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Intersection of Two Arrays II

描述​

Given two arrays, write a function to compute their intersection.

Example 1:

Input: nums1 = [1,2,2,1], nums2 = [2,2]
Output: [2,2]

Example 2:

Input: nums1 = [4,9,5], nums2 = [9,4,9,8,4]
Output: [4,9]

Note:

  • Each element in the result should appear as many times as it shows in both arrays.
  • The result can be in any order.

分析​

思路一，可以把两个数组排序，然后用两个指针，同时遍历两个数组，时间复杂度 O(nlogn+mlogm)，空间复杂度 O(logm + logn) 到 O(m+n) 之间，取决于排序算法。

思路二，基于较短的那个数组建立一个 HashMap, key 为整数, value 为出现次数，然后遍历另一个数组, 碰到一次就把哈希表里的值减一，并把该数加入到交集中，等于 0 则跳过。时间复杂度 O(m + n))，空间复杂度 O(min(m + n))。

代码​

排序​

// Intersection of Two Arrays II
// Sort
// Time Complexity: O(mlogm+nlogn)
// Space Complexity:  from O(logm+logn) to O(n+m), depending
// on the implementation of the sorting algorithm.
class Solution {
    public int[] intersect(int[] nums1, int[] nums2) {
        Arrays.sort(nums1);
        Arrays.sort(nums2);
        int i = 0, j = 0, k = 0;
        while (i < nums1.length && j < nums2.length) {
            if (nums1[i] < nums2[j]) {
                ++i;
            } else if (nums1[i] > nums2[j]) {
                ++j;
            } else {
                nums1[k++] = nums1[i++];
                ++j;
            }
        }
        return Arrays.copyOfRange(nums1, 0, k);
    }
}

HashMap​

// Intersection of Two Arrays II
// HashMap
// Time Complexity: O(m + n), Space Complexity:  O(min(m + n))
class Solution {
    public int[] intersect(int[] nums1, int[] nums2) {
        if (nums1.length > nums2.length) return intersect(nums2, nums1);

        Map<Integer, Integer> m = new HashMap<>();
        for (int x : nums1) {
            m.merge(x, 1, Integer::sum);
        }

        int k = 0;
        for (int x : nums2) {
            int count = m.getOrDefault(x, 0);
            if (count > 0) {
                nums1[k++] = x;
                m.put(x, count - 1);
            }
        }
        return Arrays.copyOfRange(nums1, 0, k);
    }
}

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