使用MapReduce开发WordCount应用程序

package com.hadoop.mapreduce;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
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.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.io.IOException;

/**
* 使用MapReduce开发WordCount应用程序
*/
public class WordCountApp {
/**
* Map:读取输入的文件
* Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT>
*/
public static class MyMapper extends Mapper<LongWritable,Text,Text,LongWritable>{
LongWritable one = new LongWritable(1);

@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//接收到的每一行数据
String line = value.toString();

//按照指定分隔符进行拆分
String[] words = line.split(" ");

for ( String word : words ) {
//通过上下文把map的处理结果输出
context.write(new Text(word),one);
}
}
}
/**
* Reduce: 归并操作
*/
public static class MyReducer extends Reducer<Text,LongWritable,Text,LongWritable>{
@Override
protected void reduce(Text key, Iterable<LongWritable> values, Context context) throws IOException, InterruptedException {

long sum = 0;
for (LongWritable value:values) {
//求key出现的次数总和
sum += value.get();
}

//最终统计结果的输出
context.write(key,new LongWritable(sum));
}
}

/**
* 定义Driver：封装了MapReduce作业的所有信息
* @param args
*/
public static void main(String[] args) throws Exception {

//创建Configuration
Configuration configuration = new Configuration();

//准备清理已存在的输出目录
Path outputPath = new Path(args[1]);
FileSystem fileSystem = FileSystem.get(configuration);
if (fileSystem.exists(outputPath)){
fileSystem.delete(outputPath,true);
System.out.println("output file exists, but is has deleted");
}

//创建Job
Job job = Job.getInstance(configuration, "wordcount");

//设置job的处理类
job.setJarByClass(WordCountApp.class);

//设置作业处理的输入路径
FileInputFormat.setInputPaths(job,new Path(args[0]));

//设置map相关参数
job.setMapperClass(MyMapper.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(LongWritable.class);

//设置reduce相关参数
job.setReducerClass(MyReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(LongWritable.class);

//设置作业处理的输出路径
FileOutputFormat.setOutputPath(job,new Path(args[1]));

System.exit(job.waitForCompletion(true) ? 0 : 1);
}

/**
* 打包：mvn clean package -DskipTests
* 上传到服务器：scp target/hadoop-train.1.0.jar hadoop@hadoop000:~/lib
* 运行：hadoop jar /home/hadoop/lib/hadoop-train-1.0.jar com.imooc.hadoop.mapreduce.WordCountApp
* hdfs://hadoop000:8020/hello.txt hdfs://hadoop000:8020/output/wc
*
* 创建文件：mkdir wc_shell.sh
* hadoop fs -rm -r /output/wc #先删除
* hadoop jar /home/hadoop/lib/hadoop-train-1.0.jar com.imooc.hadoop.mapreduce.WordCountApp
* hdfs://hadoop000:8020/hello.txt hdfs://hadoop000:8020/output/wc
* 增加执行权限：chmod u+x wc_shell.sh
*/

}