1.WordMapper.java

package WordCount;

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 java.io.IOException;

public class WordMapper extends Mapper<LongWritable, Text, Text, IntWritable> {

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        final IntWritable ONE = new IntWritable(1);

        String s = value.toString();
        String[] words = s.split(" ");
        for (String word : words) {
            context.write(new Text(word), ONE);
        }
    }
}

2.WordReducer.java

package WordCount;

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

import java.io.IOException;

public class WordReducer extends Reducer<Text, IntWritable, Text, LongWritable> {
        @Override
    protected void reduce(Text key, Iterable<IntWritable> values,
                          Reducer<Text, IntWritable, Text, LongWritable>.Context context) throws IOException, InterruptedException {
        long count = 0;
        for (IntWritable value : values) {
            count += value.get();
        }
        context.write(key, new LongWritable(count));
    }
}

3.Test.java

package WordCount;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
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;

public class Test {

    public static void main(String[] args) throws Exception{
        Configuration conf = new Configuration();

        conf.set("fs.defaultFS","hdfs://master:9000/");
        conf.set("mapreduce.job.jar", "out/artifacts/HelloMapReduce.jar");
        conf.set("mapreduce.framework.name","yarn");
        conf.set("mapreduce.jobhistory.address","192.168.56.100:10020");
        conf.set("yarn.resourcemanager.hostname","master");
        conf.set("mapreduce.app-submission.cross-platform", "true");

        Job job = Job.getInstance(conf);

//        job.setJarByClass(Test.class);

        job.setMapperClass(WordMapper.class);
        job.setReducerClass(WordReducer.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);

        FileInputFormat.setInputPaths(job, "/hello.txt");
        FileOutputFormat.setOutputPath(job, new Path("/output/"));

        job.waitForCompletion(true);
    }
}

4.生成jar包

参考 https://www.cnblogs.com/airnew/p/9540982.html

5.运行结果

mapreduce1.png
map.png
reduce.png
mapreduce2.png
mapreduce生成output.png
mapreduce-result.png

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