Count the number of distinct ages in the `users` table.

Problem Statement

<p>Count the number of distinct ages in the <code>users</code> table.</p>

Examples

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

Output: +-------+ | count | +-------+ | 2 | +-------+

Explanation: The records are grouped by category and the aggregate calculation is applied to produce the summary result.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Identify the filtering conditions needed to isolate the target rows from the table. 💡 Hint 2: Use appropriate operators: = for exact matches, LIKE for wildcard patterns, IN for sets, or BETWEEN for numeric/date ranges. 💡 Hint 3: Combine filters with AND/OR if multiple conditions exist: SELECT <cols> FROM <table> WHERE <condition>;

Editorial & Approach

Problem Overview & Intuition

To solve "Count Distinct Values", we query the relational database engine using declarative SQL. The goal is to count the number of distinct ages in the `users` table. 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 row projections to isolate the requested data.
Format & Order: Ensure columns match the expected project schema in order.

Optimal Implementation (SQL)

SELECT COUNT(DISTINCT age) FROM users;

Complexity Analysis

Time Complexity O(N)

Space Complexity O(1)

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.

Count Distinct Values

Easy

Count the number of distinct ages in the users table.

Example Scenarios

1Example 1

Input:

users table

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

Output:

count
2

Explanation:

The records are grouped by category and the aggregate calculation is applied to produce the summary result.

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