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);

        }

    }

}