Completed Sql1

[RISHIKA29]

No description provided.

[super30admin]

1. Problem 1.sql:

   • Correctness: The query correctly selects countries with area >= 3 million or population >= 25 million. This appears to solve a typical "World" table problem correctly.
   • Time Complexity: O(n) where n is the number of rows in the World table, as it requires a full table scan.
   • Space Complexity: O(1) as it only returns a subset of rows without additional storage.
   • Code Quality: Simple and readable, follows standard SQL syntax.
   • Efficiency: Could potentially benefit from indexes on area and population columns if this query is run frequently.

2. Problem 2.sql:

   • Correctness: The function correctly returns the Nth highest salary using LIMIT with offset. Handles the N-1 offset properly.
   • Time Complexity: O(n log n) due to the sorting operation, where n is the number of employees.
   • Space Complexity: O(1) for the function itself, though sorting may require temporary space.
   • Code Quality: Well-structured, uses a variable for clarity, and follows MySQL function syntax correctly.
   • Efficiency: The solution is optimal for this problem. Could consider adding error handling for cases where N exceeds the number of distinct salaries.

3. Problem 3.sql:

   • Correctness: The query correctly deletes duplicate emails, keeping only the record with the smallest id. This is a standard approach for this problem.
   • Time Complexity: O(n^2) due to the self-join operation, where n is the number of rows in the Person table.
   • Space Complexity: O(n) for the temporary result of the join operation.
   • Code Quality: Readable but could be improved with more explicit JOIN syntax (INNER JOIN instead of comma-separated tables).
   • Efficiency: Could be optimized using a window function (if available) or a subquery to identify duplicates first.

General strengths:

• Solutions are concise and solve the problems correctly.
• Good use of SQL features like DISTINCT, ORDER BY, and LIMIT.
• Proper formatting and indentation.

Areas for improvement:

• Could add comments explaining the logic, especially for more complex queries.
• For Problem 3, consider alternative approaches that might be more efficient for large tables.
• Consider adding error handling in the function (Problem 2) for edge cases.

[super30admin]

1. Problem 1.sql:

   • Correctness: The query correctly selects countries with area >= 3 million or population >= 25 million. This appears to solve a typical "World" table problem correctly.
   • Time Complexity: O(n) where n is the number of rows in the World table, as it requires a full table scan.
   • Space Complexity: O(1) as it only returns a subset of columns.
   • Code Quality: Simple and straightforward, follows good SQL practices.
   • Efficiency: Could potentially benefit from indexes on area and population columns if this query is run frequently.

2. Problem 2.sql:

   • Correctness: The function correctly returns the Nth highest salary using the LIMIT clause with offset. Handles duplicates with DISTINCT.
   • Time Complexity: O(n log n) due to the sorting operation, where n is the number of rows in Employee.
   • Space Complexity: O(1) for the function itself, though sorting may require additional memory.
   • Code Quality: Well-structured, uses a variable M for clarity. Follows good SQL function practices.
   • Efficiency: The solution is optimal for this type of problem. Could consider adding error handling for cases where N is larger than the number of distinct salaries.

3. Problem 3.sql:

   • Correctness: The query correctly deletes duplicate emails while keeping the record with the smallest id. This is a standard approach for this problem.
   • Time Complexity: O(n^2) due to the self-join operation, where n is the number of rows in Person.
   • Space Complexity: O(n) for the join operation.
   • Code Quality: Clear and concise, though could benefit from a comment explaining the logic.
   • Efficiency: For large tables, this might be slow. Alternative approaches using window functions or temporary tables could be more efficient.

Overall strengths:

• Solutions are correct and demonstrate good understanding of SQL.
• Code is clean and follows standard practices.
• Appropriate use of SQL features like DISTINCT, LIMIT, and self-joins.

Areas for improvement:

• Could add comments explaining complex logic (especially in Problem 3).
• For Problem 3, consider more efficient approaches for large datasets.
• For Problem 2, could add input validation for edge cases.