An Introduction to Trie

Strings are essentially the most important and prevalent topics for a wide range of programming issues. Trees that store data more effectively, such as a binary search tree, are presumably familiar to you. There are a variety of methods to portray something as seemingly straightforward as a group of words. A hash or dictionary, for example, is something we’re probably all familiar with, as is a hash table. However, there is another structure called a trie that was devised to answer the challenge of representing a set of words. To distinguish it from other “tree” structures, the term “trie” originates from the word retrieval and is commonly pronounced “try.”

A Trie is a very unique and valuable data structure that is based on a string’s prefix and may be seen as a graph. It is made up of nodes and edges. Each node has a maximum of 26 children, with edges connecting each parent node to its offspring. Each of the 26 letters of the English alphabet is represented by one of these 26 pointers. Values are generally not associated with every node, only with leaves, and the root is associated with the empty string.

A trie is a tree data structure that allows strings with similar character prefixes to share prefix data while keeping the tails separate. In a trie, strings are stored in a top-to-bottom order based on their prefix. All prefixes of length 1 are saved until level 1, then sorted until level 2, and so on.

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