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I started with the basic CRUD schema and felt pretty good, then the version control extension came and I had to slow down.
Start by clarifying functional and non-functional requirements, then design a normalized data model with users, recipes, ingredients, and a versioning table. Walk through the core CRUD and search/sort APIs, then extend to version control by making updates append-only and exposing history and version retrieval endpoints. Discuss trade-offs like storage overhead vs. auditability and indexing strategies.
Pro tip: Emphasize that versioning should be immutable and append-only to ensure auditability and simplify concurrency; mention that you'd store a snapshot per version for simplicity, but consider diffs if storage becomes a concern.
Ask about expected scale, consistency needs, and whether version history must be immutable. Confirm if search is by exact ingredient or fuzzy, and sorting criteria.
Define tables: Users, Recipes, Ingredients, RecipeIngredients (many-to-many), and later RecipeVersions. Include ownership via user_id foreign key and timestamps.
Outline REST endpoints: POST /recipes, PUT /recipes/{id}, DELETE /recipes/{id}, GET /recipes?ingredient=...&sort=... Ensure authorization checks for ownership.
On every update, insert a new row into RecipeVersions with a snapshot of recipe data, version number, user_id, and timestamp. Expose GET /recipes/{id}/versions and GET /recipes/{id}/versions/{version}.
Compare snapshot vs. diff storage, indexing for search (e.g., GIN on ingredient array), and caching strategies. Mention concurrency control (optimistic locking) for updates.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Talked about monotonic counters at the recipe level using optimistic locking, and mentioned using a database sequence or a compare-and-swap approach.
Start by clarifying the requirements: are we preventing lost updates, ensuring linearizability, or just assigning unique IDs? Then propose a concurrency control mechanism such as optimistic concurrency with version numbers, and discuss trade-offs between optimistic and pessimistic approaches. Finally, address edge cases like conflict resolution and scalability.
Pro tip: Mention that version IDs should be assigned atomically with the write operation, not separately, to avoid race conditions. Also, consider using a monotonic counter or timestamp with a unique node ID to ensure global uniqueness and ordering.
Ask about consistency needs, expected concurrency level, and whether conflicts are common. Determine if the system requires strong consistency or can tolerate eventual consistency.
Decide between optimistic (e.g., version numbers, CAS) and pessimistic (e.g., locks) approaches. Explain why optimistic is often preferred for low-contention scenarios.
Propose a method to generate version IDs atomically, such as using a database sequence, a distributed counter (e.g., Snowflake), or a vector clock. Ensure IDs are unique and reflect causality.
Describe how to detect conflicts (e.g., version mismatch) and resolve them, such as rejecting the write, merging changes, or retrying with the latest version.
Compare approaches in terms of latency, throughput, and complexity. Mention how the solution scales with multiple users and distributed systems.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Framed it as optional but it wasn't really optional in the conversation.
Start by clarifying the requirements and constraints of the version history system, then evaluate branching and rollback as potential features. Discuss how each would impact the data model, storage, and API design, and propose a design that balances flexibility with complexity.
Pro tip: Emphasize that branching and rollback are not just features but require careful consideration of data consistency and user workflows. Suggest starting with rollback as it's simpler and often more immediately valuable, then layering branching if needed.
Ask questions to understand the use cases, expected scale, and consistency requirements for branching and rollback. This ensures your design addresses real needs.
Consider how branching would require a tree-like structure instead of a linear history, and how rollback might involve creating new versions or reverting pointers. Discuss trade-offs in storage and query complexity.
Outline how the API would change to support branch creation, switching, merging, and rollback operations. Consider how users would interact with these features and potential for errors.
Recommend implementing rollback first as it's less complex and provides immediate value, then adding branching if needed. This shows pragmatic thinking and risk management.
Summarize the trade-offs between simplicity and flexibility, and mention any alternative designs or mitigations for potential issues like merge conflicts or storage overhead.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.