The SET and GET parts took maybe five minutes.
Start by clarifying the requirements and constraints, then propose a data model using a hash map for rows and secondary indexes for efficient filtering and sorting. Outline the core operations (SET, GET, SELECT) and discuss trade-offs between simplicity and performance, mentioning how to handle sorting and tie-breaking.
Pro tip: Demonstrate awareness of real-world database internals by discussing indexing strategies and the cost of maintaining indexes on writes, and suggest a simple but extensible design that could evolve to support more complex queries.
Ask questions to confirm the scope: single table, string values, exact match filtering, lexicographic sorting, and tie-breaking by row key. Clarify expected operations and any performance constraints.
Propose storing rows in a hash map keyed by row key, with each row as a map of column names to string values. Consider secondary indexes (e.g., hash maps or sorted structures) for columns frequently used in filters or sorts.
Define SET (insert or update a row), GET (retrieve a row by key), and SELECT (filter by column value, then sort by another column with tie-breaking by row key). Discuss how indexes can speed up these operations.
Explain that SELECT results should be sorted lexicographically by the specified column, and when values are equal, by row key. Mention using a comparator that first compares the sort column, then the row key.
Talk about time/space complexity, when to use indexes, and how the design could be extended to support more columns, range queries, or persistence. Mention potential concurrency considerations if needed.
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