java和scala分别实现TopK

最新推荐文章于 2024-12-01 01:00:06 发布

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本文详细介绍了 Spark 的 TopK 实现，包括实例描述、设计思路和代码示例，并探讨了其在热门消费分析、点击量分析、用户浏览量分析、最新热词和热门搜索分析等场景的应用。

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本文是对spark经典例子topK的实现，直接上代码

1. 实例描述

输入：

之前做hadoop时hadoop自带的README.md文件

输出：

(158,)
(28,the)
(19,to)
(18,Spark)
(17,and)
(11,Hadoop)
(10,##)
(8,you)
(8,with)
(8,for)

2. 设计思路

首先实现wordcount，topk实现是以wordcount为基础，在此不再赘述此部分

在分词统计完成后交换key/value，然后调用sortByKey进行排序

3. 代码示例

java实现：

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;

/**
 * Calculate the top k words in a file inputted
 *
 * Created by ćľŠ on 2015/3/20.
 */
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;
        }
    }
}

注：不知为何我在运行代码时报错Exception in thread "main" java.lang.NoSuchMethodError: org.apache.spark.api.java.JavaPairRDD.sortByKey(ZI)Lorg/apache/spark/api/java/JavaPairRDD;

如果出现这个问题，把sortByKey(true, 1)改成sortByKey()就可以了（造成这个问题的原因还不太清楚，怎么会报没有这个方法的错呢，API文档上都是有的）

scala实现：

import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.SparkContext._

/**
 * Created by ćľŠ on 2015/4/1.
 */
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 + ")"))
}

4. 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