实时输出topk最频繁变动的股价

网上看到了一道关于bloomburg的面试题，follow 评论的思路 自己试着写了一个HashHeap的实现。

基本思路是维护一个大小为K的最小堆，里面是topK股价变动的公司ID（假设ID是Integer）

HashHeap中维护一个companyIdHeap 之外还有一个HashMap 它的key 是CompanyId， value是Company信息 此处我假设company信息包含这个company在companyIdHeap中的index （这个index可以使delete function的复杂度降到O（logK））和它的股价变化了多少次

每当有新的估价更新，假设应用会调用HashHeap的add函数 输入是当前股价变化的公司ID 然后更新 hashmap 和 根据当前heap size更新companyIdHeap

在更新companyIdHeap的时候 如果这个变化的公司的股价变化次数大于最小堆的root 那么替换掉这个root 然后从0向下调整heap heap调整的比较条件是看谁的股价变化次数少

delete函数直接delete掉一个company O（logK）

poll函数是给heap root的company的股价变化次数减一（其实还没想好这个函数具体应该做什么 暂时把它放在注释里面）

不足之处请指出！ 多谢！

 package Heap;

 import java.util.*;

 public class HashHeap {
     //a list of companyId
     private List<Integer> companyIdHeap;
     private int size_t;
     //map from companyId to Node {index in heap and frequent}
     private Map<Integer, Node> companyToFrequent;
     private String mode; //min or max
     private int K;
     class Node{
         public int index;
         public int frequent;
         public Node (int index, int fre){
             this.index= index;
             this.frequent = fre;
         }
         public Node(Node node){
             this.index = node.index;
             this.frequent = node.frequent;
         }
     }

     public HashHeap(int K){
         this.companyIdHeap = new ArrayList<Integer>();
         this.size_t =0;
         this.companyToFrequent = new HashMap<Integer, Node>();
         mode = "min";
         this.K = K;
     }

     public int peek(){
         if(!companyIdHeap.isEmpty())
             return companyIdHeap.get(0);
         return -1;
     }

     public int size(){
         return size_t;
     }

     public boolean empty(){
         return companyIdHeap.size()==0;
     }

     public int parent(int id){
         if(id==0){
             return -1;
         }
         return (id-1)/2;
     }

     public int lson(int id){
         return 2*id +1;
     }

     public int rson(int id){
         return 2*id+2;
     }

     public boolean compare(int companyA, int companyB){
         if(companyToFrequent.get(companyA).frequent<companyToFrequent.get(companyB).frequent){
             if(mode.equals("min")){
                 return true;
             }else{
                 return false;
             }
         }else{
             if(mode.equals("min")){
                 return false;
             }else{
                 return true;
             }
         }
     }

     public void swap(int indexA, int indexB){
         int companyA = companyIdHeap.get(indexA);
         int companyB = companyIdHeap.get(indexB);
         Node compNodeA = companyToFrequent.get(companyA);
         Node compNodeB = companyToFrequent.get(companyB);
         companyIdHeap.set(indexA, companyB);
         companyIdHeap.set(indexB, companyA);
         companyToFrequent.put(companyA, new Node(indexB, compNodeA.frequent));
         companyToFrequent.put(companyB, new Node(indexA, compNodeB.frequent));
     }

     public void siftup(int index){
         while(parent(index)>-1){
             int parent = parent(index);
             if(compare(companyIdHeap.get(parent), companyIdHeap.get(index))){
                 break;
             }else{
                 swap(parent, index);
             }
             index = parent;
         }
     }

     public void siftdown(int index){
         while(lson(index)< companyIdHeap.size()){
             int leftSon = lson(index);
             int rightSon = rson(index);
             int son = rightSon;
             if(rightSon>=companyIdHeap.size()||compare(companyIdHeap.get(leftSon),companyIdHeap.get(rightSon))){
                 son = leftSon;
             }
             if(compare(companyIdHeap.get(index), companyIdHeap.get(son))){
                 break;
             }else{
                 swap(index, son);
             }
             index=son;
         }

     }

     public void add(int company){
         //update hashmap
         if(companyToFrequent.containsKey(company)){
             Node node = companyToFrequent.get(company);
             companyToFrequent.put(company, new Node(node.index, node.frequent+1));
         }else{
             companyToFrequent.put(company, new Node(-1, 1));
         }
         //update heap
         Node node = companyToFrequent.get(company);
         if(this.size_t==K){
             //if heap need to be updated
             if(compare(peek(), company)){
                 companyIdHeap.set(0, company);
                 companyToFrequent.put(company, new Node(0, node.frequent));
                 siftdown(0);
             }
             return;
         }
         companyIdHeap.add(company);
         size_t++;
         companyToFrequent.put(company, new Node(companyIdHeap.size()-1, node.frequent));
         siftup(companyIdHeap.size()-1);
     }

     public void delete(int company){
         if(companyToFrequent.containsKey(company)){
             Node node = companyToFrequent.get(company);
             int index = node.index;
             swap(index, companyIdHeap.size()-1);
             companyIdHeap.remove(companyIdHeap.size()-1);
             companyToFrequent.remove(company);
             size_t--;
             //the condition will be false if index == companyIdHeap.size()-1 before
             if(index<companyIdHeap.size()){
                 siftup(index);
                 siftdown(index);
             }
         }
     }

     /*public int poll(){
         int res = companyIdHeap.get(0);
         Node node = companyToFrequent.get(res);
         if(node.frequent==1){
             size_t--;
             swap(0, companyIdHeap.size()-1);
             companyIdHeap.remove(companyIdHeap.size()-1);
             companyToFrequent.remove(res);
             // the condition will be true is companyIdHeap.size() == 1 before
             if(companyIdHeap.size()>0){
                 siftdown(0);
             }
         }else{
             companyToFrequent.put(res, new Node(0, node.frequent-1));
         }

         return res;
     }*/
 }