Question

您好我试图在独立模式下使用map reduce技术找到少数数字的平均值。我有两个输入文件。它包含值file1：25 25 25 25 25和file2：15 15 15 15 15。

我的程序工作正常，但输出文件包含mapper的输出而不是reducer输出。

这是我的代码：

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.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.io.Writable;
import java.io.*;


public class Average {

    public static class SumCount implements Writable {

        public int sum;
        public int count;

        @Override
        public void write(DataOutput out) throws IOException {
            out.writeInt(sum);
            out.writeInt(count);
        }

        @Override
        public void readFields(DataInput in) throws IOException {
            sum = in.readInt();
            count =in.readInt();
        }  
    }
  public static class TokenizerMapper extends Mapper<Object, Text, Text, Object>{

    private final static IntWritable valueofkey = new IntWritable();
    private Text word = new Text();
    SumCount sc=new SumCount();
    public void map(Object key, Text value, Context context
                    ) throws IOException, InterruptedException {
      StringTokenizer itr = new StringTokenizer(value.toString());
      int sum=0;
      int count=0;
      int v;
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        v=Integer.parseInt(word.toString());
        count=count+1;
        sum=sum+v;       
      }
      word.set("average");
      sc.sum=sum;
      sc.count=count;
      context.write(word,sc);
    }
  }

  public static class IntSumReducer extends Reducer<Text,Object,Text,IntWritable> {
    private IntWritable result = new IntWritable();
    public void reduce(Text key, Iterable<SumCount> values,Context context) throws IOException, InterruptedException {
      int sum = 0;
      int count=0;
      int wholesum=0;
      int wholecount=0;
      for (SumCount val : values) {
        wholesum=wholesum+val.sum;
        wholecount=wholecount+val.count;
      }
      int res=wholesum/wholecount;
      result.set(res);
      context.write(key, result );
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "");
    job.setJarByClass(Average.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setMapOutputKeyClass(Text.class);
    job.setMapOutputValueClass(SumCount.class);
    job.setOutputValueClass(IntWritable.class);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

运行程序后，我的输出文件是这样的：

average Average$SumCount@434ba039
average Average$SumCount@434ba039

Answer 1

您不能将Reducer类IntSumReducer用作组合器。组合器必须接收和发出相同的键/值类型。

所以我会删除job.setCombinerClass(IntSumReducer.class);。

请记住，combine的输出是reduce的输入，因此写出Text和IntWritable不会起作用。

如果您的输出文件看起来像part-m-xxxxx，那么上述问题可能意味着它只运行了Map阶段并停止了。你的柜台会证实这一点。

您还有Reducer<Text,Object,Text,IntWritable>，Reducer<Text,SumCount,Text,IntWritable>。

输出文件包含Mapper输出而不是Reducer输出

1 个答案: