如何使用std :: priority_queue创建固定大小的最小堆？

问题描述

我可以定义一个最小堆为：

I can define a min heap as:

priority_queue<int, vector<int>, greater> pq;

我有一个整数流。最小堆的大小是固定值k。看起来priority_queue不能这样做。

I have a stream of integers. The min heap's size is a fixed value k. It seems that priority_queue can not do this.

推荐答案

如果你想使用 std :: priority_queue ，将队列的大小限制为 k 元素很简单。注意，你需要使用一个最大堆，而不是一个最小堆，因为你需要知道一个新到达的值是否应该插入堆，如果它小于当前堆的最大值将发生。 / p>

If you want to use std::priority_queue, it's trivial to limit the size of the queue to k elements. Note however that you need to use a max heap, not a min heap, because you need to know whether a newly arrived value should be inserted into the heap, which will happen if it is smaller than the maximum value currently in the heap.

class Topk {
  public:
    Topk(int k) : k_(k) {}
    void insert(int value) {
      if (q_.size() < k_) q_.push(value);
      else if (value < q_.top()) { q_.pop(); q_.push(value); }
    }
    std::vector<int> finalize() {
      std::vector<int> result(q_.size());
      while (q_.size()) {
        result[q_.size() - 1] = q_.top();
        q_.pop();
      }
      return result;
    }
  private:
    int k_;
    std::priority_queue<int> q_;
}

只是使用堆算法并不复杂：

Just using the heap algorithms is really not more complicated:

class Topk {
  public:
    Topk(int k) : k_(k) {}
    void insert(int value) {
      if (c_.size() < k_) {
        c_.push_back(value);
        if (c_.size() == k_) make_heap(c_.begin(), c_.end());
      }
      else if (value < c_[0]) {
        /* See note below */
        pop_heap(c_.begin(), c_.end());
        c_.back() = value;
        push_heap(c_.begin(), c_.end());
      }
    }
    std::vector<int> finalize() {
      if (c_.size() < k_)
        std::sort(c_.begin(), c_.end());
      else
        sort_heap(c_.begin(), c_end());
      std::vector<int> c;
      std::swap(c, c_);
      return std::move(c);
    }
  private:
    /* invariant: if c_.size() == k, then c_ is a maxheap. */
    int k_;
    std::vector<int> c_;
}

注意：< algorithm> 不包括 heap_sift_down 操作，这对于此应用程序是不幸的;可以用swap / sift_down替换pop / swap / push操作。这仍然是O（log k），但它可能稍快一点。

Note: <algorithm> does not include a heap_sift_down operation, which is unfortunate for this application; the pop / swap / push operation could be replaced with swap / sift_down. That's still O(log k), but it is probably slightly faster.

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