default
export PATH=$JAVA_HOME/bin:$PATH
export HADOOP_CLASSPATH=$JAVA_HOME/lib/tools.jar

2.创建2个测试文件，并上传到Hadoop HDFS中

[[email protected]one temp]$ cat file01
Hello World Bye World
[[email protected]-one temp]$ cat file02
Hello Hadoop Goodbye Hadoop[[email protected] temp]$ ../hadoop-2.6.0/bin/hdfs dfs -mkdir /wordcount[[email protected] temp]$ ../hadoop-2.6.0/bin/hdfs dfs -mkdir /wordcount/input../hadoop-2.6.0/bin/hdfs dfs -put file* /wordcount/input

这个是删除HDFS文件夹的命令:../hadoop-2.6.0/bin/hdfs dfs -rm -r /temp

3.编写WordCount类

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);
  }
}

4. 编译WordCount.java 并 打包为jar

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

5.运行MapReduce程序

[[email protected] temp]$ ../hadoop-2.6.0/bin/hadoop  jar wc.jar WordCount /wordcount/input /wordcount/output

查看结果

 ../hadoop-2.6.0/bin/hadoop  dfs -cat /wordcount/output/part-r-00000

Bye    1Goodbye    1Hadoop    2Hello    2World    2