题目:
Merge k sorted linked lists and return it as one sorted list. Analyze and describe its complexity.
链接: http://leetcode.com/problems/merge-k-sorted-lists/
题解:
使用min heap构建的priority queue, 遍历输入数组,将非空表头节点加入min PQ,每次从PQ中poll()出最小值作为当前结果,之后加入取出节点的下一个非空节点。 当min PQ为空时结束。
Time Complexity - O(nlogn), Space Complexity - O(m), m为输入数组的length
/** * Definition for singly-linked list. * public class ListNode { * int val; * ListNode next; * ListNode(int x) { val = x; } * } */ public class Solution { public ListNode mergeKLists(ListNode[] lists) { // using priority queue (min heap) if(lists == null || lists.length == 0) return null; PriorityQueue<ListNode> minPQ = new PriorityQueue<ListNode>(lists.length, new Comparator<ListNode>(){ public int compare(ListNode a, ListNode b) { if(a.val < b.val) return -1; else if(a.val > b.val) return 1; else return 0; } }); for(ListNode node : lists) { if(node != null) minPQ.offer(node); } ListNode dummy = new ListNode(-1); ListNode node = dummy; while(minPQ.size() > 0) { ListNode tmp = minPQ.poll(); node.next = tmp; if(tmp.next != null) minPQ.offer(tmp.next); node = node.next; } return dummy.next; } }
二刷:
Java:
跟一刷一样,也是先建立一个自带Comparator的min-oriented PriorityQueue。初始把所有非空list head都放进pq, 之后poll出当前最小的值设置为node.next,假如这条list非空,则将其之后的节点作为head放入pq中继续进行比较。这里insert和deleteMin操作复杂度都是O(logk),k是lists.length
Time Complexity - O(nlogk), Space Complexity - O(k), 这里k为lists的长度, n为所有的节点数
/** * Definition for singly-linked list. * public class ListNode { * int val; * ListNode next; * ListNode(int x) { val = x; } * } */ public class Solution { public ListNode mergeKLists(ListNode[] lists) { ListNode dummy = new ListNode(-1); ListNode node = dummy; PriorityQueue<ListNode> pq = new PriorityQueue<ListNode>(new Comparator<ListNode>() { public int compare(ListNode l1, ListNode l2) { return l1.val - l2.val; } }); for (ListNode head : lists) { if (head != null) { pq.offer(head); } } while (pq.size() > 0) { node.next = pq.poll(); node = node.next; if (node.next != null) { pq.offer(node.next); } } return dummy.next; } }
下面是把匿名Comparator换成了使用了Lambda expression, 但是巨慢无比。可能JVM还没有很好的优化。
/** * Definition for singly-linked list. * public class ListNode { * int val; * ListNode next; * ListNode(int x) { val = x; } * } */ public class Solution { public ListNode mergeKLists(ListNode[] lists) { ListNode dummy = new ListNode(-1); ListNode node = dummy; PriorityQueue<ListNode> pq = new PriorityQueue<ListNode>((ListNode l1, ListNode l2) -> l1.val - l2.val); for (ListNode head : lists) { if (head != null) { pq.offer(head); } } while (pq.size() > 0) { node.next = pq.poll(); node = node.next; if (node.next != null) { pq.offer(node.next); } node.next = null; } return dummy.next; } }
Python:
还是不熟悉Python,好难写,多参考了cbmbbz,放了tuple在pq里。
# Definition for singly-linked list. # class ListNode(object): # def __init__(self, x): # self.val = x # self.next = None from Queue import PriorityQueue class Solution(object): def mergeKLists(self, lists): """ :type lists: List[ListNode] :rtype: ListNode """ dummy = ListNode(None) node = dummy pq = PriorityQueue(); for head in lists: if head: pq.put((head.val, head)) while pq.qsize() > 0: node.next = pq.get()[1] node = node.next if node.next: pq.put((node.next.val, node.next)) return dummy.next
需要继续学习heap的原理,heapify - swim up or sink down,bionomial heap等等。
Reference:
https://leetcode.com/discuss/9279/a-java-solution-based-on-priority-queue
http://algs4.cs.princeton.edu/24pq/
https://leetcode.com/discuss/78758/10-line-python-solution-with-priority-queue
https://leetcode.com/discuss/55662/108ms-python-solution-with-heapq-and-avoid-changing-heap-size