调用 MapReduce 对文件中的特殊字符和空格进行数据清洗，并对文件中各个单词出现的次数进行统计

可以使用MapReduce对文件进行数据清洗，并对文件中各个单词出现的次数进行统计，同时将特殊字符和空格进行清洗，具体步骤如下：

1. 编写Mapper类，将每个单词作为键，将值设置为1，输出键值对。在Mapper中使用正则表达式去除特殊字符和空格。

public class WordCountMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        String line = value.toString();
        line = line.replaceAll("[^a-zA-Z0-9 ]", "").toLowerCase();
        StringTokenizer tokenizer = new StringTokenizer(line);
        while (tokenizer.hasMoreTokens()) {
            word.set(tokenizer.nextToken());
            context.write(word, one);
        }
    }
}

2. 编写Reducer类，对相同键的值进行求和。

public class WordCountReducer 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);
    }
}

3. 编写Main方法，设置Job的输入输出路径，并运行MapReduce程序。

public class WordCount {
    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(WordCountMapper.class);
        job.setCombinerClass(WordCountReducer.class);
        job.setReducerClass(WordCountReducer.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);
    }
}

4. 将以上代码打包成可执行的jar文件，并将jar文件传入Hadoop集群，然后在命令行中运行以下命令：

hadoop jar WordCount.jar WordCount input output

其中，`WordCount`是程序名称，`input`是输入文件路径，`output`是输出文件路径。

运行成功后，输出文件中将包含每个单词出现的次数。同时，经过Mapper的处理，文件中的特殊字符和空格已经被清洗掉了。