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