Databricks·Software Engineer·Onsite - System Design / Architecture·Senior

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May 2026

Summary

Databricks system design round for a software engineering role. The whole session was basically one deep question about concurrent log writing, and they really wanted you to go end-to-end on it, not just sketch a queue and call it done.

Questions Asked (1)

Design a thread-safe log writer that supports many concurrent producer threads appending entries while one or more writer threads flush to durable storage. Cover the producer API, buffering strategy, flush triggers, ordering and timestamping guarantees, graceful shutdown, and crash safety.

System DesignTechnical Trade-offs

Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints (throughput, latency, durability, ordering) to frame trade-offs. Then propose a design using a lock-free ring buffer or concurrent queue for producers and a dedicated flusher thread, detailing API, buffering, flush triggers, ordering, shutdown, and crash safety. Conclude by discussing trade-offs and potential optimizations.

Pro tip: Emphasize that crash safety requires careful handling of partial writes and fsync ordering; mention using a write-ahead log (WAL) or checksums to detect corruption. Also, highlight that batching and backpressure are key to balancing throughput and latency.

1. Clarify Requirements and Constraints

Ask about expected throughput, latency tolerance, durability guarantees (e.g., fsync per entry vs. batch), ordering requirements (global vs. per-thread), and failure scenarios. This shapes the design.

2. Design Producer API and Buffering

Define a simple API like log(level, message) that is thread-safe. Use a lock-free ring buffer or a concurrent queue (e.g., Michael-Scott queue) to decouple producers from writers, minimizing contention.

3. Define Flush Triggers and Writer Threads

Specify when to flush: buffer full, time-based (e.g., every 100ms), or explicit flush call. Use one or more writer threads that drain the buffer and write to durable storage, possibly with batching.

4. Address Ordering, Timestamping, and Shutdown

Decide on ordering guarantees (e.g., global sequence numbers or per-thread ordering). Timestamp entries at production time. Implement graceful shutdown by signaling writers to drain and flush before exit.

5. Ensure Crash Safety and Discuss Trade-offs

Use techniques like write-ahead logging, checksums, and atomic writes to handle crashes. Discuss trade-offs between durability, latency, and throughput, and potential optimizations.

Key Points to Mention

Lock-free data structures (e.g., ring buffer, concurrent queue) to minimize contention among producers.
Batching and backpressure mechanisms to balance throughput and latency.
Flush triggers: size-based, time-based, and explicit flush; use of condition variables or timers.
Ordering guarantees: global sequence numbers vs. per-thread ordering; timestamping at production time.
Graceful shutdown: draining buffers, signaling writers, and ensuring all entries are flushed.
Crash safety: write-ahead logging, fsync, checksums, and handling partial writes.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.