LEAD function for next row access in SQL - Time & Space Complexity

Time Complexity: LEAD function for next row access

O(n)

Understanding Time Complexity

We want to understand how the time needed to run a query using the LEAD function changes as the data grows.

Specifically, how does accessing the next row's value affect performance?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

SELECT employee_id, salary,
       LEAD(salary) OVER (ORDER BY employee_id) AS next_salary
FROM employees;
    

This query lists each employee's salary and the salary of the next employee ordered by their ID.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The database scans each row once and looks ahead to the next row's salary.
• How many times: Once for every row in the employees table.

How Execution Grows With Input

As the number of employees grows, the database does a similar amount of work for each employee.

Input Size (n)	Approx. Operations
10	About 10 lookups
100	About 100 lookups
1000	About 1000 lookups

Pattern observation: The work grows directly with the number of rows.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the query grows in a straight line as the number of rows increases.

Common Mistake

[X] Wrong: "LEAD causes the query to do extra loops inside loops, making it much slower than scanning once."

[OK] Correct: The LEAD function just looks ahead one row during a single pass, so it does not multiply the work by the number of rows.

Interview Connect

Understanding how window functions like LEAD work helps you explain query performance clearly and shows you know how databases handle row-by-row operations efficiently.

Self-Check

"What if we used LEAD with a PARTITION BY department? How would the time complexity change?"