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wordcount在mapreduce的例子

news 来源：原创 2025/5/13 8:14:34

1.启动集群

2.创建项目

项目结构为：

3.pom.xml文件为

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"><modelVersion>4.0.0</modelVersion><groupId>org.example</groupId><artifactId>mapReduceTest</artifactId><packaging>war</packaging><version>1.0-SNAPSHOT</version><name>mapReduceTest Maven Webapp</name><url>http://maven.apache.org</url><dependencies><dependency><groupId>junit</groupId><artifactId>junit</artifactId><version>3.8.1</version><scope>test</scope></dependency><dependency><groupId>org.apache.logging.log4j</groupId><artifactId>log4j-slf4j-impl</artifactId><version>2.12.0</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-common</artifactId><version>3.1.3</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-hdfs</artifactId><version>3.1.3</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-mapreduce-client-core</artifactId><version>3.1.3</version></dependency><dependency><groupId>org.apache.hadoop</groupId><artifactId>hadoop-client</artifactId><version>3.1.3</version><exclusions><!-- d Log4j 1.x --><exclusion><groupId>log4j</groupId><artifactId>log4j</artifactId></exclusion><!-- d SLF4J  Log4j 1.x e¥ --><exclusion><groupId>org.slf4j</groupId><artifactId>slf4j-log4j12</artifactId></exclusion></exclusions></dependency></dependencies><build><finalName>mapReduceTest</finalName></build>
</project>

4.WordCountMapper代码为

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;public class WordCountMapper extends Mapper<LongWritable,Text,Text,IntWritable> {@Overrideprotected 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 IntWritable(1));}}}

5.WordCountReduce代码为：

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

6.WordCountMain代码为：

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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.Job;public class WordCountMain {public static void main(String[] args) throws Exception {Job job = Job.getInstance(new Configuration());job.setJarByClass(WordCountMain.class);job.setMapperClass(WordCountMapper.class);job.setMapOutputKeyClass(Text.class);job.setMapOutputValueClass(IntWritable.class);job.setReducerClass(WordCountReduce.class);job.setOutputKeyClass(Text.class);job.setOutputValueClass(IntWritable.class);FileInputFormat.setInputPaths(job, new Path("hdfs://172.18.0.2:9000/input"));FileOutputFormat.setOutputPath(job, new Path("hdfs://172.18.0.2:9000/WordCountOutput"));job.waitForCompletion(true);}
}