Done SQL4

[sakshiasati17]

Done SQL4

1 Problem 1 : The Number of Seniors and Juniors to Join the Company

2 Problem 2 : League Statistics

3 Problem 3 : Sales Person

4 Problem 4 : Friend Requests II

[super30admin]

1. FriendRequestsII.sql:

   • Correctness: The solution attempts to find the user with the most friends by counting both requester and accepter relationships. However, the approach is inefficient as it recalculates the count for each id multiple times.
   • Time Complexity: O(n^2) due to the nested subqueries in the CTE.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: The code is readable but could be improved by using a more efficient approach like grouping and counting directly.
   • Efficiency: Could be optimized by using a single GROUP BY query instead of UNION and subqueries.

2. LeagueStatistics.sql:

   • Correctness: The solution correctly calculates league statistics by considering both home and away matches.
   • Time Complexity: O(n) for the UNION ALL and O(n) for the JOIN and GROUP BY, making it O(n) overall.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Well-structured and readable. Good use of CASE for point calculation.
   • Efficiency: The solution is already efficient for this problem.

3. SalesPerson.sql:

   • Correctness: Correctly identifies salespersons who didn't sell to 'RED' company.
   • Time Complexity: O(n) for the JOIN and O(n) for the NOT IN, making it O(n) overall.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Simple and effective. Good use of CTE for clarity.
   • Efficiency: Could potentially use NOT EXISTS instead of NOT IN for better performance in some databases.

4. number-of-seniors-and-juniors-to-join-the-company.sql:

   • Correctness: Correctly calculates the number of seniors and juniors that can be hired within budget.
   • Time Complexity: O(n log n) for the window function and O(n) for the filtering, making it O(n log n) overall.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Well-structured and readable. Good use of window functions.
   • Efficiency: The solution is already efficient for this problem.

General Observations:

• The student consistently uses CTEs effectively to break down complex queries.
• The solutions are generally well-structured and readable.
• Some queries could be optimized further for better performance.
• The student demonstrates good understanding of SQL concepts like joins, aggregations, and window functions.

[super30admin]

1. FriendRequestsII.sql:

   • Correctness: The solution correctly identifies the person with the most friends by counting both requester and accepter relationships. However, it could be optimized by avoiding the subquery in the CTE.
   • Time Complexity: O(n^2) due to the correlated subquery for each row.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Good structure but could be improved by using a more efficient approach without subqueries.
   • Efficiency: Could be improved by using a single GROUP BY instead of UNION with subqueries.

2. LeagueStatistics.sql:

   • Correctness: The solution correctly calculates team statistics by considering both home and away matches.
   • Time Complexity: O(n) for the CTE and O(n) for the join and aggregation.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Well-structured and readable. Good use of CASE for point calculation.
   • Efficiency: Good approach, no major optimizations needed.

3. SalesPerson.sql:

   • Correctness: Correctly identifies salespeople who didn't deal with 'RED' company.
   • Time Complexity: O(n) for the CTE and O(n) for the NOT IN check.
   • Space Complexity: O(n) for storing the CTE.
   • Code Quality: Simple and effective solution. Could use NOT EXISTS instead of NOT IN for better performance.
   • Efficiency: Consider using NOT EXISTS instead of NOT IN for better performance with NULL values.

4. number-of-seniors-and-juniors-to-join-the-company.sql:

   • Correctness: Correctly calculates the number of accepted candidates within budget constraints.
   • Time Complexity: O(n log n) for the window function and O(n) for the filtering.
   • Space Complexity: O(n) for the window function results.
   • Code Quality: Well-structured with clear logic. Good use of window functions.
   • Efficiency: Good approach, no major optimizations needed.

General Strengths:

• Consistent use of CTEs which improves readability
• Good SQL formatting and indentation
• Appropriate use of SQL features like window functions and CASE statements

Areas for Improvement:

• Avoid correlated subqueries when possible (FriendRequestsII.sql)
• Consider using NOT EXISTS instead of NOT IN when checking for absence (SalesPerson.sql)
• Could add comments to explain complex logic
• Consider adding handling for NULL values where appropriate