19 - Merge k Sorted Lists

本文探讨了如何高效地将多个已排序的链表合并为一个有序链表,介绍了两种方法:一种是两两排序合并,但因内存溢出而未通过;另一种是维护小顶堆的方法,但作者暂时未实现。重点分析了合并过程中的内存管理问题,并提出了优化策略。

Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity.


solution: 第一种方法是打算先两两排序,再递归两两排序合并直到只有一个list。时间复杂度为nlog(k),但是曝出内存不够,所以该方法没通过。

(后来发现方法一没通过是因为在merge 2list的时候没有删除预定的头结点,当时写的时候图省事没想到会超出内存,这个在merge2list的时候即17题中也没改正过来,特此标注,下次需注意。)

第二种方法是维护一个小顶堆,然后每次传最大堆的根为目标结点。这个还没有实现,小顶堆懒得实现...lol


方法一如下,

/**
 * Definition for singly-linked list.
 * struct ListNode {
 *     int val;
 *     ListNode *next;
 *     ListNode(int x) : val(x), next(NULL) {}
 * };
 */
class Solution {
public:
    ListNode *merge(ListNode *l1, ListNode *l2)
    {
        ListNode *newHead = new ListNode(0);
        ListNode *node = newHead;
        
        ListNode *n1 = l1;
        ListNode *n2 = l2;
        
        while(n1 != NULL && n2 != NULL)
        {
            if(n1->val < n2 -> val)
            {
                node -> next = n1;
                node = n1;
                n1 = n1 -> next;
                node -> next = NULL;
            }
            else
            {
                node -> next = n2;
                node = n2;
                n2 = n2 -> next;
                node -> next = NULL;
            }
        }
        
        while(n1 != NULL)
        {
            node -> next = n1;
            node = n1;
            n1 = n1 -> next;
            node -> next = NULL;
        }
        
        while(n2 != NULL)
        {
            node -> next = n2;
            node = n2;
            n2 = n2 -> next;
            node -> next = NULL;
        }
        ListNode *temp = newHead;
        newHead = newHead -> next;
        delete temp;
        
        return newHead;
    }

    ListNode *mergeKLists(vector<ListNode *> &lists) {
        // Start typing your C/C++ solution below
        // DO NOT write int main() function
        if(lists.size() == 0)
            return NULL;
        
        int n1 = lists.size();
        while (n1 > 1)
        {
            int half = (n1+1) / 2;
            for(int i = 0; (i < half) && (i + half < n1); i++)
            {
                ListNode *node1 = lists[ i ];
                ListNode *node2 = lists[ i+half ];
                lists[i] = merge(node1, node2);
            }
            n1 = half;
        }
        
        return lists[0];
    }
};






To merge k sorted linked lists, one approach is to repeatedly merge two of the linked lists until all k lists have been merged into one. We can use a priority queue to keep track of the minimum element across all k linked lists at any given time. Here's the code to implement this idea: ``` struct ListNode { int val; ListNode* next; ListNode(int x) : val(x), next(NULL) {} }; // Custom comparator for the priority queue struct CompareNode { bool operator()(const ListNode* node1, const ListNode* node2) const { return node1->val > node2->val; } }; ListNode* mergeKLists(vector<ListNode*>& lists) { priority_queue<ListNode*, vector<ListNode*>, CompareNode> pq; for (ListNode* list : lists) { if (list) { pq.push(list); } } ListNode* dummy = new ListNode(-1); ListNode* curr = dummy; while (!pq.empty()) { ListNode* node = pq.top(); pq.pop(); curr->next = node; curr = curr->next; if (node->next) { pq.push(node->next); } } return dummy->next; } ``` We start by initializing a priority queue with all the head nodes of the k linked lists. We use a custom comparator that compares the values of two nodes and returns true if the first node's value is less than the second node's value. We then create a dummy node to serve as the head of the merged linked list, and a current node to keep track of the last node in the merged linked list. We repeatedly pop the minimum node from the priority queue and append it to the merged linked list. If the popped node has a next node, we push it onto the priority queue. Once the priority queue is empty, we return the head of the merged linked list. Note that this implementation has a time complexity of O(n log k), where n is the total number of nodes across all k linked lists, and a space complexity of O(k).
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