What is the most efficient way to solve the "Find the Kth Largest Integer in the Array" problem?

Using a heap (priority queue) is often the most efficient solution as it maintains the kth largest integer in O(n log k) time complexity.

How do I compare string numbers to find the largest integer?

String numbers should be compared numerically, which requires handling different string lengths correctly by considering their numeric values.

What is the time complexity of sorting the array for this problem?

The time complexity of sorting the array is O(n log n), where n is the length of the array.

How does Quickselect help with this problem?

Quickselect helps by reducing the time complexity to O(n) on average, allowing you to find the kth largest element without sorting the entire array.

What happens if the numbers in the array are not unique?

Even if numbers are duplicated, they are counted distinctly. For example, repeated numbers will still occupy their respective largest positions in the order.

#1985

Medium

auto_awesome数组·string

LeetCode 题解工作台

找出数组中的第 K 大整数

给你一个字符串数组 nums 和一个整数 k 。 nums 中的每个字符串都表示一个不含前导零的整数。返回 nums 中表示第 k 大整数的字符串。注意：重复的数字在统计时会视为不同元素考虑。例如，如果 nums 是 ["1","2","2"] ，那么 "2" 是最大的整数， "2" 是第二大…

数组字符串分治排序堆（优先队列）

题目描述

给你一个字符串数组 nums 和一个整数 k 。nums 中的每个字符串都表示一个不含前导零的整数。

返回 nums 中表示第 k 大整数的字符串。

注意：重复的数字在统计时会视为不同元素考虑。例如，如果 nums 是 ["1","2","2"]，那么 "2" 是最大的整数，"2" 是第二大的整数，"1" 是第三大的整数。

示例 1：

输入：nums = ["3","6","7","10"], k = 4
输出："3"
解释：
nums 中的数字按非递减顺序排列为 ["3","6","7","10"]
其中第 4 大整数是 "3"

示例 2：

输入：nums = ["2","21","12","1"], k = 3
输出："2"
解释：
nums 中的数字按非递减顺序排列为 ["1","2","12","21"]
其中第 3 大整数是 "2"

示例 3：

输入：nums = ["0","0"], k = 2
输出："0"
解释：
nums 中的数字按非递减顺序排列为 ["0","0"]
其中第 2 大整数是 "0"

提示：

1 <= k <= nums.length <= 10⁴
1 <= nums[i].length <= 100
nums[i] 仅由数字组成
nums[i] 不含任何前导零

lightbulb

解题思路

方法一：排序或快速选择

我们可以将 $\textit{nums}$ 数组中的字符串按照整数从大到小排序，然后取第 $k$ 个元素即可。也可以使用快速选择算法，找到第 $k$ 大的整数。

时间复杂度 $O(n \times \log n)$ 或 $O(n)$ ，其中 $n$ 是 $\textit{nums}$ 数组的长度。空间复杂度 $O(\log n)$ 或 $O(1)$ 。

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class Solution:
    def kthLargestNumber(self, nums: List[str], k: int) -> str:
        return nlargest(k, nums, key=lambda x: int(x))[k - 1]

speed

复杂度分析

指标	值
时间	Depends on the final approach
空间	Depends on the final approach

psychology

面试官常问的追问

外企场景

question_mark
Look for understanding of string comparison versus numerical comparison.
question_mark
Test knowledge of heap data structures, especially in maintaining kth largest elements.
question_mark
Evaluate efficiency considerations between sorting, heaps, and Quickselect.

warning

常见陷阱

外企场景

error
Misunderstanding how to compare strings numerically, particularly when strings have different lengths.
error
Overusing sorting when a more efficient heap or Quickselect approach could be applied.
error
Confusing the ordering of integers and failing to handle duplicates correctly.

swap_horiz

进阶变体

外企场景

arrow_right_alt
Find the kth smallest integer in the array instead of the kth largest.
arrow_right_alt
Handle an array of numbers with leading zeros.
arrow_right_alt
Consider a scenario where k equals the length of the array.

help

常见问题

外企场景

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