这不是hadoop所期望的行为。但你可以用 MultipleOutputs 对你有利。创建一个命名的输出，并在所有的reducer中使用它来获得一个文件本身的最终输出。javadoc本身建议如下：

JobConf conf = new JobConf();

 conf.setInputPath(inDir);
 FileOutputFormat.setOutputPath(conf, outDir);

 conf.setMapperClass(MOMap.class);
 conf.setReducerClass(MOReduce.class);
 ...

 // Defines additional single text based output 'text' for the job
 MultipleOutputs.addNamedOutput(conf, "text", TextOutputFormat.class,
 LongWritable.class, Text.class);;
 ...

 JobClient jc = new JobClient();
 RunningJob job = jc.submitJob(conf);

 ...

作业配置使用模式为：

public class MOReduce implements
   Reducer<WritableComparable, Writable> {
 private MultipleOutputs mos;

 public void configure(JobConf conf) {
 ...
 mos = new MultipleOutputs(conf);
 }

 public void reduce(WritableComparable key, Iterator<Writable> values,
 OutputCollector output, Reporter reporter)
 throws IOException {
 ...
 mos.getCollector("text", reporter).collect(key, new Text("Hello"));
 ...
 }

 public void close() throws IOException {
 mos.close();
 ...
 }

 }

如果您使用的是新的 mapreduce 然后看这里。

MultipleOutputs.addNamedOutput(conf, "text", TextOutputFormat.class,
 LongWritable.class, Text.class);

在这里 text 输出目录或单个大文件名为 text ?