Group the `users` table by age and only include ages that have more than 1 user.

Problem Statement

<p>Group the <code>users</code> table by age and only include ages that have more than 1 user.</p>

Examples

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

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

Explanation: Only records matching the specified criteria are returned in the final result.

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 "Filter Groups (HAVING)", we query the relational database engine using declarative SQL. The goal is to group the `users` table by age and only include ages that have more than 1 user. 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 HAVING COUNT(*) > 1;

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.

Filter Groups (HAVING)

Easy

Group the users table by age and only include ages that have more than 1 user.

Example Scenarios

1Example 1

Input:

users table

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

Output:

age	count
30	2

Explanation:

Only records matching the specified criteria are returned in the final result.

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