[刷题]Merge k Sorted Lists

本文介绍两种合并K个已排序链表的方法:一种通过遍历寻找最小元素,另一种使用优先队列实现堆排序。这两种方法均实现了链表的合并,并返回一个排序后的链表。

[LintCode]Merge k Sorted Lists

Version I

/**
 * Definition for ListNode.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode(int val) {
 *         this.val = val;
 *         this.next = null;
 *     }
 * }
 */ 
public class Solution {
    /**
     * @param lists: a list of ListNode
     * @return: The head of one sorted list.
     */
    public ListNode mergeKLists(List<ListNode> lists) {  
        // 2015-08-21
        if (lists == null || lists.size() == 0) {
            return null;
        }
        
        ListNode dummy = new ListNode(0);
        ListNode tail = dummy; // sorted list的尾节点
        // 这个数组保存了各链表中未排序的部分的表头
        ArrayList<ListNode> headList = new ArrayList<>(lists); 
        
        while (true) {
            int minValue = Integer.MAX_VALUE;
            int indexOfMin = -1;
            // 遍历数组,找到值最小的节点,并保存其序号
            for (int i = 0; i < headList.size(); i++) {
                ListNode temp = headList.get(i);
                if (temp == null) {
                    continue;
                }
                if (minValue > temp.val) {
                    minValue = temp.val;
                    indexOfMin = i;
                }                
            }
            // 更新sorted list和headList
            if (indexOfMin == -1) {
                break;
            } else {
                ListNode minNode = headList.get(indexOfMin);
                tail.next = minNode;
                tail = tail.next;
                headList.set(indexOfMin, minNode.next);
            }
        }
        return dummy.next;
    }
}


Version II 堆排序

/**
 * Definition for ListNode.
 * public class ListNode {
 *     int val;
 *     ListNode next;
 *     ListNode(int val) {
 *         this.val = val;
 *         this.next = null;
 *     }
 * }
 */ 
public class Solution {
    /**
     * @param lists: a list of ListNode
     * @return: The head of one sorted list.
     */
    private Comparator<ListNode> ListNodeComparator = new Comparator<ListNode>() {
        public int compare(ListNode left, ListNode right) {
            if (left == null) {
                return 1;
            } else if (right == null) {
                return -1;
            }
            return left.val - right.val;
        }
    };
    
    public ListNode mergeKLists(List<ListNode> lists) {
        if (lists == null || lists.size() == 0) {
            return null;
        }
        
        Queue<ListNode> heap = new PriorityQueue<ListNode>(lists.size(), ListNodeComparator);
        for (int i = 0; i < lists.size(); i++) {
            if (lists.get(i) != null) {
                heap.add(lists.get(i));
            }
        }
        
        ListNode dummy = new ListNode(0);
        ListNode tail = dummy;
        while (!heap.isEmpty()) {
            ListNode head = heap.poll();
            tail.next = head;
            tail = head;
            if (head.next != null) {
                heap.add(head.next);
            }
        }
        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).
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