mapreduce实验

 

 

 

 

 

 代码：

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/mymapreduce1/in/buyer_favorite1");  
        Path out = new Path("hdfs://localhost:9000/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);  
        }  
    }  
}