What is the best approach to solve Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit?

The best approach is using a sliding window technique that maintains the maximum and minimum values of the current subarray, expanding and contracting the window based on the absolute difference condition.

How do I handle large arrays efficiently for this problem?

For large arrays, you should use a sliding window approach with data structures like deques or multisets that allow for efficient tracking of the window's maximum and minimum values in O(1) time.

Why is the sliding window approach optimal for this problem?

The sliding window approach ensures that each element is processed only once, leading to an O(n) time complexity. This is much more efficient than checking every pair of elements directly.

What are some common mistakes in solving this problem?

Common mistakes include not correctly adjusting the window when the absolute difference exceeds the limit, and using inefficient data structures for tracking the max/min values.

How can GhostInterview help me solve problems like Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit?

GhostInterview provides targeted practice on sliding window techniques and helps you master optimal data structures for maintaining dynamic ranges in problems like this.

#1438

Medium

auto_awesome滑动窗口（状态滚动更新）

LeetCode 题解工作台

绝对差不超过限制的最长连续子数组

给你一个整数数组 nums ，和一个表示限制的整数 limit ，请你返回最长连续子数组的长度，该子数组中的任意两个元素之间的绝对差必须小于或者等于 limit 。示例 1：输入： nums = [8,2,4,7], limit = 4 输出： 2 解释：所有子数组如下： [8] 最大绝对差 …

数组队列滑动窗口堆（优先队列）有序集合

题目描述

给你一个整数数组 nums ，和一个表示限制的整数 limit，请你返回最长连续子数组的长度，该子数组中的任意两个元素之间的绝对差必须小于或者等于 limit。

示例 1：

输入：nums = [8,2,4,7], limit = 4
输出：2 
解释：所有子数组如下：
[8] 最大绝对差 |8-8| = 0 <= 4.
[8,2] 最大绝对差 |8-2| = 6 > 4. 
[8,2,4] 最大绝对差 |8-2| = 6 > 4.
[8,2,4,7] 最大绝对差 |8-2| = 6 > 4.
[2] 最大绝对差 |2-2| = 0 <= 4.
[2,4] 最大绝对差 |2-4| = 2 <= 4.
[2,4,7] 最大绝对差 |2-7| = 5 > 4.
[4] 最大绝对差 |4-4| = 0 <= 4.
[4,7] 最大绝对差 |4-7| = 3 <= 4.
[7] 最大绝对差 |7-7| = 0 <= 4. 
因此，满足题意的最长子数组的长度为 2 。

示例 2：

输入：nums = [10,1,2,4,7,2], limit = 5
输出：4 
解释：满足题意的最长子数组是 [2,4,7,2]，其最大绝对差 |2-7| = 5 <= 5 。

示例 3：

输入：nums = [4,2,2,2,4,4,2,2], limit = 0
输出：3

提示：

1 <= nums.length <= 10⁵
1 <= nums[i] <= 10⁹
0 <= limit <= 10⁹

lightbulb

解题思路

方法一：有序集合 + 滑动窗口

我们可以枚举每个位置作为子数组的右端点，找到其对应的最靠左的左端点，满足区间内中最大值与最小值的差值不超过 $limit$ 。过程中，我们用有序集合维护窗口内的最大值和最小值。

时间复杂度 $O(n \times \log n)$ ，空间复杂度 $O(n)$ 。其中 $n$ 是数组 nums 的长度。

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class Solution:
    def longestSubarray(self, nums: List[int], limit: int) -> int:
        sl = SortedList()
        ans = j = 0
        for i, x in enumerate(nums):
            sl.add(x)
            while sl[-1] - sl[0] > limit:
                sl.remove(nums[j])
                j += 1
            ans = max(ans, i - j + 1)
        return ans

speed

复杂度分析

指标	值
时间	O(n)
空间	O(n)

psychology

面试官常问的追问

外企场景

question_mark
Look for understanding of sliding window techniques.
question_mark
Evaluate how efficiently the candidate handles window adjustments and tracking of max/min values.
question_mark
Assess the ability to explain why O(n) time complexity is achievable.

warning

常见陷阱

外企场景

error
Failing to update the window correctly when the absolute difference exceeds the limit.
error
Using inefficient data structures for tracking max/min values, leading to suboptimal time complexity.
error
Not handling edge cases such as very small arrays or large limit values properly.

swap_horiz

进阶变体

外企场景

arrow_right_alt
Allowing the subarray to contain negative numbers and adjusting the absolute difference condition.
arrow_right_alt
Extending the problem to find the sum of elements in the longest subarray that meets the condition.
arrow_right_alt
Modifying the condition to check for differences in specific positions within the subarray instead of all pairs.

help

常见问题

外企场景

继续练习

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