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Top K Frequent Elements

描述​

Given a non-empty array of integers, return the k most frequent elements.

Example 1:

Input: nums = [1,1,1,2,2,3], k = 2
Output: [1,2]

Example 2:

Input: nums = [1], k = 1
Output: [1]

Note:

  • You may assume k is always valid, 1 ≤ k ≤ number of unique elements.
  • Your algorithm's time complexity must be better than O(n log n), where n is the array's size.
  • It's guaranteed that the answer is unique, in other words the set of the top k frequent elements is unique.
  • You can return the answer in any order.

分析​

看到 Top K, 很显然，用堆。先用一个 HashMap 统计每个元素出现的频率，然后建立一个大小为k的小根堆，按照频率排序，堆顶就是频率最小的元素，遍历 HashMap，将元素不断压入堆，当堆大小达到 k 时，压入一个并弹出一个，保持堆的大小恒定为 k，最后，堆中的 k 个元素就是频率最高 k 个元素，将堆转换为数组，就是所求的结果。时间复杂度 O(nlogk)，空间复杂度 O(n+k)。

代码​

// Top K Frequent Elements
// HashMap + Min Heap
// Time Complexity: O(nlogk), Space Complexity: O(n+k)
class Solution {
    public int[] topKFrequent(int[] nums, int k) {
        Map<Integer, Integer> m = new HashMap<>();
        for (int x: nums) {
          m.merge(x, 1, Integer::sum);
        }

        // Min heap, sorted by frequency
        PriorityQueue<Integer> pq = new PriorityQueue<>(
            (x, y) -> m.get(x) - m.get(y));

        for (int x: m.keySet()) {
          pq.offer(x);
          if (pq.size() > k) pq.poll();
        }

        int[] top = new int[k];
        for(int i = k - 1; i >= 0; --i) {
            top[i] = pq.poll();
        }
        return top;
    }
}

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