知识点
[https://blog.csdn.net/catoop/article/details/50630106](StringTokenizer 用法)，在大数据操作时， StringTokenizer 性能要优于 split 和 substring 方法
代码
/**
* Definition of OutputCollector:
* class OutputCollector<K, V> {
* public void collect(K key, V value);
* // Adds a key/value pair to the output buffer
* }
*/
public class WordCount {
public static class Map {
public void map(String key, String value, OutputCollector<String, Integer> output) {
// Write your code here
// Output the results into output buffer.
// Ps. output.collect(String key, int value);
StringTokenizer tokenizer = new StringTokenizer(value);
while (tokenizer.hasMoreTokens()) {
String word = tokenizer.nextToken();
output.collect(word, 1);
}
}
}
// 将同一个 key 的所有 value 聚集到同一个集合中
public static class Reduce {
public void reduce(String key, Iterator<Integer> values,
OutputCollector<String, Integer> output) {
// Write your code here
// Output the results into output buffer.
// Ps. output.collect(String key, int value);
int sum = 0;
while (values.hasNext()) {
sum += values.next();
}
output.collect(key, sum);
}
}
}```