mapreduce课堂测试

源代码如下：

package mapreduce;  
import java.io.IOException;  
import java.util.StringTokenizer;  
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 void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {  
        Job job = Job.getInstance();  
        job.setJobName("WordCount");  
        job.setJarByClass(WordCount.class);  
        job.setMapperClass(doMapper.class);  
        job.setReducerClass(doReducer.class);  
        job.setOutputKeyClass(Text.class);  
        job.setOutputValueClass(IntWritable.class);  
        Path in = new Path("hdfs://localhost:9000/user/hadoop/mymapreduce1/in/buyer_favorite1.txt");  
        Path out = new Path("hdfs://localhost:9000/user/hadoop/mymapreduce1/out");  
        FileInputFormat.addInputPath(job, in);  
        FileOutputFormat.setOutputPath(job, out);  
        System.exit(job.waitForCompletion(true) ? 0 : 1);  
    }  
    public static class doMapper extends Mapper<Object, Text, Text, IntWritable>{  
        public static final IntWritable one = new IntWritable(1);  
        public static Text word = new Text();  
        @Override  
        protected void map(Object key, Text value, Context context)  
                    throws IOException, InterruptedException {  
            StringTokenizer tokenizer = new StringTokenizer(value.toString(), " ");  
                word.set(tokenizer.nextToken());  
                context.write(word, one);  
        }  
    }  
    public static class doReducer extends Reducer<Text, IntWritable, Text, IntWritable>{  
        private IntWritable result = new IntWritable();  
        @Override  
        protected void reduce(Text key, Iterable<IntWritable> values, Context context)  
        throws IOException, InterruptedException {  
        int sum = 0;  
        for (IntWritable value : values) {  
        sum += value.get();  
        }  
        result.set(sum);  
        context.write(key, result);  
        }  
    }  
}  

这里在运行时需要用到一个名为：hadoop-eclipse-plugin-2.8.3.jar 的插件。通过它可以也可以观看hdfs中的文件情况！如下图：

但是并不能通过这个插件来添加或修改文件，本人是通过shell命令来向hdfs中添加文件的。

数据文件的部分内容如下：

 运行截图如下：

 

 注意：

1.操作hdfs和运行程序前一定要把hadoop开启。

2.本人无法通过浏览器访问localhost：50070，但是并不影响通过shell命令对hdfs的文件操作。

3.在命令行输入  jps 命令应该显示如下几个进程：

 缺一不可。