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@PranathiDeepak
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@super30admin
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Let me evaluate each solution separately.

Problem1.sql:

  1. Correctness: The solution appears correct for calculating total distance traveled by each user, including users with no rides (handled by LEFT JOIN and IFNULL).
  2. Time Complexity: O(n + m) where n is number of users and m is number of rides, due to the GROUP BY operation.
  3. Space Complexity: O(n) for storing the CTE results.
  4. Code Quality: Well-structured with clear CTE usage. Good practice to include both id and name in GROUP BY for consistency.
  5. Efficiency: Could potentially use a subquery instead of CTE for such a simple case, but CTE is more readable.

Problem2.sql:

  1. Correctness: The solution correctly calculates the difference between apples and oranges sold per date, but has a potential issue - it assumes exactly one apple and one orange record per date.
  2. Time Complexity: O(n^2) due to the self-join without proper indexing conditions.
  3. Space Complexity: O(n) for the result set.
  4. Code Quality: Could be improved with explicit JOIN syntax and better aliases. The WHERE clause mixing join conditions with filters is not ideal.
  5. Efficiency: Could be optimized with a pivot approach or conditional aggregation:
    SELECT sale_date,
           SUM(CASE WHEN fruit = 'apples' THEN sold_num ELSE 0 END) - 
           SUM(CASE WHEN fruit = 'oranges' THEN sold_num ELSE 0 END) AS diff
    FROM sales
    GROUP BY sale_date
    ORDER BY sale_date
    

General improvements needed:

  1. Problem2.sql needs better handling of potential missing records for either fruit.
  2. Both solutions could benefit from comments explaining the approach.
  3. Consistent formatting (Problem1.sql has better formatting than Problem2.sql).

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