Applications, Advantages and Disadvantages of Segment Tree
Last Updated :
23 Jul, 2025
First, let us understand why we need it prior to landing on the introduction so as to get why this concept was introduced. Suppose we are given an array and we need to find out the subarray
Purpose of Segment Trees:
A segment tree is a data structure that deals with a range of queries over an array. It has a divide and conquers approach. Used to solve range minimum and maximum & Sum Queries and Range Update Queries in O (log n) time complexity.
Construction of Segment Tree:
array[]: 5, 3, 2, 4, 1, 8, 6 10
we'll use divide and conquer
Now we'll see how to segment the tree Construction is done.
Number of nodes will be = n + n/2 + n/4 + ...... + 2+1
Geometric progression: common difference will be 2
let, number of terms be 'x', a=first term and r = common ratio.
(ar)^x-1 = n
a=1,r=2
(2)^x-1=n
log2(2)^x-1=log2n
x=1+log2n=number of levels
(2) - number of nodes = 1+2+4+....+n/2+n/4+n
1[(2)^1+logn - 1]/2-1 => (2n-1)
Let us take an example of returning and updating the sum of the subarray a[i.....j] of size n.
Example:
Query: output the sum from i=1 to i=5
Approach 1: Iterate from i = 1 to i = 5 and calculate the sum, update the element at i'th index, we'll update a[i] = updated element. now, the time complexity of the query is O(n) and the update is O(1).
Approach 2: Prefix Sum approach
First, we'll build the prefix sum array.
Query: Output the sum from i to j
sum[i....j] = {pref[j] - pref[i-1]} (if i!=0)
pref[j] (if i=0)
Time Complexity : O(1)
Updating value: Put a[i] = updated value.
To update the prefix array we need to change all prefix[i].
Array:
i=4,
Prefix sum array:
Let's take an example to understand this.
Example: Update the 4th index element to 13.
Original array: arr[]
Prefix sum: arr[] all elements get changed because the 4th index is updated so it will affect all elements after the 3rd index.
Time Complexity comparison table:
| Query | Update |
Approach-1 | O(n) | O(1) |
Approach-2 | O(1) | O(n) |
Segment Tree | O(log(n)) | O(log(n)) |
Requirement of log(n) time complexity: Many times, the number of queries and number of updates are of the order of 105-106, we will get TLE if we use Approach 1 or Approach 2.
Building a segment tree:
It is very simple to build a segment tree, we use the divide and conquer approach to build the segment tree.
pseudocode for implementation of Segment tree:
const int N = 1e5+2;
int a[N];
int tree[4*N];
void build(int node, int st, int en) {
if(st==en) {
tree[node] = a[st];
return;
}
int mid = (st+en)/2;
build(2*node, st, mid);
build(2*node+1, mid+1, en);
tree[node] = tree[2*node] + tree[2*node+1];
}
Applications of Segment trees:
Segment tree data structure can be used to solve various problems like:
- Range Min, Max & Sum Queries, and Range Update Queries
- segment tree with the max build, query, and update.
- segment tree with min build, query, and update.
- Computational geometry: Computational geometry is a mathematical field that includes the design, and analysis of efficient algorithms for solving geometric I/O problems. It is also used for pattern recognition and describes solid modeling algorithms.
- Geographic information systems: A Geographic Information System is a system that uses data that is attached to a unique location, and analyzes and generates geographically referenced information.
- Storing segments in an arbitrary manner.
- Used in competitive programming.
- Segment trees can be used to count the frequency of elements in a given range.
- : Segment trees can be used for image processing tasks.
Advantages and Disadvantages of segment trees:
S.No | Advantages | Disadvantages |
1 | There is no need to know tree rotation because in the test cases a divide and conquer algorithm. | Time Complexity of each and every query is O(log^2 max(n)) |
2 | Fast execution of code in general test cases. | Source code is longer than source using a balanced tree. |
3 | Allows processing interval or range queries in logarithmic time. | Segment trees require a large amount of memory to store all the nodes of the tree. |
4 | It performs well for large datasets. | The implementation of segment trees can be complex and difficult to understand. |
5 | Segment trees can be used to perform both static and dynamic operations on an array. | Slower for point update. |
Related Topic: Segment Tree
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem