← Databricks Interview Insights
This is more involved than a plain LRU cache question.
Start by clarifying requirements (e.g., durability guarantees, performance targets, concurrency) and then outline the core components: an in-memory key-value store, a write-ahead log for durability, and a recovery mechanism. Discuss trade-offs such as fsync frequency, log compaction, and concurrency control, and explain how they affect durability and performance.
Pro tip: Emphasize that durability requires fsync on every write, but batching writes can amortize the cost—demonstrate awareness of the latency-throughput trade-off and how to tune it based on workload.
Ask about expected workload (read/write ratio, key size, value size), durability guarantees (e.g., no data loss on crash), performance targets (latency, throughput), and concurrency needs.
Describe the in-memory hash map for fast access, the WAL for durability (append-only log of operations), and a recovery process that replays the log on startup.
Discuss fsync policies (e.g., fsync on every write vs. periodic), batching, and how they impact durability and latency. Mention log compaction to prevent unbounded growth.
Explain locking or lock-free approaches for concurrent reads/writes, and how to ensure the WAL is written before acknowledging a write (write-ahead logging rule).
Outline how to recover from crashes (replay WAL, handle partial writes), and consider checksums or other integrity checks to detect corruption.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.