使用ArrayWritable的序列化似乎以一种有趣的方式工作

Question

我正在使用ArrayWritable,在某些时候我需要检查Hadoop如何序列化ArrayWritable,这是我通过设置得到的job.setNumReduceTasks(0):

0    IntArrayWritable@10f11b8
3    IntArrayWritable@544ec1
6    IntArrayWritable@fe748f
8    IntArrayWritable@1968e23
11    IntArrayWritable@14da8f4
14    IntArrayWritable@18f6235

这是我使用的测试映射器:

public static class MyMapper extends Mapper<LongWritable, Text, LongWritable, IntArrayWritable> {

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        int red = Integer.parseInt(value.toString());
        IntWritable[] a = new IntWritable[100];

        for (int i =0;i<a.length;i++){
            a[i] = new IntWritable(red+i);
        }

        IntArrayWritable aw = new IntArrayWritable();
        aw.set(a);
        context.write(key, aw);
    }
}

IntArrayWritable取自javadoc:ArrayWritable中给出的示例.

import org.apache.hadoop.io.ArrayWritable;
import org.apache.hadoop.io.IntWritable;

public class IntArrayWritable extends ArrayWritable {
    public IntArrayWritable() {
        super(IntWritable.class);
    }
}

我实际上检查了Hadoop的源代码,这对我没有意义. ArrayWritable不应该序列化类名,并且IntWritable不能使用6/7十六进制值序列化100的数组.应用程序实际上似乎工作正常,reducer反序列化正确的值...发生了什么？我错过了什么？

Answer 1

您必须覆盖默认toString()方法.

它被称为TextOutputFormat创建一个人类可读的格式.

尝试以下代码并查看结果:

public class IntArrayWritable extends ArrayWritable {
    public IntArrayWritable() {
        super(IntWritable.class);
    }

    @Override
    public String toString() {
        StringBuilder sb = new StringBuilder();
        for (String s : super.toStrings())
        {
            sb.append(s).append(" ");
        }
        return sb.toString();
    }
}

Answer 2

问题是您从 MapReduce 作业获得的输出不是该数据的序列化版本。它被翻译成漂亮的打印字符串。

当您将化简器的数量设置为零时，您的映射器现在将通过输出格式传递，该输出格式将格式化您的数据，可能将其转换为可读字符串。它不会将其序列化转储出来，就好像它将被减速器拾取一样。