hadoop统计以a和b字母开头的单词的个数

你可以使用Hadoop的MapReduce编程模型来实现统计以a和b字母开头的单词的个数。以下是一个可能的实现步骤：

1. 编写一个Mapper类，将输入的文本文件拆分成单词，并标记以a或b字母开头的单词。
2. 编写一个Reducer类，对标记过的单词进行计数。
3. 配置Hadoop作业的输入和输出路径，并指定Mapper和Reducer类。
4. 运行Hadoop作业并等待结果。

以下是一个可能的Mapper和Reducer实现示例：

public class ABWordsMapper 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();
        StringTokenizer tokenizer = new StringTokenizer(line);

        while (tokenizer.hasMoreTokens()) {
            String token = tokenizer.nextToken();
            if (token.startsWith("a") || token.startsWith("b")) {
                word.set(token);
                context.write(word, one);
            }
        }
    }
}

public class ABWordsReducer 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);
    }
}

配置Hadoop作业的输入和输出路径：

Job job = Job.getInstance(conf, "AB word count");
job.setJarByClass(ABWordCount.class);
job.setMapperClass(ABWordsMapper.class);
job.setCombinerClass(ABWordsReducer.class);
job.setReducerClass(ABWordsReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));

运行Hadoop作业：

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

注意：以上代码示例仅供参考，实际实现可能需要根据具体情况进行修改。