利用Java的Spark做单词统计并排序

import java.util.ArrayList;import java.util.Arrays;import java.util.Collections;import java.util.HashMap;import java.util.List;import java.util.Map;import java.util.Comparator;import org.apache.spark.SparkConf;import org.apache.spark.api.java.JavaPairRDD;import org.apache.spark.api.java.JavaRDD;import org.apache.spark.api.java.JavaSparkContext;import org.apache.spark.api.java.function.FlatMapFunction;import org.apache.spark.api.java.function.Function2;import org.apache.spark.api.java.function.PairFunction;import scala.Tuple2;public class Demo {    public static void main(String[] args) {        String filename = "/home/iiip/PycharmProjects/InterestModel/data/sample/机器学习/D0002033.txt";        Demo demo = new Demo();        demo.CountWord(filename);    }    public List<Map.Entry<String, Integer>> CountWord(String filename) {        SparkConf conf = new SparkConf();        conf.set("Spark.testing.memory", "2147480000");        JavaSparkContext sc = new JavaSparkContext("local[*]", "Spark", conf);        JavaRDD<String> lines = sc.textFile(filename);   // 读取文件的每一行        JavaRDD<String> words = lines.flatMap(new FlatWord());    // 从每一个行中读取单个的词        JavaPairRDD<String, Integer> wordsPair = words.mapToPair(new MapOne()); // 将词语做成<key,Value>键值对        JavaPairRDD<String , Integer> wordWithNum = wordsPair.reduceByKey(new WordCount());  // 对<key,Value>做一个Reduce操作        List<Tuple2<String, Integer>>  result = wordWithNum.collect(); // 获取结果        Map<String, Integer> map = new HashMap<String , Integer> ();        for(Tuple2<String , Integer> tuple : result){            map.put(tuple._1(), tuple._2());        }        //根据结果的键值对, 按值排序        List<Map.Entry<String, Integer>> sortedWord = new ArrayList<Map.Entry<String, Integer>>(map.entrySet());        Collections.sort(sortedWord, new Comparator<Map.Entry<String, Integer>>(){            public int compare(Map.Entry<String, Integer> o1, Map.Entry<String, Integer> o2){                return (o2.getValue() - o1.getValue());            }        });        for(Map.Entry<String, Integer> word : sortedWord){            System.out.println(word.getKey() + "   " + word.getValue());        }        return sortedWord;    }    static class FlatWord implements FlatMapFunction<String, String>{         // 将每个单词映射成为单个元素        @Override        public Iterable<String> call(String sentence) throws Exception {            String[] words = sentence.split(" ");            return Arrays.asList(words);        }    }    static class MapOne implements PairFunction<String, String, Integer>{        @Override        public Tuple2<String, Integer> call(String word){            return new Tuple2<String, Integer>(word, 1);        }    }    static class WordCount implements Function2<Integer, Integer , Integer>{        @Override        public Integer call(Integer i1, Integer i2){            return i1 + i2;        }    }}