开发MapReduce算法实现单词统计-EW帮帮网

一、导包erer

1、打开idear创建一个项目（JDK选择自己下载的已有的）

2、创建好项目以后可以看见自己JDK的jar包已经存在

3、点击File->Project Structure...

4、点击modules->Dependencies->+加入jar包

5、解压hadoop的压缩包，下载链接hadoop 提取码：6s5a,找到hadoop-common-3.3.0.jar(路径hadoop-3.3.0\share\hadoop\common)点击OK

6、lib下的jar包全部选中

7、hdfs下hadoop-hdfs-3.3.0.jar也选中

8、mapreducr下的jar包全部选中

9、最后点击Apply点击ok确定导入

二、代码

1、创建一个名为Mapper的类写入以下内容

import org.apache.hadoop.io. *;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class WordCountMapper extends Mapper<LongWritable ,Text, Text , IntWritable> {
    @Override
    public void map( LongWritable key, Text value, Context context)throws IOException,
            InterruptedException{
//拿到一行文本内容，转换成String
        String line=value . toString();
//将这行文本切分成单词
        String[] words=line . split(",");
//输出单词
        for(String word:words){
            context . write(new Text(word) , new IntWritable(1));
        }
    }
}

2、WordCountReducer内容

import org .apache . hadoop.io.*;
import org .apache . hadoop . mapreduce . Reducer;
import java . io. IOException;
public class WordCountReducer extends Reducer<Text,IntWritable,Text,IntWritable> {
    @Override
    public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException,
            InterruptedException {
//定义一个计数器
        int count = 0;
        for (IntWritable value : values) {
            count += value.get();
        }
        context.write(key, new IntWritable(count));
    }
}

3、WordCountJobSubmitter

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 WordCountJobSubmitter {
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        Job wordCountJob = Job.getInstance(conf);
//指定本job所在的jar包
        wordCountJob.setJarByClass(WordCountJobSubmitter.class);
//设置wordCountJob所在的mapper逻辑为哪个类
        wordCountJob.setMapperClass(WordCountMapper.class);
//设置wordCountJob所用的reducer逻辑类为哪个类
        wordCountJob.setReducerClass(WordCountReducer.class);
//设置map阶段输出的KV数据类型
        wordCountJob.setMapOutputKeyClass(Text.class);
        wordCountJob.setMapOutputValueClass(IntWritable.class);
//设置最终的KV数据类型
        wordCountJob.setOutputKeyClass(Text.class);
        wordCountJob.setMapOutputValueClass(IntWritable.class);
//设置要处理的文本数据所存放的路径
        FileInputFormat.setInputPaths(wordCountJob, "hdfs://192.168.43.26:9000/mapreduce/mydata02");
        FileOutputFormat.setOutputPath(wordCountJob, new Path("hdfs://192.168.43.26:9000/mapreduce/output/"));
        wordCountJob.waitForCompletion(true);
    }
}

三、打jar包

1、点击Artifacts->JAR->选择第二项