这次有人应该取悦 我正在努力使用分布式cahe运行我的代码。我已经在hdfs上有文件，但是当我运行这段代码时：
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.awt.image.Raster;
import java.io.BufferedReader;
import java.io.ByteArrayInputStream;
import java.io.DataInputStream;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.io.InputStreamReader;
import java.net.URISyntaxException;
import java.util.logging.Level;
import java.util.logging.Logger;
import javax.imageio.ImageIO;
import org.apache.hadoop.filecache.*;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.*;
import java.lang.String;
import java.lang.Runtime;
import java.net.URI;
import java.util.StringTokenizer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
public class blur2 {
public static class BlurMapper extends MapReduceBase implements Mapper<Text, BytesWritable, LongWritable, BytesWritable>
{
OutputCollector<LongWritable, BytesWritable> goutput;
int IMAGE_HEIGHT = 240;
int IMAGE_WIDTH = 320;
public BytesWritable Gmiu;
public BytesWritable Gsigma;
public BytesWritable w;
byte[] bytes = new byte[IMAGE_HEIGHT*IMAGE_WIDTH*3];
public BytesWritable emit = new BytesWritable(bytes);
int count = 0;
int initVar = 125;
public LongWritable l = new LongWritable(1);
byte[] byte1 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH];
byte[] byte2 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH];
byte[] byte3 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH];
public void map(Text key, BytesWritable file,OutputCollector<LongWritable, BytesWritable> output, Reporter reporter) throws IOException {
goutput = output;
BufferedImage img = ImageIO.read(new ByteArrayInputStream(file.getBytes()));
Raster ras=img.getData();
DataBufferByte db= (DataBufferByte)ras.getDataBuffer();
byte[] data = db.getData();
if(count==0){
for(int i=0;i<IMAGE_HEIGHT*IMAGE_WIDTH;i++)
{
byte1[i]=20;
byte2[i]=125;
}
Gmiu = new BytesWritable(data);
Gsigma = new BytesWritable(byte1);
w = new BytesWritable(byte2);
count++;
}
else{
byte1 = Gmiu.getBytes();
byte2 = Gsigma.getBytes();
byte3 = w.getBytes();
for(int i=0;i<IMAGE_HEIGHT*IMAGE_WIDTH;i++)
{
byte pixel = data[i];
Double tempmiu=new Double(0.0);
Double tempsig=new Double(0.0);
double temp1=0.0; double alpha = 0.05;
tempmiu = (1-alpha)*byte1[i] + alpha*pixel;
temp1=temp1+(pixel-byte1[i])*(pixel-byte1[i]);
tempsig=(1-alpha)*byte2[i]+ alpha*temp1;
byte1[i] = tempmiu.byteValue();
byte2[i]= tempsig.byteValue();
Double w1=new Double((1-alpha)*byte3[i]+alpha*100);
byte3[i] = w1.byteValue();
}
Gmiu.set(byte1,0,IMAGE_HEIGHT*IMAGE_WIDTH);
Gsigma.set(byte2,0,IMAGE_HEIGHT*IMAGE_WIDTH);
w.set(byte3,0,IMAGE_HEIGHT*IMAGE_WIDTH);
}
byte1 = Gsigma.getBytes();
for(int i=0;i<IMAGE_HEIGHT*IMAGE_WIDTH;i++)
{
bytes[i]=byte1[i];
}
byte1 = Gsigma.getBytes();
for(int i=0;i<IMAGE_HEIGHT*IMAGE_WIDTH;i++)
{
bytes[IMAGE_HEIGHT*IMAGE_WIDTH+i]=byte1[i];
}
byte1 = w.getBytes();
for(int i=0;i<IMAGE_HEIGHT*IMAGE_WIDTH;i++)
{
bytes[2*IMAGE_HEIGHT*IMAGE_WIDTH+i]=byte1[i];
}
emit.set(bytes,0,3*IMAGE_HEIGHT*IMAGE_WIDTH);
}
@Override
public void close(){
try{
goutput.collect(l, emit);
}
catch(Exception e){
e.printStackTrace();
System.exit(-1);
}
}
}
//end of first job , this is running perfectly
public static void main(String[] args) throws URISyntaxException {
if(args.length!=3) {
System.err.println("Usage: blurvideo input output");
System.exit(-1);
}
JobClient client = new JobClient();
JobConf conf = new JobConf(blur2.class);
conf.setOutputValueClass(BytesWritable.class);
conf.setInputFormat(SequenceFileInputFormat.class);
//conf.setNumMapTasks(n)
SequenceFileInputFormat.addInputPath(conf, new Path(args[0]));
TextOutputFormat.setOutputPath(conf, new Path(args[1]));
conf.setMapperClass(BlurMapper.class);
conf.setNumReduceTasks(0);
//conf.setReducerClass(org.apache.hadoop.mapred.lib.IdentityReducer.class);
client.setConf(conf);
try {
JobClient.runJob(conf);
} catch (Exception e) {
e.printStackTrace();
}
// exec("jar cf /home/hmobile/hadoop-0.19.2/imag /home/hmobile/hadoop-0.19.2/output");
JobClient client2 = new JobClient();
JobConf conf2 = new JobConf(blur2.class);
