The goal of this tutorial is to provide an understanding of window functions in SQL (Structured Query Language). SQL is a language for managing data held in a relational database management system. A window function performs a calculation across a set of table rows that are somehow related to the current row, which is a common need when performing data analysis.
At the end of this tutorial, you will be able to understand the concept of window functions, know when to use them, and write SQL queries using window functions.
Prerequisites: Basic knowledge of SQL, including how to write simple SELECT queries.
A window function in SQL performs a calculation across a set of rows that are related to the current row. Unlike aggregate functions, which return a single result per group, window functions do not cause rows to become grouped into a single output row — the rows retain their separate identities.
A window function call always contains an OVER clause. This clause specifies the "window" — the set of rows used in each calculation. The OVER clause can include a PARTITION BY clause, which divides the rows into groups, or "partitions", to which the function is applied.
Window functions are used for tasks such as ranking items (e.g., top sales by region), calculating running totals, or creating moving averages.
Let's look at an example. Suppose we have a sales table and we want to rank each sale by the amount sold:
SELECT sale_date, sale_amount,
RANK() OVER (ORDER BY sale_amount DESC) as rank
FROM sales
In this query:
- RANK() is a window function that assigns a unique rank to each distinct row within the partition of the result set.
- OVER (ORDER BY sale_amount DESC) specifies the window over which the RANK() function operates. The window is ordered by sale_amount in descending order.
The expected output would be a list of sales, each with a rank. The rank would be 1 for the sale with the highest amount, 2 for the second highest, and so on.
Key points covered:
- Window functions perform a calculation over a set of rows related to the current row.
- Window functions retain the identities of the rows.
- The OVER clause, which is always present in a window function call, specifies the window of rows for each calculation.
Next steps for learning:
- Learn about various window functions such as ROW_NUMBER(), RANK(), DENSE_RANK(), LEAD(), LAG(), etc.
- Learn how to use different clauses in OVER, such as PARTITION BY, ROWS BETWEEN, etc.
Additional resources:
- Window Functions in SQL
- SQL Window Functions: A Practical Guide
Solution:
SELECT employee_name, salary,
RANK() OVER (ORDER BY salary ASC) as rank
FROM employees
Solution:
SELECT sale_date, sale_amount,
SUM(sale_amount) OVER (ORDER BY sale_date) as running_total
FROM sales
Tips for further practice: Think about how you can use window functions to analyze the data you work with in your projects or job. Try to write SQL queries using window functions to solve these problems.