Matriz de saída MapReduceWritable

Estou tentando obter uma saída de um ArrayWritable em um simples MapReduce-Task. Encontrei algumas perguntas com um problema semelhante, mas não consigo resolver o problema no meu próprio código. Então, estou ansioso por sua ajuda. Obrigado :)!

Entrada: Arquivo de texto com alguma frase.

Resultado deveria estar:

<Word, <length, number of same words in Textfile>>
 Example: Hello  5  2 

A saída que recebo no meu trabalho é:

hello WordLength_V01$IntArrayWritable@221cf05
test WordLength_V01$IntArrayWritable@799e525a

Acho que o problema está na subclasse de IntArrayWritable, mas não recebo a correção correta para corrigir isso. Pelo que temos Hadoop 2.5. Eu uso o seguinte código para obter este resultado:

Método principal:

public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "word length V1");

    // Set Classes
    job.setJarByClass(WordLength_V01.class);
    job.setMapperClass(MyMapper.class);
    // job.setCombinerClass(MyReducer.class);
    job.setReducerClass(MyReducer.class);

    // Set Output and Input Parameters
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(IntWritable.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntArrayWritable.class);

    // Number of Reducers
    job.setNumReduceTasks(1);

    // Set FileDestination
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));

    System.exit(job.waitForCompletion(true) ? 0 : 1);
}

Mapeador:

public static class MyMapper extends Mapper<Object, Text, Text, IntWritable> {

    // Initialize Variables
    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    // Map Method
    public void map(Object key, Text value, Context context) throws IOException, InterruptedException {

        // Use Tokenizer
        StringTokenizer itr = new StringTokenizer(value.toString());

        // Select each word
        while (itr.hasMoreTokens()) {
            word.set(itr.nextToken());

            // Output Pair
            context.write(word, one);
        }
    }
}

Redutor:

public static class MyReducer extends Reducer<Text, IntWritable, Text, IntArrayWritable> {

    // Initialize Variables
    private IntWritable count = new IntWritable();
    private IntWritable length = new IntWritable();

    // Reduce Method
    public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {

        // Count Words
        int sum = 0;
        for (IntWritable val : values) {
            sum += val.get();
        }

        count.set(sum);

        // Wordlength
        length.set(key.getLength());

        // Define Output
        IntWritable[] temp = new IntWritable[2];
        IntArrayWritable output = new IntArrayWritable(temp);

        temp[0] = count;
        temp[1] = length;

        // Output
        output.set(temp);
        context.write(key, new IntArrayWritable(output.get()));
    }
}

Subclasse

public static class IntArrayWritable extends ArrayWritable {
    public IntArrayWritable(IntWritable[] intWritables) {
        super(IntWritable.class);
    }

    @Override
    public IntWritable[] get() {
        return (IntWritable[]) super.get();
    }

    @Override
    public void write(DataOutput arg0) throws IOException {
        for(IntWritable data : get()){
            data.write(arg0);
        }
    }
}   

Usei os seguintes links para encontrar uma solução:

Gravável na interface (hadoop.apache.org)Classe ArrayWritable (hadoop.apache.org)stackoverflow.com (1)stackoverflow.com (2)

Sou muito grato por qualquer ideia!

-------- Solução --------

Nova subclasse:

public static class IntArrayWritable extends ArrayWritable {

    public IntArrayWritable(IntWritable[] values) {
        super(IntWritable.class, values);
    }

    @Override
    public IntWritable[] get() {
        return (IntWritable[]) super.get();
    }

    @Override
    public String toString() {
        IntWritable[] values = get();
        return values[0].toString() + ", " + values[1].toString();
    }
}

Novo método de redução:

public void reduce(Text key, Iterable<IntWritable> values,
            Context context) throws IOException, InterruptedException {

        // Count Words
        int sum = 0;
        for (IntWritable val : values) {
            sum += val.get();
        }

        count.set(sum);

        // Wordlength
        length.set(key.getLength());

        // Define Output
        IntWritable[] temp = new IntWritable[2];
        temp[0] = count;
        temp[1] = length;

        context.write(key, new IntArrayWritable(temp));
}

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