Beginner friendly solution with deep explaination :
To solve the problem of identifying customers who have bought all the products listed in the Product table, we can break down the problem into several steps and
To solve the problem of identifying customers who have bought all the products listed in the `Product` table, we can break down the problem into several steps and then write an SQL query that accomplishes this task. Here\u2019s a detailed explanation:\n\n## Intuition\nThe key idea is to compare the number of distinct products each customer has bought to the total number of products available. If a customer has bought every product at least once, the count of distinct products they have purchased will match the total count of products.\n\n## Approach\n1. **Count Total Products**: First, we need to determine how many distinct products exist in the `Product` table.\n2. **Count Distinct Products per Customer**: For each customer, we need to count the number of distinct products they have purchased.\n3. **Compare Counts**: Identify customers whose count of distinct purchased products matches the total count of products.\n\n## Complexity\n- **Time Complexity**: \n  - Counting total products requires a full scan of the `Product` table: \\(O(m)\\), where \\(m\\) is the number of products.\n  - Counting distinct products per customer requires scanning the `Customer` table and grouping by `customer_id`: \\(O(n)\\), where \\(n\\) is the number of purchases.\n  - Combining these results involves filtering the grouped results: \\(O(n)\\).\n  Overall, the time complexity is \\(O(n + m)\\).\n\n- **Space Complexity**:\n  - The space required to store intermediate counts and results is \\(O(k)\\), where \\(k\\) is the number of customers.\n  - Additionally, any sorting or grouping operations might require temporary space proportional to the input size.\n\n## Code\nHere\u2019s the SQL query that implements the approach:\n\n```sql\n-- Write your MySQL query statement below\n\n-- Step 1: Get the total number of distinct products\nWITH TotalProducts AS (\n    SELECT COUNT(*) AS product_count\n    FROM Product\n),\n\n-- Step 2: Count the distinct products purchased by each customer\nCustomerProductCounts AS (\n    SELECT customer_id, COUNT(DISTINCT product_key) AS distinct_product_count\n    FROM Customer\n    GROUP BY customer_id\n)\n\n-- Step 3: Select customers whose count of distinct purchased products matches the total number of products\nSELECT customer_id\nFROM CustomerProductCounts, TotalProducts\nWHERE distinct_product_count = product_count;\n```\n\n### Explanation\n1. **TotalProducts CTE**:\n   - This common table expression (CTE) calculates the total number of distinct products by counting rows in the `Product` table.\n   \n2. **CustomerProductCounts CTE**:\n   - This CTE groups purchases by `customer_id` and counts the number of distinct `product_key` values for each customer.\n\n3. **Final Selection**:\n   - The main query joins the two CTEs and selects customers where the count of distinct products they have purchased matches the total product count.\n\nThis approach ensures that we accurately identify customers who have purchased all available products.\n\n\nCODE : \n\n```.sql\n\n# Write your MySQL query statement below\nSELECT  customer_id FROM Customer GROUP BY customer_id\nHAVING COUNT(distinct product_key) = (SELECT COUNT(product_key) FROM Product)\n\n\n```
['MySQL']