The join logic itself wasn't bad once I clarified the schema upfront, which I actually remembered to do this time.
Start by clarifying the input data structure and edge cases, then propose a solution that iterates through the dataset to build a dictionary mapping internal IDs to external IDs. Discuss trade-offs such as handling duplicates, missing mappings, and data validation, and consider time/space complexity.
Pro tip: Demonstrate awareness of real-world data issues by mentioning how you would handle conflicts (e.g., multiple external IDs for one internal ID) and ensure the mapping is deterministic and reliable.
Ask questions to understand the dataset structure: is it a list of records, a nested object, or a database table? What are the fields and their types? Are there any constraints or expected outputs?
Consider scenarios like missing internal or external IDs, duplicate entries, conflicting mappings, and invalid data. Discuss how to handle them (e.g., skip, log, or raise errors).
Propose an approach: iterate through the dataset, extract internal and external IDs, and populate a dictionary. If duplicates exist, decide on a resolution strategy (e.g., last-write-wins, first-write-wins, or flag conflict).
Discuss time and space complexity (typically O(n) time, O(m) space where m is number of unique internal IDs). Mention trade-offs between simplicity and robustness, and potential optimizations.
Write clean, readable code with appropriate data structures. Suggest test cases covering normal, edge, and error scenarios to validate correctness.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.