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SQL MAX() Function - GeeksforGeeks

Last Updated : 23 Jul, 2025

The MAX() function in SQL is a powerful aggregate function used to retrieve the maximum (highest) value from a specified column in a table. It is commonly employed for analyzing data to identify the largest numeric value, the latest date, or other maximum values in various datasets. The MAX() function automatically excludes NULL values from its computation, ensuring accuracy.

In this article, we will cover the syntax, use cases, sample tables, and practical examples with detailed explanations of how to use the MAX() function effectively. Whether we are a beginner or an advanced SQL user, this guide will help us understand and apply the MAX() function confidently.

Syntax:

SELECT MAX(column_name)
FROM table_name
[WHERE condition];

• column_name: The column for which you want to find the maximum value.
• table_name: The table containing the data.
• condition (optional): Filters rows before calculating the maximum value.

In this section, we will demonstrate the usage of the MAX() function with examples using a two sample tables. Product Prices table contains product IDs and their corresponding prices. The Sales table contains sales data with sale IDs, product IDs, sale dates, and amounts.

Product Prices Table

Sales Table

To find the highest price in the product_prices table. This query is simple yet effective for identifying the most expensive product in the dataset. It excludes NULL values, ensuring only valid prices are considered.

Query:

SELECT MAX(price) AS [Highest Price]
FROM product_prices;

Output

Explanation: The MAX(price) function evaluates all the values in the price column and returns the largest value, $199.99.

To determine the highest sale amount from the Sales table. This query is commonly used in sales data analysis to find the most significant transaction in terms of value. It helps businesses track their peak sales performances.

Query:

SELECT MAX(amount) AS [Highest Sale]
FROM Sales;

Output:

Explanation: The MAX(amount) function scans the amount column in the Sales table and identifies the largest sale, which is $1500.00

Find the maximum price for products under a specific category, e.g., Electronics: This query is valuable for targeted analysis such as identifying the product with highest price within a specific category.

Query:

SELECT MAX(price) AS [Highest Price in Electronics]
FROM product_prices
WHERE category = 'Electronics';

Output:

Explanation: The WHERE clause filters rows to include only products in the 'Electronics' category. The MAX(price) function then calculates the maximum price within this subset.

To find the most recent sale date in the Sales table. This query is particularly useful for tracking the last activity in a dataset, such as identifying the latest transaction or update.

Query:

SELECT MAX(sale_date) AS [Latest Sale Date]
FROM Sales;

Output:

Explanation: The MAX(sale_date) function evaluates all dates in the sale_date column and returns the most recent one, 2023-02-01

Find the highest sale amount for each product. This query is helpful for analyzing performance metrics at the product level, allowing businesses to track the best-performing products.

Query:

SELECT product_id, MAX(amount) AS [Highest Sale]
FROM Sales
GROUP BY product_id;

Explanation: The GROUP BY clause groups rows by product_id, and the MAX(amount) function calculates the highest sale amount for each group.

Retrieve details of the product with the highest price. The main query retrieves the full record associated with this maximum price, providing detailed information about the most expensive product.

Query:

SELECT *
FROM product_prices
WHERE price = (SELECT MAX(price) FROM product_prices);

Output:

Explanation: The subquery (SELECT MAX(price) FROM product_prices) determines the highest price ($199.99). The main query fetches all records matching this price.

The MAX() function in SQL is a fundamental tool for data analysis, enabling users to find the highest value in a column. It can be used independently or in combination with other SQL clauses like WHERE, GROUP BY, and subqueries to handle complex data requirements. By mastering the MAX() function, WE can efficiently analyze and summarize data in various scenarios, such as identifying maximum prices, latest dates, or highest scores.

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