Explain the SQL queries for the following two questions: (1) Retrieve distinct student_name, class, and section; (2) Find student names that appear more than once in the table.

Q1 uses the DISTINCT keyword to eliminate duplicate rows across all selected columns: SELECT DISTINCT student_name, class, section FROM students; This scans the table once and removes exact duplicates, producing a set of unique combinations. Q2 identifies duplicate student names by grouping and counting: SELECT student_name, COUNT() AS count FROM students GROUP BY student_name HAVING COUNT() > 1; The GROUP BY aggregates rows by name, COUNT(*) tallies occurrences, and HAVING filters to those with more than one record. Both queries are O(n) in time, with the GROUP BY query also requiring a hash or sort operation to aggregate, which is typically O(n log n) in worst‑case implementations. These patterns are standard in relational databases for deduplication and duplicate detection.