Why use Ternary search tree (TST)?

Ternary search tree (TST) is a very popular data structure used in the problem solving becaus of following reasons:

• First, they offer efficient search operations, particularly for strings, with lookup times typically on the order of O(log n), where n is the length of the search key. This makes them suitable for applications requiring fast data retrieval based on string keys.
• Second, TSTs are space-efficient, storing common prefixes only once and branching out into three parts: less than, equal to, and greater than the current character in the key. This can lead to better memory utilization, especially for large sets of keys with common prefixes.
• Third, TSTs naturally support prefix matching operations, making them well-suited for autocomplete functionality or dictionary-like applications.

However, it’s essential to consider trade-offs such as complexity, memory overhead, and performance characteristics before deciding to use TSTs in a particular application.

Now if you are wondering where you are and what is this Ternary Search Tree (TST), dont worry. We got you covered.

What is Ternary Search Tree?

A ternary search tree (TST) is a tree data structure used for storing strings. It is similar to a binary search tree (BST), but each node in a TST can have three children: one for each of the three possible outcomes of comparing the current character in the string to the character stored in the node.

Node Structure of Ternary Search Tree

Each node in a TST has the following structure:

• Character: The character stored in the node.
• Left child: The child node that stores characters less than the current character.
• Middle child: The child node that stores characters equal to the current character.
• Right child: The child node that stores characters greater than the current character.

Advantages of Ternary Search Tree

• Fast search: TSTs support fast search operations because they utilize the characters of the string to navigate the tree, reducing the number of comparisons required.
• Efficient storage: TSTs store only the unique characters of the strings, making them memory-efficient compared to other string storage structures.
• Prefix search: TSTs allow for efficient prefix searches, making them useful for applications like autocompletion and spell checking.

Applications of Ternary Search Tree

TSTs are used in various applications, including:

• String matching: Searching for strings in large datasets.
• Autocompletion: Suggesting possible completions for partially entered strings.
• Spell checking: Identifying misspelled words and suggesting corrections.
• Data compression: Compressing strings by storing only unique characters.