SQL Essentials: GROUP BY vs. PARTITION BY explained

In SQL, GROUP BY and PARTITION BY are used for organizing and analyzing data, but they serve different purposes and are used in different contexts. Here’s an explanation of each, including their differences and use cases:

GROUP BY

Purpose:

• GROUP BY is used to aggregate data into summary rows based on one or more columns. It’s often used with aggregate functions (e.g., SUM(), COUNT(), AVG(), MAX(), MIN()) to perform calculations on each group of rows.

How It Works:

• When you use GROUP BY, SQL groups rows that have the same values in specified columns into aggregate rows. Each group will produce a single row in the result set.

Syntax Example:

SELECT column1, COUNT(*)

FROM table_name

GROUP BY column1;

In this example, COUNT(*) calculates the number of rows for each unique value in column1.

Use Cases:

• Aggregating data to get summary statistics.


• Producing reports that group data by specific criteria, such as total sales by region or average salary by department.

PARTITION BY

Purpose:

• PARTITION BY is used with window functions to perform calculations across a set of rows that share the same value in one or more columns, but it does not reduce the number of rows returned by the query. It helps in performing calculations across partitions of data.

How It Works:

• PARTITION BY divides the result set into partitions based on the values of one or more columns. Within each partition, you can apply window functions to calculate values such as running totals or rankings.

Syntax Example:

SELECT column1, column2, SUM(column2) OVER (PARTITION BY column1) AS running_total

FROM table_name;

In this example, SUM(column2) OVER (PARTITION BY column1) calculates the running total of column2 within each partition defined by column1.

Use Cases:

• Calculating running totals, moving averages, or rankings.


• Performing calculations that require knowledge of the data's position within a partition without changing the number of rows in the result set.

Key Differences

1.     Purpose and Result:

o    GROUP BY: Aggregates data and reduces the result set to one row per group. It’s used to summarize data.

o    PARTITION BY: Applies calculations within partitions of data, preserving the original number of rows. It’s used to compute values across a set of rows.

2.     Result Set:

o    GROUP BY: Returns a summarized result set with one row per group.

o    PARTITION BY: Returns the same number of rows as the original query but with additional calculated columns.

3.     Usage Context:

o    GROUP BY: Typically used in conjunction with aggregate functions.

o    PARTITION BY: Used with window functions to compute calculations over partitions of data.

Examples

Example with GROUP BY:

SELECT department, AVG(salary) AS average_salary

FROM employees

GROUP BY department;

This query calculates the average salary for each department, returning one row per department with the average salary.

Example with PARTITION BY:

SELECT employee_id, department, salary,

       RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rank

FROM employees;

This query ranks employees within each department based on their salary, but it returns all rows with the calculated rank for each employee.

Summary

• GROUP BY is used for aggregating data into summary rows based on specified columns.


• PARTITION BY is used with window functions to calculate values across partitions of data while retaining the original row structure.

Understanding when to use each of these clauses depends on whether you need to aggregate data into summary rows or perform calculations within specific partitions of your dataset.