我使用的是hadoop版本2.6.4。我正在写一个mapreduce作业，它需要3个参数，即关键字、输入文件路径和输出文件。我的理想输出应该是包含关键字的所有文件的名称。简单的逻辑是遍历文本中的每一行并将其与关键字匹配。如果返回true，则打印文件名。
在大量的google搜索之后，我找到了3个获取文件名的选项
Context.getConfiguration().get("map.input.file") Context.getConfiguration().get("mapreduce.map.input.file") 两个方法都返回一个值为“null”的字符串，即它们在终端屏幕上打印“null”。
最后我在site.google.com上试了一下

public Path filesplit;
filesplit=((FileSplit)context.getInputSplit()).getPath();
System.out.println(filesplit.getName())

上述方法产生了一个错误。终端输出如下：-

java.lang.Exception: java.lang.ClassCastException: org.apache.hadoop.mapreduce.lib.input.FileSplit cannot be cast to org.apache.hadoop.mapred.FileSplit
    at org.apache.hadoop.mapred.LocalJobRunner$Job.runTasks(LocalJobRunner.java:462)
    at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:522)
Caused by: java.lang.ClassCastException: org.apache.hadoop.mapreduce.lib.input.FileSplit cannot be cast to org.apache.hadoop.mapred.FileSplit
    at org.myorg.DistributedGrep$GrepMapper.map(DistributedGrep.java:23)
    at org.myorg.DistributedGrep$GrepMapper.map(DistributedGrep.java:1)
    at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:145)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:784)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
    at org.apache.hadoop.mapred.LocalJobRunner$Job$MapTaskRunnable.run(LocalJobRunner.java:243)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
    at java.util.concurrent.FutureTask.run(FutureTask.java:262)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

有人能提出纠正这些错误的方法吗？可能出了什么问题？我有什么错误吗？
或者您对获取在Map器上执行的当前行的文件名有其他想法吗。
如果你想在这里有一个完整的代码看看

package org.myorg;

import java.io.*;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.FileSplit;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class DistributedGrep {

    public static class GrepMapper extends
            Mapper<Object, Text, NullWritable, Text> {
        public  Path filesplit;

        public void map(Object key, Text value, Context context)
                throws IOException, InterruptedException {
            filesplit = ((FileSplit)context.getInputSplit()).getPath();

            String txt = value.toString();
            String mapRegex = context.getConfiguration().get("mapregex");
//          System.out.println(context.getConfiguration().get("mapreduce.map.input.file");
            System.out.println(filesplit.getName());
            if (txt.matches(mapRegex)) {
                System.out.println("Matched a line");
                context.write(NullWritable.get(), value);
            }
        }
    }

    public static void main(String[] args) throws Exception {

        Configuration conf = new Configuration();

        conf.set("mapregex", args[0]);

        Job job = new Job(conf, "Distributed Grep");
        job.setJarByClass(DistributedGrep.class);
        job.setMapperClass(GrepMapper.class);
        job.setOutputKeyClass(NullWritable.class);
        job.setOutputValueClass(Text.class);
        job.setNumReduceTasks(0); // Set number of reducers to zero
        FileInputFormat.addInputPath(job, new Path(args[1]));
        FileOutputFormat.setOutputPath(job, new Path(args[2]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}