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);
        }
    }
}