1.hadoop-window的安装这里不过多赘述 运行成功之后的结果如下图
2.在idea中新建一个maven项目
pom.xml
<xml version="1.0" encoding="UTF-8">
<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.test</groupId>
<artifactId>wordcount</artifactId>
<version>1.0-SNAPSHOT</version>
<packaging>jar</packaging>
<url>http://maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.8.0</version>
</dependency>
<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>2.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-common</artifactId>
<version>2.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-yarn-client</artifactId>
<version>2.8.0</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-mapreduce-client-core</artifactId>
<version>2.8.0</version>
</dependency>
<dependency>
<groupId>io.netty</groupId>
<artifactId>netty-common</artifactId>
<version>4.1.5.Final</version>
</dependency>
</dependencies>
<build>
<finalName>${project.artifactId}</finalName>
</build>
</project>
新建一个wordcount类
package com.hadoop.wordcount;
import org.apache.hadoop.fs.FileUtil;
import org.apache.hadoop.io.IntWritable;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.util.Iterator;
import java.util.StringTokenizer;
/**
* Created by bee on 8/30/18.
*/
public class WordCount {
public static class TokenizerMapper extends
Mapper<Object, Text, Text, IntWritable> {
public static final IntWritable one = new IntWritable(1);
private Text word = new Text();
public void map(Object key, Text value, Context context)
throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
this.word.set(itr.nextToken());
context.write(this.word, one);
}
}
}
public static class IntSumReduce extends
Reducer<Text, IntWritable, Text, IntWritable> {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable<IntWritable> values,
Context context)
throws IOException, InterruptedException {
int sum = 0;
IntWritable val;
for (Iterator i = values.iterator(); i.hasNext(); sum += val.get()) {
val = (IntWritable) i.next();
}
this.result.set(sum);
context.write(key, this.result);
}
}
public static void main(String[] args)
throws IOException, ClassNotFoundException, InterruptedException {
Configuration conf = new Configuration();
//设置hdfs地址之后就会自动寻找数据然后进行mapreduce操作,输入地址不能自己新建,程序运行会自动创建
String[] otherArgs = new String[]{"hdfs://localhost:9000/input/dream.txt","hdfs://localhost:9000/output/wordcount/"};
/*String[] otherArgs = new String[]{"input/dream.txt","output"};*/
if (otherArgs.length != 2) {
System.err.println("Usage:Merge and duplicate removal <in> <out>");
System.exit(2);
}
Job job = Job.getInstance(conf, "WordCount");
job.setJarByClass(WordCount.class);
job.setMapperClass(WordCount.TokenizerMapper.class);
job.setReducerClass(WordCount.IntSumReduce.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) 0 : 1);
}
}
在hdf地址中创建input文件夹
hadoop fs -mkdir /input
将本地文件dream拷贝到input文件夹下
hadoop fs -put F:\dream.txt /input
点进运行idea中的worcount
运行成功之后
点击之后下载,结果如下
至此wordcount运行完成