在 Horton works 沙盒上运行 Modified Wordcount 程序时需要帮助。答案

【问题标题】：Need help in running Modified Wordcount program on Horton works sandbox.在 Horton works 沙盒上运行 Modified Wordcount 程序时需要帮助。
【发布时间】：2015-03-25 01:21:18
【问题描述】：

在运行 Wordcount 程序的修改版本时出现错误（添加了映射器逻辑以从单词中分离出符号）。

错误：java.lang.RuntimeException：java.lang.ClassNotFoundException：类 wcount.WordCount$TokenizerMapper

操作系统：HortonWorks Sandbox 托管 2.6 Hadoop 版本这就是我所做的 -

修改 Wordcount.java 以引入映射器逻辑
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jar cvf wordcount.jar wcount 创建了 WordCount.jar（其中 wcount 是包含所有 3 个类（wordcount、tokenizer 和 intsumreducer）的文件夹。这是jar文件的样子 wcount wcount/WordCount.class wcount/WordCount$TokenizerMapper.class wcount/WordCount$intsumreducer.class
使用命令运行它 - hadoop jar wordcount.jar WordCount /home/user/test_user/wordcount/wordcount.txt /home/user/test_user/wordcount/out8

尝试运行地图作业Error: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class wcount.WordCount$TokenizerMapper后出错

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);
  }
}

【问题讨论】：

标签： java hadoop jar word-count hortonworks-data-platform

【解决方案1】：

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。因此，这项工作可能需要LongWritable，而不是普通的Object。您可以尝试将extends Mapper<Object 更改为extends Mapper<LongWritable 并将map(Object key 更改为map(LongWritable key 吗？

【讨论】：