SQL3 Submitted

[PranathiDeepak]

No description provided.

[super30admin]

1. Problem1.sql (Consecutive Numbers):

   • Correctness: The solution correctly identifies consecutive numbers by joining the logs table with itself and checking for three consecutive IDs with the same number.
   • Time Complexity: O(n^3) due to the triple self-join, which could be inefficient for large datasets.
   • Space Complexity: O(n) for storing the intermediate join results.
   • Code Quality: The code is clear and concise. Using DISTINCT ensures no duplicates in the result.
   • Improvement: Consider using window functions (if available) for better performance with large datasets.

2. Problem2.sql (Passengers and Buses):

   • Correctness: The solution correctly matches passengers to the earliest bus they can catch and counts passengers per bus.
   • Time Complexity: O(n log n) for the join and group by operations.
   • Space Complexity: O(n) for the CTE storage.
   • Code Quality: Well-structured with a CTE for clarity. The LEFT JOIN ensures all buses are included.
   • Improvement: The query could be optimized by adding indexes on arrival_time columns.

3. Problem3.sql (Active Users):

   • Correctness: The solution correctly counts distinct active users per day within the specified date range.
   • Time Complexity: O(n) for scanning the table and grouping.
   • Space Complexity: O(n) for storing grouped results.
   • Code Quality: Simple and effective. The date range condition is clear.
   • Improvement: Consider using BETWEEN for date range for better readability.

4. Problem4.sql (Pivot Products):

   • Correctness: The dynamic pivot implementation is correct and handles variable store names.
   • Time Complexity: O(n) for building the dynamic SQL and executing it.
   • Space Complexity: O(n) for storing the dynamic SQL string.
   • Code Quality: Excellent use of dynamic SQL and proper handling of GROUP_CONCAT length.
   • Improvement: None needed; this is a well-implemented solution.

Overall, the solutions are correct and demonstrate good SQL knowledge. The main areas for improvement are performance optimization for large datasets and minor readability enhancements.