← Valon Mortgage Interview Insights
I started with the insert and select logic pretty confidently, but the WHERE clause is where things got messy.
Start by clarifying requirements and constraints (e.g., data types, concurrency, memory limits), then propose a simple in-memory table structure (e.g., array of rows or columnar store) and outline the core operations. Implement each operation with clear separation of concerns: parsing, filtering, projection, sorting, and output formatting, while discussing trade-offs and potential optimizations.
Pro tip: Demonstrate awareness of real-world constraints by mentioning that a fixed schema allows pre-validation and type enforcement, and that sorting can be optimized with indexes or by leveraging stable sort algorithms. Also, discuss how you would handle edge cases like nulls, empty results, and invalid queries.
Ask questions to understand the expected scale, data types, query complexity, and performance requirements. Confirm whether concurrency, persistence, or transactions are needed.
Choose an in-memory representation for the table, such as a list of rows (each row a struct/object) or a columnar store. Define how to store schema metadata and enforce types.
Break down each operation: INSERT validates and appends a row; SELECT applies WHERE filter, then projects columns, then sorts by ORDER BY. Use helper functions for filtering and sorting.
Discuss potential optimizations like indexing for WHERE or ORDER BY, and handle edge cases such as null values, empty tables, and invalid column references.
Outline a testing strategy: unit tests for each operation, integration tests for combined queries, and performance tests for large datasets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.