spark-TopK算法

• Case:
  输入：文本文件
  输出：
  (158,)
  (28,the)
  (19,to)
  (18,Spark)
  (17,and)
  (11,Hadoop)
  (10,##)
  (8,you)
  (8,with)
  (8,for)
• 算法：
  首先实现wordcount，topk实现是以wordcount为基础，在分词统计完成后交换key/value，然后调用sortByKey进行排序。
• java

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;import java.io.Serializable;import java.util.Arrays;import java.util.Comparator;import java.util.List;import java.util.regex.Pattern;public class TopK {    public static final Pattern SPACE = Pattern.compile(" ");    public static void main(String[] args)throws Exception {        String inPath = null;        if (args.length == 1) {            inPath = args[0];        } else {            System.out.println("Usage: <src> [des]");        }        SparkConf sparkConf = new SparkConf().setAppName("Word Count");        JavaSparkContext jsc = new JavaSparkContext(sparkConf);        JavaRDD<String> lines = jsc.textFile(inPath);        JavaRDD<String> words = lines.flatMap(new FlatMapFunction<String, String>() {            @Override            public Iterable<String> call(String s) throws Exception {                return Arrays.asList(SPACE.split(s));            }        });        JavaPairRDD<String, Integer> pairs = words.mapToPair(new PairFunction<String, String, Integer>() {            @Override            public Tuple2<String, Integer> call(String s) throws Exception {                return new Tuple2<String, Integer>(s, 1);            }        });        JavaPairRDD<String, Integer> counts = pairs.reduceByKey(new Function2<Integer, Integer, Integer>() {            @Override            public Integer call(Integer i1 , Integer i2) throws Exception {                return i1 + i2;            }        });        JavaPairRDD<Integer, String> converted = counts.mapToPair(new PairFunction<Tuple2<String, Integer>, Integer, String>() {            @Override            public Tuple2<Integer, String> call(Tuple2<String, Integer> tuple) throws Exception {                return new Tuple2<Integer, String>(tuple._2(), tuple._1());            }        });        JavaPairRDD<Integer, String> sorted = converted.sortByKey(true, 1);        List<Tuple2<Integer, String>> topK = sorted.top(5, new Comp());        for(Tuple2<Integer, String> top: topK) {            System.out.println(top._2() + ": " + top._1());        }        jsc.stop();    }}class Comp implements Comparator<Tuple2<Integer, String>>, Serializable {    @Override    public int compare(Tuple2<Integer, String> o1, Tuple2<Integer, String> o2) {        if(o1._1() < o2._1()) {            return -1;        }else if(o1._1() > o2._1()) {            return 1;        }else {            return 0;        }    }}

• scala

import org.apache.spark.{SparkConf, SparkContext}import org.apache.spark.SparkContext._object TopK {  def main(args: Array[String]) {    if (args.length != 2) {      System.out.println("Usage: <src> <num>")      System.exit(1)    }    val conf = new SparkConf().setAppName("TopK")    val sc = new SparkContext(conf)    val lines = sc.textFile(args(0))    val ones = lines.flatMap(_.split(" ")).map(word => (word, 1))    val count = ones.reduceByKey((a, b) => a + b)    val convert = count.map {      case (key, value) => (value, key)    }.sortByKey(true, 1)    convert.top(args(1).toInt).foreach(a => System.out.println("(" + a._2 + "," + a._1 + ")"))}

• 应用场景：
  TopK模型常用于分析消费者热门消费分析、网站/博客点击量、用户浏览量分析，最新热词及热门搜索等的分析处理