MapReduce自定义Driver类实现（第三步）

1、Driver类：配置Mapper和Reducer的相关属性
通过WordCountApp.java将Mapper和Reducer关联起来
使用MapReduce统计HDFS上的文件对应的词频
提交到本地运行：开发过程中使用

2、WordCountApp.java

package com.imooc.bigdata.hadoop.mapreduce.wordcount;


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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

/*
 * Driver类：配置Mapper和Reducer的相关属性
 * 通过WordCountApp.java将Mapper和Reducer关联起来
 * 使用MapReduce统计HDFS上的文件对应的词频
 *
 * 提交到本地运行：开发过程中使用
 */

public class WordCountApp {

    public static void main(String[] args) throws Exception{

        //设置权限
        System.setProperty("HADOOP_USER_NAME", "hadoop");

        Configuration configuration = new Configuration();
        //在configuration里设置一些东西：
        configuration.set("fs.defaultFS", "hdfs://192.168.126.101:8020");

        //创建一个Job
        //将configuration传进来
        Job job = Job.getInstance(configuration);

        //设置Job对应的参数：主类
        job.setJarByClass(WordCountApp.class);

        //设置Job对应的参数：设置自定义的Mapper和Reducer处理类
        job.setMapperClass(WordCountMapper.class);
        job.setReducerClass(WordCountReducer.class);

        //设置Job对应的参数：Mapper输出key和value的类型
        //不需要关注Mapper输入
        //Mapper<LongWritable, Text, Text, IntWritable>
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        //设置Job对应的参数：Reducer输出key和value的类型
        //不需要关注Reducer输入
        //Reducer<Text, IntWritable, Text, IntWritable>
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        //设置Job对应的参数：Mapper输出key和value的类型：作业输入和输出的路径
        FileInputFormat.setInputPaths(job, new Path("/wordcount/input"));
        FileOutputFormat.setOutputPath(job, new Path("/wordcount/output"));

        //提交job
        boolean result = job.waitForCompletion(true);

        System.exit(result ? 0 : -1);

    }
    //若输出失败，添加以下代码
    static {

        try {
            //G:\BaiduNetdiskDownload\hadoop2.7.6\bin\hadoop.dll
            System.load("G:\\BaiduNetdiskDownload\\hadoop2.7.6\\bin\\hadoop.dll");

        } catch (UnsatisfiedLinkError e) {

            System.err.println("Native code library failed to load.\n" + e);

            System.exit(1);

        }

    }
}

3、log4j.properties

由于日志中不报错，添加后，可查看错误原因

在resources中新建file

log4j.rootLogger=INFO,stdout
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.Target=System.out
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=[%-5p] method:%l%n%m%n

4、在命令行中多层新建input文件夹，并放入文件h.txt

5、运行