嗨，我在使用 Hadoop 分布式缓存时遇到了一些麻烦。我在一个单节点集群（http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-single-node-cluster/）中运行 Hadoop。
我需要将文件传递给每个映射器的问题，我已经阅读了很多 Hadoop 的 DistributedCache，但是直到现在我每次尝试打开本地文件时都没有成功，我得到一个“FileNotFoundException”，我怎么能确定缓存实际上是在处理文件吗？
谢谢你的帮助
这是我的代码：
package br.ufmg.dcc.bigdata.hadoop;
import java.io.IOException;
import java.util.*;
import org.apache.hadoop.filecache.DistributedCache;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import br.ufmg.dcc.bigdata.Result;
import au.com.bytecode.opencsv.CSVReader;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.FileReader;
import java.io.InputStream;
import java.io.ObjectInput;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.StringReader;
import java.io.InputStreamReader;
import java.io.BufferedReader;
import java.net.URI;
import weka.core.Instances;
import weka.classifiers.rules.LAC;
public class Ladoop {
public static class Map extends Mapper<Text, Text, Text, IntWritable> {
//private
private final static IntWritable one = new IntWritable(1);
private LAC classifier;
private Path[] localFiles;
private final static Text missesText = new Text("misses");
private final static Text hitsText = new Text("hits");
protected void setup(Context context) throws IOException, InterruptedException {
FileReader teste = new FileReader("dilma_00.lac"); //error in this line
classifier = new LAC("/home/hduser/dilma_00.lac"); //There is no problem if I force to read the local file
}
public void map(Text key, Text value, Context context) throws IOException, InterruptedException {
String line = value.toString();
try
{
Result result = this.classifier.distributionForInstance(line.split(" "));
context.write(missesText, new IntWritable(result.getMisses()));
context.write(hitsText, new IntWritable(result.getHits()));
} catch (Exception e) {
System.out.println("MAP ERROR");
e.printStackTrace();
}
}
}
public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {
public void reduce(Text key, Iterable<IntWritable> results, Context context)
throws IOException, InterruptedException {
int value = 0;
for (IntWritable result : results) {
value += result.get();
}
System.out.println(value);
context.write(key, new IntWritable(value));
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
Job job = new Job(conf, "Ladoop");
DistributedCache.addCacheFile(new URI("/user/hduser/dilma_00.lac#dilma_00.lac"), conf);
DistributedCache.createSymlink(conf);
job.setJarByClass(Ladoop.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setInputFormatClass(NonSplittableKeyValueTextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.waitForCompletion(true);
}
}
编辑：也尝试过，但没有运气。
protected void setup(Context context) throws IOException, InterruptedException {
Path[] cacheFiles = DistributedCache.getLocalCacheFiles(context.getConfiguration());
FileInputStream fileStream = new FileInputStream(cacheFiles[0].toString());
classifier = new LAC(cacheFiles[0].toString());
}