IDEA关联hadoop执行wordcount程序

output里面没有数据，jar包好像都导上了，就是不行，
Mapper代码如下

package com.atguigu.mapreduce.wordcount;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.util.Tool;
import java.io.IOException;
//KEYIN     map阶段输入的key类型：LongWritable
//VALUEIN   map阶段输入value类型：Text
//KEYOUT    map阶段输出的key类型：Text
//VALUEOUT  map阶段输出的value类型：IntWritable
class WordCountUpMR extends Configured implements Tool {
    @Override
    public int run(String[] strings) throws Exception {
        return 0;
    }
    public class WorldCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
        private Text outK = new Text();
        private IntWritable outV = new IntWritable(1);
        @Override
        protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            super.map(key, value, context);
            //1  获取一行，数据如下
            //atguigu atguigu
            String line = value.toString();
            //2  切割操作，成为
            //atguigu
            //atguigu
            String[] words = line.split(" ");
            //3  循环写出
            for (String word : words) {
                //封装outK
                outK.set(word);
                //写出
                context.write(outK, outV);
            }
        }
    }
}

Driver代码如下

package com.atguigu.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;
import java.io.IOException;
public class WordCountDriver {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        //1.获取job
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);
        //2.获取jar包路径
        job.setJarByClass(WordCountDriver.class);
        //3.关联mapper和reducer
        job.setMapperClass(WordCountUpMR.WorldCountMapper.class);
        job.setReducerClass(WorldCountReducer.class);
        //4.设置map输出的k-v类型
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        //5.设置最终输出的k-v类型
        job.setOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        //6.设置输入路径和输出路径
        FileInputFormat.setInputPaths(job,new Path("E:\\hadoop\\input"));
        FileOutputFormat.setOutputPath(job,new Path("E:\\hadoop\\output"));
        //7.提交job
        boolean result = job.waitForCompletion(true);
        System.exit(result ? 0 : 1);
    }
}

Reducer代码如下

package com.atguigu.mapreduce.wordcount;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

//KEYIN       reduce阶段输入的key类型：LongWritable
//VALUEIN     reduce阶段输入value类型：Text
//KEYOUT      reduce阶段输出的Key类型：Text
//VALUEOUT    reduce阶段输出的value类型：IntWritable
public class WorldCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
    private IntWritable outV = new IntWritable();
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        int sum = 0;
        //atguigu,(1,1)
        //ss,(1,1)
        //进行累加
        for (IntWritable value : values) {
            sum += value.get();
        }

        outV.set(sum);

        //写出
        context.write(key,outV);
    }
}