window下eclipse配制hadoop插件 （四）

1.把插件hadoop-eclipse-plugin-2.6.2.jar拷贝到eclipse安装目录下的plugins中

2.重启一下Eclipse

配制hadoop

3.进入map/reduce视图模式

4.向hadoop分布式存储系统中存入数据

5.连接hadoop

6.创建hadoop工程

7.创建类MyWordCount.java

package com.yc.hadoop;
import java.io.IOException;
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 MyWordCount {
          public static class MyWordCountMapper 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 {
                      String[] words = value.toString().split("\\s");
                      for (String w : words) {
                            word.set(w);
                            context.write(word, one);
                      }
                }
          }

          public static class MyWordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
                private IntWritable result = new IntWritable();
                public void reduce(Text key, Iterable<IntWritable> 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, "mywordcount");
                job.setJarByClass(MyWordCount.class);
                job.setMapperClass(MyWordCountMapper.class);
                job.setCombinerClass(MyWordCountReducer.class);
                job.setReducerClass(MyWordCountReducer.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);
          }
    }

8.运行hadoop项目