Hadoop上传、下载以及word count简单示例

首先看一个hadoop自带的example

1.启动 start-dfs.sh 

启动start-yarn.sh

2.输入http://hadoop-0000:50070/，查看HDFS

 

3.  上传一个文件，比如JDK

hadoop fs -put jdk-8u77-linux-x64.tar.gz hdfs://hadoop-0000:9000/

 

4.查看HDFS

5.下载一个文件

hadoop fs -get hdfs://hadoop-0000:9000/jdk-8u77-linux-x64.tar.gz

 

6. 创建两个目录

hadoop fs -mkdir /wordcount
hadoop fs -mkdir /wordcount/input

 

7.新建一个文件，输入一些数据，保存

上传

hadoop fs -put wordcount.txt /wordcount/input

 
8.测试wordcount

hadoop jar hadoop-mapreduce-examples-2.6.4.jar wordcount /wordcount/input /wordcount/output

 

9.查看输出

hadoop fs -ls /wordcount/output

 
 

10.查看结果

hadoop fs -cat /wordcount/output/part-r-00000

 

接着自己实现一个word count的简单示例

Maven Dependency

<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>org.fool.hadoop</groupId>
	<artifactId>hadoop</artifactId>
	<version>0.0.1-SNAPSHOT</version>
	<packaging>jar</packaging>

	<name>hadoop</name>
	<url>http://maven.apache.org</url>

	<properties>
		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
		<hadoop.version>2.6.4</hadoop.version>
	</properties>

	<dependencies>
		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-common</artifactId>
			<version>${hadoop.version}</version>
		</dependency>

		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-hdfs</artifactId>
			<version>${hadoop.version}</version>
		</dependency>

		<dependency>
			<groupId>org.apache.hadoop</groupId>
			<artifactId>hadoop-client</artifactId>
			<version>${hadoop.version}</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>

		<dependency>
			<groupId>junit</groupId>
			<artifactId>junit</artifactId>
			<version>4.12</version>
			<scope>test</scope>
		</dependency>
	</dependencies>

	<build>
		<plugins>
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-compiler-plugin</artifactId>
				<version>3.5.1</version>
				<configuration>
					<source>1.8</source>
					<target>1.8</target>
				</configuration>
			</plugin>

			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-surefire-plugin</artifactId>
				<version>2.19.1</version>
				<configuration>
					<skip>true</skip>
				</configuration>
			</plugin>

			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-assembly-plugin</artifactId>
				<version>2.6</version>
				<configuration>
					<appendAssemblyId>false</appendAssemblyId>
					<descriptorRefs>
						<descriptorRef>jar-with-dependencies</descriptorRef>
					</descriptorRefs>
					<archive>
						<manifest>
							<mainClass>org.fool.hadoop.mapred.WordCountJob</mainClass>
						</manifest>
					</archive>
				</configuration>
				<executions>
					<execution>
						<id>make-assembly</id>
						<phase>package</phase>
						<goals>
							<goal>assembly</goal>
						</goals>
					</execution>
				</executions>
			</plugin>
		</plugins>
	</build>
</project>

 

WordCountMapper.java

package org.fool.hadoop.mapred;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

import com.google.common.base.Splitter;

public class WordCountMapper extends Mapper<LongWritable, Text, Text, LongWritable> {
	@Override
	protected void map(LongWritable key, Text value, Mapper<LongWritable, Text, Text, LongWritable>.Context context)
			throws IOException, InterruptedException {

		String line = value.toString();
		
		Iterable<String> words = Splitter.on(" ").split(line);
		
		for (String word : words) {
			context.write(new Text(word), new LongWritable(1));
		}
	}
}

 

WordReducer.java

package org.fool.hadoop.mapred;

import java.io.IOException;

import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class WordCountReducer extends Reducer<Text, LongWritable, Text, LongWritable> {

	@Override
	protected void reduce(Text key, Iterable<LongWritable> values,
			Reducer<Text, LongWritable, Text, LongWritable>.Context context) throws IOException, InterruptedException {

		long count = 0;
		
		for (LongWritable value : values) {
			count += value.get();
		}
		
		context.write(key, new LongWritable(count));
	}
}

 

WordCountJob.java

package org.fool.hadoop.mapred;

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;

public class WordCountJob {
	public static void main(String[] args) throws Exception {
		Configuration conf = new Configuration();

		Job job = Job.getInstance(conf);

		job.setJarByClass(WordCountJob.class);

		job.setMapperClass(WordCountMapper.class);
		job.setReducerClass(WordCountReducer.class);

		job.setMapOutputKeyClass(Text.class);
		job.setMapOutputValueClass(LongWritable.class);

		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(LongWritable.class);

		FileInputFormat.setInputPaths(job, new Path("hdfs://hadoop-0000:9000/wc/input"));
		FileOutputFormat.setOutputPath(job, new Path("hdfs://hadoop-0000:9000/wc/output"));

		job.waitForCompletion(true);
	}
}

 

 写完之后，maven install打成一个JAR包，上传到Linux，接着创建两个目录，上传一个source

 

运行如下命令

hadoop jar hadoop-0.0.1-SNAPSHOT.jar

神奇的事情发生了

 

最后，查看输出结果