Spent the first few minutes thinking it was basically just a nested hashmap problem, which it mostly is, but then the locking rules started stacking up.
Start by clarifying the requirements: the database stores records with fields, supports CRUD operations at the field level, and provides exclusive per-record locks. Then design the data structures: a hash map for records, each record as a map of fields, and a lock manager using a hash map of record keys to lock objects. Implement the operations and process queries sequentially, ensuring thread safety if concurrency is required.
Pro tip: Mention that you would use a fine-grained locking strategy (e.g., per-record locks) to allow concurrent access to different records, and discuss how to handle lock timeouts or deadlocks to demonstrate production-level thinking.
Ask about expected operations, concurrency requirements, lock semantics (e.g., blocking vs. non-blocking), and whether queries are processed in a single thread or multiple threads.
Choose a hash map for the database (key -> record), represent each record as a hash map of field names to values, and implement a lock manager using a concurrent map of record keys to lock objects.
For each operation (create, read, update, delete), acquire the appropriate lock (if needed), perform the operation on the record's field map, and release the lock. Ensure atomicity for multi-field updates.
Use per-record locks (e.g., ReentrantLock or synchronized blocks) to ensure exclusive access. Consider lock acquisition order to avoid deadlocks and provide a way to release locks (e.g., explicit unlock command).
Parse each query, execute the corresponding operation, and collect results (e.g., success/failure, field values). Handle edge cases like non-existent records or fields and return appropriate outputs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.