语法看起来是正确的，我已经测试了2.5纱mr2与以下它的工作：

hadoop jar hadoop-mapreduce-examples.jar wordcount -Dmapreduce.job.reduces=5 input output

最可能的问题是驱动程序类没有实现toolrunner，它与GenericOptions Parser协同工作来解析通用命令行参数。
下面是如何在mapreduce驱动程序类中实现toolrunner的示例：

// imports ignored

public class ExampleDriver extends Configured implements Tool {

    public int run(String[] args) throws Exception {
        if (args.length != 2) {
            System.err.println("Usage: ExampleDriver <in> <out>");
            System.exit(2);
        }

        Configuration conf = getConf();
        Job job = Job.getInstance(conf);

        job.setJobName("example driver");
        job.setJarByClass(ExampleDriver.class);
        job.setMapperClass(YourMapper.class);
        job.setReducerClass(YourReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

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

        int ret = job.waitForCompletion(true) ? 0 : 1;

        return ret;
    }

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