Given a binary tree, the task is to find the distance between two keys in a binary tree, no parent pointers are given. The distance between two nodes is the minimum number of edges to be traversed to reach one node from other.
We have already discussed a method which uses segment tree to reduce the query time to O(logn), here the task is to reduce query time to O(1) by compromising space complexity to O(n logn). In this post, we will use Sparse table instead of segment tree for finding the minimum in given range, which uses dynamic programming and bit manipulation to achieve O(1) query time.
A sparse table will preprocess the minimum values of given range for L array in Nlogn space i.e. each node will contain chain of values of log(i) length where i is the index of the ith node in L array. Each entry in the sparse table says M[i][j] will represent the index of the minimum value in the subarray starting at i having length 2^j.
The distance between two nodes can be obtained in terms of lowest common ancestor.
Dist(n1, n2) = Level[n1] + Level[n2] - 2*Level[lca]
This problem can be breakdown into:
- Finding levels of each node
- Finding the Euler tour of binary tree
- Building sparse table for LCA.
These steps are explained below :
- Find the levels of each node by applying level order traversal.
- Find the LCA of two nodes in binary tree in O(logn) by Storing Euler tour of Binary tree in array and computing two other arrays with the help of levels of each node and Euler tour.
These steps are shown below:
- First, find Euler Tour of binary tree.
- Then, store levels of each node in Euler array.
- Then, store First occurrences of all nodes of binary tree in Euler array. H stores the indices of nodes from Euler array, so that range of query for finding minimum can be minimized and their by further optimizing the query time.
- Then build sparse table on L array and find the minimum value say X in range (H[A] to H[B]). Then, we use the index of value X as an index to Euler array to get LCA, i.e. Euler[index(X)].
Let, A=8 and B=5.- H[8]= 1 and H[5]=2
- we get min value in L array between 1 and 2 as X=0, index=7
- Then, LCA= Euler[7], i.e LCA=1.
- Finally, apply distance formula discussed above to get the distance between two nodes.
Implementation:
C++
#include <bits/stdc++.h> #define MAX 100001 using namespace std; /* A tree node structure */ struct Node { int data; struct Node* left; struct Node* right; }; /* Utility function to create a new Binary Tree node */ struct Node* newNode( int data) { struct Node* temp = new struct Node; temp->data = data; temp->left = temp->right = NULL; return temp; } // Array to store level of each node int level[MAX]; // Utility Function to store level of all nodes void FindLevels( struct Node* root) { if (!root) return ; // queue to hold tree node with level queue<pair< struct Node*, int > > q; // let root node be at level 0 q.push({ root, 0 }); pair< struct Node*, int > p; // Do level Order Traversal of tree while (!q.empty()) { p = q.front(); q.pop(); // Node p.first is on level p.second level[p.first->data] = p.second; // If left child exits, put it in queue // with current_level +1 if (p.first->left) q.push({ p.first->left, p.second + 1 }); // If right child exists, put it in queue // with current_level +1 if (p.first->right) q.push({ p.first->right, p.second + 1 }); } } // Stores Euler Tour int Euler[MAX]; // index in Euler array int idx = 0; // Find Euler Tour void eulerTree( struct Node* root) { // store current node's data Euler[++idx] = root->data; // If left node exists if (root->left) { // traverse left subtree eulerTree(root->left); // store parent node's data Euler[++idx] = root->data; } // If right node exists if (root->right) { // traverse right subtree eulerTree(root->right); // store parent node's data Euler[++idx] = root->data; } } // checks for visited nodes int vis[MAX]; // Stores level of Euler Tour int L[MAX]; // Stores indices of the first occurrence // of nodes in Euler