sql6: solution to problems 1, 2, 4

[avishwak]

submitted by Akanksha Vishwakarma_RN31MAY2025DS

[super30admin]

FEEDBACK: The student has not provided any solution to the problem. For a medium difficulty SQL problem, I would expect to see at least a basic query structure addressing the problem requirements. Without seeing any code, I cannot evaluate correctness, complexity, or quality. I recommend the student attempt to solve the problem and submit their solution for review. Some general advice for SQL problems: start by understanding the database schema and requirements clearly, write simple queries first and then build up complexity as needed, and always test queries with different edge cases.

[super30admin]

1. Correctness:

   • For Game Play Analysis II (01-GamePlayAnalysis-II.sql), the solution correctly identifies the first login device for each player by using MIN(event_date) and grouping by player_id. However, the query could be more precise by explicitly selecting the device_id associated with the minimum event_date.
   • For Game Play Analysis III (02-GamePlayAnalysis-III.sql), both the window function and subquery approaches correctly calculate the running total of games played. The window function approach is more efficient.
   • For Combine Two Tables (04-CombineTwoTables.sql), the solution correctly performs a LEFT JOIN to include all persons even if they don't have an address.

2. Time Complexity:

   • Game Play Analysis II: O(n) for the GROUP BY operation.
   • Game Play Analysis III: The window function approach is O(n log n) due to the PARTITION BY and ORDER BY. The subquery approach is O(n^2) as noted by the student.
   • Combine Two Tables: O(n) for the JOIN operation.

3. Space Complexity:

   • All solutions have O(n) space complexity as they process and return a result set proportional to the input size.

4. Code Quality:

   • The code is generally readable and well-structured.
   • Comments are helpful, especially in explaining why certain approaches are less efficient.
   • For Game Play Analysis II, the query could be improved by using a more explicit approach like:

     SELECT player_id, device_id 
     FROM Activity 
     WHERE (player_id, event_date) IN (
         SELECT player_id, MIN(event_date) 
         FROM Activity 
         GROUP BY player_id
     )

5. Efficiency:

   • The student correctly identifies the inefficiency of the subquery approach in Game Play Analysis III and prefers the window function approach, which is good.
   • The solution for Game Play Analysis II could be optimized as mentioned above to ensure it correctly handles cases where multiple devices might have the same minimum event_date.

[avishwak]

Added solution to two more problems i.e 3 and 5