MapReduce学习总结之java版wordcount实现

一、代码实现：

package rdb.com.hadoop01.mapreduce;
 
import java.io.IOException;
 
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
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;
 
/**
 * mapreduce word count 应用
 * @author rdb
 *
 */
public class WordCountApp {
 
    /**
     * map读取输入文件
     * @author rdb
     *
     */
    public static class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable>{
         
        LongWritable one = new LongWritable(1);
        @Override
        protected void map(LongWritable key, Text value,
                Mapper<LongWritable, Text, Text, LongWritable>.Context context)
                throws IOException, InterruptedException {
            //接收每一行数据
            String line = value.toString();
            //按空格进行分割 
            String[] words = line.split(" ");
            for(String word :words){
                //通过上下文把map处理结果输出
                context.write(new Text(word), one);
            }
        }
    }
     
    /**
     * reduce程序，归并统计
     * @author rdb
     *
     */
    public static class MyReduce extends Reducer<Text, LongWritable, Text, LongWritable>{
         
        @Override
        protected void reduce(Text key, Iterable<LongWritable> values,
                Reducer<Text, LongWritable, Text, LongWritable>.Context context)
                throws IOException, InterruptedException {
            long sum = 0;
            for (LongWritable value : values){
                //求单词次数
                sum += value.get();
            }
            //通过上下文把reduce处理结果输出
            context.write(key, new LongWritable(sum));
        }
    }
     
    /**
     * 自定义driver:封装mapreduce作业所有信息
     *@param args
     * @throws IOException 
     */
    public static void main(String[] args) throws Exception {
         
        //创建配置
        Configuration configuration = new Configuration();
         
        //清理已经存在的输出目录
        Path out = new Path(args[1]);
        FileSystem fileSystem = FileSystem.get(configuration);
        if(fileSystem.exists(out)){
            fileSystem.delete(out, true);
            System.out.println("output exists,but it has deleted");
        }
         
        //创建job
        Job job = Job.getInstance(configuration,"WordCount");
         
        //设置job的处理类
        job.setJarByClass(WordCountApp.class);
         
        //设置作业处理的输入路径
        FileInputFormat.setInputPaths(job, new Path(args[0]));
         
        //设置map相关的参数
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);
         
        //设置reduce相关参数
        job.setReducerClass(MyReduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);
         
        //设置作业处理的输出路径
        FileOutputFormat.setOutputPath(job, new Path(args[1]));
         
        System.exit(job.waitForCompletion(true)? 0 : 1) ;
    }
}

二、运行结果：

调用：

hadoop jar ~/lib/hadoop01-0.0.1-SNAPSHOT.jar rdb.com.hadoop01.mapreduce.WordCountApp 
hdfs://hadoop01:8020/hello.txt  hdfs://hadoop01:8020/output/wc

输入的文件内容：

Deer Bear River
Car Car River
Deer Car Bear

输出的结果：

Bear    2
Car     3
Deer    2
River   2