[NeetCode 150] Merge K Sorted Linked Lists

Merge K Sorted Linked Lists

You are given an array of k linked lists lists, where each list is sorted in ascending order.

Return the sorted linked list that is the result of merging all of the individual linked lists.

Example 1:

复制代码
Input: lists = [[1,2,4],[1,3,5],[3,6]]

Output: [1,1,2,3,3,4,5,6]

Example 2:

复制代码
Input: lists = []

Output: []

Example 3:

复制代码
Input: lists = [[]]

Output: []

Constraints:

复制代码
0 <= lists.length <= 1000
0 <= lists[i].length <= 100
-1000 <= lists[i][j] <= 1000

Solution

To take advantage of the feature that each list is sorted in ascending order, it is OK to use O ( number of elements in 2 lists ) O(\text{number of elements in 2 lists}) O(number of elements in 2 lists) two pointers method to merge 2 ordered lists. The overall time complexity will be O ( number of all elements × number of linked lists ) O(\text{number of all elements}\times \text{number of linked lists}) O(number of all elements×number of linked lists).

We can accelerate this process by a simple priority queue, reducing the time complexity to O ( n log ⁡ n ) O(n\log n) O(nlogn), where n n n denotes the total number of all elements in linked lists.

However, by using hash, or bucket sort, wo can achieve O ( V ) O(V) O(V) time complexity, where V V V denotes the size of the discrete value domain of elements, and V ≤ n V\le n V≤n. Additionally, it does not require the given linked lists to be ordered.

To be more detailed, we can use a dictionary to store the nodes of different values and link them together in the end. The code might look like:

python 复制代码
# Definition for singly-linked list.
# class ListNode:
#     def __init__(self, val=0, next=None):
#         self.val = val
#         self.next = next

class Solution:    
    def mergeKLists(self, lists: List[Optional[ListNode]]) -> Optional[ListNode]:
        buket = {number:None for number in range(-1000, 1001)}
        for node in lists:
            while node.next:
                buket[node.val].append(node)
                node = node.next
            buket[node.val].append(node)
        preNode = None
        rootNode = None
        for value in buket.values():
            for node in value:
                if preNode:
                    preNode.next = node
                else:
                    rootNode = node
                preNode = node
        return rootNode

However, that is not perfect! As the elements are all stored in linked lists, we only need to store the head and tail nodes of each value. When a new element coming in, we just link it as the new head/tail. In the end, we only need to link head and tail of different values' linked list one by one. This method only takes O ( V ) O(V) O(V) extra space and O ( V ) O(V) O(V) time to link.

Code

Please ignore the typo of "bucket".

python 复制代码
# Definition for singly-linked list.
# class ListNode:
#     def __init__(self, val=0, next=None):
#         self.val = val
#         self.next = next

class Solution:    
    def mergeKLists(self, lists: List[Optional[ListNode]]) -> Optional[ListNode]:
        head_buket = {}
        tail_buket = {}
        for node in lists:
            while True:
                if node.val not in tail_buket:
                    tail_buket[node.val] = node
                nextNode = node.next
                node.next = head_buket.get(node.val, None)
                head_buket[node.val] = node
                node = nextNode
                if node is None:
                    break
        preNode = None
        rootNode = None
        for key in range(-1000, 1001):
            if key in head_buket:
                if preNode is None:
                    rootNode = head_buket[key]
                else:
                    preNode.next = head_buket[key]
                preNode = tail_buket[key] 
        return rootNode
相关推荐
(Charon)2 分钟前
【C++面试】手写智能指针(二):从shared_ptr理解引用计数与共享所有权
c++·算法
一条大祥脚11 分钟前
26 ICPC上海 交互|二分|重心|构造|二分图|贪心|SOSDP|三进制枚举|线性基|字典序贪心|DFS|分块|单侧递归线段树
算法·深度优先·交互·分块·icpc上海站·单侧递归线段树
言乐615 分钟前
Python根据关联词搜索模型
开发语言·人工智能·python·机器学习·django
吹什么轩17 分钟前
数据结构复习:二叉搜索树
数据结构·算法
H.莓飛19 分钟前
【数据结构】堆
linux·数据结构·算法
纪念 22928 分钟前
C++算法(二)
开发语言·c++·算法
lie..37 分钟前
30天从零开始学AI应用开发(Day 16):Embedding 是什么?用人话讲明白“向量检索”
人工智能·算法·embedding
泡海椒4 小时前
JQuick-Excel FORMAT 导出格式实战:日期、金额显示与 TRANSFORM 的边界
前端·python·excel
承渊政道4 小时前
星空组网+Python实战:在另一台电脑上查看CSV报表
运维·开发语言·python·csv·星空组网
LOVE️YOU9 小时前
Python 中 Tuple 为什么有时可 Hash,有时不可 Hash?
开发语言·python·哈希算法