I am using the folllowing code to do the reduce side join 



    /*
     * HadoopMapper.java
     *
     * Created on Apr 8, 2012, 5:39:51 PM
     */
    
    
    import java.io.DataInput;
    import java.io.DataOutput;
    import java.io.IOException;
    // import org.apache.commons.logging.Log;
    // import org.apache.commons.logging.LogFactory;
    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.TextInputFormat;
    import org.apache.hadoop.mapred.TextOutputFormat;
    import org.apache.hadoop.util.GenericOptionsParser;
    import org.apache.hadoop.util.Tool;
    import org.apache.hadoop.util.ToolRunner;
    import org.apache.hadoop.fs.Path;
    import org.apache.hadoop.io.Text;
    import org.apache.hadoop.io.Writable;
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.conf.Configured;
    import org.apache.hadoop.contrib.utils.join.*; 
    
    /**
     *
     * @author 
     */
    public class DataJoin extends Configured implements Tool 
        {
            public static class MapClass extends DataJoinMapperBase 
                {
                    protected Text generateInputTag(String inputFile) 
                        {
                            String datasource = inputFile.split("-")[0];
                            return new Text(datasource);
                        }
                protected Text generateGroupKey(TaggedMapOutput aRecord) 
                    {
                        String line = ((Text) aRecord.getData()).toString();
                        String[] tokens = line.split(",");
                        String groupKey = tokens[0];
                        return new Text(groupKey);
                    }
                protected TaggedMapOutput generateTaggedMapOutput(Object
value) 
                    {
                        TaggedWritable retv = new TaggedWritable((Text)
value);
                        retv.setTag(this.inputTag);
                        return retv;
                    }
                }
            public static class Reduce extends DataJoinReducerBase 
                {
                    protected TaggedMapOutput combine(Object[] tags,
Object[] values) 
                        {
                            if (tags.length < 2) return null;
                            String joinedStr = "";
                            for (int i=0; i<values.length; i++) 
                            {
                                if (i > 0) joinedStr += ",";
                                TaggedWritable tw = (TaggedWritable)
values[i];
                                String line = ((Text)
tw.getData()).toString();
                                String[] tokens = line.split(",", 2);
                                joinedStr += tokens[1];
                            }
                            TaggedWritable retv = new TaggedWritable(new
Text(joinedStr));
                            retv.setTag((Text) tags[0]);
                            return retv;
                        }
                }
            public static class TaggedWritable extends TaggedMapOutput 
                {
                    private Writable data;
                    public TaggedWritable(Writable data) 
                        {
                            this.tag = new Text("");
                            this.data = data;
                        }
    
                    public Writable getData() 
                        {
                            return data;
                        }
                    public void write(DataOutput out) throws IOException
                        {
                            this.tag.write(out);
                            this.data.write(out);
                        }
                    public void readFields(DataInput in) throws IOException 
                        {
                            this.tag.readFields(in);
                            this.data.readFields(in);
                        }
                }
            public int run(String[] args) throws Exception 
                {
                    
    
                                    Configuration conf = getConf();
                    JobConf job = new JobConf(conf, DataJoin.class);
                                    String[] otherArgs = new
GenericOptionsParser(conf, args).getRemainingArgs();
                                    if (otherArgs.length != 2) 
                                    {
                                      System.err.println("Usage: wordcount
<in> <out>");
                                      System.exit(2);
                                    }
                    
                    Path in = new Path(args[0]);
                    Path out = new Path(args[1]);
                    FileInputFormat.setInputPaths(job, in);
                    FileOutputFormat.setOutputPath(job, out);
                    job.setJobName("DataJoin");
                    job.setMapperClass(MapClass.class);
                    job.setReducerClass(Reduce.class);
                    job.setInputFormat(TextInputFormat.class);
                    job.setOutputFormat(TextOutputFormat.class);
                    job.setOutputKeyClass(Text.class);
                    job.setOutputValueClass(TaggedWritable.class);
                    job.set("mapred.textoutputformat.separator", ",");
                    JobClient.runJob(job);
                    return 0;
                }
            public static void main(String[] args) throws Exception 
                {
                    int res = ToolRunner.run(new Configuration(),
                    new DataJoin(),
                    args);
                    System.exit(res);
                }
        }




I am able to compile my code. When I run in hadoop I am getting the
following error  with the combiner


    12/04/17 19:59:29 INFO mapred.JobClient:  map 100% reduce 27%
    12/04/17 19:59:38 INFO mapred.JobClient:  map 100% reduce 30%
    12/04/17 19:59:47 INFO mapred.JobClient:  map 100% reduce 33%
    12/04/17 20:00:23 INFO mapred.JobClient: Task Id :
attempt_201204061316_0018_r_000000_2, Status : FAILED
    java.lang.RuntimeException: java.lang.NoSuchMethodException:
DataJoin$TaggedWritable.<init>()
            at
org.apache.hadoop.util.ReflectionUtils.newInstance(ReflectionUtils.java:115)
            at
org.apache.hadoop.io.serializer.WritableSerialization$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:1136)
            at
org.apache.hadoop.mapred.Task$ValuesIterator.next(Task.java:1076)
            at
org.apache.hadoop.mapred.ReduceTask$ReduceValuesIterator.moveToNext(ReduceTask.java:246)
            at
org.apache.hadoop.mapred.ReduceTask$ReduceValuesIterator.next(ReduceTask.java:242)
            at
org.apache.hadoop.contrib.utils.join.DataJoinReducerBase.regroup(DataJoinReducerBase.java:106)
            
            
I checked some forums and found out that the error may occur due to non
static class. My program has no non static class!

The command I use to run hadoop is 
    /hadoop/core/bin/hadoop jar /export/scratch/lopez/Join/DataJoin.jar
DataJoin /export/scratch/user/lopez/Join 
/export/scratch/user/lopez/Join_Output 

and the DataJoin.jar file has DataJoin$TaggedWritable packaged in it

Could someone please help me
-- 
View this message in context: 
http://old.nabble.com/Reduce-side-join---Hadoop-default---error-in-combiner-tp33705493p33705493.html
Sent from the Hadoop core-dev mailing list archive at Nabble.com.

Reply via email to