Start by clarifying requirements and constraints, then design a modular validation engine that separates rule definition from execution. Implement incrementally: begin with basic field checks, then add cross-field constraints, and finally extend with more complex rules, ensuring each part is testable and extensible.
Pro tip: Emphasize extensibility and performance: use a rule registry and consider streaming validation to handle large volumes without loading all records into memory. Mention how you would test each rule and the system as a whole.
Ask about the stream's characteristics (volume, velocity, variety), validation rules' complexity, error handling expectations, and performance requirements. Confirm whether rules can be added dynamically and if validation is stateless per record.
Propose a rule-based system where each validation rule is a separate, composable unit. Use interfaces or abstract classes for rules, and a validator that applies rules to records. Consider a rule registry for easy addition of new rules.
Start with simple rules: field presence (required fields) and type checking (e.g., string, number, date). Ensure these are efficient and can short-circuit on failure to avoid unnecessary checks.
Extend the system to support rules that depend on multiple fields (e.g., start date before end date, conditional requirements). Discuss how to represent these rules and handle dependencies between fields.
Discuss further extensions like custom business rules, external data lookups, or asynchronous validation. Address performance: batching, parallel processing, and streaming to handle high throughput. Mention testing strategies and error reporting.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.