tour int H[MAX]; // Preprocessing Euler Tour for finding LCA void preprocessEuler( int size) { for ( int i = 1; i <= size; i++) { L[i] = level[Euler[i]]; // If node is not visited before if (vis[Euler[i]] == 0) { // Add to first occurrence H[Euler[i]] = i; // Mark it visited vis[Euler[i]] = 1; } } } // Sparse table of size [MAX][LOGMAX] // M[i][j] is the index of the minimum value in // the sub array starting at i having length 2^j int M[MAX][18]; // Utility function to preprocess Sparse table void preprocessLCA( int N) { for ( int i = 0; i < N; i++) M[i][0] = i; for ( int j = 1; 1 << j <= N; j++) for ( int i = 0; i + (1 << j) - 1 < N; i++) if (L[M[i][j - 1]] < L[M[i + (1 << (j - 1))][j - 1]]) M[i][j] = M[i][j - 1]; else M[i][j] = M[i + (1 << (j - 1))][j - 1]; } // Utility function to find the index of the minimum // value in range a to b int LCA( int a, int b) { // Subarray of length 2^j int j = log2(b - a + 1); if (L[M[a][j]] <= L[M[b - (1 << j) + 1][j]]) return M[a][j]; else return M[b - (1 << j) + 1][j]; } // Function to return distance between // two nodes n1 and n2 int findDistance( int n1, int n2) { // Maintain original Values int prevn1 = n1, prevn2 = n2; // Get First Occurrence of n1 n1 = H[n1]; // Get First Occurrence of n2 n2 = H[n2]; // Swap if low>high if (n2 < n1) swap(n1, n2); // Get position of minimum value int lca = LCA(n1, n2); // Extract value out of Euler tour lca = Euler[lca]; // return calculated distance return level[prevn1] + level[prevn2] - 2 * level[lca]; } void preProcessing(Node* root, int N) { // Build Tree eulerTree(root); // Store Levels FindLevels(root); // Find L and H array preprocessEuler(2 * N - 1); // Build sparse table preprocessLCA(2 * N - 1); } /* Driver function to test above functions */ int main() { // Number of nodes int N = 8; /* Constructing tree given in the above figure */ Node* root = newNode(1); root->left = newNode(2); root->right = newNode(3); root->left->left = newNode(4); root->left->right = newNode(5); root->right->left = newNode(6); root->right->right = newNode(7); root->right->left->right = newNode(8); // Function to do all preprocessing preProcessing(root, N); cout << "Dist(4, 5) = " << findDistance(4, 5) << "\n" ; cout << "Dist(4, 6) = " << findDistance(4, 6) << "\n" ; cout << "Dist(3, 4) = " << findDistance(3, 4) << "\n" ; cout << "Dist(2, 4) = " << findDistance(2, 4) << "\n" ; cout << "Dist(8, 5) = " << findDistance(8, 5) << "\n" ; return 0; } |
Java
// Java implementation of the approach import java.util.*; class GFG { static class Pair<T, V> { T first; V second; Pair() { } Pair(T first, V second) { this .first = first; this .second = second; } } static class Node { int data; Node left, right; Node( int data) { this .data = data; this .left = this .right = null ; } } static int MAX = 100001 ; // Array to store level of each node static int [] level = new int [MAX]; // Utility Function to store level of all nodes static void FindLevels(Node root) { if (root == null ) return ; // queue to hold tree node with level Queue<Pair<Node, Integer>> q = new LinkedList<>(); // let root node be at level 0 q.add( new Pair<>(root, 0 )); Pair<Node, Integer> p = new Pair<>(); // Do level Order Traversal of tree while (!q.isEmpty()) { p = q.poll(); // Node p.first is on level p.second level[p.first.data] = p.second; // If left child exits, put it in queue // with current_level +1 if (p.first.left != null ) q.add( new Pair<>(p.first.left, p.second + 1 )); // If right child exists, put it in queue // with current_level +1 if (p.first.right != null ) q.add( new Pair<>(p.first.right, p.second + 1 )); } } // Stores Euler Tour static int [] Euler = new int [MAX]; // index in Euler array static int idx = 0 ; // Find Euler Tour static void eulerTree(Node root) { // store current node's data Euler[++idx] = root.data; // If left node exists if (root.left != null ) { // traverse left subtree eulerTree(root.left); // store parent node's data Euler[++idx] = root.data; } // If right node