Start by clarifying requirements and assumptions, then present a data model that uses version chains per field with timestamps and TTLs, and explain how each operation (get, put, delete, scan, snapshot, restore) is implemented. Finally, discuss trade-offs in time and space complexity, and mention optimizations like indexing and compaction.
Pro tip: Emphasize that per-field TTL and versioning require careful handling of tombstones and expiration during time-travel reads; explicitly state that snapshots are immutable and restores are atomic to avoid consistency issues.
Ask about expected read/write patterns, timestamp source (client vs. server), and whether TTL is absolute or relative. State assumptions like monotonic timestamps and single-node in-memory store.
Propose a nested map: key -> field -> list of versions (timestamp, value, ttl). Include tombstones for deletes and discuss how to handle expiration lazily or eagerly.
For each operation (put, get, delete, scan, snapshot, restore), specify behavior with respect to timestamps, TTL, and versioning. For scans, explain how to iterate keys in lexicographic order and filter fields by timestamp and TTL.
Compare time and space complexity for each operation, and discuss trade-offs between eager vs. lazy expiration, snapshot copying vs. copy-on-write, and indexing for scans.
Mention possible optimizations like version compaction, using balanced trees for ordered scans, and handling edge cases like clock skew, concurrent writes, and snapshot consistency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.