Completed Mock_SQL2

[HaswathaSridharan]

No description provided.

[super30admin]

1. Correctness:

   • Problem 1: The solution correctly identifies customers who bought all products by comparing the count of distinct products bought by each customer with the total count of products available. This approach is correct.
   • Problem 2: The solution correctly identifies the first year of sales for each product and retrieves the corresponding sales data. The use of a subquery with MIN(year) is appropriate.

2. Time Complexity:

   • Problem 1: The solution involves a join and a group by operation, which typically run in O(n log n) time, where n is the number of records. The subquery for counting products is O(m), where m is the number of products. Overall, it's efficient.
   • Problem 2: The solution uses a subquery with GROUP BY and MIN, which is O(n log n) for grouping and O(n) for the MIN operation. The main query's WHERE IN clause could be O(n^2) in the worst case, but databases often optimize this.

3. Space Complexity:

   • Both solutions should have space complexity proportional to the result set size, which is efficient for typical database operations.

4. Code Quality:

   • The code is well-structured and readable. Both solutions follow SQL best practices.
   • For Problem 1, using DISTINCT in the COUNT is correct but could be noted that it's necessary because a customer might buy the same product multiple times.
   • For Problem 2, the solution is concise and clear. An alternative could be using a JOIN with the subquery for potentially better readability, but the current approach is fine.

5. Efficiency:

   • Both solutions are efficient for their respective problems. No major optimizations are needed.
   • For Problem 2, if performance is a concern with large datasets, an index on (product_id, year) would help the subquery run faster.

[super30admin]

The student has provided solutions to two SQL problems. Let's evaluate each one separately.

Problem 1: Customers Who Bought All Products

• Correctness: The solution appears correct. It properly groups by customer_id and checks if the count of distinct products matches the total product count.
• Time Complexity: O(n + m) where n is the number of customer records and m is the number of products (for the subquery).
• Space Complexity: O(n) for the grouping operation.
• Code Quality: The code is well-structured and readable. The use of DISTINCT in the count is important here.
• Efficiency: The solution is efficient. An alternative could be to use a window function, but this approach is straightforward.

Problem 2: Product Sales Analysis III

• Correctness: The solution correctly identifies the first year of sales for each product. The subquery approach is appropriate.
• Time Complexity: O(n) for the main query plus O(n) for the subquery (assuming proper indexing).
• Space Complexity: O(n) for storing the intermediate results of the subquery.
• Code Quality: The code is clean and easy to understand. The use of a tuple in the WHERE clause is a good approach.
• Efficiency: The solution is efficient. An alternative could be to use a window function with ROW_NUMBER(), but this approach is equally valid.

General Observations:

1. The solutions are well-formatted and easy to read.
2. Both solutions follow standard SQL best practices.
3. The student has chosen appropriate approaches for each problem.
4. The solutions handle edge cases well (like multiple products per customer in Problem 1 and multiple sales years in Problem 2).

Areas for Improvement:

1. Adding comments to explain the logic could be helpful for more complex queries.
2. For Problem 1, the INNER JOIN with Product table might be unnecessary since we're only counting distinct product_keys from the Customer table.
3. The README could include problem descriptions to make it more self-contained.