Completed Sql3

[kaaviyavarrshini]

No description provided.

[super30admin]

1. Problem1_ConsecutiveNumbers.sql:

   • Correctness: The solution correctly identifies consecutive numbers by joining the table with itself and checking for consecutive IDs and matching numbers. This is a standard approach.
   • Time Complexity: O(n^3) due to the triple self-join, which could be inefficient for large tables.
   • Space Complexity: O(n) for storing intermediate join results.
   • Code Quality: The code is clean and readable. Using table aliases (l1, l2, l3) is good practice.
   • Improvement: Could consider using window functions (LEAD/LAG) for better performance with large datasets.

2. Problem2_PassengerInBus.sql:

   • Correctness: The solution correctly matches passengers to buses using a CTE and counts passengers per bus. The logic appears sound.
   • Time Complexity: O(n log n) for the join and group by operations.
   • Space Complexity: O(n) for storing the CTE results.
   • Code Quality: Well-structured with clear CTE usage. The left join ensures all buses are included.
   • Improvement: Consider adding comments to explain the CTE's purpose for better readability.

3. Problem3_UserActivity.sql:

   • Correctness: Correctly counts active users within the last 30 days. The date filtering and grouping are appropriate.
   • Time Complexity: O(n) for the table scan and group by.
   • Space Complexity: O(n) for storing grouped results.
   • Code Quality: Simple and effective. The HAVING clause is redundant since COUNT(DISTINCT) will never be negative.
   • Improvement: The HAVING clause can be removed as it doesn't filter anything.

4. Problem4_DynamicPivoting.sql:

   • Correctness: The dynamic pivot implementation is correct and handles variable store names well.
   • 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 prepared statements. Good practice setting group_concat_max_len.
   • Improvement: Consider adding error handling for the prepared statement.

Overall strengths:

• Good understanding of SQL concepts across different problem types
• Effective use of joins, CTEs, and dynamic SQL
• Clean and readable code formatting

Areas for improvement:

• Consider performance optimizations for large datasets
• Add comments for complex logic
• Remove unnecessary clauses (HAVING in Problem3)
• Consider window functions as alternatives to self-joins