This took me a full read through to figure out. The problem is that
you're using your reducer as a combiner and when it runs, the output
of the map stage then becomes the wrong type.
In pseudo-visual-speak:
Object, Int -> Map() -> MyText, Int -> Combine() -> YourText, Int -> EXCEPTION!
When using your reducer as a combiner, the reducer outputs *must*
match the map outputs. In other words, your combiner - which is
*optional* in the chain at Hadoop's pleasure - is changing the key
space. That's a no-no. In your case, you can't reuse your reducer as a
combiner.
(The hint is in the exception: it's occurring in the combiner classes
in Hadoop.)
Hope that helps.
On Fri, Jun 18, 2010 at 2:09 PM, Steve Lewis <lordjoe2...@gmail.com> wrote:
>
> This class is a copy of a standard WordCount class with one critical
> exception
> Instead of the Mapper Emitting a Key of Type Text it emits a key of type
> MyText - s simple subclass of Text
> The reducer emits a different subclass of Text - YourText
> I say
> job.setMapOutputKeyClass(MyText.class);
> job.setMapOutputValueClass(IntWritable.class);
> job.setOutputKeyClass(YourText.class);
> job.setOutputValueClass(IntWritable.class);
> which should declare these classes directly and yet I get the following
> exception using hadoop 0.2 on a local box
> What am I doing wrong
>
> java.io.IOException: wrong key class: class
> org.systemsbiology.hadoop.CapitalWordCount$YourText is not class
> org.systemsbiology.hadoop.CapitalWordCount$MyText
> at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:164)
> at
> org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:880)
> at
> org.apache.hadoop.mapred.Task$NewCombinerRunner$OutputConverter.write(Task.java:1201)
> at
> org.apache.hadoop.mapreduce.TaskInputOutputContext.write(TaskInputOutputContext.java:80)
> at
> org.systemsbiology.hadoop.CapitalWordCount$IntSumReducer.reduce(CapitalWordCount.java:89)
>
> package org.systemsbiology.hadoop;
> import com.lordjoe.utilities.*;
> import org.apache.hadoop.conf.*;
> import org.apache.hadoop.fs.*;
> import org.apache.hadoop.io.*;
> import org.apache.hadoop.mapreduce.*;
> import org.apache.hadoop.mapreduce.lib.input.*;
> import org.apache.hadoop.mapreduce.lib.output.*;
> import org.apache.hadoop.util.*;
> import java.io.*;
> import java.util.*;
> /**
> * org.systemsbiology.hadoop.CapitalWordCount
> */
> public class CapitalWordCount {
> public static class YourText extends Text
> {
> public YourText() {
> }
> /**
> * Construct from a string.
> */
> public YourText(final String string) {
> super(string);
> }
> }
> public static class MyText extends Text
> {
> public MyText() {
> }
> /**
> * Construct from a string.
> */
> public MyText(final String string) {
> super(string);
> }
>
> }
> public static class TokenizerMapper
> extends Mapper<Object, Text, MyText, IntWritable> {
> private final static IntWritable one = new IntWritable(1);
> private MyText word = new MyText();
> public void map(Object key, Text value, Context context
> ) throws IOException, InterruptedException {
> StringTokenizer itr = new StringTokenizer(value.toString());
> while (itr.hasMoreTokens()) {
> String s = itr.nextToken().toUpperCase();
> s = dropNonLetters(s);
> if (s.length() > 0) {
> word.set(s);
> context.write(word, one);
> }
> }
> }
> }
> public static String dropNonLetters(String s) {
> StringBuilder sb = new StringBuilder();
> for (int i = 0; i < s.length(); i++) {
> char c = s.charAt(i);
> if (Character.isLetter(c))
> sb.append(c);
> }
> return sb.toString();
> }
> public static class IntSumReducer
> extends Reducer<MyText, IntWritable, YourText, IntWritable> {
> private IntWritable result = new IntWritable();
> public void reduce(MyText key, Iterable<IntWritable> values,
> Context context
> ) throws IOException, InterruptedException {
> int sum = 0;
> for (IntWritable val : values) {
> sum += val.get();
> }
> result.set(sum);
> context.write(new YourText(key.toString()), result);
> }
> }
> public static class MyPartitioner extends Partitioner<Text, IntWritable>
> {
> /**
> * Get the partition number for a given key (hence record) given the
> total
> * number of partitions i.e. number of reduce-tasks for the job.
> * <p/>
> * <p>Typically a hash function on a all or a subset of the key.</p>
> *
> * @param key the key to be partioned.
> * @param value the entry value.
> * @param numPartitions the total number of partitions.
> * @return the partition number for the <code>key</code>.
> */
> �...@override
> public int getPartition(Text key, IntWritable value, int
> numPartitions) {
> String s = key.toString();
> if (s.length() == 0)
> return 0;
> char c = s.charAt(0);
> int letter = Character.toUpperCase(c) - 'A';
> if (letter < 0 || letter > 26)
> return 0;
> return letter % numPartitions;
> }
> }
>
> /**
> * Force loading of needed classes to make
> */
> public static final Class[] NEEDED =
> {
> org.apache.commons.logging.LogFactory.class,
> org.apache.commons.cli.ParseException.class
> };
>
> public static final int DEFAULT_REDUCE_TASKS = 14;
> public static void main(String[] args) throws Exception {
> Configuration conf = new Configuration();
> String[] otherArgs = new GenericOptionsParser(conf,
> args).getRemainingArgs();
> // if (otherArgs.length != 2) {
> // System.err.println("Usage: wordcount <in> <out>");
> // System.exit(2);
> // }
> Job job = new Job(conf, "word count");
> job.setJarByClass(CapitalWordCount.class);
> job.setMapperClass(TokenizerMapper.class);
> job.setCombinerClass(IntSumReducer.class);
> job.setReducerClass(IntSumReducer.class);
>
> job.setMapOutputKeyClass(MyText.class);
> job.setMapOutputValueClass(IntWritable.class);
> job.setOutputKeyClass(YourText.class);
> job.setOutputValueClass(IntWritable.class);
>
> // added Slewis
> job.setNumReduceTasks(DEFAULT_REDUCE_TASKS);
> job.setPartitionerClass(MyPartitioner.class);
> if(otherArgs.length > 1) {
> FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
> }
> String athString = otherArgs[otherArgs.length - 1];
> File out = new File(athString);
> if (out.exists()) {
> FileUtilities.expungeDirectory(out);
> out.delete();
> }
> Path outputDir = new Path(athString);
>
> FileOutputFormat.setOutputPath(job, outputDir);
>
> boolean ans = job.waitForCompletion(true);
> int ret = ans ? 0 : 1;
> System.exit(ret);
> }
> }
> --
> Steven M. Lewis PhD
> Institute for Systems Biology
> Seattle WA
>
--
Eric Sammer
twitter: esammer
data: www.cloudera.com
