Hadoop：减速器没有被调用

Question

我知道这是一个非常基本的问题，但我无法找到我在哪里犯了错误。我的 Reducer 没有从驱动程序代码中调用。如果有人可以帮助我，我将不胜感激。

我的驱动程序代码

package com.mycompany.myorg;

import java.io.IOException;

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.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class carsDriver {

    public static void main(String args[]) throws IOException, ClassNotFoundException, InterruptedException{

        Configuration conf = new Configuration();

        String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();

        if(otherArgs.length != 2){
            System.err.println("specified input and output path is not correct");
            System.exit(-1);
        }

        // set up the job details

        Job job = new Job(conf,"Cars Avg Fuel Economy");
        job.setJarByClass(carsDriver.class);
        //job.setJobName("Cars Avg Fuel Economy");

        //setup the input and output paths for the MR job
        FileInputFormat.setInputPaths(job, new Path(args[0]));
        FileOutputFormat.setOutputPath(job, new Path(args[1]));

        // setup of the Mapper, combiner and Reducer classes
        job.setMapperClass(carsMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        //job.setCombinerClass(carsCombiner.class);
        job.setReducerClass(carsReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

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

}

映射器代码

package com.mycompany.myorg;

import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;

public class carsMapper extends Mapper<Object, Text, Text, IntWritable> {

    private Text mapkey = new Text();
    private final static IntWritable mapval = new IntWritable(1);

     public void map(Object key, Text Value,Mapper<Object, Text, Text, IntWritable>.Context context  ) throws IOException, InterruptedException{

         System.out.println("Running the Mapper");
         String items[] = Value.toString().split(",");

         System.out.println(items[2]+" "+Integer.parseInt(items[23].toString()));

         mapkey.set(items[2]);
         mapval.set(Integer.parseInt(items[23].toString()));

         context.write(mapkey, mapval);

     }
}

Reducer 代码

package com.mycompany.myorg;

import java.io.IOException;

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

public class carsReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

    public void reducer(Text key, Iterable<IntWritable> value,Reducer<Text, IntWritable, Text, IntWritable>.Context context) throws IOException, InterruptedException {

        System.out.println("Reducer Code");
        Text redKey = new Text();
        IntWritable redVal = new IntWritable();


        redKey.set(key);

        int sum=0;
        int count=0;
        for(IntWritable val: value){
            sum= sum +val.get();
            count= count + 1;
        }

        redVal.set((sum/count));

        context.write(redKey, redVal);

    }
}

Answer 1

经过长时间调试发现问题出在reduce覆盖方法上。

我用过

public void reducer

而不是

public void reduce

注意它应该是 reduce 而不是 reducer。