conf2.setOutputValueClass(BytesWritable.class);
conf2.setInputFormat(SequenceFileInputFormat.class);
//conf.setNumMapTasks(n)
SequenceFileInputFormat.addInputPath(conf2, new Path(args[0]));
SequenceFileOutputFormat.setOutputPath(conf2, new Path(args[2]));
conf2.setMapperClass(BlurMapper2.class);
conf2.setNumReduceTasks(0);
DistributedCache.addCacheFile(new URI("~/ayush/output/part-00000"), conf2);// these files are already on the hdfs
DistributedCache.addCacheFile(new URI("~/ayush/output/part-00001"), conf2);
client2.setConf(conf2);
try {
JobClient.runJob(conf2);
} catch (Exception e) {
e.printStackTrace();
}
}
public static class BlurMapper2 extends MapReduceBase implements Mapper<Text, BytesWritable, LongWritable, BytesWritable>
{
int IMAGE_HEIGHT = 240;
int T =60;
int IMAGE_WIDTH = 320;
public BytesWritable Gmiu;
public BytesWritable Gsigma;
public BytesWritable w;
byte[] bytes = new byte[IMAGE_HEIGHT*IMAGE_WIDTH];
public BytesWritable emit = new BytesWritable(bytes);
int initVar = 125;int gg=0;
int K=64;int k=0,k1=0,k2=0;
public LongWritable l = new LongWritable(1);
byte[] Gmiu1 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH*K];
byte[] Gsigma1 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH*K];
byte[] w1 = new byte[IMAGE_HEIGHT*IMAGE_WIDTH*K];
public Path[] localFiles=new Path[2];
private FileSystem fs;
@Override
public void configure(JobConf conf2)
{
try {
fs = FileSystem.getLocal(new Configuration());
localFiles = DistributedCache.getLocalCacheFiles(conf2);
//System.out.println(localFiles[0].getName());
} catch (IOException ex) {
Logger.getLogger(blur2.class.getName()).log(Level.SEVERE, null, ex);
}
}
public void map(Text key, BytesWritable file,OutputCollector<LongWritable, BytesWritable> output, Reporter reporter) throws IOException
{
if(gg==0){
//System.out.println(localFiles[0].getName());
String wrd; String line;
for(Path f:localFiles)
{
if(!f.getName().endsWith("crc"))
{
// FSDataInputStream localFile = fs.open(f);
BufferedReader br = null;
try {
br = new BufferedReader(new InputStreamReader(fs.open(f)));
int c = 0;
try {
while ((line = br.readLine()) != null) {
StringTokenizer itr = new StringTokenizer(line, " ");
while (itr.hasMoreTokens()) {
wrd = itr.nextToken();
c++;
int i = Integer.parseInt(wrd, 16);
Integer I = new Integer(i);
byte b = I.byteValue();
if (c < IMAGE_HEIGHT * IMAGE_WIDTH) {
Gmiu1[k] = b;k++;
} else {
if ((c >= IMAGE_HEIGHT * IMAGE_WIDTH) && (c < 2 * IMAGE_HEIGHT * IMAGE_WIDTH)) {
Gsigma1[k] = b;k1++;
} else {
w1[k] = b;k2++;
}
}
}
}
} catch (IOException ex) {
Logger.getLogger(blur2.class.getName()).log(Level.SEVERE, null, ex);
}
} catch (FileNotFoundException ex) {
Logger.getLogger(blur2.class.getName()).log(Level.SEVERE, null, ex);
} finally {
try {
br.close();
} catch (IOException ex) {
Logger.getLogger(blur2.class.getName()).log(Level.SEVERE, null, ex);
}
}
}
}
gg++;
}
}
}
}
解决了很多问题，任何人都可以告诉我为什么会收到此错误：
java.io.FileNotFoundException: File does not exist: ~/ayush/output/part-00000
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:394)
at org.apache.hadoop.filecache.DistributedCache.getTimestamp(DistributedCache.java:475)
at org.apache.hadoop.mapred.JobClient.configureCommandLineOptions(JobClient.java:676)
at org.apache.hadoop.mapred.JobClient.submitJob(JobClient.java:774)
at org.apache.hadoop.mapred.JobClient.runJob(JobClient.java:1127)
at blur2.main(blur2.java:175)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.util.RunJar.main(RunJar.java:165)
at org.apache.hadoop.mapred.JobShell.run(JobShell.java:54)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:65)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:79)
at org.apache.hadoop.mapred.JobShell.main(JobShell.java:68)
答案 0 :(得分：6)
问题在于您使用的文件名“〜/ ayush / output / part-00000”依赖于Unix shell（sh，bash，ksh）代码扩展以将“〜”替换为主目录的路径名。
Java（以及C和C ++，以及大多数其他编程语言）不做波浪扩展。您需要提供路径名为“/ home / ayush / output / part-00000”...或者倾斜表单扩展为的任何绝对路径名。
严格地说，URI应该按如下方式创建：
new File("/home/ayush/output/part-00000").toURI()
不为
new URI("/home/ayush/output/part-00000")
后者创建一个没有“协议”的URI，这可能会有问题。