How to set a a reducer to emmit <Text, IntWritable> and a mapper to receive <Text, IntWritable>?

问题

I'm developing some code on hadoop with mapreduce that uses two mappers and two reducers. I've been told to use SequenceFileInputFormat and SequenceFileOutputFormat to make the output of the first reducer and the input of the second mapper to work together. The problem is that i'm recibing an error and after googleing a lot i don't know why.

The error:

java.lang.Exception: java.io.IOException: Type mismatch in key from map: expected org.apache.hadoop.io.IntWritable, received org.apache.hadoop.io.Text

Type mismatch in key from map: expected org.apache.hadoop.io.IntWritable, received org.apache.hadoop.io.Text

The code:

package casoTaxis;

import java.io.IOException;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;

public class Eje1{

    public static class MapperJob1 extends Mapper<Object, Text, Text, IntWritable> {
        //El metodo map recibe un conjunto clave-valor, lo procesa y lo vuelca en un contexto.adasdadada 
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            Text hackLicense; IntWritable totalAmount; //salidas
            StringTokenizer itr = new StringTokenizer(value.toString(), ",");
            itr.nextToken();
            hackLicense = new Text(itr.nextToken());
            for(int i=2; i<itr.countTokens(); i++) itr.nextToken();
            totalAmount = new IntWritable( Integer.parseInt(itr.nextToken()) );
            context.write(hackLicense, totalAmount);
        }
    }

    public static class ReducerJob1 extends Reducer<Text, IntWritable, Text, IntWritable> { //No encontre una clase InpuFormat que sea Text, IntWritable
        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            context.write(key, new IntWritable(sum));
        }
    }

    public static class MapperJob2 extends Mapper<Text, IntWritable, Text, IntWritable> {
        //El metodo map recibe un conjunto clave-valor, lo procesa y lo vuelca en un contexto.adasdadada 
        public void map(Text key, IntWritable value, Context context) throws IOException, InterruptedException {
            context.write(key, value);
        }
    }

    public static class ReducerJob2 extends Reducer<Text, IntWritable, Text, Text> {
        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int max = 0;
            for (IntWritable val : values) {
                int maxVal = val.get();
                if( maxVal>max ) max = maxVal;
            }
            String licencia = "Conductor con licencia = " + key;
            String recaudacion = "Recaudacion = " + max;
            context.write(new Text(licencia), new Text(recaudacion));
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf1 = new Configuration();
        Configuration conf2 = new Configuration();
        //conf2.set("mapreduce.input.keyvaluelinerecordreader.key.value.separator", " ");
        Job job1 = Job.getInstance(conf1, "Eje1-Job1");
        Job job2 = Job.getInstance(conf2, "Eje1-Job2");
        job1.setJarByClass(Eje1.class);
        job2.setJarByClass(Eje1.class);
        job1.setMapperClass(MapperJob1.class);
        job2.setMapperClass(MapperJob2.class);
        job1.setReducerClass(ReducerJob1.class);
        job2.setReducerClass(ReducerJob2.class);

        job1.setMapOutputKeyClass(Text.class);
        job1.setMapOutputValueClass(IntWritable.class);
        job1.setOutputKeyClass(Text.class);
        job1.setOutputValueClass(IntWritable.class);
        job2.setMapOutputKeyClass(Text.class);
        job2.setMapOutputKeyClass(IntWritable.class);
        job2.setOutputKeyClass(Text.class);
        job2.setOutputValueClass(Text.class);

        job1.setOutputFormatClass(SequenceFileOutputFormat.class);
        job2.setInputFormatClass(SequenceFileInputFormat.class);///asdasdads

        FileInputFormat.addInputPath(job1, new Path(args[0]));
        FileOutputFormat.setOutputPath(job1, pathIntermedio);
        FileInputFormat.addInputPath(job2, pathIntermedio);
        FileOutputFormat.setOutputPath(job2, new Path(args[1]));

        job1.waitForCompletion(true);
        System.exit(job2.waitForCompletion(true) ? 0 : 1);
    }

    private static final Path pathIntermedio = new Path("intermediate_output");

}

Why i'm receiving this error? is there a better way to accomplish this?

回答1:

The error is with the lines

job2.setMapOutputKeyClass(Text.class);
job2.setMapOutputKeyClass(IntWritable.class);

The second of those should be:

job2.setMapOutputValueClass(IntWritable.class);

来源：https://stackoverflow.com/questions/40221115/how-to-set-a-a-reducer-to-emmit-text-intwritable-and-a-mapper-to-receive-tex