My first instinct was a plain hashmap and I started going that direction before realizing get() needed something smarter than a linear scan.
Clarify requirements and constraints, then propose a design using a hash map from keys to time-ordered structures (e.g., sorted list or balanced BST) to support efficient timestamp-based lookups. Discuss trade-offs between different data structures and algorithms, and consider edge cases and scalability.
Pro tip: Mention that timestamps are monotonically increasing per key in typical use cases, allowing append-only structures and binary search for O(log n) lookups. Also, discuss how to handle out-of-order writes if they are allowed.
Ask about expected operations, data volume, timestamp ordering, concurrency, and persistence needs. Confirm whether timestamps are unique per key and if out-of-order writes are allowed.
Propose a hash map for key lookup, with each key mapping to a time-ordered collection (e.g., dynamic array, balanced BST, or skip list) for efficient timestamp-based retrieval.
For set, append or insert the (timestamp, value) pair; for get, perform binary search to find the largest timestamp ≤ query timestamp. Discuss time complexities: O(1) average for set, O(log n) for get.
Address cases like missing key, no timestamp ≤ query, duplicate timestamps, and out-of-order writes. Explain how the design handles them.
Compare alternatives (e.g., B-tree, skip list) and mention concurrency, memory usage, and potential for caching or compression.
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