运行Hadoop Jar包报错：参数数量不正确，求排查方案

我是Hadoop新手，在Ubuntu系统中参照网上的WordCount MapReduce示例操作，已完成除任务运行外的所有步骤：将输入文件上传至集群，路径为/user/inputdata/test.txt，指定/user/output作为输出目录。执行以下命令：

hadoop jar /home/wasim/Downloads/jar_files/MapReduceDemo.jar MapReduceDemo.WordCounter /user/inputdata/test.txt /user/output

时，收到错误提示：

usage: WordCount <input_file> <output_directory>

我知晓该错误源于Java代码的参数校验，但多次调整命令仍未解决问题，附上相关代码：

package MapReduceDemo;

import java.io.IOException;
import java.util.Iterator;
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 WordCounter {
    
    public static class TokenizeMapper extends Mapper<Object,Text,Text,IntWritable>{
        
        public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
            StringTokenizer st = new StringTokenizer(value.toString());
            Text wordOut = new Text();
            IntWritable one = new IntWritable(1);
            while(st.hasMoreTokens()){
                wordOut.set(st.nextToken());
                context.write(wordOut, one);
                
            }       
        }
    }
    
    public static class SumReducer extends Reducer<Text,IntWritable,Text,IntWritable>{
        public void reduce(Text term,Iterable<IntWritable> ones, Context context) throws IOException, InterruptedException {
            int count = 0;
            Iterator<IntWritable> iterator = ones.iterator();
            while(iterator.hasNext()) {
                count++;
                iterator.next();
            }
            IntWritable output = new IntWritable(count);
            context.write(term, output);
        }
    }

    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        
        if(otherArgs.length !=2) {
            System.err.println("usage: WordCount <input_file> <output_directory>");
            System.exit(2);
        }
        
        Job job = Job.getInstance(conf,"Word Count");
        job.setJarByClass(WordCounter.class);
        job.setMapperClass(TokenizeMapper.class);
        job.setReducerClass(SumReducer.class);
        job.setNumReduceTasks(10);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        
        FileInputFormat.addInputPath(job,new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job,new Path(otherArgs[1]));
        boolean status = job.waitForCompletion(true);
        if(status) {
            System.exit(0);
        }
        else {
            System.exit(1);
        }
    }
}

排查与解决步骤 #

1. 清理已存在的输出目录
   Hadoop不允许输出目录提前存在，先执行命令删除：

hdfs dfs -rm -r /user/output

2. 修正参数校验提示
   代码中错误提示写的是WordCount，但主类实际是WordCounter，修改主方法中的提示语句，避免混淆：

if(otherArgs.length !=2) {
    System.err.println("usage: WordCounter <input_file> <output_directory>");
    System.exit(2);
}

3. 替换参数解析逻辑
   GenericOptionsParser可能会处理Hadoop通用参数导致解析异常，若命令中未使用-conf等通用参数，直接用args数组替代原解析逻辑：

// 删除GenericOptionsParser相关代码，替换为：
if(args.length !=2) {
    System.err.println("usage: WordCounter <input_file> <output_directory>");
    System.exit(2);
}
// 后续路径引用改为args
FileInputFormat.addInputPath(job,new Path(args[0]));
FileOutputFormat.setOutputPath(job,new Path(args[1]));

4. 验证jar包结构
   检查jar包中是否包含正确的类文件：

jar tf /home/wasim/Downloads/jar_files/MapReduceDemo.jar | grep WordCounter

确保输出中存在MapReduceDemo/WordCounter.class。

5. 重新打包运行
   修正代码后重新打包，再执行原命令即可。

内容的提问来源于stack exchange，提问作者Wasim_Khan