← Perplexity AI Interview Insights
I started with buffered writes and batching, then moved to write-ahead logging and memory-mapped files.
Start by clarifying the context—what kind of data, volume, and latency requirements—then structure your answer around the I/O stack: batching, buffering, async writes, and file system choices. Emphasize trade-offs between throughput, latency, and durability, and tie your techniques to real-world scenarios like log ingestion or database persistence.
Pro tip: Mention that write performance is often limited by fsync and disk seek times, so techniques like group commit and write-ahead logging can drastically improve throughput while maintaining durability. Also, consider using memory-mapped files or direct I/O to bypass OS caching when appropriate.
Ask about data volume, write frequency, latency vs. throughput needs, and durability guarantees to tailor your answer.
Explain how accumulating writes in memory and flushing in larger chunks reduces syscalls and disk seeks, improving throughput.
Describe how non-blocking writes, multiple threads, or I/O queues can overlap computation with disk operations and utilize multiple disks.
Discuss write-back caching, memory-mapped files, direct I/O, and choosing file systems or storage engines optimized for writes (e.g., LSM trees).
Explain techniques like group commit, write-ahead logging, and tuning fsync frequency to balance performance and data safety.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.