Completed SQL5

[HaswathaSridharan]

No description provided.

[super30admin]

1. Correctness:

   • Problem 1 (Report Contiguous Dates): The solution correctly identifies contiguous date ranges for failed and succeeded periods using window functions and grouping. It handles the filtering for year 2019 appropriately.
   • Problem 2 (Student Report By Geography): The solution correctly pivots the data by continent using row numbers for alignment. The right join and left join ensure all continents are represented.
   • Problem 3 (Average Salary Department vs Company): The solution correctly compares department averages with company averages using CASE statements and proper joins.
   • Problem 4 (Game Play Analysis I): The simple solution correctly finds the first login date for each player.

2. Time Complexity:

   • All solutions use efficient window functions and joins where appropriate. The time complexity is generally O(n) or O(n log n) for sorting operations.

3. Space Complexity:

   • The solutions create temporary tables (CTEs) but don't appear to use excessive space. The space complexity is reasonable for the problem sizes.

4. Code Quality:

   • The code is generally well-structured and readable.
   • Some improvements could be made:
     • Consistent formatting (some queries have extra spaces before AS keywords)
     • More descriptive CTE names (e.g., 'companyAvg' could be 'company_average')
     • The first problem could benefit from comments explaining the grouping logic
     • Problem 2 could use a more elegant solution with PIVOT if available in MySQL

5. Efficiency:

   • All solutions appear efficient for their respective problems.
   • For Problem 1, the solution could potentially be optimized by combining the two CTEs into one with conditional aggregation.
   • For Problem 2, the solution could be made more concise if using PIVOT operations were available.

[super30admin]

1. Problem 1 (Report Contiguous Dates):

   • Correctness: The solution correctly identifies contiguous date ranges for failed and succeeded periods in 2019 using a ranking approach. The GROUP BY on the calculated grp is a standard technique for this type of problem.
   • Time Complexity: O(n log n) due to the sorting in RANK() operations.
   • Space Complexity: O(n) for storing the CTEs.
   • Code Quality: Well-structured with clear CTEs. The column aliases could be more descriptive (e.g., 'date' instead of 'dat').
   • Efficiency: The solution is efficient for this problem type. No obvious optimizations needed.

2. Problem 2 (Student Report By Geography):

   • Correctness: The solution correctly pivots the student data by continent using row numbers for alignment. The RIGHT JOIN and LEFT JOIN combination ensures all American students are included.
   • Time Complexity: O(n log n) for the sorting in ROW_NUMBER() operations.
   • Space Complexity: O(n) for storing the CTEs.
   • Code Quality: Good structure with CTEs. The column aliases with quotes are unnecessary in MySQL. Could use more descriptive names for CTEs.
   • Efficiency: The approach is standard for this type of pivot problem. No major optimizations needed.

3. Problem 3 (Average Salary Department vs Company):

   • Correctness: The solution correctly compares department averages to company averages by month. The CASE statement handles the comparison logic well.
   • Time Complexity: O(n) for the aggregations.
   • Space Complexity: O(n) for storing the CTEs.
   • Code Quality: Well-structured with clear CTEs. The column aliases with quotes are unnecessary. The date formatting could be moved to the final SELECT for consistency.
   • Efficiency: The solution is efficient. No obvious optimizations needed.

4. Problem 4 (Game Play Analysis I):

   • Correctness: The solution correctly finds the first login date for each player using MIN() with GROUP BY.
   • Time Complexity: O(n) for the grouping operation.
   • Space Complexity: O(n) for the result set.
   • Code Quality: Simple and effective. Could add a comment explaining the straightforward approach.
   • Efficiency: This is the most efficient solution possible for this problem.

General Observations:

• The solutions demonstrate good understanding of SQL window functions and CTEs.
• Consistent use of CTEs improves readability.
• Some minor style improvements could be made (column naming, quote usage).
• All solutions handle the problem requirements effectively.