Start by writing a SQL query that joins the city table to the zip table on city_id (or equivalent foreign key) and sums the population, filtering by the given city name. Then discuss the ambiguity when multiple cities share the same name, and propose solutions such as requiring additional parameters (state/country) or returning a list of matches with their locations.
Pro tip: Mention that you would clarify the input requirements with the interviewer before writing the query, and consider adding a unique identifier (like city_id) to the output to disambiguate results.
Ask about the table structures, especially foreign keys linking city to zip, and whether the input is just a city name or includes state/country. Confirm if population is stored per ZIP and if a city can have multiple ZIPs.
Construct a query that joins city to zip on city_id, filters by city name, and sums the population. Use GROUP BY if needed, and ensure proper aggregation.
Explain that multiple cities can share the same name across states/countries, so the query might return an aggregate for all matching cities. Discuss options: return separate rows per city with location details, or require additional input to disambiguate.
Suggest modifying the query to group by city_id and include state/country names, or changing the API to accept city_id or a combination of city, state, and country. Mention handling NULLs or missing data.
Talk about performance implications of joins and aggregations, and edge cases like cities with no ZIP codes or duplicate ZIP entries. Highlight the importance of data integrity and indexing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.