大数据算法设计模式(1) - topN spark实现

topN算法，spark实现

package com.kangaroo.studio.algorithms.topn;

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 org.apache.spark.broadcast.Broadcast;
import scala.Tuple2;

import java.io.Serializable;
import java.util.*;

public class TopnSpark implements Serializable {

    private JavaSparkContext jsc;
    Broadcast<Integer> topNum;
    private String inputPath;

    /*
    *   构造函数
    *   1. 初始化JavaSparkContext
    *   2. 初始化广播变量topN个数, 可以被所有partition共享
    *   3. 初始化输入路径
    * */
    public TopnSpark(Integer Num, String path) {
        jsc = new JavaSparkContext();
        topNum = jsc.broadcast(Num);
        inputPath = path;
    }

    /*
    *   程序入口函数
    * */
    public void run() {
        /*
        *   读入inputPath中的数据
        * */
        JavaRDD<String> lines = jsc.textFile(inputPath, 1);

        /*
        *   将rdd规约到9个分区
        * */
        JavaRDD<String> rdd = lines.coalesce(9);

        /*
        *   将输入转化为kv格式
        *   key是规约的主键, value是排序参考的个数
        *   注: 这里的key并不唯一, 即相同的key可能有多条记录, 所以下面我们规约key成唯一键
        *   输入:line, 输出:kv
        * */
        JavaPairRDD<String, Integer> kv = rdd.mapToPair(new PairFunction<String, String, Integer>() {
            public Tuple2<String, Integer> call(String s) throws Exception {
                String[] tokens = s.split(",");
                return new Tuple2<String, Integer>(tokens[0], Integer.parseInt(tokens[1]));
            }
        });

        /*
        *   规约主键成为唯一键
        *   输入:kv, 输出:kv
        * */
        JavaPairRDD<String, Integer> uniqueKeys = kv.reduceByKey(new Function2<Integer, Integer, Integer>() {
            public Integer call(Integer i1, Integer i2) throws Exception {
                return i1 + i2;
            }
        });

        /*
        *   计算各个分区的topN
        *   这里通过广播变量拿到了topN具体个数, 每个分区都保留topN, 所有分区总个数: partitionNum * topN
        *   输入:kv, 输出:SortMap, 长度topN
        * */
        JavaRDD<SortedMap<Integer, String>> partitions = uniqueKeys.mapPartitions(new FlatMapFunction<Iterator<Tuple2<String,Integer>>, SortedMap<Integer, String>>() {
            public Iterable<SortedMap<Integer, String>> call(Iterator<Tuple2<String, Integer>> iter) throws Exception {
                final int N = topNum.getValue();
                SortedMap<Integer, String> topN = new TreeMap<Integer, String>();
                while (iter.hasNext()) {
                    Tuple2<String, Integer> tuple = iter.next();
                    topN.put(tuple._2, tuple._1);

                    if (topN.size() > N) {
                        topN.remove(topN.firstKey());
                    }
                }
                return Collections.singletonList(topN);
            }
        });

        /*
        *   规约所有分区的topN SortMap, 得到最终的SortMap, 长度topN
        *   reduce过后, 数据已经到了本地缓存, 这是最后结果
        *   输入: SortMap, 长度topN, 当然有partitionNum个, 输出:SortMap, 长度topN
        * */
        SortedMap<Integer, String> finalTopN = partitions.reduce(new Function2<SortedMap<Integer, String>, SortedMap<Integer, String>, SortedMap<Integer, String>>() {
            public SortedMap<Integer, String> call(SortedMap<Integer, String> m1, SortedMap<Integer, String> m2) throws Exception {
                final int N = topNum.getValue();
                SortedMap<Integer, String> topN = new TreeMap<Integer, String>();
                for (Map.Entry<Integer, String> entry : m1.entrySet()) {
                    topN.put(entry.getKey(), entry.getValue());
                    if (topN.size() > N) {
                        topN.remove(topN.firstKey());
                    }
                }
                for (Map.Entry<Integer, String> entry : m2.entrySet()) {
                    topN.put(entry.getKey(), entry.getValue());
                    if (topN.size() > N) {
                        topN.remove(topN.firstKey());
                    }
                }
                return topN;
            }
        });

        /*
        *   将本地缓存的最终结果打印出来
        * */
        for (Map.Entry<Integer, String> entry : finalTopN.entrySet()) {
            System.out.println(entry.getKey() + " -- " + entry.getValue());
        }
    }

    public static void main(String[] args) {
        String inputPath = args[0];
        TopnSpark topnMapper = new TopnSpark(10, inputPath);
        topnMapper.run();

    }
}