Ubuntu中使用终端运行Hadoop程序

liwya

　　接上一篇《Ubuntu Kylin系统下安装Hadoop2.6.0》
　　通过上一篇，Hadoop伪分布式基本配好了。
　　下一步是运行一个MapReduce程序，以WordCount为例：
　　1. 构建实现类：



cd /usr/local/hadoop
mkdir workspace
cd workspace
gedit WordCount.java
　　将代码复制粘贴。



import java.io.IOException;
import java.util.StringTokenizer;
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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class WordCount {
public static class TokenizerMapper
extends Mapper{
private final static 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()) {
word.set(itr.nextToken());
context.write(word, one);
}
}
}
public static class IntSumReducer
extends Reducer {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable values,
Context context
) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = Job.getInstance(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(TokenizerMapper.class);
job.setCombinerClass(IntSumReducer.class);
job.setReducerClass(IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
　　对于代码的具体分析，下一篇再详细讲解。
　　2. 编译
　　(1) 添加JAVA_HOME



　　export JAVA_HOME=/usr/lib/jvm/java-8u5-sun

　　忘记JAVA_HOME的可以使用：



　　echo $JAVA_HOME

　　(2) 将jdk目录下的bin文件夹添加到环境变量



export PATH=$JAVA_HOME/bin:$PATH

　　(3) 将hadoop_classpath添加到环境变量



export HADOOP_CLASSPATH=$JAVA_HOME/lib/tools.jar

　　编译WordCount.java文件



../bin/hadoop com.sun.tools.javac.Main WordCount.java

　　其中com.sun.tools.javac.Main是生成一个编译器的实例
　　上述语句生成三个class: WordCount.class  Reducer.class  TokenizerMapper.class
　　将上述三个class打包成.jar包



jar cf WordCount.jar WordCount*.class

　　生成WordCount.jar
　　3. 运行



bin/hdfs dfs -mkdir /user
bin/hdfs dfs -mkdir /user/hadoop

　　构造输入文件：



bin/hdfs dfs -put etc/hadoop /input

　　其中，etc/hadoop是输入文件，可替换为其他文件



bin/hadoop jar /usr/local/hadoop/workspace/WordCount.jar /input /output

　　查看运行结果



bin/hdfs dfs -cat /output/*
　　4. 结束Hadoop



sbin/stop-dfs.sh