exists if (root.right != null ) { // traverse right subtree eulerTree(root.right); // store parent node's data Euler[++idx] = root.data; } } // checks for visited nodes static int [] vis = new int [MAX]; // Stores level of Euler Tour static int [] L = new int [MAX]; // Stores indices of the first occurrence // of nodes in Euler tour static int [] H = new int [MAX]; // Preprocessing Euler Tour for finding LCA static void preprocessEuler( int size) { for ( int i = 1 ; i <= size; i++) { L[i] = level[Euler[i]]; // If node is not visited before if (vis[Euler[i]] == 0 ) { // Add to first occurrence H[Euler[i]] = i; // Mark it visited vis[Euler[i]] = 1 ; } } } // Sparse table of size [MAX][LOGMAX] // M[i][j] is the index of the minimum value in // the sub array starting at i having length 2^j static int [][] M = new int [MAX][ 18 ]; // Utility function to preprocess Sparse table static void preprocessLCA( int N) { for ( int i = 0 ; i < N; i++) M[i][ 0 ] = i; for ( int j = 1 ; 1 << j <= N; j++) for ( int i = 0 ; i + ( 1 << j) - 1 < N; i++) if (L[M[i][j - 1 ]] < L[M[i + ( 1 << (j - 1 ))][j - 1 ]]) M[i][j] = M[i][j - 1 ]; else M[i][j] = M[i + ( 1 << (j - 1 ))][j - 1 ]; } // Utility function to find the index of the minimum // value in range a to b static int LCA( int a, int b) { // Subarray of length 2^j int j = ( int ) (Math.log(b - a + 1 ) / Math.log( 2 )); if (L[M[a][j]] <= L[M[b - ( 1 << j) + 1 ][j]]) return M[a][j]; else return M[b - ( 1 << j) + 1 ][j]; } // Function to return distance between // two nodes n1 and n2 static int findDistance( int n1, int n2) { // Maintain original Values int prevn1 = n1, prevn2 = n2; // Get First Occurrence of n1 n1 = H[n1]; // Get First Occurrence of n2 n2 = H[n2]; // Swap if low>high if (n2 < n1) { int temp = n1; n1 = n2; n2 = temp; } // Get position of minimum value int lca = LCA(n1, n2); // Extract value out of Euler tour lca = Euler[lca]; // return calculated distance return level[prevn1] + level[prevn2] - 2 * level[lca]; } static void preProcessing(Node root, int N) { // Build Tree eulerTree(root); // Store Levels FindLevels(root); // Find L and H array preprocessEuler( 2 * N - 1 ); // Build sparse table preprocessLCA( 2 * N - 1 ); } // Driver Code public static void main(String[] args) { // Number of nodes int N = 8 ; /* Constructing tree given in the above figure */ Node root = new Node( 1 ); root.left = new Node( 2 ); root.right = new Node( 3 ); root.left.left = new Node( 4 ); root.left.right = new Node( 5 ); root.right.left = new Node( 6 ); root.right.right = new Node( 7 ); root.right.left.right = new Node( 8 ); // Function to do all preprocessing preProcessing(root, N); System.out.println( "Dist(4, 5) = " + findDistance( 4 , 5 )); System.out.println( "Dist(4, 6) = " + findDistance( 4 , 6 )); System.out.println( "Dist(3, 4) = " + findDistance( 3 , 4 )); System.out.println( "Dist(2, 4) = " + findDistance( 2 , 4 )); System.out.println( "Dist(8, 5) = " + findDistance( 8 , 5 )); } } // This code is contributed by // sanjeev2552 |
Python3
from collections import deque from math import log2 MAX = 100001 # A tree node structure class Node: def __init__( self , data): self .data = data self .left = None self .right = None # Array to store level of each node level = [ 0 ] * MAX # Utility Function to store level of all nodes def findLevels(root: Node): global level if root is None : return # queue to hold tree node with level q = deque() # let root node be at level 0 q.append((root, 0 )) # Do level Order Traversal of tree while q: p = q[ 0 ] q.popleft() # Node p.first is on level p.second level[p[ 0 ].data] = p[ 1 ] # If left child exits, put it in queue # with current_level +1 if p[ 0 ].left: q.append((p[ 0 ].left, p[ 1 ] + 1 )) # If right child exists, put it in queue # with current_level +1 if p[ 0 ].right: q.append((p[ 0 ].right, p[ 1 ] + 1 )) # Stores Euler Tour Euler = [ 0 ] * MAX # index in Euler array idx = 0 # Find Euler Tour def eulerTree(root: Node): global Euler, idx idx + = 1 # store current node's data Euler[idx] = root.data # If left node exists if root.left: # traverse left subtree eulerTree(root.left) idx + = 1 # store parent node's data Euler[idx] = root.data # If right node exists if root.right: # traverse right subtree eulerTree(root.right) idx + = 1 # store parent node's data Euler[idx] = root.data # checks for visited nodes vis = [ 0 ] * MAX # Stores level of Euler Tour L = [ 0 ] * MAX # Stores indices of the first occurrence # of nodes in Euler tour H = [ 0 ] * MAX # Preprocessing Euler Tour for finding LCA def preprocessEuler(size: int ): global L, H, vis for i in range ( 1 , size + 1 ): L[i] = level[Euler[i]] # If node is not visited before if vis[Euler[i]] = = 0 : # Add to first occurrence H[Euler[i]] = i # Mark it visited vis[Euler[i]] = 1 # Sparse table of size [MAX][LOGMAX] # M[i][j] is the index of the minimum value in # the sub array starting at i having length 2^j M = [[ 0 for i in range ( 18 )] for j in range ( MAX )] # Utility function to preprocess Sparse table def preprocessLCA(N: int ): global M for i in range (N): M[i][ 0 ] = i j = 1 while 1 << j < = N: i = 0 while i + ( 1 << j) - 1 < N: if L[M[i][j - 1 ]] < L[M[i + ( 1 << (j - 1 ))][j - 1 ]]: M[i][j] = M[i][j - 1 ] else : M[i][j] = M[i + ( 1 << (j - 1 ))][j - 1 ] i + = 1 j + = 1 # Utility function to find the index of the minimum # value in range a to b def LCA(a: int , b: int ) - > int : # Subarray of length 2^j j = int (log2(b - a + 1 )) if L[M[a][j]] < = L[M[b - ( 1 << j) + 1 ][j]]: return M[a][j] else : return M[b - ( 1 << j) + 1 ][j] # Function to return distance between # two nodes n1 and n2 def findDistance(n1: int , n2: int ) - > int : # Maintain original Values prevn1 = n1 prevn2 = n2 # Get First Occurrence of n1 n1 = H[n1] # Get First Occurrence of n2 n2 = H[n2] # Swap if low>high if n2 < n1: n1, n2 = n2, n1 # Get position of minimum value lca = LCA(n1, n2) # Extract value out of Euler tour lca = Euler[lca] # return calculated distance return level[prevn1] + level[prevn2] - 2 * level[lca] def preProcessing(root: Node, N: int ): # Build Tree eulerTree(root) # Store Levels findLevels(root) # Find L and H array preprocessEuler( 2 * N - 1 ) # Build sparse table preprocessLCA( 2 * N - 1 ) # Driver Code if __name__ = = "__main__" : # Number of nodes N = 8 # Constructing tree given in the above figure root = Node( 1 ) root.left = Node( 2 ) root.right = Node( 3 ) root.left.left = Node( 4 ) root.left.right = Node( 5 ) root.right.left = Node( 6 ) root.right.right = Node( 7 ) root.right.left.right = Node( 8 ) # Function to do all preprocessing preProcessing(root, N) print ( "Dist(4, 5) =" , findDistance( 4 , 5 )) print ( "Dist(4, 6) =" , findDistance( 4 , 6 )) print ( "Dist(3, 4) =" , findDistance( 3 , 4 )) print ( "Dist(2, 4) =" , findDistance( 2 , 4 )) print ( "Dist(8, 5) =" , findDistance( 8 , 5 )) # This code is contributed by # sanjeev2552 |
C#
// C# implementation of the approach using System; using System.Collections.Generic; public class GFG { public class Pair<T, V> { public T first; public V second; public Pair() { } public Pair(T first, V second) { this .first = first; this .second = second; } } public class Node { public int data; public Node left, right; public Node( int data) { this .data = data; this .left = this .right = null ; } } static int MAX = 100001; // Array to store level of each node static int [] level = new int [MAX]; // Utility Function to store level of all nodes static void FindLevels(Node root) { if (root == null ) return ; // queue to hold tree node with level Queue<Pair<Node, int >> q = new Queue<Pair<Node, int >>(); // let root node be at level 0 q.Enqueue( new Pair<Node, int >(root, 0)); Pair<Node, int > p = new Pair<Node, int >(); // Do level Order Traversal of tree while (q.Count != 0) { p = q.Peek(); q.Dequeue(); // Node p.first is on level p.second level[p.first.data] = p.second; // If left child exits, put it in queue // with current_level +1 if (p.first.left != null ) q.Enqueue( new Pair<Node, int >(p.first.left, p.second + 1)); // If right child exists, put it in queue // with current_level +1 if (p.first.right != null ) q.Enqueue( new Pair<Node, int >(p.first.right, p.second + 1)); } } // Stores Euler Tour static int [] Euler = new int [MAX]; // index in Euler array static int idx = 0; // Find Euler Tour static void eulerTree(Node root) { // store current node's data Euler[++idx] = root.data; // If left node exists if (root.left != null ) { // traverse left subtree eulerTree(root.left); // store parent node's data Euler[++idx] = root.data; } // If right node exists if (root.right != null ) { // traverse right subtree eulerTree(root.right); // store parent node's data Euler[++idx] = root.data; } } // checks for visited nodes static int [] vis = new int [MAX]; // Stores level of Euler Tour static int [] L = new int [MAX]; // Stores indices of the first occurrence // of nodes in Euler tour static int [] H = new int [MAX]; // Preprocessing Euler Tour for finding LCA static void preprocessEuler( int size) { for ( int i = 1; i <= size; i++) { L[i] = level[Euler[i]]; // If node is not visited before if (vis[Euler[i]] == 0) { // Add to first occurrence H[Euler[i]] = i; // Mark it visited vis[Euler[i]] = 1; } } } // Sparse table of size [MAX,LOGMAX] // M[i,j] is the index of the minimum value in // the sub array starting at i having length 2^j static int [,] M = new int [MAX, 18]; // Utility function to preprocess Sparse table static void preprocessLCA( int N) { for ( int i = 0; i < N; i++) M[i, 0] = i; for ( int j = 1; 1 << j <= N; j++) for ( int i = 0; i + (1 << j) - 1 < N; i++) if (L[M[i, j - 1]] < L[M[i + (1 << (j - 1)), j - 1]]) M[i, j] = M[i, j - 1]; else M[i, j] = M[i + (1 << (j - 1)), j - 1]; } // Utility function to find the index of the minimum // value in range a to b static int LCA( int a, int b) { // Subarray of length 2^j int j = ( int ) (Math.Log(b - a + 1) / Math.Log(2)); if (L[M[a,j]] <= L[M[b - (1 << j) + 1,j]]) return M[a,j]; else return M[b - (1 << j) + 1,j]; } // Function to return distance between // two nodes n1 and n2 static int findDistance( int n1, int n2) { // Maintain original Values int prevn1 = n1, prevn2 = n2; // Get First Occurrence of n1 n1 = H[n1]; // Get First Occurrence of n2 n2 = H[n2]; // Swap if low>high if (n2 < n1) { int temp = n1; n1 = n2; n2 = temp; } // Get position of minimum value int lca = LCA(n1, n2); // Extract value out of Euler tour lca = Euler[lca]; // return calculated distance return level[prevn1] + level[prevn2] - 2 * level[lca]; } static void preProcessing(Node root, int N) { // Build Tree eulerTree(root); // Store Levels FindLevels(root); // Find L and H array preprocessEuler(2 * N - 1); // Build sparse table preprocessLCA(2 * N - 1); } // Driver Code public static void Main(String[] args) { // Number of nodes int N = 8; /* Constructing tree given in the above figure */ Node root = new Node(1); root.left = new Node(2); root.right = new Node(3); root.left.left = new Node(4); root.left.right = new Node(5); root.right.left = new Node(6); root.right.right = new Node(7); root.right.left.right = new Node(8); // Function to do all preprocessing preProcessing(root, N); Console.WriteLine( "Dist(4, 5) = " + findDistance(4, 5)); Console.WriteLine( "Dist(4, 6) = " + findDistance(4, 6)); Console.WriteLine( "Dist(3, 4) = " + findDistance(3, 4)); Console.WriteLine( "Dist(2, 4) = " + findDistance(2, 4)); Console.WriteLine( "Dist(8, 5) = " + findDistance(8, 5)); } } // This code is contributed by aashish1995 |
Javascript
