hadoop - Iterar a través de ArrayWritable-NoSuchMethodException

mapreduce iteration

Question

Empecé a trabajar con MapReduce y me encontré con un error extraño que no he podido responder a través de Google. Estoy haciendo un programa básico usando ArrayWritable, pero cuando lo ejecuto, aparece el siguiente error durante la reducción:

java.lang.RuntimeException:
java.lang.NoSuchMethodException:org.apache.hadoop.io.ArrayWritable.<init>()
at org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:115)
at org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:62)
at org.apache.hadoop.io.serializer.WritableSerialization$WritableDeserializer.deserialize(WritableSerialization.java:40)
at org.apache.hadoop.mapred.Task$ValuesIterator.readNextValue(Task.java:1276)
at org.apache.hadoop.mapred.Task$ValuesIterator.next(Task.java:1214)
at org.apache.hadoop.mapred.ReduceTask$ReduceValuesIterator.moveToNext(ReduceTask.java:250)
at org.apache.hadoop.mapred.ReduceTask$ReduceValuesIterator.next(ReduceTask.java:246)
at PageRank$Reduce.reduce(Unknown Source)
at PageRank$Reduce.reduce(Unknown Source)
at org.apache.hadoop.mapred.ReduceTask.runOldReducer(ReduceTask.java:522)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:421)
at org.apache.hadoop.mapred.Child$4.run(Child.java:255)

Estoy usando Hadoop 1.2.1. Aquí está mi código:

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapred.join.*;
import java.io.IOException;
import java.util.Iterator;
public class TempClass {
public static class MapClass extends MapReduceBase
implements Mapper<LongWritable, Text, Text, ArrayWritable> {
public void map(LongWritable key, Text value,
OutputCollector<Text, ArrayWritable> output,
Reporter reporter) throws IOException {
String[] arr_str = new String[]{"a","b","c"};
for(int i=0; i<3; i++)
output.collect(new Text("my_key"), new ArrayWritable(arr_str));
}
}
public static class Reduce extends MapReduceBase
implements Reducer<Text, ArrayWritable, Text, ArrayWritable> {
public void reduce(Text key, Iterator<ArrayWritable> values,
OutputCollector<Text, ArrayWritable> output,
Reporter reporter) throws IOException {
ArrayWritable tmp;
while(values.hasNext()){
tmp = values.next();
output.collect(key, tmp);
}
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
JobConf job = new JobConf(conf, TempClass.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(ArrayWritable.class);
job.setOutputFormat(TextOutputFormat.class);
job.setInputFormat(TextInputFormat.class);
job.setMapperClass(MapClass.class);
job.setReducerClass(Reduce.class);
FileInputFormat.setInputPaths( job, new Path( args[0] ) );
FileOutputFormat.setOutputPath( job, new Path( args[1] ) );
job.setJobName( "TempClass" );
JobClient.runJob(job);
}
}

Si hago un comentario debajo de las líneas (Reducir clase):

 //while(values.hasNext()){
// tmp = values.next();
output.collect(key, tmp);
//}

todo estará bien. ¿Tienes alguna idea?

Answer 1

A Escribir para matrices que contienen instancias de una clase. Los elementos de este permiso de escritura deben ser todos ejemplos de la misma clase. Si esto de escritura será la entrada para un Reducer, necesitará crear una subclase que establezca que el valor sea del tipo apropiado. Por ejemplo: la clase pública IntArrayWritable extiende ArrayWritable {public IntArrayWritable () {super (IntWritable.class); }}

Aquí está el documento de ArrayWritable . En general, Writable debe tener un constructor sin parámetro.

Acabo de modificar tu código para:

import java.io.IOException;
import java.util.Iterator;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.ArrayWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
public class TempClass {
public static class TextArrayWritable extends ArrayWritable {
public TextArrayWritable() {
super(Text.class);
}
public TextArrayWritable(String[] strings) {
super(Text.class);
Text[] texts = new Text[strings.length];
for (int i = 0; i < strings.length; i++) {
texts[i] = new Text(strings[i]);
}
set(texts);
}
}
public static class MapClass extends MapReduceBase implements
Mapper<LongWritable, Text, Text, ArrayWritable> {
public void map(LongWritable key, Text value,
OutputCollector<Text, ArrayWritable> output, Reporter reporter)
throws IOException {
String[] arr_str = new String[] {
"a", "b", "c" };
for (int i = 0; i < 3; i++)
output.collect(new Text("my_key"), new TextArrayWritable(
arr_str));
}
}
public static class Reduce extends MapReduceBase implements
Reducer<Text, TextArrayWritable, Text, TextArrayWritable> {
public void reduce(Text key, Iterator<TextArrayWritable> values,
OutputCollector<Text, TextArrayWritable> output,
Reporter reporter) throws IOException {
TextArrayWritable tmp;
while (values.hasNext()) {
tmp = values.next();
output.collect(key, tmp);
}
}
}
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
JobConf job = new JobConf(conf, TempClass.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(TextArrayWritable.class);
job.setOutputFormat(TextOutputFormat.class);
job.setInputFormat(TextInputFormat.class);
job.setMapperClass(MapClass.class);
job.setReducerClass(Reduce.class);
FileInputFormat.setInputPaths(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
job.setJobName("TempClass");
JobClient.runJob(job);
}
}