准备

创建项目

新建项目

在新建项目中选择新建项目（不要选择生成器中的Maven）语言为Java，构建系统为Maven

添加依赖

右上角齿轮图标中找到项目结构，在项目设置-模块中找到依赖，添加以下文件或目录

  • hadoop-3.2.4\share\hadoop\common
  • hadoop-3.2.4\share\hadoop\common\lib
  • hadoop-3.2.4\share\hadoop\mapreduce
  • hadoop-3.2.4\share\hadoop\mapreduce\lib

测试代码

在 IDE 中测试运行

在 \src\main\java 下新建 Java类 WordCount,填入

import java.io.IOException;
import java.util.Iterator;
import java.util.StringTokenizer;

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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {
    public WordCount() {
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        String[] otherArgs = (new GenericOptionsParser(conf, args)).getRemainingArgs();
        if (otherArgs.length < 2) {
            System.err.println("Usage: wordcount <in> [<in>...] <out>");
            System.exit(2);
        }
        Job job = Job.getInstance(conf, "word count");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(WordCount.TokenizerMapper.class);
        job.setCombinerClass(WordCount.IntSumReducer.class);
        job.setReducerClass(WordCount.IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        for (int i = 0; i < otherArgs.length - 1; ++i) {
            FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
        }
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }

    public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {
        private static final IntWritable one = new IntWritable(1);
        private Text word = new Text();

        public TokenizerMapper() {
        }

        public void map(Object key, Text value, Mapper<Object, Text, Text, IntWritable>.Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            while (itr.hasMoreTokens()) {
                this.word.set(itr.nextToken());
                context.write(this.word, one);
            }
        }
    }

    public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
        private IntWritable result = new IntWritable();

        public IntSumReducer() {
        }

        public void reduce(Text key, Iterable<IntWritable> values, Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {
            int sum = 0;
            IntWritable val;
            for (Iterator i$ = values.iterator(); i$.hasNext(); sum += val.get()) {
                val = (IntWritable) i$.next();
            }
            this.result.set(sum);
            context.write(key, this.result);
        }
    }
}

运行项目，会得到结果

Usage: wordcount <in> [<in>...] <out>

出现报错 HADOOP_HOME and hadoop.home.dir are unset 无伤大雅

打包JAR

右上角齿轮图标中找到项目结构，在项目设置-工件中点击加号，选择JAR - 来自具有依赖项的模块，在主类中选择刚刚编写的WordCount，点击确认，返回

在 菜单 - 构建 中 选择 构建工件... 选择构建

不出意外即可在输出目录找到生成的文件

服务端测试

把文件上传到服务器

启动集群

start-all.sh

创建1.txt 里面编写若干英语单词，并上传到hdfs

hdfs dfs -put /home/1.txt /input

运行测试

hadoop jar /home/word.jar /input /output

如果能在output中看到结果就是好的