Finding Top N Records Within Each Group in MySQL Queries (Greatest-N-per-Group)

• You'll first need to group your data based on a specific column or set of columns. This creates categories within your results. The GROUP BY clause is used for this purpose.

Identifying the Maximum Value:

• Once you have the groups defined, you need to identify the maximum value within each group for a specific column. This is achieved using window functions like MAX. Window functions operate on sets of data defined by the GROUP BY clause.

Selecting the Records:

• Finally, you can select the desired columns along with the maximum value for each group. The SELECT clause is used to choose the specific data points you want in the final result set.

Here's an example to illustrate this concept:

SELECT product_category, product_name, MAX(price) AS max_price
FROM products
GROUP BY product_category;

In this example:

• We're grouping the products table by the product_category column.
• We're using the MAX function to find the maximum value in the price column for each group.
• The AS max_price renames the result of the MAX function for better readability.
• Finally, we're selecting the product_category, product_name, and the maximum price (max_price) for each group.

This query will return a list of products, categorized by type, along with the most expensive product within each category.

Additional Points:

• You can use other window functions besides MAX depending on your needs. For example, MIN can find the minimum value.
• You can combine multiple grouping columns in the GROUP BY clause for more granular results.

Example Codes for "Greatest-N-per-Group" in MySQL

Using ROW_NUMBER() and LIMIT:

This method assigns a row number within each group, then filters the top N rows based on that number.

SELECT product_category, product_name, price
FROM (
  SELECT product_category, product_name, price,
         ROW_NUMBER() OVER (PARTITION BY product_category ORDER BY price DESC) AS row_num
  FROM products
) AS ranked_products
WHERE row_num <= 3;  -- Replace 3 with your desired number (N)

Explanation:

• The subquery calculates a row number (row_num) for each product within its category, ordered by price descending (highest first).
• The outer query then selects the desired columns and filters based on row_num being less than or equal to your desired N (e.g., 3 for top 3).

Using LIMIT with Subquery:

This method uses a subquery to find the maximum N values in each group and then joins that back to the main table to retrieve the corresponding records.

SELECT p.product_category, p.product_name, p.price
FROM products p
INNER JOIN (
  SELECT product_category, MAX(price) AS max_price
  FROM products
  GROUP BY product_category
  ORDER BY max_price DESC
  LIMIT 3  -- Replace 3 with your desired number (N)
) AS top_prices
ON p.product_category = top_prices.product_category
AND p.price = top_prices.max_price;

• The subquery finds the maximum price (max_price) for each category, ordered by price descending (highest first), limited to N rows (e.g., 3).
• The main query joins the products table (p) with the subquery result on both category and price to ensure we retrieve the actual records with the top N prices.

This method leverages user-defined variables within a loop to track the current maximum value and row count within each group.

Note: This approach is only available in MySQL 8 and above.

SELECT product_category, product_name, price
FROM products
ORDER BY product_category, price DESC;

SET @group_category = NULL;
SET @row_count = 0;

SELECT * FROM (
  SELECT @group_category AS category, @row_count := IF(@group_category = product_category, @row_count + 1, 1) AS row_num,
         product_category, product_name, price
  FROM (
    -- Your original query selecting products (replace with your actual query)
  ) AS product_data
  ORDER BY product_category, price DESC
) AS ranked_products
WHERE (row_num <= 3 OR @group_category IS NULL) AND (@group_category := product_category) IS NOT NULL;

1. We define user-defined variables @group_category and @row_count.
2. The main query retrieves and orders products by category and price descending.
3. We then set these variables outside the main query for initialization.
4. A subquery processes the product data while setting row_num based on the current group and incrementing a counter within each group.
5. The outer query filters the subquery results based on row_num being less than or equal to N (3 in this case) and ensures we're within a new group based on category change.
6. We update the @group_category variable within the WHERE clause to track the current group for row counting.

Using Temporary Tables (For Complex Scenarios):

This method involves creating a temporary table to store the maximum values for each group and then joining back to the main table.

CREATE TEMPORARY TABLE IF NOT EXISTS top_prices (
  product_category VARCHAR(255) PRIMARY KEY,
  max_price DECIMAL(10,2) NOT NULL
);

INSERT INTO top_prices (product_category, max_price)
SELECT product_category, MAX(price) AS max_price
FROM products
GROUP BY product_category;

SELECT p.product_category, p.product_name, p.price
FROM products p
INNER JOIN top_prices t ON p.product_category = t.product_category
WHERE p.price = t.max_price
LIMIT 3 * (SELECT COUNT(DISTINCT product_category) FROM products);

DROP TEMPORARY TABLE IF EXISTS top_prices;

1. We create a temporary table top_prices to store the maximum price for each category.
2. We populate this table using a subquery similar to the previous methods.
3. The main query joins the products table (p) with the temporary table (t) on category.
4. We filter for products where the price matches the maximum price for the category.
5. Finally, we use a LIMIT clause with a subquery to retrieve the top N records overall (considering the number of groups).
6. After retrieving the results, we drop the temporary table.