cloudera中hadoop单词计数示例中的数字获取

ccgok5k5  于 2021-05-27  发布在  Hadoop
关注(0)|答案(1)|浏览(325)

下面我们使用了代码:map类是wcmapper。reduce类是wcreducer。
不太清楚为什么输出是生成number而不是wordcount。

public class WCMapper extends Mapper { 
    public void map(LongWritable key,Text value,Context context) throws 
    IOException,InterruptedException 
       { String line = key.toString(); 
        StringTokenizer tokenizer = new StringTokenizer(line); 
          while(tokenizer.hasMoreTokens()) 
          { value.set(tokenizer.nextToken()); 
           context.write(value, new IntWritable(1)); 
            }
            }

       }

 public class WCReducer 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 x: values)
    {
        sum+=x.get();

    }

    result.set(sum);
    System.out.println("Key: "+key+"Value: "+sum);
    context.write(key, result);

}
   }    

public static void main(String[] args) throws Exception{
    Configuration conf = new Configuration();

    Job job = Job.getInstance(conf, "WordCount");

    job.setJarByClass(WorCount.class);
    job.setMapperClass(WCMapper.class);
    job.setReducerClass(WCReducer.class);

    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);

    job.setInputFormatClass(TextInputFormat.class);
    job.setOutputFormatClass(TextOutputFormat.class);

     Path outputPath = new Path(args[1]);

     FileInputFormat.addInputPath(job, new Path(args[0]));
     FileOutputFormat.setOutputPath(job, new Path(args[1]));

     outputPath.getFileSystem(conf).delete(outputPath, true);

     System.exit(job.waitForCompletion(true)? 0: 1);
}

输入文件:这是cloudera这是smart
预期输出:这2是2 cloudera 1 smart 1
获得的输出:0 1 17 1

sh7euo9m

sh7euo9m1#

问题出在Map器中:

String line = key.toString();

这个 key 在这种情况下是 LongWritable 表示文件中行的字节偏移量。如果你把那行改成 value ,然后不要使用 value 下面你会得到正确的答案。
新Map器:

public void map(LongWritable key, Text value, Context context) throws IOException,InterruptedException { 
    String line = value.toString(); 
    StringTokenizer tokenizer = new StringTokenizer(line); 
    Text word = new Text();

    while(tokenizer.hasMoreTokens()) {
        word.set(tokenizer.nextToken()); 
        context.write(word, new IntWritable(1)); 
    }
}

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