Start by clarifying the table schema and whether ties need handling. Then use a window function like ROW_NUMBER() partitioned by continent and ordered by population descending to select the top country per continent. Finally, filter to only the top-ranked rows.
Pro tip: Mention that window functions are more efficient and readable than self-joins or correlated subqueries, and that you'd handle ties by either using RANK() or specifying a tiebreaker like country name.
Confirm the table name, columns (country, continent, population), and whether ties should be broken or all tied countries returned.
Decide between window functions (e.g., ROW_NUMBER, RANK) or alternative methods like GROUP BY with a join, considering performance and readability.
Use ROW_NUMBER() OVER (PARTITION BY continent ORDER BY population DESC) to rank countries within each continent, then filter for rank = 1.
Consider ties (use RANK() if needed), null populations, and verify the query returns one row per continent.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Basically the same query, just changed the filter from rank = 1 to rank <= 2.
Use a window function like ROW_NUMBER() partitioned by continent and ordered by population descending, then filter to ranks 1 and 2. This efficiently handles ties and returns the top 2 per group in a single query.
Pro tip: Mention that if ties are possible, you might need to decide between ROW_NUMBER, RANK, or DENSE_RANK based on business requirements, and clarify that ROW_NUMBER arbitrarily breaks ties while RANK assigns the same rank to ties.
Confirm the definition of 'top 2' (e.g., handle ties) and the desired output columns (continent, country, population, rank).
Select ROW_NUMBER() for unique ranks, or RANK()/DENSE_RANK() if ties should share ranks, and explain the trade-offs.
Use a window function partitioned by continent, ordered by population descending, and filter for rank <= 2.
Check for ties, ensure correct ordering, and consider indexing or partitioning strategies for large datasets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This one took me longer than I'd like to admit.
Clarify the definition of 'top 2 countries per continent' (e.g., by population) and the data source. Then write a SQL query that ranks countries within each continent by population, filters to top 2, and computes each country's population as a percentage of the continent's total population, rounding to 2 decimal places.
Pro tip: Always confirm whether 'top 2' means top 2 by population or another metric, and whether the continent total includes all countries or only the top 2. This ambiguity can change the result significantly.
Ask clarifying questions: What defines 'top 2'? Is it by population? Should the continent total include all countries or only the top 2? What is the data source and schema?
Use a window function like ROW_NUMBER() or RANK() partitioned by continent and ordered by population descending to identify the top 2 countries per continent.
Calculate the total population for each continent, either as a separate aggregation or using a window function SUM() OVER (PARTITION BY continent).
For each top 2 country, divide its population by the continent total, multiply by 100, and round to 2 decimal places using ROUND().
Check that the sum of shares for each continent is ≤ 100% (or exactly 100% if only top 2 are considered) and format the output clearly.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.