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@sakshiasati17
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  1. Correctness:

    • For Market_Analysis_II.sql, the solution correctly identifies the second item sold by each seller and checks if it matches their favorite brand. The use of RANK() and LEFT JOIN handles cases where a seller might not have a second item.
    • For Tournament_Winners.sql, the solution correctly calculates total scores for each player, groups them, and selects the top player in each group based on score and player_id. The use of COALESCE ensures players with no matches are included with a score of 0.
  2. Time Complexity:

    • Both solutions use window functions (RANK() and ROW_NUMBER()) which typically have O(n log n) complexity due to sorting operations.
    • The JOIN operations in both solutions are O(n) assuming proper indexing.
  3. Space Complexity:

    • Both solutions create temporary tables (CTEs) which require O(n) space for storing intermediate results.
  4. Code Quality:

    • The code is generally well-structured and readable.
    • CTE names could be more descriptive (e.g., "SecondItems" instead of "ACTE" in Market_Analysis_II.sql).
    • In Market_Analysis_II.sql, the column alias "2nd_item_fav_brand" should be quoted as it starts with a number.
    • Consistent indentation and spacing would improve readability.
  5. Efficiency:

    • Both solutions are efficient for typical database sizes.
    • In Tournament_Winners.sql, the UNION ALL could potentially be optimized if we know more about the data distribution.
    • Adding comments explaining the purpose of each CTE would improve maintainability.

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