Finished Sql3

[Aniruddh-2512]

No description provided.

[super30admin]

1. Correctness:

   • ConsecutiveNumbers.sql: The solution correctly identifies consecutive numbers by joining the logs table with itself and checking for three consecutive IDs with the same number. This is a standard approach for this type of problem.
   • Numberofpassengers.sql: The solution attempts to count passengers per bus using a window function, but there might be issues with the LEFT JOIN condition as it doesn't account for passengers who haven't boarded any bus yet.
   • PivotProducts.sql: The solution correctly implements a dynamic pivot table using prepared statements, which is appropriate for this problem.
   • useractivity.sql: The solution correctly counts active users per day within the specified date range.

2. Time Complexity:

   • ConsecutiveNumbers.sql: O(n^3) due to the triple self-join, which could be inefficient for large tables.
   • Numberofpassengers.sql: O(n log n) due to the sorting for the window function and the GROUP BY operation.
   • PivotProducts.sql: O(n) for the GROUP_CONCAT and O(n) for the final query, where n is the number of distinct stores.
   • useractivity.sql: O(n) for the GROUP BY operation, where n is the number of rows in the Activity table.

3. Space Complexity:

   • ConsecutiveNumbers.sql: O(n) for storing the intermediate join results.
   • Numberofpassengers.sql: O(n) for storing the window function results.
   • PivotProducts.sql: O(n) for storing the dynamic SQL string.
   • useractivity.sql: O(n) for storing the grouped results.

4. Code Quality:

   • ConsecutiveNumbers.sql: The code is readable but could benefit from using JOIN syntax explicitly instead of comma-separated tables.
   • Numberofpassengers.sql: The code is well-structured but the LEFT JOIN condition might not correctly handle all edge cases.
   • PivotProducts.sql: The code is well-structured and follows best practices for dynamic SQL.
   • useractivity.sql: The code is clean and straightforward.

5. Efficiency:

   • ConsecutiveNumbers.sql: Could be optimized by using window functions to avoid the triple self-join.
   • Numberofpassengers.sql: The LEFT JOIN condition should be reviewed to ensure it correctly counts passengers who haven't boarded any bus.
   • PivotProducts.sql: No major optimizations needed.
   • useractivity.sql: No major optimizations needed.