Why Trie Exists and What Hash Map Cannot Do for Strings in DSA Javascript - Quick Recap

Recall & Review

beginner

What is a Trie data structure?

A Trie is a tree-like data structure that stores strings by sharing common prefixes. Each node represents a character, and paths from root to leaves form words.

beginner

Why can't a Hash Map efficiently handle prefix searches on strings?

Hash Maps store keys independently and do not share prefixes. So, searching for all keys with a common prefix requires checking every key, which is slow.

intermediate

How does a Trie improve prefix search compared to a Hash Map?

Trie nodes share prefixes, so searching for all words with a prefix is fast by following the prefix path once, then exploring its subtree.

beginner

What is a real-life example where Trie is better than Hash Map for strings?

Autocomplete in search engines: Trie quickly finds all words starting with typed letters, while Hash Map would check all stored words.

intermediate

What is a limitation of Hash Maps when storing many strings with shared prefixes?

Hash Maps store each string separately, wasting space by repeating prefixes, while Trie stores shared prefixes once, saving memory.

What does a Trie node typically represent?

A A character in a string

B A whole string

C A number

D A hash value

Each Trie node represents a single character, building strings by connecting nodes.

Why is prefix search slow in a Hash Map?

A Because Hash Maps use linked lists

B Because Hash Maps share prefixes

C Because Hash Maps store keys as trees

D Because Hash Maps do not store keys in order

Hash Maps store keys independently without order or prefix sharing, so prefix search requires checking all keys.

Which data structure is best for autocomplete features?

A Queue

B Trie

C Stack

D Hash Map

Trie efficiently finds all words with a given prefix, ideal for autocomplete.

How does Trie save memory compared to Hash Map for many strings with shared prefixes?

A By storing shared prefixes once

B By hashing prefixes

C By compressing strings

D By storing strings in arrays

Trie nodes represent shared prefixes once, reducing repeated storage.

Which operation is faster in Trie than in Hash Map?

A Inserting a number

B Finding a string by exact key

C Finding all strings with a given prefix

D Deleting a node

Trie is optimized for prefix searches, unlike Hash Map.

Explain why Trie is used for string prefix searches instead of Hash Maps.

Think about how strings share beginnings and how each data structure stores keys.

Describe a real-world scenario where Trie is better than Hash Map for handling strings.

Consider typing in a search box and how suggestions appear quickly.