Hadoop项目---坚持步骤：文件输出提交者算法版本为1

Question

我是一个hadoop新手。我在本教程中运行代码时遇到了问题：

https://github.com/hortonworks/hadoop-tutorials/blob/master/Community/T09_Write_And_Run_Your_Own_MapReduce_Java_Program_Poll_Result_Analysis.md

地图缩减过程将停止步骤：

[main] WARN org.apache.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
[main] INFO org.apache.hadoop.conf.Configuration.deprecation - session.id is deprecated. Instead, use dfs.metrics.session-id
[main] INFO org.apache.hadoop.metrics.jvm.JvmMetrics - Initializing JVM Metrics with processName=JobTracker, sessionId=
[main] WARN org.apache.hadoop.mapreduce.JobResourceUploader - Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
[main] WARN org.apache.hadoop.mapreduce.JobResourceUploader - No job jar file set.  User classes may not be found. See Job or Job#setJar(String).
[main] INFO org.apache.hadoop.mapreduce.lib.input.FileInputFormat - Total input paths to process : 4
[main] INFO org.apache.hadoop.mapreduce.JobSubmitter - number of splits:4
[main] INFO org.apache.hadoop.mapreduce.JobSubmitter - Submitting tokens for job: job_local61587531_0001
[main] INFO org.apache.hadoop.mapreduce.Job - The url to track the job: http://localhost:8080/
[Thread-19] INFO org.apache.hadoop.mapred.LocalJobRunner - OutputCommitter set in config null
[Thread-19] INFO org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter - File Output Committer Algorithm version is 1

map-reduce应用程序的代码是

public class VoteCountApplication extends Configured implements Tool {

 public static void main(String[] args) throws Exception {
  int res = ToolRunner.run(new Configuration(), new VoteCountApplication(), args);
  System.exit(res);
 }

 @Override
 public int run(String[] args) throws Exception {
  if (args.length != 2) {
   System.out.println("usage: [input] [output]");
   System.exit(-1);
  }

  Job job = Job.getInstance(new Configuration());
  job.setOutputKeyClass(Text.class);
  job.setOutputValueClass(IntWritable.class);

  job.setMapperClass(VoteCountMapper.class);
  job.setReducerClass(VoteCountReducer.class);

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

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

  job.setJarByClass(VoteCountApplication.class);

  job.submit();
  return 0;
 }
}

但是，如果我使用WordCount示例中的main方法来运行此项目

public class VoteCountApplication extends Configured implements Tool {

 public static void main(String[] args) throws Exception {

  Configuration conf = new Configuration();
  Job job = Job.getInstance(conf, "vote count");
  job.setJarByClass(VoteCountApplication.class);
  job.setMapperClass(VoteCountMapper.class);
  job.setCombinerClass(VoteCountReducer.class);
  job.setReducerClass(VoteCountReducer.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);

 }
}

这是完美的！我不知道教程代码中的问题是什么。有没有人能理解代码之间的区别？感谢

这是Map和Reduce代码：

public class VoteCountMapper extends Mapper<Object, Text, Text, IntWritable> {

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

@Override
public void map(Object key, Text value, Context output) throws IOException,
        InterruptedException {

    //If more than one word is present, split using white space.
    String[] words = value.toString().split(" ");
    //Only the first word is the candidate name
    output.write(new Text(words[0]), one);
}
}

public class VoteCountReducer extends Reducer<Text, IntWritable, Text, IntWritable> {

@Override
public void reduce(Text key, Iterable<IntWritable> values, Context output)
        throws IOException, InterruptedException {
    int voteCount = 0;
    for(IntWritable value: values){
        voteCount+= value.get();
    }
    output.write(key, new IntWritable(voteCount));
}
}