Completed Sql5

[Paneripatel]

No description provided.

[super30admin]

1. Correctness:

   • Sql5 (ReportContiguosDates): The solution correctly identifies contiguous dates and groups them by state. It handles both failed and succeeded states appropriately.
   • StudentReportByGeography: The solution correctly pivots the data by continent using ROW_NUMBER() and joins, which is a valid approach.
   • AverageSalaryDepartmentVsCompany: The solution correctly calculates and compares department vs company averages.
   • GamePlayAnalysisI: The solution correctly finds the first login date for each player.

2. Time Complexity:

   • All solutions use appropriate window functions (RANK(), ROW_NUMBER()) which typically operate in O(n log n) time due to sorting.
   • The joins in StudentReportByGeography could be O(n^2) in worst case but are likely O(n) with proper indexing.

3. Space Complexity:

   • All solutions create temporary tables (CTEs) which use O(n) space.
   • The StudentReportByGeography solution creates three CTEs which could be optimized.

4. Code Quality:

   • Good use of CTEs to improve readability.
   • Consistent formatting and clear column aliases.
   • The CASE statement in AverageSalaryDepartmentVsCompany is well-structured.
   • Could improve by adding comments explaining the logic, especially for the more complex solutions like ReportContiguosDates.

5. Efficiency:

   • The ReportContiguosDates solution could potentially be optimized by combining the two date tables first before applying RANK().
   • The StudentReportByGeography solution could use PIVOT if available in the SQL dialect.
   • All solutions are already quite efficient for their problem domains.

[super30admin]

1. Correctness:

   • Sql5 (ReportContiguosDates): The solution correctly identifies contiguous date ranges for failed and succeeded periods in 2019 using a ranking approach. It handles the union and grouping well.
   • StudentReportByGeography: The solution correctly pivots the student data by continent using row numbering and joins, producing the desired output format.
   • AverageSalaryDepartmentVsCompany: The solution correctly compares department averages with company averages by month using CTEs and a case statement.
   • GamePlayAnalysisI: The simple solution correctly finds the first login date for each player.

2. Time Complexity:

   • All solutions use appropriate SQL operations (joins, group by, window functions) that are generally efficient for their respective problems. The most complex is the ReportContiguosDates solution with multiple window functions, which would be O(n log n) due to the sorting.

3. Space Complexity:

   • The solutions create temporary tables (CTEs) but don't appear to use excessive memory. The StudentReportByGeography solution creates three CTEs which is reasonable.

4. Code Quality:

   • Good use of CTEs to break down complex queries.
   • Consistent formatting and clear column aliases.
   • The StudentReportByGeography solution could be more readable with better CTE names (instead of first, second, third).
   • The ReportContiguosDates solution's subquery could be made clearer with better variable naming.

5. Efficiency:

   • All solutions are efficient for their problem sizes.
   • The GamePlayAnalysisI solution is optimally simple.
   • The ReportContiguosDates solution might benefit from adding an index on the date columns if this were a production system.