Hash Map

4 problems using this pattern

About this pattern:

Use hash tables for O(1) lookups and frequency counting. Great for key-value relationships.

Often used with: Sorting Array Heap Sliding Window String

Complexity Range

Time Complexity

O(n) (2 problems)
O(n * k log k) (1 problem)
O(n log n) (1 problem)

Space Complexity

O(n) (2 problems)
O(n * k) (1 problem)
O(k) (1 problem)

Problems Using Hash Map

Two Sum

Given an array of integers and a target, return the indices of two numbers that add up to the target.

Easy LeetCode
Time:
O(n)?
Why O(n)?
Single pass through the array
We visit each element exactly once in the loop. For each element, hash lookup and insertion are O(1) operations.
Example: Array of 1000 elements = ~1000 operations
Space:
O(n)?
Why O(n)?
Hash map stores up to n elements
In the worst case, we might store almost every element in the hash map before finding the solution.
Example: Array [1,2,3,4] with target 7 stores 3 elements in hash
Example: nums = [2,7,11,15], target = 9 → [0,1]
Hash Map Array
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Group Anagrams

Groups words that are anagrams of each other.

Medium LeetCode
Time: O(n * k log k)
Space: O(n * k)
Example: ["eat","tea","tan","ate","nat","bat"] → [["eat","tea","ate"],["tan","nat"],["bat"]]
Hash Map String Sorting
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Top K Frequent Elements

Returns the k most frequent elements in the array.

Medium LeetCode
Time: O(n log n)
Space: O(n)
Example: [1,1,1,2,2,3], k=2 → [1,2]
Hash Map Sorting Heap
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Longest Substring Without Repeating Characters

Find the length of the longest substring without repeating characters.

Medium LeetCode
Time: O(n)
Space: O(k)
Example: "abcabcbb" → 3 ("abc")
Sliding Window Hash Map
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