Hadoop Eclipse开发环境的建立

package com.kawa.hdfs;

import java.io.InputStream;

import java.net.URL;

import org.apache.hadoop.fs.FsUrlStreamHandlerFactory;

import org.apache.hadoop.io.IOUtils;

/**

 * 使用Hadoop URL操作HDFS

 * @author Administrator

 */

public class HadoopURICatFile {

     //让java虚拟机能够识别HDFS URL

     static {

         URL.setURLStreamHandlerFactory(new FsUrlStreamHandlerFactory());

     }

     public static void main(String[] args) {

         InputStream in = null;

         try {

              in = new URL("hdfs://192.168.74.137:9000/input2/file1.txt").openStream();

              IOUtils.copyBytes(in, System.out, 4096,false);

         } catch (Exception e) {

              // TODO: handle exception

         }finally {

              IOUtils.closeStream(in);

         }

     }

}

package com.kawa.hdfs;

import java.io.IOException;

import java.io.InputStream;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IOUtils;

/**

 * 使用Hadoop FileSystem API进行HDFS的操作

 * @author Administrator

 *   注意：我们在window上面开发程序操作Linux上面的HDFS，默认是以windows当前用户身份进行，因此可能是administrator也可能是其他用户，

 *        而这些用户在hadoop上面一般只有读取权限。如何进行增删改操作呢？

 *        方式一：在windows下创建一个hadoop用户  之后在这个用户下进行玩耍HDFS操作

 *        方式二：对HDFS上面的文件开放权限(eg:hadoop fs -chmod 777 /input2/*)

 */

public class HadoopAPICatFile {

     public static void main(String[] args) throws IOException {

         //1.获取configuration对象

         Configuration conf = new Configuration();

         //第一种方式手动设置默认文件系统 /手动设置Configuration参数

         //conf.set("fs.defaultFS", "hdfs://192.168.74.137:9000");

         //第二种方式 将core-site.xml直接放到src下面 会进行自动加载 无需再进行设置configuration对象了，如果没有则自动加载core-site-default.xml

         //2.获取FileSystem对象

         FileSystem fs = FileSystem.get(conf);

         //3.使用FileSystem对象操作文件

         boolean flag = fs.rename(new Path("/input2/file1.txt"), new Path("/input2/a.txt"));

         if(flag)

              System.out.println("修改成功！");

         else

              System.out.println("修改失败！");

         /*InputStream in = fs.open(new Path("/input2/file2.txt"));

         IOUtils.copyBytes(in, System.out, 4096);

         IOUtils.closeStream(in);*/

     }

}

package com.kawa.mp;

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 {

     //创建Mapper

     public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> {

         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 {

              // Object key, Text value就是输入的key和value, Context记录输入的key和value

              StringTokenizer itr = new StringTokenizer(value.toString());

              while (itr.hasMoreTokens()) {

                   word.set(itr.nextToken());

                   context.write(word, one);

              }

         }

     }

     //创建Reducer

     public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

         private IntWritable result = new IntWritable();

         public void reduce(Text key, Iterable<IntWritable> values, Context context)

                   throws IOException, InterruptedException {

              //reduce函数与map函数基本相同，但value是一个迭代器的形式Iterable<IntWritable> values，也就是说reduce的输入是一个key对应一组的值的value

              int sum = 0;

              for (IntWritable val : values) {

                   sum += val.get();

              }

              result.set(sum);

              context.write(key, result); // 结果例如World, 2

         }

     }

     //配置job

     public static void main(String[] args) throws Exception {

         Configuration conf = new Configuration();

         Job job = Job.getInstance(conf, "word count");// 指定job名称，及运行对象

         job.setJarByClass(WordCount.class);

         job.setMapperClass(TokenizerMapper.class); // 指定map函数

         job.setCombinerClass(IntSumReducer.class); // combiner整合

         job.setReducerClass(IntSumReducer.class);// 设定reduce函数

         job.setOutputKeyClass(Text.class);// 设定输出key数据类型

         job.setOutputValueClass(IntWritable.class);// 设定输出value数据类型

         FileInputFormat.addInputPath(job, new Path(args[0]));// 设定输入目录

         FileOutputFormat.setOutputPath(job, new Path(args[1]));

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

     }

}

./bin/hadoop jar ~/wordcount.jar com.kawa.mp.WordCount /input2/ /output2/wordcount2