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Segment Tree | Range Minimum Query

Last Updated : 11 Feb, 2025
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We have introduced a segment tree with a simple example in the previous post. In this post, the Range Minimum Query problem is discussed as another example where a Segment Tree can be used. The following is the problem statement:
We have an array arr[0 . . . n-1]. We should be able to efficiently find the minimum value from index qs (query start) to qe (query end) where 0 <= qs <= qe <= n-1
 
A simple solution is to run a loop from qs to qe and find the minimum element in the given range. This solution takes O(n) time in the worst case. 
Another solution is to create a 2D array where an entry [i, j] stores the minimum value in range arr[i..j]. The minimum of a given range can now be calculated in O(1) time, but preprocessing takes O(n2) time. Also, this approach needs O(n2) extra space which may become huge for large input arrays.
Segment tree can be used to do preprocessing and query in moderate time. With a segment tree, preprocessing time is O(n) and the time complexity for a range minimum query is O(log n). The extra space required is O(n) to store the segment tree.

Representation of Segment trees 

1. Leaf Nodes are the elements of the input array. 
2. Each internal node represents minimum of all leaves under it.
An array representation of tree is used to represent Segment Trees. For each node at index i, the left child is at index (2 * i + 1), right child at (2 * i + 2) and the parent is at (i – 1) / 2

Construction of Segment Tree from given array 

We start with a segment arr[0 . . . n-1]. and every time we divide the current segment into two halves (if it has not yet become a segment of length 1), and then call the same procedure on both halves, and for each such segment, we store the minimum value in a segment tree node. 

All levels of the constructed segment tree will be completely filled except the last level. Also, the tree will be a Full Binary Tree because we always divide segments in two halves at every level. Since the constructed tree is always full binary tree with n leaves, there will be n – 1 internal nodes. So total number of nodes will be 2 * n – 1. 
Height of the segment tree will be ?log?n?. Since the tree is represented using array and relation between parent and child indexes must be maintained, size of memory allocated for segment tree will be  2 * 2?log2n?  – 1

Query for minimum value of given range 

Once the tree is constructed, how to do range minimum query using the constructed segment tree. Following is algorithm to get the minimum. 

// qs–> query start index, qe –> query end index
int RMQ(node, qs, qe) {
if range of node is within qs and qe
return value in node
else if range of node is completely outside qsand qe
return INFINITE
else
return min ( RMQ(node’s left child, qs, qe), RMQ (node’s right child, qs, qe) )
}

C++
// C++ program for range minimum
// query using segment tree 
#include <bits/stdc++.h>
using namespace std;

// A utility function to get minimum of two numbers 
int minVal(int x, int y) { 
    return (x < y)? x: y; 
} 

// A utility function to get the 
// middle index from corner indexes. 
int getMid(int s, int e) { 
    return s + (e -s)/2; 
} 

// A recursive function to get the
// minimum value in a given range of array
// st --> Pointer to segment tree 
// index --> Index of current node in the tree
// ss & se --> Starting and ending indexes 
// qs & qe --> Starting and ending indexes of query range
int RMQUtil(vector<int> &st, int ss, int se, int qs, 
                                int qe, int index) { 

    // If segment of this node is a part of given range
    // then return the min of the segment
    if (qs <= ss && qe >= se) 
        return st[index]; 

    // If segment of this node if outside the range
    if (se < qs || ss > qe) 
        return INT_MAX; 

    // If a part of this segment
    // overlaps with the given range 
    int mid = getMid(ss, se); 
    return minVal(RMQUtil(st, ss, mid, qs, qe, 2*index+1), 
                RMQUtil(st, mid+1, se, qs, qe, 2*index+2)); 
} 

// Return minimum of elements in range
// from index qs to qe
int RMQ(vector<int> &st, int n, int qs, int qe) { 

    // Check for invalid input
    if (qs < 0 || qe > n-1 || qs > qe) { 
        cout<<"Invalid Input"; 
        return -1; 
    } 
    return RMQUtil(st, 0, n-1, qs, qe, 0); 
} 

// A recursive function that constructs
// Segment Tree for array[ss..se]. 
int constructSTUtil(vector<int> &arr, int ss, int se,
                            vector<int> &st, int si) {

    // If there is one element in array,
    // store it in current node of 
    // segment tree and return 
    if (ss == se) { 
        st[si] = arr[ss]; 
        return arr[ss]; 
    } 

    // If there are more than one elements, 
    // then recur for left and right subtrees 
    // and store the minimum of two values in this node 
    int mid = getMid(ss, se); 
    st[si] = minVal(constructSTUtil(arr, ss, mid, st, si*2+1), 
                    constructSTUtil(arr, mid+1, se, st, si*2+2)); 
    return st[si]; 
} 

// Function to construct segment tree 
vector<int> constructST(vector<int> &arr, int n) { 

    //Height of segment tree 
    int x = (int)(ceil(log2(n))); 

    // Maximum size of segment tree 
    int max_size = 2*(int)pow(2, x) - 1; 

    vector<int> st(max_size);

    // Fill the allocated memory st 
    constructSTUtil(arr, 0, n-1, st, 0); 

    // Return the constructed segment tree 
    return st; 
} 

int main() {
 
    vector<int> arr = {1, 3, 2, 7, 9, 11}; 
    int n = arr.size();

    // Build segment tree from given array 
    vector<int> st = constructST(arr, n); 

    // Starting index of query range 
    int qs = 1; 
    
    // Ending index of query range 
    int qe = 5; 

    // Print minimum value in arr[qs..qe] 
    cout<<"Minimum of values in range ["<<qs<<", "<<qe<<"] "<<
    "is = "<<RMQ(st, n, qs, qe)<<endl; 

    return 0; 
}
C Java Python C# JavaScript

Output: 

 Minimum of values in range [1, 5] is = 2

Time Complexity: 

  • Tree Construction: Time Complexity for tree construction is O(n). There are total 2n-1 nodes, and value of every node is calculated only once in tree construction.
  • Query: Time complexity for each query is O(log n). To query a range minimum, we process at most two nodes at every level and number of levels is O(log n). 

Auxiliary Space: O(n),  since n extra space has been taken.

Further read  
https://www.geeksforgeeks.org/range-minimum-query-for-static-array/ 



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