mapreduce编程实例——wordcount

package com.leokadia.mapreduce.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;
/**
* KEYIN, map阶段输入的key的类型：LongWritable
* VALUEIN,map阶段输入value类型：Text
* KEYOUT,map阶段输出的Key类型：Text
* VALUEOUT,map阶段输出的value类型：IntWritable
*/
public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
private Text outK = new Text();
private IntWritable outV = new IntWritable(1);
//map阶段不进行聚合
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
// 1 获取一行 
String line = value.toString();
// 2 切割(取决于原始数据的中间分隔符) 
String[] words = line.split(" ");
// 3 循环写出
for (String word : words) {
// 封装outk
outK.set(word);
// 写出
context.write(outK, outV);
}
}
}

package com.leokadia.mapreduce.wordcount;
/**
* @author sa
* @create 2021-05-05 10:47
*/
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
/**
* KEYIN, reduce阶段输入的key的类型：Text
* VALUEIN,reduce阶段输入value类型：IntWritable
* KEYOUT,reduce阶段输出的Key类型：Text
* VALUEOUT,reduce阶段输出的value类型：IntWritable
*/
public class WordCountReducer extends Reducer<Text, IntWritable,Text,IntWritable> {
private IntWritable outV = new IntWritable();
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
// xxxxxxx xxxxxxx ->(xxxxxxx,1),(xxxxxxx,1)
// xxxxxxx, (1,1)
// 将values进行累加
for (IntWritable value : values) {
sum += value.get();
}
outV.set(sum);
// 写出
context.write(key,outV);
}
}

package com.leokadia.mapreduce.wordcount;
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 WordCountDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
// 1 获取job
Configuration conf = new Configuration();
Job job = Job.getInstance(conf);
// 2 设置jar包路径
job.setJarByClass(WordCountDriver.class);
// 3 关联mapper和reducer
job.setMapperClass(WordCountMapper.class);
job.setReducerClass(WordCountReducer.class);
// 4 设置map输出的kv类型
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
// 5 设置最终输出的kV类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
// 6 设置输入路径和输出路径
FileInputFormat.setInputPaths(job, new Path("D:\input\inputword"));
FileOutputFormat.setOutputPath(job, new Path("D:\hadoop\output888"));
// 7 提交job
boolean result = job.waitForCompletion(true);
System.exit(result ? 0 : 1);
}
}

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