Statistical code word - in conjunction with Hadoop to do with java, there is source code comments

Statistics word statistics, statistical word frequency of each word. To better understand the idea of ​​Hadoop framework.

package mapreduce;

import org.apache.hadoop.conf.Configuration;
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;

import java.io.IOException;

/**
 * 词频统计
 */
public class WordCountApp {

    /**
     * Mapper：读取源文件，进行单词拆分
     */
    public static class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable> {

        LongWritable one = new LongWritable(1);

        @Override
        protected void map(LongWritable key, Text value, Context context)
                throws IOException, InterruptedException {

            // 获取文件一行的内容
            String line = value.toString();

            // 将行内容拆分成一个个单词
            String[] words = line.split(" ");

            // 将单词做成键值对输出
            for(String word : words) {
                context.write(new Text(word), one);
            }

        }
    }

    /**
     * 对mapper的输出进行合并统计
     */
    public static class MyReducer extends Reducer<Text, LongWritable, Text, LongWritable> {

        @Override
        protected void reduce(Text key, Iterable<LongWritable> values, Context context)
                throws IOException, InterruptedException {
            long sum = 0;
            for(LongWritable value : values){
                // 将当前key对应的多个values进行累加
                sum += value.get();
            }

            // 将统计完成的结果按照(text, long)键值对输出
            context.write(key, new LongWritable(sum));

        }
    }

    public static void main(String[] args) throws Exception{
        // 创建配置实例
        Configuration configuration = new Configuration();

        // 创建一个job
        Job job = Job.getInstance(configuration, "wordcount");
        // 设置该job的处理类
        job.setJarByClass(WordCountApp.class);

        // 设置输入文件的路径
        FileInputFormat.setInputPaths(job, new Path(args[0]));

        // 设置mapper的相关参数
        job.setMapperClass(MyMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);

        // 设置reducer的相关参数
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);

        // 设置处理的结果文件输出目录
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        // 提交给yarn运行，等待运行完成之后退出
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}