Left join `users` and `orders` tables, keeping all users even if they have no orders.

Problem Statement

<p>Left join <code>users</code> and <code>orders</code> tables, keeping all <code>users</code> even if they have no <code>orders</code>.</p>

Examples

Input: users table: +----+---------+ | id | name | +----+---------+ | 1 | Alice | | 2 | Bob | | 3 | Charlie | +----+---------+ orders table: +-----+---------+-------+ | id | user_id | total | +-----+---------+-------+ | 101 | 1 | 50 | +-----+---------+-------+

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

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Determine which tables contain the required columns and relate them using LEFT JOIN on the corresponding foreign/primary keys. 💡 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. 💡 Hint 3: Select only the requested columns in the SELECT clause with clear aliases if needed: SELECT ... FROM ... LEFT JOIN ... ON ...;

Editorial & Approach

Problem Overview & Intuition

To solve "Basic Left Join", we query the relational database engine using declarative SQL. The goal is to left join `users` and `orders` tables, keeping all users even if they have no orders. 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 LEFT 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.

Basic Left Join

Easy

Left join users and orders tables, keeping all users even if they have no orders.

Example Scenarios

1Example 1

Input:

users table

id	name
1	Alice
2	Bob
3	Charlie

orders table

id	user_id	total
101	1	50

Output:

name	total
Alice	50
Bob	null
Charlie	null

Explanation:

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

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