LeetCode Hot 100：堆

215. 数组中的第K个最大元素

思路 1：优先队列

class Solution {
public:int findKthLargest(vector<int>& nums, int k) {priority_queue<int> pq;for (int& num : nums)pq.push(num);for (int i = 0; i < k - 1; i++)pq.pop();return pq.top();}
};

思路 2：排序

class Solution {
public:int findKthLargest(vector<int>& nums, int k) {if (k > nums.size())return -1;sort(nums.begin(), nums.end(), greater<int>());return nums[k - 1];}
};

347. 前 K 个高频元素

思路 1：哈希表 + 优先队列

class Solution {
private:class comp {public:bool operator()(const pair<int, int>& p1, const pair<int, int>& p2) {return p1.second > p2.second;}};public:vector<int> topKFrequent(vector<int>& nums, int k) {unordered_map<int, int> hashMap;for (int i = 0; i < nums.size(); i++)hashMap[nums[i]]++;priority_queue<pair<int, int>, vector<pair<int, int>>, comp> pq;for (auto &p : hashMap) {pq.push(p);if (pq.size() > k)pq.pop();}vector<int> ans(k);for (int i = 0; i < k; i++) {ans[i] = pq.top().first;pq.pop();}return ans;}
};

295. 数据流的中位数

思路 1：有序集合 + 双指针

class MedianFinder
{
private:multiset<int> nums;multiset<int>::iterator left, right;public:MedianFinder() : left(nums.end()), right(nums.end()) {}void addNum(int num){const size_t n = nums.size();nums.insert(num);if (n == 0){left = right = nums.begin();}else if (n % 2 == 1){if (num < *left)left--;elseright++;}else{if (num > *left && num < *right){left++;right--;}else if (num >= *right)left++;else{right--;left = right;}}}double findMedian(){return (*left + *right) / 2.0;}
};

思路 2：对顶堆

class MedianFinder {
private:// 大顶堆，top 是其最大的元素，存储小于等于中位数的数priority_queue<int, vector<int>, less<int>> maxHeap;// 小顶堆，top 是其最小的元素，存储大于中位数的数priority_queue<int, vector<int>, greater<int>> minHeap;public:MedianFinder() {}void addNum(int num) {maxHeap.push(num);if (maxHeap.size() > minHeap.size() + 1) {minHeap.push(maxHeap.top());maxHeap.pop();}while (!minHeap.empty() && maxHeap.top() > minHeap.top()) {int x = maxHeap.top(), y = minHeap.top();maxHeap.pop();maxHeap.push(y);minHeap.pop();minHeap.push(x);}}double findMedian() {double res;if ((maxHeap.size() + minHeap.size()) % 2 == 1)res = (double)maxHeap.top();elseres = (maxHeap.top() + minHeap.top()) / 2.0;return res;}
};/*** Your MedianFinder object will be instantiated and called as such:* MedianFinder* obj = new MedianFinder();* obj->addNum(num);* double param_2 = obj->findMedian();*/