The core design wasn't too bad once I settled on a Playlist owning a map of guide IDs to Guide objects, with each Guide tracking its creator, timestamp, and vote tally.
Start by clarifying requirements and constraints, then define the core classes (Guide, Playlist) and their relationships. Design the data model to support efficient add, vote, and sorted retrieval, discussing trade-offs between different data structures and algorithms.
Pro tip: Demonstrate awareness of concurrency and scalability: mention how you would handle concurrent votes and large playlists, and consider caching or pre-sorting for performance.
Ask questions to understand expected scale, read/write patterns, and whether votes can be changed or removed. Confirm that getPlaylist should return a sorted list and discuss if it needs to be a snapshot or live view.
Identify main entities: Guide (with id, timestamp, vote count) and Playlist (with collection of guides). Define methods: addGuide, vote, getPlaylist, and any helper methods.
Choose data structures for storing guides and votes. Consider using a hash map for quick guide lookup and a balanced BST or sorted list for maintaining order by vote count and timestamp.
Define a comparator that sorts by vote count descending, then by timestamp ascending (or descending, based on tie-breaking rule). Ensure getPlaylist returns guides in that order efficiently.
Talk about time/space complexity, concurrency handling, and potential optimizations like caching sorted results or using a priority queue. Mention how to extend for features like user-specific votes or pagination.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This is where I kind of hung myself by having the sort logic baked directly into getPlaylist.
Start by clarifying the requirements and constraints, then propose a flexible design that decouples sorting logic from the core playlist retrieval. Discuss trade-offs between different implementation strategies, and emphasize extensibility, performance, and maintainability.
Pro tip: Mention that you would first check if there's an existing pattern or library in the codebase for sorting, and if not, propose a strategy pattern with a registry to allow easy addition of new sort orders without modifying existing code.
Ask questions to understand what sort orders are needed, expected frequency of new additions, performance requirements, and whether sorting should be done in-memory or at the database level.
Suggest using the Strategy pattern to encapsulate each sort algorithm, with a factory or registry to map sort keys to strategies. This allows adding new sort orders without changing the core getPlaylist method.
Explain how to handle parameters (e.g., sort direction, pagination), ensure thread safety, and integrate with existing data access layers. Consider using comparators or database ORDER BY clauses.
Compare approaches: in-memory sorting vs. database sorting, flexibility vs. performance, and complexity vs. maintainability. Highlight how the chosen design aligns with Amazon's scalability and operational excellence principles.
Conclude with how this design supports future extensions, such as composite sorts or dynamic sort orders, and mention testing and monitoring considerations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.