Full outer join `users` and `orders` to show all users and all orders, matched or not.
Problem Statement
Examples
Input: users table: +----+---------+ | id | name | +----+---------+ | 1 | Alice | | 2 | Bob | | 3 | Charlie | +----+---------+ orders table: +-----+---------+-------+ | id | user_id | total | +-----+---------+-------+ | 101 | 1 | 50 | | 102 | 4 | 75 | +-----+---------+-------+
Output: +---------+-------+ | name | total | +---------+-------+ | Alice | 50 | | null | 75 | | Bob | null | | Charlie | null | +---------+-------+
Explanation: The query joins the matching records on the related keys and projects the requested fields.
Complexity
Time Complexity: -
Space Complexity: -
Hints
Editorial & Approach
Problem Overview & Intuition
To solve "Full Outer Join", we query the relational database engine using declarative SQL. The goal is to full outer join `users` and `orders` to show all users and all orders, matched or not. By formulating an optimal execution plan with appropriate projection and filtering, the database engine executes the query with minimal overhead.
Step-by-Step Approach
- Analyze Schema: Identify the target tables, necessary foreign keys, and expected output columns.
- Construct Filtering & Logic: Apply table joins to isolate the requested data.
- Format & Order: Ensure columns match the expected project schema in order.
Optimal Implementation (SQL)
SELECT users.name, orders.total FROM users FULL OUTER JOIN orders ON users.id = orders.user_id;
Complexity Analysis
Key Considerations & Edge Cases
- Empty Tables: The query executes safely returning zero rows without syntax error.
- NULL Values: Columns containing NULL values are properly handled by standard ANSI SQL semantics.
- Case Sensitivity: String comparisons and keywords adhere to PostgreSQL/standard SQL rules.