2736. Maximum Sum Queries

Description

You are given two 0-indexed integer arrays nums1 and nums2, each of length n, and a 1-indexed 2D array queries where queries[i] = [xi, yi].

For the ith query, find the maximum value of nums1[j] + nums2[j] among all indices j (0 <= j < n), where nums1[j] >= xi and nums2[j] >= yi, or -1 if there is no j satisfying the constraints.

Return an array answer where answer[i] is the answer to the ith query.

 

Example 1:

Input: nums1 = [4,3,1,2], nums2 = [2,4,9,5], queries = [[4,1],[1,3],[2,5]]
Output: [6,10,7]
Explanation: 
For the 1st query xi = 4 and yi = 1, we can select index j = 0 since nums1[j] >= 4 and nums2[j] >= 1. The sum nums1[j] + nums2[j] is 6, and we can show that 6 is the maximum we can obtain.

For the 2nd query xi = 1 and yi = 3, we can select index j = 2 since nums1[j] >= 1 and nums2[j] >= 3. The sum nums1[j] + nums2[j] is 10, and we can show that 10 is the maximum we can obtain. 

For the 3rd query xi = 2 and yi = 5, we can select index j = 3 since nums1[j] >= 2 and nums2[j] >= 5. The sum nums1[j] + nums2[j] is 7, and we can show that 7 is the maximum we can obtain.

Therefore, we return [6,10,7].

Example 2:

Input: nums1 = [3,2,5], nums2 = [2,3,4], queries = [[4,4],[3,2],[1,1]]
Output: [9,9,9]
Explanation: For this example, we can use index j = 2 for all the queries since it satisfies the constraints for each query.

Example 3:

Input: nums1 = [2,1], nums2 = [2,3], queries = [[3,3]]
Output: [-1]
Explanation: There is one query in this example with xi = 3 and yi = 3. For every index, j, either nums1[j] < xi or nums2[j] < yi. Hence, there is no solution. 

 

Constraints:

• nums1.length == nums2.length 
• n == nums1.length 
• 1 <= n <= 105
• 1 <= nums1[i], nums2[i] <= 109 
• 1 <= queries.length <= 105
• queries[i].length == 2
• xi == queries[i][1]
• yi == queries[i][2]
• 1 <= xi, yi <= 109

Solutions

Solution 1: Binary Indexed Tree

This problem belongs to the category of two-dimensional partial order problems.

A two-dimensional partial order problem is defined as follows: given several pairs of points $(a_1, b_1)$, $(a_2, b_2)$, ..., $(a_n, b_n)$, and a defined partial order relation, now given a point $(a_i, b_i)$, we need to find the number/maximum value of point pairs $(a_j, b_j)$ that satisfy the partial order relation. That is:

$$ \left(a_{j}, b_{j}\right) \prec\left(a_{i}, b_{i}\right) \stackrel{\text { def }}{=} a_{j} \lesseqgtr a_{i} \text { and } b_{j} \lesseqgtr b_{i} $$

The general solution to two-dimensional partial order problems is to sort one dimension and use a data structure to handle the second dimension (this data structure is generally a binary indexed tree).

For this problem, we can create an array $nums$, where $nums[i]=(nums_1[i], nums_2[i])$, and then sort $nums$ in descending order according to $nums_1$. We also sort the queries $queries$ in descending order according to $x$.

Next, we iterate through each query $queries[i] = (x, y)$. For the current query, we loop to insert the value of $nums_2$ for all elements in $nums$ that are greater than or equal to $x$ into the binary indexed tree. The binary indexed tree maintains the maximum value of $nums_1 + nums_2$ in the discretized $nums_2$ interval. Therefore, we only need to query the maximum value corresponding to the interval greater than or equal to the discretized $y$ in the binary indexed tree. Note that since the binary indexed tree maintains the prefix maximum value, we can insert $nums_2$ in reverse order into the binary indexed tree in the implementation.

The time complexity is $O((n + m) \times \log n + m \times \log m)$, and the space complexity is $O(n + m)$. Here, $n$ is the length of the array $nums$, and $m$ is the length of the array $queries$.

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Python3JavaC++GoTypeScript

class BinaryIndexedTree:
    __slots__ = ["n", "c"]

    def __init__(self, n: int):
        self.n = n
        self.c = [-1] * (n + 1)

    def update(self, x: int, v: int):
        while x <= self.n:
            self.c[x] = max(self.c[x], v)
            x += x & -x

    def query(self, x: int) -> int:
        mx = -1
        while x:
            mx = max(mx, self.c[x])
            x -= x & -x
        return mx


class Solution:
    def maximumSumQueries(
        self, nums1: List[int], nums2: List[int], queries: List[List[int]]
    ) -> List[int]:
        nums = sorted(zip(nums1, nums2), key=lambda x: -x[0])
        nums2.sort()
        n, m = len(nums1), len(queries)
        ans = [-1] * m
        j = 0
        tree = BinaryIndexedTree(n)
        for i in sorted(range(m), key=lambda i: -queries[i][0]):
            x, y = queries[i]
            while j < n and nums[j][0] >= x:
                k = n - bisect_left(nums2, nums[j][1])
                tree.update(k, nums[j][0] + nums[j][1])
                j += 1
            k = n - bisect_left(nums2, y)
            ans[i] = tree.query(k)
        return ans

class BinaryIndexedTree {
    private int n;
    private int[] c;

    public BinaryIndexedTree(int n) {
        this.n = n;
        c = new int[n + 1];
        Arrays.fill(c, -1);
    }

    public void update(int x, int v) {
        while (x <= n) {
            c[x] = Math.max(c[x], v);
            x += x & -x;
        }
    }

    public int query(int x) {
        int mx = -1;
        while (x > 0) {
            mx = Math.max(mx, c[x]);
            x -= x & -x;
        }
        return mx;
    }
}

class Solution {
    public int[] maximumSumQueries(int[] nums1, int[] nums2, int[][] queries) {
        int n = nums1.length;
        int[][] nums = new int[n][0];