前言
实现一个手写的WC程序，并打包在集群上运行。
创建一个Maven工程，导入pom
工程目录
导入pom
<?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.zhengkw</groupId>
<artifactId>wordcount</artifactId>
<version>1.0-SNAPSHOT</version>
<dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>RELEASE</version>
</dependency>
<dependency>
<groupId>org.apache.logging.log4j</groupId>
<artifactId>log4j-core</artifactId>
<version>2.8.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-common</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.7.2</version>
</dependency>
<!-- <dependency>
<groupId>jdk.tools</groupId>
<artifactId>jdk.tools</artifactId>
<version>1.8</version>
<scope>system</scope>
<systemPath>${JAVA_HOME}/lib/tools.jar</systemPath>
</dependency>-->
</dependencies>
<build>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>2.3.2</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<!--打包工具，利用maven共计打包成jar -->
<plugin>
<artifactId>maven-assembly-plugin</artifactId>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
<archive>
<manifest>
<mainClass>com.atguigu.mapreduce.WordcountDriver</mainClass>
</manifest>
</archive>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
Mapper
package com.mr.hdfsmapredurce;
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;
/**
* @ClassName:WordcountMapper
* @author: zhengkw
* @description: mapper
* @date: 20/02/24上午 8:42
* @version:1.0
* @since: jdk 1.8
*/
public class WordcountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
Text k = new Text();
IntWritable v = new IntWritable(1);
/**
* @param key
* @param value
* @param context
* @descrption:重写map 实现wordcount
* @return: void
* @date: 20/02/24 上午 8:47
* @author: zhengkw
*/
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
// 1 获取一行
String line = value.toString().trim();
// 2 切割
String[] words = line.split(" ");
// 3 输出
for (String word : words
) {
k.set(word);
//期望输出的是<hadoop,1> --> <string,int>
context.write(k, v);
}
}
}
Reduce
package com.mr.hdfsmapredurce;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
/**
* @ClassName:WordcountRedurce
* @author: zhengkw
* @description: redurce
* @date: 20/02/24上午 8:42
* @version:1.0
* @since: jdk 1.8
*/
public class WordcountReduce extends Reducer<Text, IntWritable, Text, IntWritable> {
int sum;
IntWritable v = new IntWritable();
/**
* @param key
* @param values
* @param context
* @descrption:
* @return: void
* @date: 20/02/24 上午 8:51
* @author: zhengkw
*/
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
// 1 累加求和
for (IntWritable value : values
) {
sum += value.get();
}
// 2 输出
v.set(sum);
context.write(key, v);
}
}
Driver
package com.mr.hdfsmapredurce;
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;
/**
* @descrption:
* @return:
* @date: 20/02/24 上午 8:53
* @author: zhengkw
*/
public class WordcountDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
//1 获取配置信息以及封装任务
Configuration configuration = new Configuration();
//用配置文件反射实例化job对象
Job job = Job.getInstance(configuration);
// 2 设置jar加载路径
job.setJarByClass(WordcountDriver.class);
// 3 设置map和reduce类
job.setMapperClass(WordcountMapper.class);
job.setReducerClass(WordcountReduce.class);
// 4 设置map输出
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
// 5 设置最终输出kv类型
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
// 6 设置输入和输出路径
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
// 7 提交
boolean result = job.waitForCompletion(true);
System.exit(result ? 0 : 1);
}
}
注意！！！
参数是由main中的args[]接收！，测试的时候需要在运行的时候传入参数，参数为pathIN,pathOUT！！
打包在集群上运行
打包后生产2种jar
选择jar
选择jar取决于jar运行的环境中是否有依赖，在集群上执行，集群上有各种依赖，所以可以选择不带依赖的jar！
上传jar到集群并且运行
运行手写的WCjar需要用bin/hadoop jar 后面跟上驱动类的全类名！！！！
准备数据
测试
运行手写的WCjar需要用bin/hadoop jar 后面跟上驱动类的全类名！！！！
运行手写的WCjar需要用bin/hadoop jar 后面跟上驱动类的全类名！！！！
运行手写的WCjar需要用bin/hadoop jar 后面跟上驱动类的全类名！！！！
运行成功
检验
查看结果
总结
- 打包jar在集群上运行可以不选用含依赖的jar包。
- 运行jar包时 hadoop jar 后面跟上自己的驱动类全类名！！很重要，否则会报错，找不到类！
- 程序的参数必须由args数组传递，不能写死！
