MapReduce 输出 ArrayWritable

Question

我正在尝试从一个简单的 MapReduce 任务中的 ArrayWritable 获取输出。我发现了几个有类似问题的问题，但我无法在自己的代码中解决问题。所以我期待着你的帮助。谢谢:)！

输入： 带有句子的文本文件。

输出应该是：

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

我在作业中得到的输出是：

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

我认为问题出在 IntArrayWritable 的子类中，但我没有得到正确的更正来解决这个问题。顺便说一句，我们有 Hadoop 2.5，我使用以下代码得到这个结果：

主要方法：

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);
}

映射器：

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);
        }
    }
}

减速器：

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()));
    }
}

子类

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);
        }
    }
}

我使用以下链接找到解决方案：

我真的很感谢任何想法！

--------解决方案--------

新子类：

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();
    }
}

新的减少方法：

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));
}

Answer 1

一切看起来都很完美。只需要在子类中再编写一个方法 printStrings() 即可 return 是一个字符串而不是数组。在内置的 toString() 中将 return 字符串数组，这就是它在输出中给出地址而不是值的原因。

public String printStrings() {
     String strings = "";
        for (int i = 0; i < values.length; i++) {
         strings = strings + " "+ values[i].toString();
       }
      return strings;
    }

MapReduce 输出 ArrayWritable

MapReduce Output ArrayWritable

java

apache

hadoop

mapreduce

writable