In this lesson, we will introduce the trie (pronounced "try"), which is a kind of tree that's often used for storing and retrieving strings. In fact, the word trie is associated with the "trie" in retrieval. We'll focus on the basics of what a trie is in this lesson. Then, if you like, you can do further research on your own to learn about how to add, remove, and find values in a trie.
A trie always has an "empty" root node with references to other nodes. Because of the references, it's not really empty - but the root node doesn't have a value on its own. It's common to use tries to store words, so if we were going to use a trie to store English words, we'd have a root node with 26 child nodes. Each child node would represent a letter of the alphabet.
To simplify things, the trie above just shows the first three letters of the alphabet.
So what happens once we want to add actual words to a trie?
Each child node has a reference to each letter of the alphabet - just like the root node. So we'd construct words by adding more child nodes to the trie.
This trie now includes three words: cat, call, and cot. Each use the C node, which now has two child nodes to represent the three words we've added: an A node and an O node. Cat and call both use the C and its child A node. If we were going to add the word can, it would also use these two nodes before diverging.
The main advantage of tries is that they can retrieve strings very quickly. However, a significant disadvantage of tries is that they take a large amount of memory. Despite the memory issue, there are many important use cases for quick string retrieval. For instance, consider the autofill feature on search engines. A trie can be used to quickly determine possible substrings if a user has typed in the letters c and a. You can likely imagine many other use cases where quickly retrieving strings is important - ranging from the fields of genomics to data analytics.
Lesson 3 of 5
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