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Full outer join `users` and `orders` to show all users and all orders, matched or not.

Problem Statement

<p>Full outer join <code>users</code> and <code>orders</code> to show all <code>users</code> and all <code>orders</code>, matched or not.</p>

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

šŸ’” Hint 1: Determine which tables contain the required columns and relate them using FULL OUTER JOIN on the corresponding foreign/primary keys. šŸ’” Hint 2: Write out the ON condition matching key fields (e.g. ON a.key = b.key) and apply any filtering in the WHERE clause. šŸ’” Hint 3: Select only the requested columns in the SELECT clause with clear aliases if needed: SELECT ... FROM ... FULL OUTER JOIN ... ON ...;

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

  1. Analyze Schema: Identify the target tables, necessary foreign keys, and expected output columns.
  2. Construct Filtering & Logic: Apply table joins to isolate the requested data.
  3. 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

Time Complexity O(N * M) worst-case, O(N + M) with hash/merge join on indexed keys.
Space Complexity O(N) for join buffer and result set.

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.

Full Outer Join

Medium

Full outer join users and orders to show all users and all orders, matched or not.

Example Scenarios
1Example 1
Input:
users table
idname
1Alice
2Bob
3Charlie
orders table
iduser_idtotal
101150
102475
Output:
nametotal
Alice50
null75
Bobnull
Charlienull
Explanation:

The query joins the matching records on the related keys and projects the requested fields.

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