6.Hadoop MapReduce

6.1编辑WordCount.java

创建wordcount测试目录

 编辑WordCount.java

输入下面代码：

可以访问https://hadoop.apache.org/docs/current/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html查看

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);
  }
}

可以看到创建的java文件

 6.2编译WordCount.java文件

编辑~/.bashrc文件：sudo gedit ~/.bashrc

输入：

export PATH=${JAVA_HOME}/bin:${PATH}
export HADOOP_CLASSPATH=${JAVA_HOME}/lib/tools.jar

 让文件生效：source ~/.bashrc

编译程序：hadoop com.sun.tools.javac.Main WordCount.java -Xlint:deprecation

打包成wc.jar：jar cf wc.jar WordCount*.class

 6.3创建测试文本文件

启动所有虚拟机，启动Hadoop Multi-Node Cluster

在HDFS创建目录：hadoop fs -mkdir -p /user/hduser/wordcount/input

cd ~/wordcount/input

上传文件：hadoop fs -copyFromLocal LICENSE.txt /user/hduser/wordcount/input

查看：

 6.4运行WordCount.java

切换目录：cd ~/wordcount

运行WordCount程序：

hadoop jar wc.jar WordCount /user/hduser/wordcount/input/LICENSE.txt /user/hduser/wordcount/output

 查看运行结果

hadoop fs -cat /user/hduser/wordcount/output/part-r-00000|more

 删除输出目录