hadoop编程之词频统计

数据集实例

java代码，编程

实例

我们要先创建三个类分别为WordCoutMain、WordCoutMapper、WordCoutReducer这三个类

对应的代码如下

WordCoutMain

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
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.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
 
public class WordCountMain{
	public static void main(String[] args) throws Exception {
	    Configuration conf = new Configuration();
	    Job job = Job.getInstance(conf);
	    job.setJarByClass(WordCountMain.class);
	    job.setMapperClass(WordCountMapper.class);
	    job.setReducerClass(WordCountReducer.class);
	    job.setMapOutputKeyClass(Text.class);
	    job.setMapOutputValueClass(LongWritable.class);
	    job.setOutputKeyClass(Text.class);
	    job.setOutputValueClass(LongWritable.class);
	    FileInputFormat.setInputPaths(job, new Path(args[0]));
	    FileOutputFormat.setOutputPath(job, new Path(args[1]));
	    job.waitForCompletion(true);
	}
 
}

WordCoutMapper

import java.io.IOException;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
 
public class WordCountMapper extends Mapper<LongWritable, Text, Text, LongWritable> {
@Override
protected void map(LongWritable key1, Text value1, Context context)
throws IOException, InterruptedException {
		String data = value1.toString();
      	String[] words = data.split(" ");
        	for(String w:words)
       	 {
        		context.write(new Text(w),new LongWritable(1));
       	 }
        }
}

WordCoutReducer

import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
 
 
public class WordCountReducer extends Reducer<Text, LongWritable,Text, LongWritable> {
@Override
protected void reduce(Text k3, Iterable<LongWritable> v3,Context   context) throws IOException,InterruptedException {
        	long  total = 0;
        	for(LongWritable v:v3)
       	 {
        		total+=v.get();
       	 }
        	context.write(k3, new LongWritable(total));
        }
}

对应的使用命令

hadoop jar 1.jar  ch01.WordCountMain  /user/data/input/hamlet.txt  /user/data/output/ch1

hadoop jar 包名   引用主类   输入文件路径  输出文件路径

结果展示

学习链接：

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 hadoop编程之工资序列化排序-CSDN博客

hadoop编程之部门工资求和-CSDN博客

hadoop编程之词频统计-CSDN博客