要按降序排列数据，需要另一个 mapreduce 工作。Map器将发出“关注者数量”作为键，twitter句柄作为值。

class SortingMap extends Map<LongWritable, Text, LongWritable, Text> {
    private Text value = new Text();
    private LongWritable key = new LongWritable(0);

    @Overwrite
    public void map(LongWritable key, Text value, Context context) throws IOException {
        String line = value.toString();
        // Assuming that the input data is "TweeterId <number of follower>" separated by tab
        String tokens[] = value.split(Pattern.quote("\t"));
        if(tokens.length > 1) {
            key.set(Long.parseLong(tokens[1]));
            value.set(tokens[0]);
            context.write(key, value);
        }
    }
}

对于减速器，使用 IdentityReducer<K,V> ```
// SortedComparator Class

public class DescendingOrderKeyComparator extends WritableComparator {
@Override
public int compare(WritableComparable w1, WritableComparable w2) {
return -1 * w1.compareTo(w2);
}
}

在driver类中，设置 `SortedComparator` ```
job.setSortComparatorClass(DescendingOrderKeyComparator.class);

如果你有大的输入文件的格式 user_id = number_of_followers 一种简单的Map归约算法来寻找顶部 N 用户是：
每个Map器处理自己的输入，并在其文件中找到前n个用户，然后将它们写入一个reducer
单减速机接收 number_of_mappers * N 行并查找其中前n个用户