Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG) in SQL

Window functions are a powerful feature in SQL that allows you to perform calculations across a set of rows that are related to the current row. They are similar to aggregate functions, but while aggregate functions return a single result row, window functions return several result rows. Window functions come in a variety of flavors, each providing different functionality. This blog post will delve deep into the understanding and usage of five important window functions: ROW_NUMBER, RANK, DENSE_RANK, LEAD, and LAG.

Introduction to Window Functions

SQL window functions are functions that perform calculations across a set of rows, which are termed as a 'window'. A window function can access more than just the current row of the query result. By framing a 'window' of rows onto the result set, you can work with data from additional rows, which can result in more dynamic and powerful queries.

SELECT ..., window_function(arg1, arg2, ...) OVER ([PARTITION BY partition_expression] [ORDER BY sort_expression [ASC | DESC] ...]) ...
FROM ...

Each window function includes an OVER clause that defines a window of rows around the row being evaluated. The PARTITION BY clause divides the result set into partitions (or groups), and the window function is applied to each partition separately. The ORDER BY clause orders rows within a partition.

ROW_NUMBER Function

The ROW_NUMBER function is the simplest of all window functions. It assigns a unique row number to each row within a partition, which starts from 1. When the data changes, the row number changes.

SELECT name, salary, ROW_NUMBER() OVER (ORDER BY salary DESC) as row_number
FROM employees

In the above query, the ROW_NUMBER() function is applied on the salary column in descending order, meaning the employee with the highest salary will have a row number of 1, the next highest will be 2, and so on.

RANK and DENSE_RANK Functions

The RANK and DENSE_RANK functions are similar to ROW_NUMBER function but handle ties (rows with equal values) differently. When there is a tie, RANK function leaves a gap in the sequence for the tied rows, whereas DENSE_RANK function doesn't leave any gaps.

SELECT name, salary, 
RANK() OVER (ORDER BY salary DESC) as rank,
DENSE_RANK() OVER (ORDER BY salary DESC) as dense_rank
FROM employees

In the above query, both RANK() and DENSE_RANK() functions are applied to the salary column. If two employees have the same salary, they will receive the same rank, but the next rank will be skipped in RANK() while it won't be in DENSE_RANK().

LEAD and LAG Functions

The LEAD and LAG functions are quite unique as they allow access to a row at a given physical offset that follows or precedes the current row.

LEAD function accesses data from a subsequent row without using a self-join. Conversely, LAG function fetches data from a previous row.

SELECT name, salary, 
LAG(salary) OVER (ORDER BY salary DESC) as prev_salary,
LEAD(salary) OVER (ORDER BY salary DESC) as next_salary
FROM employees

In the above query, LAG(salary) gives the salary of the employee who earns less than the current employee, and LEAD(salary) gives the salary of the employee who earns more than the current employee.

FAQ

1. Can I use window functionsin a WHERE clause in SQL?

No, you cannot directly use window functions in a WHERE clause. This is because window functions are computed after the WHERE clause in the SQL execution order. However, you can overcome this by using a subquery or a common table expression (CTE) and then applying the WHERE clause.

2. What's the difference between a window function and an aggregate function?

The key difference is that aggregate functions return a single result for each group of rows, while window functions return a single result for each row of the table based on the window frame of rows defined. This makes window functions more flexible for certain types of calculations.

3. Can I use more than one window function in a single SQL query?

Absolutely. You can use as many window functions in a single SQL query as you need. Just remember that each function needs its own OVER clause.

4. What is the use of the PARTITION BY clause in a window function?

The PARTITION BY clause divides the result set into partitions, i.e., smaller sets or subsets. The window function is applied to each subset separately. This allows for more granular calculations, like performing computations within each group.

5. What happens if I don’t specify an ORDER BY clause in the OVER clause of a window function?

If you don’t specify an ORDER BY clause in the OVER clause of a window function, SQL considers the entire partition as a single window frame. The function will then operate on this entire partition.

Understanding and effectively using SQL window functions can level up your data analysis capabilities and help you extract more insights from your data. I hope this blog post has given you a solid foundation on the window functions and you're ready to apply them in your SQL queries.