The continent column in the country table contains no null values. Examine this output: A. B. C. D.

Question

Exhibits

Options

• ASELECT Continent, Population as pop, COUNT(DISTINCT code) as num_country FROM country GROUP BY Continent ORDER BY Continent;
• BSELECT Continent, Population as pop, COUNT(DISTINCT code) as num_country FROM country GROUP BY Continent WITH ROLLUP ORDER BY Continent;
• CSELECT Continent, SUM(Population) as pop, COUNT(DISTINCT code) as num_country FROM country GROUP BY Continent ORDER BY Continent;
• DSELECT Continent, SUM(Population) as pop, COUNT(DISTINCT code) as num_country FROM country GROUP BY Continent WITH ROLLUP ORDER BY Continent;

• A
  93% (43)
• B
  2% (1)
• D
  4% (2)

Explanation

Note: The stated answer of A appears to be an error in this question - the correct answer should be C. Here's why:

Why C is correct: SUM(Population) is the proper aggregate function to total population values across all countries per continent. Without SUM(), selecting Population in a GROUP BY query (as in A and B) is non-deterministic or invalid in standard SQL - it would return an arbitrary single row's population value rather than the continent total.

Why A is wrong: Population is not wrapped in an aggregate function. In a GROUP BY query, every non-grouped column must be aggregated. MySQL's non-strict mode may allow this, but it returns a meaningless arbitrary value, not a continent-wide total.

Why B is wrong: Same non-aggregated Population problem as A, plus WITH ROLLUP generates an extra summary row where Continent is NULL - but the question states Continent has no nulls, so a NULL row in the output would come only from ROLLUP, which doesn't appear in the described output.

Why D is wrong: Although SUM(Population) is correct, WITH ROLLUP adds a grand-total row with Continent = NULL. Since the output being matched doesn't include that extra row, D doesn't match.

Memory tip: The hint "continent has no null values" is your signal - any query using WITH ROLLUP introduces a NULL in the grouping column for the summary row, so you can quickly eliminate B and D. Then ask: "Is the population summed or raw?" - aggregation requires SUM(), eliminating A.

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