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SQL Aggregate Functions

SQL aggregate functions are powerful tools that perform calculations on multiple rows of a table, returning a single result. These functions are essential for data analysis and reporting in relational databases.

Purpose and Role

Aggregate functions allow you to summarize data across rows, providing insights such as totals, averages, and counts. They're commonly used with the GROUP BY clause to generate meaningful summaries from large datasets.

Common SQL Aggregate Functions

  • COUNT(): Counts the number of rows or non-null values
  • SUM(): Calculates the sum of a set of values
  • AVG(): Computes the average of a set of values
  • MAX(): Finds the maximum value in a set
  • MIN(): Finds the minimum value in a set

Basic Syntax

The general syntax for using aggregate functions is:

SELECT aggregate_function(column_name)
FROM table_name
[WHERE condition]
[GROUP BY column_name];

Examples

1. Counting Rows

SELECT COUNT(*) AS total_customers
FROM customers;

This query counts the total number of rows in the customers table.

2. Calculating Average

SELECT AVG(price) AS average_price
FROM products
WHERE category = 'Electronics';

This example calculates the average price of products in the 'Electronics' category.

Using Aggregate Functions with GROUP BY

Combining aggregate functions with GROUP BY allows for more complex analysis:

SELECT category, COUNT(*) AS product_count, AVG(price) AS avg_price
FROM products
GROUP BY category;

This query groups products by category and calculates the count and average price for each.

Important Considerations

  • Aggregate functions ignore NULL values (except COUNT(*)).
  • When using GROUP BY, all non-aggregated columns in the SELECT list must appear in the GROUP BY clause.
  • Use the HAVING clause to filter results based on aggregate function results.

Advanced Usage

Aggregate functions can be combined with other SQL features for more sophisticated analysis:

  • Use with subqueries for complex calculations
  • Combine multiple aggregate functions in a single query
  • Utilize window functions for running totals and moving averages

Conclusion

SQL aggregate functions are indispensable for data analysis and reporting. By mastering these functions, you can efficiently summarize large datasets and extract valuable insights from your databases.