需要帮助在horton works沙盒上运行修改后的wordcount程序

vof42yt1  于 2021-06-04  发布在  Hadoop
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运行wordcount程序的修改版本时出错(添加了Map器逻辑以将符号从单词中分离出来)。
错误:java.lang.runtimeexception:java.lang.classnotfoundexception:class wcount.wordcount$tokenizermapper
os:hortonworks沙盒托管2.6 hadoop版本我就是这么做的-
修改wordcount.java以引入Map器逻辑
使用命令编译wordcount.java javac -classpath /home/test_user/jars/commons-cli-1.2.jar:/home/test_user/jars/hadoop-common-2.6.0.2.2.0.0-2041.jar:/home/test_user/jars/hadoop-mapreduce-client-core-2.6.0.2.2.0.0-2041.jar -d /home/test_user/hadoopjar/wordcountclass -Xlint:deprecation WordCount.java 使用创建wordcount.jar jar cvf wordcount.jar wcount (其中wcount是包含所有3个类(wordcount、tokenizer和intsumreducer)的文件夹)。下面是jar文件的样子 wcount wcount/WordCount.class wcount/WordCount$TokenizerMapper.class wcount/WordCount$intsumreducer.class 使用命令- hadoop jar wordcount.jar WordCount /home/user/test_user/wordcount/wordcount.txt /home/user/test_user/wordcount/out8 它在尝试运行Map作业后出错 Error: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class wcount.WordCount$TokenizerMapper 代码是

package wcount;

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.util.GenericOptionsParser;

public class WordCount {

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

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

    public void map(Object key, Text value, Context context
                    ) throws IOException, InterruptedException {
      StringTokenizer itr = new StringTokenizer(value.toString());
       char[] chararray = {'(' , ')' , ';' , ':' , '.' , '/' , '{' , '}' , ']' , ']'};
       String temp;
      while (itr.hasMoreTokens())
      {
          temp = itr.nextToken();
          for (short i = 0; i < chararray.length; i++)
          {
              if (temp.charAt(0) == chararray[i])
              {
                  temp = temp.substring(1);
              }
           if (temp.charAt(temp.length() - 1) == chararray[i])
              {
                  temp = temp.substring(0, temp.length() - 1);
              }
          }
        word.set(temp);
        context.write(word, one);
      }
    }
  }

  public static class IntSumReducer
       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);
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    if (otherArgs.length < 2) {
      System.err.println("Usage: wordcount <in> [<in>...] <out>");
      System.exit(2);
    }
    Job job = new Job(conf, "word count");
    job.setJarByClass(WordCount.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    for (int i = 0; i < otherArgs.length - 1; ++i) {
      FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
    }
    FileOutputFormat.setOutputPath(job,
      new Path(otherArgs[otherArgs.length - 1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}
sg2wtvxw

sg2wtvxw1#

您没有在作业设置中设置任何inputformatter,因此默认情况下,您的输入格式化程序是textinputformatter。所以这项工作可能需要一个 LongWritable 相对于普通的 Object . 你能换一下房间吗 extends Mapper<Objectextends Mapper<LongWritable 还有 map(Object keymap(LongWritable key ?

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