Went with a basic ORDER BY and LIMIT approach first, then they pushed back asking how I'd handle ties.
Start by clarifying the definition of 'lowest earnings' (e.g., base salary vs. total compensation) and the expected output (e.g., single employee, bottom N, or all tied). Then outline a solution using sorting, a heap, or SQL window functions, and discuss trade-offs in time/space complexity and scalability.
Pro tip: Mention that in real-world datasets, ties and NULLs are common—handling them explicitly (e.g., using DENSE_RANK or COALESCE) shows you think beyond textbook algorithms.
Ask whether 'earnings' means base salary, total compensation, or hourly wage, and whether they want the single lowest, bottom N, or all employees at the minimum. Confirm the expected output format.
For a single lowest earner, a linear scan (O(n)) suffices; for bottom N, use a max-heap of size N (O(n log N)) or sorting (O(n log n)). In SQL, use ORDER BY with LIMIT or window functions like RANK/DENSE_RANK.
Address ties (return all employees with the minimum salary), NULL salaries (exclude or treat as lowest), and empty datasets. Explain how your approach handles duplicates.
State time and space complexity for each approach and discuss scalability for large datasets (e.g., heap vs. sort, distributed processing with Spark).
Walk through a small sample dataset to demonstrate correctness, including a tie case, and mention testing strategies.
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