<script> // Javascript implementation of the approach class Pair{ constructor(first, second) { this .first = first; this .second = second; } } class Node{ constructor(data) { this .data = data; this .left = null ; this .right = null ; } } var MAX = 100001; // Array to store level of each node var level = Array(MAX); // Utility Function to store level of all nodes function FindLevels(root) { if (root == null ) return ; // queue to hold tree node with level var q = []; // let root node be at level 0 q.push( new Pair(root, 0)); var p = new Pair(); // Do level Order Traversal of tree while (q.length != 0) { p = q[0]; q.shift(); // Node p.first is on level p.second level[p.first.data] = p.second; // If left child exits, put it in queue // with current_level +1 if (p.first.left != null ) q.push( new Pair(p.first.left, p.second + 1)); // If right child exists, put it in queue // with current_level +1 if (p.first.right != null ) q.push( new Pair(p.first.right, p.second + 1)); } } // Stores Euler Tour var Euler = Array(MAX); // index in Euler array var idx = 0; // Find Euler Tour function eulerTree(root) { // store current node's data Euler[++idx] = root.data; // If left node exists if (root.left != null ) { // traverse left subtree eulerTree(root.left); // store parent node's data Euler[++idx] = root.data; } // If right node exists if (root.right != null ) { // traverse right subtree eulerTree(root.right); // store parent node's data Euler[++idx] = root.data; } } // checks for visited nodes var vis = Array(MAX).fill(0); // Stores level of Euler Tour var L = Array(MAX).fill(0); // Stores indices of the first occurrence // of nodes in Euler tour var H = Array(MAX).fill(0); // Preprocessing Euler Tour for finding LCA function preprocessEuler(size) { for ( var i = 1; i <= size; i++) { L[i] = level[Euler[i]]; // If node is not visited before if (vis[Euler[i]] == 0) { // Add to first occurrence H[Euler[i]] = i; // Mark it visited vis[Euler[i]] = 1; } } } // Sparse table of size [MAX,LOGMAX] // M[i,j] is the index of the minimum value in // the sub array starting at i having length 2^j var M = Array.from(Array(MAX), ()=>Array(18)); // Utility function to preprocess Sparse table function preprocessLCA(N) { for ( var i = 0; i < N; i++) M[i][0] = i; for ( var j = 1; 1 << j <= N; j++) for ( var i = 0; i + (1 << j) - 1 < N; i++) if (L[M[i][j - 1]] < L[M[i + (1 << (j - 1))][j - 1]]) M[i][j] = M[i][j - 1]; else M[i][j] = M[i + (1 << (j - 1))][j - 1]; } // Utility function to find the index of the minimum // value in range a to b function LCA(a, b) { // Subarray of length 2^j var j = parseInt(Math.log(b - a + 1) / Math.log(2)); if (L[M[a][j]] <= L[M[b - (1 << j) + 1][j]]) return M[a][j]; else return M[b - (1 << j) + 1][j]; } // Function to return distance between // two nodes n1 and n2 function findDistance( n1, n2) { // Maintain original Values var prevn1 = n1, prevn2 = n2; // Get First Occurrence of n1 n1 = H[n1]; // Get First Occurrence of n2 n2 = H[n2]; // Swap if low>high if (n2 < n1) { var temp = n1; n1 = n2; n2 = temp; } // Get position of minimum value var lca = LCA(n1, n2); // Extract value out of Euler tour lca = Euler[lca]; // return calculated distance return level[prevn1] + level[prevn2] - 2 * level[lca]; } function preProcessing(root, N) { // Build Tree eulerTree(root); // Store Levels FindLevels(root); // Find L and H array preprocessEuler(2 * N - 1); // Build sparse table preprocessLCA(2 * N - 1); } // Driver Code // Number of nodes var N = 8; /* Constructing tree given in the above figure */ var root = new Node(1); root.left = new Node(2); root.right = new Node(3); root.left.left = new Node(4); root.left.right = new Node(5); root.right.left = new Node(6); root.right.right = new Node(7); root.right.left.right = new Node(8); // Function to do all preprocessing preProcessing(root, N); document.write( "Dist(4, 5) = " + findDistance(4, 5) + "<br>" ); document.write( "Dist(4, 6) = " + findDistance(4, 6) + "<br>" ); document.write( "Dist(3, 4) = " + findDistance(3, 4) + "<br>" ); document.write( "Dist(2, 4) = " + findDistance(2, 4) + "<br>" ); document.write( "Dist(8, 5) = " + findDistance(8, 5) + "<br>" ); // This code is contributed by itsok. </script> |
Dist(4, 5) = 2 Dist(4, 6) = 4 Dist(3, 4) = 3 Dist(2, 4) = 1 Dist(8, 5) = 5
Complexity Analysis:
- Time Complexity: O(N log N)
- Space Complexity: O(N log N)
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