Question

我正在尝试运行wordcount示例

这是代码

ByteArrayInputStream contentsAsStream = new ByteArrayInputStream(contentAsBytes);
ObjectMetadata md = new ObjectMetadata();
md.setContentLength(contentAsBytes.length);
md.setContentEncoding("text/html");
s3.putObject(new PutObjectRequest(ARTIST_BUCKET_NAME, artistId, contentsAsStream, md));

我看到类似

的内容

   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;

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());
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        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();
    Job job = Job.getInstance(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);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

我发现了这篇文章Wordcount program is stuck in hadoop-2.3.0 但解决方案对我不起作用

Answer 1

您正在使用Hadoop 2.6并使用mapred包。我认为新的包名包括mapreduce。请按照示例here运行正确的版本。您也可以使用link1和link2来了解两者之间的差异

Answer 2

最后，我解决了这个问题。我需要在yarn-site.xml中添加以下属性

a2'

这可以解决您的问题。

MapReduce作业无法在HADOOP-2.6.0中运行

2 个答案: