Group the `users` table by age and count the number of users per age.

Problem Statement

<p>Group the <code>users</code> table by age and count the number of <code>users</code> per age.</p>

Examples

Input: users table: +----+---------+-----+ | id | name | age | +----+---------+-----+ | 1 | Alice | 30 | | 2 | Bob | 30 | | 3 | Charlie | 25 | +----+---------+-----+

Output: +-----+-------+ | age | count | +-----+-------+ | 30 | 2 | | 25 | 1 | +-----+-------+

Explanation: The query retrieves the requested records satisfying all problem requirements.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Identify the grouping dimension(s) and which columns require aggregate functions (such as COUNT, SUM, AVG, MIN, or MAX). 💡 Hint 2: Add the GROUP BY clause for all non-aggregated columns listed in the SELECT projection. 💡 Hint 3: If filtering groups, use HAVING; otherwise use WHERE before grouping: SELECT <group_col>, <AGG>(...) FROM <table> GROUP BY <group_col>;

Editorial & Approach

Problem Overview & Intuition

To solve "Group By Single Column", we query the relational database engine using declarative SQL. The goal is to group the `users` table by age and count the number of users per age. 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 grouping & aggregates to isolate the requested data.
Format & Order: Ensure columns match the expected project schema in order.

Optimal Implementation (SQL)

SELECT age, COUNT(*) FROM users GROUP BY age;

Complexity Analysis

Time Complexity O(N log N) for sorting or partitioning rows.

Space Complexity O(N) for intermediate group hash tables or window buffers.

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.

Group By Single Column

Easy

Group the users table by age and count the number of users per age.

Example Scenarios

1Example 1

Input:

users table

id	name	age
1	Alice	30
2	Bob	30
3	Charlie	25

Output:

age	count
30	2
25	1

Explanation:

The query retrieves the requested records satisfying all problem requirements.

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