The first part was fine, walked through hashing, collision handling, load factor.
Start by explaining the core components of a hashmap (array of buckets, hash function, collision resolution) and how they enable O(1) average operations. Then describe the resizing process when load factor exceeds a threshold, and finally discuss techniques to mitigate latency spikes during resizing, such as incremental rehashing or using a larger initial capacity.
Pro tip: Mention that Apple often deals with real-time systems, so tying your answer to maintaining consistent latency (e.g., for audio/video processing) shows you understand their priorities. Also, acknowledge trade-offs: incremental resizing adds complexity and memory overhead, so it's not always worth it.
Describe how a hashmap uses an array of buckets, a hash function to map keys to indices, and collision handling (e.g., chaining or open addressing).
Explain that when the load factor (entries/buckets) exceeds a threshold (e.g., 0.75), the map doubles the bucket array and rehashes all existing entries into the new array.
Acknowledge that rehashing all entries at once causes a pause proportional to the number of entries, which can be problematic for latency-sensitive applications.
Discuss incremental rehashing: gradually move entries to the new table during subsequent operations, or use a larger initial capacity to reduce resize frequency.
Mention that incremental rehashing adds complexity and memory overhead (two tables), and that alternative data structures like concurrent hashmaps or consistent hashing may be better for distributed systems.
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