Warning: file_get_contents(/data/phpspider/zhask/data//catemap/0/hadoop/6.json): failed to open stream: No such file or directory in /data/phpspider/zhask/libs/function.php on line 167

Warning: Invalid argument supplied for foreach() in /data/phpspider/zhask/libs/tag.function.php on line 1116

Notice: Undefined index: in /data/phpspider/zhask/libs/function.php on line 180

Warning: array_chunk() expects parameter 1 to be array, null given in /data/phpspider/zhask/libs/function.php on line 181
Hadoop MapReduce不还原?_Hadoop_Mapreduce - Fatal编程技术网

Hadoop MapReduce不还原?

Hadoop MapReduce不还原?,hadoop,mapreduce,Hadoop,Mapreduce,我正在学习教程,这是我的代码 import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.*; import org.apache.hadoop.mapreduce.*; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.

我正在学习教程,这是我的代码

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

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

public class WordCount {
    public static class WordCountMapper extends Mapper<Object, Text, Text, IntWritable> {

        private Text word = new Text();
        private final IntWritable one = new IntWritable(1);

        @Override
        public void map(Object key, Text val, Context context) throws IOException, InterruptedException {
            String line = val.toString();
            StringTokenizer tokenizer = new StringTokenizer(line.toLowerCase());
            while (tokenizer.hasMoreTokens()) {
                word.set(tokenizer.nextToken());
                context.write(word, one);
            }
        }
    }

    public static class WordCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

        public void reduce(Text key, Iterator<IntWritable> value, Context context) throws IOException, InterruptedException {
            int sum = 0;
            while (value.hasNext()) {
                IntWritable val = (IntWritable) value.next();
                sum += val.get();
            }
        context.write(key, new IntWritable(sum));
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration config = new Configuration();
        Job job = Job.getInstance(config, "word count");
        job.setJarByClass(WordCount.class);
        job.setMapperClass(WordCountMapper.class);
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);
        job.setCombinerClass(WordCountReducer.class);
        job.setReducerClass(WordCountReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new     Path("/user/Icarus/words.txt"));
        FileOutputFormat.setOutputPath(job, new Path("/user/Icarus/words.out"));
        job.waitForCompletion(true);
    }
}

我一定错过了一些非常琐碎的事情,但我想不出是什么。请帮助。

此问题的根本原因是,您没有使用Hadoop调用所需的确切签名调用reduce。签名应如下所示,以供参考

第二个:第二个解决方案很简单, 不要手动定义reduce类,只需将Reducer类设置为IntSumReducer或LongSumReducer,这将与上面的代码相同。 因此,不要定义WordCountReducer类并添加以下代码

job.setReducerClass(LongSumReducer.class); or  
job.setReducerClass(IntSumReducer.class);
基于所需的计数类型


希望有帮助

您的第一个代码可以工作,但为什么。。看起来唯一的区别是我们如何使用迭代器。您应该使用Iterable而不是iterator来处理代码,并使用for循环来迭代它
protected void reduce(KEYIN key, Iterable<VALUEIN> values, org.apache.hadoop.mapreduce.Reducer.Context context)
               throws IOException, InterruptedException
public static class WordCountReducer
       extends Reducer<Text,IntWritable,Text,IntWritable> {
    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values,
                       Context context
                       ) throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      result.set(sum);
      context.write(key, result);
    }
  }  
job.setReducerClass(LongSumReducer.class); or  
job.setReducerClass(IntSumReducer.class);