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Top K Frequent Elements at Apple — Interview Guide

How to approach Top K Frequent Elements in a Apple interview: the optimal approach, what Apple interviewers look for, and company-specific tips.

Updated 2026-09MediumHeaps & Hashing

The problem at Apple

Given a non-empty array and an integer k, return the k most frequent elements. The answer is guaranteed unique.

Apple uses this problem to assess craft, detail, and domain depth. Expect Apple-specific follow-ups that tie the solution back to production reasoning and the company's engineering bar.

Key concepts

Count frequencies with a hash map in O(n).
A min-heap of size k keeps the top k by frequency in O(n log k).
Bucket sort by frequency achieves O(n) when values are bounded.

Approach

import heapq, collections
def top_k(nums, k):
    freq = collections.Counter(nums)
    return heapq.nlargest(k, freq.keys(), key=freq.get)

What Apple looks for

Domain expertise relevant to the team.
Craft — performance, edge cases, and polish.
Passion for the product and user experience.
Independence and ownership of a feature end-to-end.

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