Mapreduce Combiner

Question

I have a simple mapreduce code with mapper, reducer and combiner. The output from mapper is passed to combiner. But to the reducer, instead of output from combiner,output from mapper is passed.

Kindly help

Code:

package Combiner;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.Mapper.Context;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class AverageSalary
{
public static class Map extends  Mapper<LongWritable, Text, Text, DoubleWritable> 
{
    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException 
    {    
        String[] empDetails= value.toString().split(",");
        Text unit_key = new Text(empDetails[1]);      
        DoubleWritable salary_value = new DoubleWritable(Double.parseDouble(empDetails[2]));
        context.write(unit_key,salary_value);    

    }  
}
public static class Combiner extends Reducer<Text,DoubleWritable, Text,Text> 
{
    public void reduce(final Text key, final Iterable<DoubleWritable> values, final Context context)
    {
        String val;
        double sum=0;
        int len=0;
        while (values.iterator().hasNext())
        {
            sum+=values.iterator().next().get();
            len++;
        }
        val=String.valueOf(sum)+":"+String.valueOf(len);
        try {
            context.write(key,new Text(val));
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (InterruptedException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
    }
}
public static class Reduce extends Reducer<Text,Text, Text,Text> 
{
    public void reduce (final Text key, final Text values, final Context context)
    {
        //String[] sumDetails=values.toString().split(":");
        //double average;
        //average=Double.parseDouble(sumDetails[0]);
        try {
            context.write(key,values);
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        } catch (InterruptedException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }
    }
}
public static void main(String args[])
{
    Configuration conf = new Configuration();
    try
    {
     String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();    
     if (otherArgs.length != 2) {      
         System.err.println("Usage: Main <in> <out>");      
         System.exit(-1);    }    
     Job job = new Job(conf, "Average salary");    
     //job.setInputFormatClass(KeyValueTextInputFormat.class);    
     FileInputFormat.addInputPath(job, new Path(otherArgs[0]));    
     FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));    
     job.setJarByClass(AverageSalary.class);    
     job.setMapperClass(Map.class);    
     job.setCombinerClass(Combiner.class);
     job.setReducerClass(Reduce.class);    
     job.setOutputKeyClass(Text.class);    
     job.setOutputValueClass(Text.class);    

        System.exit(job.waitForCompletion(true) ? 0 : -1);
    } catch (ClassNotFoundException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    } catch (IOException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    } catch (InterruptedException e) {
        // TODO Auto-generated catch block
        e.printStackTrace();
    }
}

}

Answer 1

The #1 rule of Combiners are: do not assume that the combiner will run. Treat the combiner only as an optimization.

The Combiner is not guaranteed to run over all of your data. In some cases when the data doesn't need to be spilled to disk, MapReduce will skip using the Combiner entirely. Note also that the Combiner may be ran multiple times over subsets of the data! It'll run once per spill.

In your case, you are making this bad assumption. You should be doing the sum in the Combiner AND the Reducer.

Also, you should follow @user987339's answer as well. The input and output of the combiner needs to be identical (Text,Double -> Text,Double) and it needs to match up with the output of the Mapper and the input of the Reducer.