Hash Map / Set

Trade space for time using O(1) lookup to find pairs, duplicates, and frequencies.

12 problems 6 Easy 6 Medium 0 Hard

Overview

Hash maps and sets enable O(1) average-time lookup, insertion, and deletion. They are the go-to tool for counting, grouping, and finding complements.

When to Use

Two sum (find complement)
Anagram grouping
Longest consecutive sequence
Frequency counting
Finding duplicates
LRU Cache design

Common Mistakes

Using arrays for large key ranges — use Map/object instead
Forgetting hash collisions can degrade to O(n)
Not considering the space cost

Complexity

Time

O(1) average for lookup/insert, O(n) space

Space

O(n)

// Frequency count
const freq = new Map();
for (const x of arr) freq.set(x, (freq.get(x) ?? 0) + 1);

// Two sum
function twoSum(nums, target) {
  const seen = new Map(); // value -> index
  for (let i = 0; i < nums.length; i++) {
    const complement = target - nums[i];
    if (seen.has(complement)) return [seen.get(complement), i];
    seen.set(nums[i], i);
  }
}

Problems (12)

Hide completed

Problem	Difficulty	Companies	Freq
Two Sum	Easy	AmazonGoogle +3	High
Group Anagrams	Medium	AmazonFacebook +2	High
Top K Frequent Elements	Medium	FacebookAmazon +1	High
Valid Anagram	Easy	AmazonApple +1	High
Longest Consecutive Sequence	Medium	GoogleFacebook +1	High
Contains Duplicate	Easy	AmazonGoogle +1	High
Word Pattern	Easy	LinkedInDropbox	Medium
Isomorphic Strings	Easy	LinkedInAmazon	Medium
LRU Cache	Medium	AmazonMicrosoft +4	High
4Sum II	Medium	AmazonGoogle	Medium
Number of Good Pairs	Easy	Amazon	Medium
Subarray Sum Divisible by K	Medium	FacebookAmazon +1	Medium

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