1.pom准备

2.定义一个mapper类

3.定义一个reducer类

-----------------------------------------------------------------------------------------------------------------

此上与本地的MapReduce无任何区别，参照：

https://blog.csdn.net/weixin_44036154/article/details/103053844

大数据篇（17）--分布式计算框架MapReduce初体验（本地计算）

4.定义一个主类

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

/**
 * @author kismet
 * @date 2019-11-13 8:33
 */
public class WordCountDriver extends Configured implements Tool {
    @Override
    public int run(String[] args) throws Exception {

        Job job = Job.getInstance(new Configuration(), "name");
        job.setJarByClass(WordCountreduce.class);

        job.setInputFormatClass(TextInputFormat.class);
        TextInputFormat.addInputPath(job,new Path("hdfs://192.168.100.88:8020/abc"));

        job.setMapperClass(WordCountMap.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(LongWritable.class);

        job.setReducerClass(WordCountreduce.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(LongWritable.class);

        job.setOutputFormatClass(TextOutputFormat.class);
        TextOutputFormat.setOutputPath(job,new Path("hdfs://192.168.100.88:8020/abb"));

        job.setNumReduceTasks(2);

        return job.waitForCompletion(true)?0:1;
    }


    public static void main(String[] args) throws Exception {
        int run = ToolRunner.run(new WordCountDriver(), args);
    }
}