使用自定义可写入从Hadoop Map Reduce作业输出列表

Question

我正在尝试通过更改hadoop给出的wordcount示例来创建一个简单的map reduce工作.

我正在尝试列出一个列表而不是一个单词的计数.wordcount示例给出以下输出

hello 2
world 2

我试图将其作为列表输出,这将构成未来工作的基础

hello 1 1
world 1 1

我认为我走在正确的轨道上,但我在编写清单时遇到了麻烦.而不是上述,我得到了

Hello   foo.MyArrayWritable@61250ff2
World   foo.MyArrayWritable@483a0ab1

这是我的MyArrayWritable.我把一个sys放在了,write(DataOuptut arg0)但它从来没有输出任何东西所以我认为这个方法可能不会被调用,我不知道为什么.

class MyArrayWritable extends ArrayWritable{

public MyArrayWritable(Class<? extends Writable> valueClass, Writable[] values) {
    super(valueClass, values);
}
public MyArrayWritable(Class<? extends Writable> valueClass) {
    super(valueClass);
}

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

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

编辑 - 添加更多源代码

public class WordCount {

public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {
    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String line = value.toString();
        StringTokenizer tokenizer = new StringTokenizer(line);
        while (tokenizer.hasMoreTokens()) {
            word.set(tokenizer.nextToken());
            context.write(word, one);
        }
    }
} 

public static class Reduce extends Reducer<Text, IntWritable, Text, MyArrayWritable> {

    public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        ArrayList<IntWritable> list = new ArrayList<IntWritable>();    
        for (IntWritable val : values) {
            list.add(val);
        }
        context.write(key, new MyArrayWritable(IntWritable.class, list.toArray(new IntWritable[list.size()])));
    }
}

public static void main(String[] args) throws Exception {
    if(args == null || args.length == 0)
        args = new String[]{"./wordcount/input","./wordcount/output"};
    Path p = new Path(args[1]);
    FileSystem fs = FileSystem.get(new Configuration());
    fs.exists(p);
    fs.delete(p, true);

    Configuration conf = new Configuration();

    Job job = new Job(conf, "wordcount");
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    job.setMapperClass(Map.class);
    job.setReducerClass(Reduce.class);
    job.setJarByClass(WordCount.class);
    job.setInputFormatClass(TextInputFormat.class);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));

    job.waitForCompletion(true);
}

}

Answer 1

你的reducer中有一个'bug' - 值迭代器在整个循环中重复使用相同的IntWritable,所以你应该将添加到列表中的值包装如下:

public void reduce(Text key, Iterable<IntWritable> values, Context context)
                                      throws IOException, InterruptedException {
    ArrayList<IntWritable> list = new ArrayList<IntWritable>();    
    for (IntWritable val : values) {
        list.add(new IntWritable(val));
    }
    context.write(key, new MyArrayWritable(IntWritable.class, list.toArray(new IntWritable[list.size()])));
}

这实际上不是一个问题,因为你正在使用一个数组列表而你的映射器只输出一个值(一个),但如果你扩展这个代码,可能会让你失望.

您还需要在作业中定义您的地图和减速器输出类型是不同的:

// map output types
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
// reducer output types

job.setOutputValueClass(Text.class);
job.setOutputValueClass(MyArrayWritable.class);

您可能希望显式定义reducers的数量(这可能是您从未看到sysout写入任务日志的原因,尤其是在您的集群管理员已将默认数字定义为0时):

job.setNumReduceTasks(1);

您使用默认的Text输出格式,它在输出键和值对上调用toString() - MyArrayWritable没有重写的toString方法,因此您应该在MyArrayWritable中放置一个:

@Override
public String toString() {
  return Arrays.toString(get());
}

最后write从MyArrayWritable中删除重写的方法 - 这不是与免费的readFields方法兼容的有效实现.你不需要覆盖这个方法但是如果你这样做(比如说你想看一个sysout来验证它被调用),那么就这样做:

@Override
public void write(DataOutput arg0) throws IOException {
  System.out.println("write method called");
  super.write(arg0);
}