Source
Given an array of integers and a number k, the majority number is the number that occurs more than 1/k of the size of the array. Find it. Example Given [3,1,2,3,2,3,3,4,4,4] and k=3, return 3. Note There is only one majority number in the array. Challenge O(n) time and O(k) extra space
题解
Majority Number II 的升级版,有了前两道题的铺垫,此题的思路已十分明了,对 K-1个数进行相互抵消,这里不太可能使用 key1, key2...等变量,用数组使用上不太方便,且增删效率不高,故使用哈希表较为合适,当哈希表的键值数等于 K 时即进行清理,当然更准备地来讲应该是等于 K-1时清理。故此题的逻辑即为:
1. 更新哈希表,若遇哈希表 size == K 时则执行删除操作,
2. 最后遍历哈希表取真实计数器值,返回最大的 key.
Java
public class Solution { /** * @param nums: A list of integers * @param k: As described * @return: The majority number */ public int majorityNumber(ArrayList<Integer> nums, int k) { HashMap<Integer, Integer> hash = new HashMap<Integer, Integer>(); if (nums == null || nums.isEmpty()) return -1; // update HashMap for (int num : nums) { if (!hash.containsKey(num)) { hash.put(num, 1); if (hash.size() >= k) { removeZeroCount(hash); } } else { hash.put(num, hash.get(num) + 1); } } // reset for (int key : hash.keySet()) { hash.put(key, 0); } for (int key : nums) { if (hash.containsKey(key)) { hash.put(key, hash.get(key) + 1); } } // find max int maxKey = -1, maxCount = 0; for (int key : hash.keySet()) { if (hash.get(key) > maxCount) { maxKey = key; maxCount = hash.get(key); } } return maxKey; } private void removeZeroCount(HashMap<Integer, Integer> hash) { Set<Integer> keySet = hash.keySet(); for (int key : keySet) { hash.put(key, hash.get(key) - 1); } /* solution 1 */ Iterator<Map.Entry<Integer, Integer>> it = hash.entrySet().iterator(); while (it.hasNext()) { Map.Entry<Integer, Integer> entry = it.next(); if(entry.getValue() == 0) { it.remove(); } } /* solution 2 */ // List<Integer> removeList = new ArrayList<>(); // for (int key : keySet) { // hash.put(key, hash.get(key) - 1); // if (hash.get(key) == 0) { // removeList.add(key); // } // } // for (Integer key : removeList) { // hash.remove(key); // } /* solution3 lambda expression for Java8 */ } }
源码分析
此题的思路不算很难,但是实现起来还是有点难度的,Java 中删除哈希表时需要考虑线程安全。
复杂度分析
时间复杂度 O(n), 使用了哈希表,空间复杂度 O(k).