Completed Sql6

[sangeeths29]

No description provided.

[super30admin]

Let me evaluate each solution file individually:

1. 01-GamePlayAnalysis-II.sql:

• Both approaches are correct and solve the problem effectively.
• The subquery approach is straightforward but may be less efficient for large datasets.
• The CTE approach with RANK() is more modern and efficient.
• Good practice to provide multiple approaches.

2. 02-GamePlayAnalysis-III.sql:

• Correct implementation using window functions.
• Efficient solution with O(n log n) time complexity due to the PARTITION BY and ORDER BY.
• Clear and concise code.

3. 03-ShortestDistanceInAPlane.sql:

• Both approaches are correct.
• The second approach is more efficient as it eliminates duplicate calculations.
• The tuple comparison (p1.x, p1.y) < (p2.x, p2.y) is elegant.
• Time complexity is O(n^2) which is expected for this problem.

4. 04-CombineTwoTables.sql:

• Both approaches produce correct results.
• LEFT JOIN is more intuitive for this problem than RIGHT JOIN.
• Simple and effective solutions.

5. 05-CustomersWithStrictlyIncreasingPurchases.sql:

• Correct but complex solution.
• The HAVING clause logic is clever but might be hard to understand.
• Could benefit from comments explaining the COUNT(*) - COUNT(y2.customer_id) = 1 logic.
• Time complexity is O(n^2) due to the self-join.

General strengths:

• Good use of SQL features like CTEs, window functions, and joins.
• Multiple approaches provided where applicable.
• Mostly clear and readable code.

Areas for improvement:

• Could add more comments explaining complex logic (especially in problem 5).
• Some queries could benefit from explicit column aliases for better readability.
• Consider adding index hints for production-level queries.