1、将wordcount.txt文本文件上传到/data/目录下,wordcount.txt文件内容如下:
red black green yellow
red blue blue
black big small small yellow
red red red red
blue
2、创建一个java maven工程,pom.xml中添加hdfs、mapreduce的引用,如下
<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/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.che</groupId>
<artifactId>demo</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<name>demo</name>
<url>http://maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.7.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.7.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.7.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.0</version>
</dependency>
</dependencies>
</project>
3、代码如下:
3.1 WordCount Mapper实现类WordCountMapper.java
package com.che.demo.mapreduce;
import java.io.IOException;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
/**
* WordCount Mapper实现类
*/
public class WordCountMapper extends Mapper<LongWritable, Text,Text,LongWritable> {
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
// 将Text类型的value 转换成 string
String datas = value.toString();
// 将这一行用 " " 切分出各个单词
String[] words = datas.split(" ");
for (String word : words) {
context.write(new Text(word),new LongWritable(1));
}
}
}
3.2 WordCount Reducer实现类WordCountReducer.java
package com.che.demo.mapreduce;
import java.io.IOException;
import java.util.Iterator;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
/**
* WordCount Reducer实现类
*/
public class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable>{
@Override
protected void reduce(Text word, Iterable<IntWritable> valuesIterator,Context context)throws IOException, InterruptedException {
int count=0;
//统计单词数量
Iterator<IntWritable> iterator = valuesIterator.iterator();
while(iterator.hasNext()){
iterator.next();
count++;
}
context.write(word, new IntWritable(count));
}
}
3.3 WordCount Main方法实现类WordCountJob.java
package com.che.demo.mapreduce;
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;
import java.io.IOException;
/**
* WordCount Main方法实现类
*/
public class WordCountJob {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
Job wcjob = Job.getInstance(conf);
wcjob.setJarByClass(WordCountJob.class);
wcjob.setMapperClass(WordCountMapper.class);
wcjob.setReducerClass(WordCountReducer.class);
wcjob.setMapOutputKeyClass(Text.class);
wcjob.setMapOutputValueClass(LongWritable.class);
wcjob.setMapOutputKeyClass(Text.class);
wcjob.setOutputValueClass(LongWritable.class);
//指定要处理的数据所在的位置
FileInputFormat.setInputPaths(wcjob,"/user/che/1021001/input");
//指定处理完成之后的结果所保存的位置
FileOutputFormat.setOutputPath(wcjob, new Path("/user/che/1021001/output"));
// 向yarn集群提交这个job
boolean res = wcjob.waitForCompletion(true);
System.out.println(res?0:1);
}
}
3.4 在eclipse中将项目工程打成一个jar包,操作如下图
然后工程target目录就会多出一个jar文件如下图
3.5 将demo-0.0.1-SNAPSHOT.jar重命名为demo.jar后,上传到centos7上的/data/目录下
3.6 将centos7中的/data/wordcount.txt文件上传hdfs上的/user/che/1021001/input目录下
hdfs dfs -put /data/wordcount.txt /user/che/1021001/input
3.7 使用hadoop jar命令执行
hadoop jar /data/demo.jar com.che.demo.mapreduce.WordCountJob