Start by clarifying requirements: in-memory, single-process, thread-safe, and expected scale. Then design a simple yet extensible architecture using a map of topics, each with a list of subscribers, and implement publish to iterate over subscribers and deliver messages. Discuss trade-offs like synchronous vs asynchronous delivery, backpressure, and concurrency control.
Pro tip: Show awareness of real-world concerns: mention that Snapchat's scale would require distributed pub/sub, but for in-memory you'd focus on thread safety and efficient delivery. Also, propose a simple API and test cases to validate behavior.
Ask about expected number of topics, subscribers per topic, message throughput, delivery guarantees (at-most-once, at-least-once), and whether persistence or ordering is needed.
Propose a Topic class holding a list of subscribers, and a PubSubSystem class with a map from topic name to Topic. Consider using concurrent data structures for thread safety.
Implement createTopic to add a new topic, subscribe to add a subscriber to a topic, and publish to iterate over subscribers and deliver the message (e.g., via callback).
Discuss thread safety: use locks or concurrent collections. Decide on synchronous vs asynchronous delivery, and handle slow subscribers (e.g., queues, backpressure).
Outline unit tests for basic operations and edge cases. Mention possible extensions like wildcard subscriptions, message filtering, or persistence.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the current publish method and subscriber model, then propose a push-based design using callbacks or per-subscriber queues. Discuss trade-offs like backpressure, delivery guarantees, and scalability, and outline how you would implement and test the change.
Pro tip: Emphasize idempotency and backpressure handling—Snapchat deals with massive scale, so showing awareness of these concerns will set you apart. Also, mention that you'd consider a hybrid approach if some subscribers still need polling.
Ask questions to understand the existing publish method, subscriber interface, and constraints (e.g., message ordering, delivery guarantees). Identify why polling is used and what push delivery should achieve.
Decide between callbacks (direct invocation) and per-subscriber queues (decoupled). Consider factors like subscriber count, message volume, and failure isolation.
Address backpressure, retries, dead-letter queues, and idempotency. Ensure the system can handle slow or failing subscribers without affecting others.
Modify the publish method to enqueue messages or invoke callbacks. Update subscriber registration to provide callback or queue endpoints.
Write unit and integration tests for delivery, failure scenarios, and performance. Compare metrics (latency, throughput) with the polling approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
No code needed here, just verbal design, which I actually appreciated.
Start by defining the problem: multiple threads or processes publishing and subscribing concurrently, requiring synchronization to avoid race conditions. Then walk through a mutex-based solution, highlighting its simplicity and limitations (serialized access). Finally, introduce a read/write lock, explaining how it allows concurrent reads (subscribers) while writes (publishers) remain exclusive, thus improving throughput.
Pro tip: Mention that read/write locks are not a silver bullet: they add overhead and can cause writer starvation; consider using a fair lock or a read-copy-update (RCU) mechanism for read-heavy workloads. This shows you understand trade-offs beyond the textbook answer.
Ask or state assumptions about the system: are publishers and subscribers threads in the same process, or separate processes? What is the expected read/write ratio? This sets the stage for choosing the right synchronization primitive.
Describe using a single mutex to protect the shared data structure (e.g., a queue or topic list). Publishers and subscribers must acquire the mutex before accessing, ensuring mutual exclusion. Note that this serializes all operations, limiting throughput.
Explain that with a mutex, even multiple subscribers (readers) cannot access concurrently, leading to unnecessary blocking and reduced throughput, especially in read-heavy scenarios.
Propose a read/write lock: subscribers acquire a shared (read) lock, allowing multiple concurrent reads; publishers acquire an exclusive (write) lock, blocking all others. This increases parallelism for reads while maintaining data consistency.
Mention that read/write locks have overhead and can lead to writer starvation. Suggest alternatives like fair locks, RCU, or lock-free data structures for specific scenarios. Conclude with a recommendation based on the read/write ratio.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.