Select all distinct age values from the `users` table.
Problem Statement
<p>Select all distinct age values from the <code>users</code> table.</p>
Examples
Input: users table: +----+---------+-----+ | id | name | age | +----+---------+-----+ | 1 | Alice | 30 | | 2 | Bob | 30 | | 3 | Charlie | 25 | +----+---------+-----+
Output: +-----+ | age | +-----+ | 30 | | 25 | +-----+
Explanation: Only records matching the specified criteria are returned in the final result.
Complexity
Time Complexity: -
Space Complexity: -
Hints
š” Hint 1:
Identify the filtering conditions needed to isolate the target rows from the table.
š” Hint 2:
Use appropriate operators: = for exact matches, LIKE for wildcard patterns, IN for sets, or BETWEEN for numeric/date ranges.
š” Hint 3:
Combine filters with AND/OR if multiple conditions exist: SELECT <cols> FROM <table> WHERE <condition>;
Editorial & Approach
Problem Overview & Intuition
To solve "DISTINCT Select", we query the relational database engine using declarative SQL. The goal is to select all distinct age values from 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 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.