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Window Functions in SQL
Computer ScienceData Analytics

# Window Functions in SQL

Mastering Advanced Data Analysis Techniques

by Kyryl Sidak

Data Scientist, ML Engineer

Jul, 2024

Window Functions are designed to perform calculations across a set of table rows that are somehow related to the current row. Unlike aggregate functions, which return a single value for a group of rows, window functions return a value for each row in the group.

Why Use Window Functions?

• Enhanced Data Analysis: Perform calculations like cumulative sums and moving averages.
• Ranking and Row Numbering: Assign ranks to rows within a partition of a result set.
• Data Comparison: Compare values between current and previous or next rows.

## Syntax and Basic Usage

The basic syntax of a window function involves using the `OVER` clause, which defines the window or the set of rows the function operates on.

Here is an example:

This query ranks employees based on their salaries in descending order.

## ROW_NUMBER()

The `ROW_NUMBER()` function assigns a unique sequential integer to rows within a partition of a result set.

## RANK()

The `RANK()` function assigns a rank to each row within a partition of a result set. If there are ties, gaps are left in the ranking sequence.

## DENSE_RANK()

Similar to `RANK()`, but without gaps in the ranking sequence.

## NTILE()

The `NTILE()` function distributes rows of an ordered partition into a specified number of approximately equal groups.

## LAG() and LEAD()

These functions access data from previous and subsequent rows in the same result set without the need for a self-join.

## PARTITION BY

The `PARTITION BY` clause divides the result set into partitions to which the window function is applied.

## ORDER BY

The `ORDER BY` clause specifies the logical order in which the window function calculation is performed.

## FRAME CLAUSE

Defines a subset of rows within a partition for the window function to operate on.

## FAQs

Q: What are SQL Window Functions?
A: SQL Window Functions perform calculations across sets of table rows that are related to the current row, providing advanced data analysis capabilities.

Q: How do Window Functions differ from aggregate functions?
A: Unlike aggregate functions, which return a single value for a group of rows, window functions return a value for each row in the group.

Q: Can I use multiple Window Functions in a single query?
A: Yes, you can use multiple window functions in a single query, each with its own `OVER` clause.

Q: Do Window Functions improve query performance?
A: Window functions enhance analytical capabilities but can be resource-intensive. Proper indexing and query optimization are essential for performance.

Q: Are Window Functions supported in all SQL databases?
A: Most modern SQL databases support window functions, including PostgreSQL, MySQL, SQL Server, and Oracle.

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