21. Merge Two Sorted Lists

本文介绍了一种将两个已排序的链表合并为一个新排序链表的方法。提供了递归和非递归两种实现方式,并详细展示了每种方法的具体步骤。通过比较不同实现方式的空间复杂度,帮助读者理解各种解决方案的特点。

   Merge two sorted linked lists and return it as a new list. The new list should be made by splicing together the nodes of the first two lists.


// recursive solution, time O(m+n), much more space complexity

/**
 * Definition for singly-linked list.
 * struct ListNode {
 *     int val;
 *     ListNode *next;
 *     ListNode(int x) : val(x), next(NULL) {}
 * };
 */
class Solution {
public:
    ListNode* mergeTwoLists(ListNode* l1, ListNode* l2) {
        if(l1 == NULL)
        return l2;
        if(l2 == NULL)
        return l1;
        if(l1->val <= l2->val)
        {
            l1->next =  mergeTwoLists(l1->next, l2);
            return l1;
        }
        else
        {
            l2->next =  mergeTwoLists(l1, l2->next);
            return l2; 
        }
        
     
    }
};



  my 非递归法

class Solution {
public:
    ListNode* mergeTwoLists(ListNode* l1, ListNode* l2) {
        if(l1 == NULL)
        return l2;
        if(l2 == NULL)
        return l1;
        ListNode* p = l1;
        ListNode* q = l2;
        ListNode* x = (l1->val <= l2->val) ? l1 :l2;
        ListNode* c;
        
        
        while(p&&q)
        {
            if(p->val <=q->val)
            {
                c->next = p;
                c = c->next;
                p = p->next;
            }
            else
            {
                c->next = q;
                c = c->next;
                q = q->next;
            }
            
        }
        if(!p)
        {
            c->next = q;
            
        }
        if(!q)
        {
            c->next = p;
            
        }
        return x;
        
        
     
    }
};



// merge sort, adding while comparing, time O(m+n)
class Solution_MergeSort {
public:
    ListNode* mergeTwoLists(ListNode* l1, ListNode* l2) {
        ListNode dummy(0);                                     //头!
        ListNode *curr = &dummy;
        while (l1 && l2)
        {
            if (l1->val < l2->val)
            {
                curr->next = l1;
                curr = l1;
                l1 = l1->next;
            }
            else
            {
                curr->next = l2;
                curr = l2;
                l2 = l2->next;
            }
        }

        if (!l1)
        {
            curr->next = l2;
        }

        if (!l2)
        {
            curr->next = l1;
        }

        return dummy.next;
    }
};



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).
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值