给定一个链表，其中每个节点代表一个链表并包含两个其类型的指针：
- 指向主列表中下一个节点的指针(我们在下面的代码中称之为“右”指针)
- 指向此节点所在的链表的指针(我们在下面的代码中将其称为“向下”指针)。
所有链表都已排序。看下面的例子
例子：
Input:
5 -> 10 -> 19 -> 28
| | | |
V V V V
7 20 22 35
| | |
V V V
8 50 40
| |
V V
30 45
Output: 5->7->8->10->19->20->22->28->30->35->40->45->50
Input:
5 -> 10 -> 19 -> 28
| |
V V
7 22
| |
V V
8 50
|
V
30
Output: 5->7->8->10->19->20->22->30->50
在上一篇文章中，我们必须使用对链表进行归并排序的merge()过程来展平链表。
在这篇文章中，我们将使用堆解决它。
方法：思想是观察从每个顶部节点开始有N个向下连接的节点，但观察所有向下的节点都是按顺序排列的。所以任务是按升序(或降序)对整个事物进行排序。
- 将优先队列中向下列表中所有链表的头部压入。
- 从优先级队列中弹出最小的节点。
- 检查节点的位置，以便将当前节点指向的下一个节点推入优先级队列。
- 再次弹出最小元素并插入当前节点指向的下一个节点，直到堆变为空。
- 继续在新链表中添加节点的数据，这些数据被导出到新链表中。
- 打印上面形成的链表。
下面是上述方法的实现：
C++
// C++ program for Flattening
// a linked list using Heaps
#include
using namespace std;
// Structure of given Linked list
struct Node {
int data;
struct Node* right;
struct Node* down;
Node(int x)
{
data = x;
right = NULL;
down = NULL;
}
};
// Function to print the
// linked list
void printList(Node* Node)
{
while (Node != NULL) {
printf("%d ", Node->data);
Node = Node->down;
}
}
// Function that compares the value
// pointed by node and returns true
// if first data is greater
struct compare {
bool operator()(Node* a, Node* b)
{
return a->data > b->data;
}
};
// Function which returns the root
// of the flattened linked list
Node* flatten(Node* root)
{
Node* ptr = root;
Node* head = NULL;
// Min Heap which will return
// smallest element currently
// present in heap
priority_queue,
compare> pq;
// Push the head nodes of each
// downward linked list
while (ptr != NULL) {
pq.push(ptr);
ptr = ptr->right;
}
// This loop will execute
// till the map becomes empty
while (!pq.empty()) {
// Pop out the node that
// contains element
// currently in heap
Node* temp = pq.top();
pq.pop();
// Push the next node pointed by
// the current node into heap
// if it is not null
if (temp->down != NULL) {
pq.push(temp->down);
}
// Create new linked list
// that is to be returned
if (head == NULL) {
head = temp;
ptr = temp;
ptr->right = NULL;
}
else {
ptr->down = temp;
ptr = temp;
ptr->right = NULL;
}
}
// Pointer to head node
// in the linked list
return head;
}
// Create and push new nodes
void push(Node** head_ref, int new_data)
{
Node* new_node = (Node*)malloc(sizeof(Node));
new_node->right = NULL;
new_node->data = new_data;
new_node->down = (*head_ref);
(*head_ref) = new_node;
}
// Driver Code
int main()
{
Node* root = NULL;
// Given Linked List
push(&root, 30);
push(&root, 8);
push(&root, 7);
push(&root, 5);
push(&(root->right), 20);
push(&(root->right), 10);
push(&(root->right->right), 50);
push(&(root->right->right), 22);
push(&(root->right->right), 19);
push(&(root->right->right->right), 45);
push(&(root->right->right->right), 40);
push(&(root->right->right->right), 35);
push(&(root->right->right->right), 20);
// Flatten the list
root = flatten(root);
// Print the flatened linked list
printList(root);
return 0;
} Java
// Java program for Flattening
// a linked list using Heaps
import java.util.*;
// Linked list Node
class Node {
int data;
Node right, down;
Node(int data)
{
this.data = data;
right = null;
down = null;
}
}
class pair {
int val;
Node head;
pair(Node head, int val)
{
this.val = val;
this.head = head;
}
}
// Class that compares the value
// pointed by node and make
// LinkedList sorted
class pairComp implements Comparator {
public int compare(pair p1, pair p2)
{
return p1.val - p2.val;
}
}
class GFG {
// Function which returns the root
// of the flattened linked list
public static Node flatten(Node root)
{
Node ptr = root;
Node h = null;
// Min Heap which will return
// smallest element currently
// present in heap
PriorityQueue pq
= new PriorityQueue(
new pairComp());
// Push the head nodes of each
// downward linked list
while (ptr != null) {
pq.add(new pair(ptr, ptr.data));
ptr = ptr.right;
}
// This loop will execute
// till the pq becomes empty
while (!pq.isEmpty()) {
// Pop out the node that
// contains element
// currently in heap
Node temp = pq.poll().head;
// Push the next node pointed by
// the current node into heap
// if it is not null
if (temp.down != null) {
pq.add(new pair(temp.down,
temp.down.data));
}
// Create new linked list
// that is to be returned
if (h == null) {
h = temp;
ptr = temp;
ptr.right = null;
}
else {
ptr.down = temp;
ptr = temp;
ptr.right = null;
}
}
// Pointer to head node
// in the linked list
return h;
}
// Create and push new nodes
public static Node push(Node head_ref,
int data)
{
// Allocate the Node &
// Put in the data
Node new_node = new Node(data);
// Make next of new Node as head
new_node.down = head_ref;
// Move the head to point to new Node
head_ref = new_node;
// return to link it back
return head_ref;
}
// Function to print the
// linked list
public static void printList(Node h)
{
while (h != null) {
System.out.print(h.data + " ");
h = h.down;
}
}
// Driver code
public static void main(String args[])
{
Node head = null;
head = push(head, 30);
head = push(head, 8);
head = push(head, 7);
head = push(head, 5);
head.right = push(head.right, 20);
head.right = push(head.right, 10);
head.right.right = push(
head.right.right, 50);
head.right.right = push(
head.right.right, 22);
head.right.right = push(
head.right.right, 19);
head.right.right.right
= push(
head.right.right.right, 45);
head.right.right.right
= push(
head.right.right.right, 40);
head.right.right.right
= push(
head.right.right.right, 35);
head.right.right.right
= push(head.right.right.right, 20);
// Flatten the list
head = flatten(head);
printList(head);
}
}
// This code is contributed by Naresh Saharan
// and Sagar Jangra and Tridib Samanta 输出
5 7 8 10 19 20 20 22 30 35 40 45 50 时间复杂度： O(k * log k) + O((Nk) * log k) = O(N * log k) ，其中“ k ”是最顶层水平链表中的节点数，“ N ”是所有链表中的节点总数。 ‘ log k ‘ 时间用于 min-heapify 过程。
辅助空间：最小堆的O(k) ，其中“ k ”是最顶层水平链表中的节点数。最小堆在任何时候都将具有最多 ‘ k ‘ 个节点。
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