SQL Query to Filter Customers Who Have Purchased the Same Product Multiple Times with a Quantity Greater Than 5

Introduction

In this article, we will explore how to write an efficient SQL query to filter customers who have purchased the same product multiple times with a quantity greater than 5. We’ll discuss the use of subqueries and window functions as solutions.

Background

Suppose we have a database table Customer_Order_Data that stores information about customer orders, including customer_id, order_id, product_id, and quantity. Our goal is to identify customers who have purchased the same product multiple times with a quantity greater than 5.

The provided table data contains several rows of order information for different customers and products. We can use this data to illustrate how to write an efficient SQL query using subqueries and window functions.

Using Subqueries

One possible approach is to use a subquery to count the number of times each customer has purchased the same product with a quantity greater than 5.

SELECT t.*
FROM mytable t
WHERE (
    SELECT COUNT(*)
    FROM mytable t1
    WHERE 
        t1.customer_id = t.customer_id 
        AND t1.product_id = t.product_id 
        AND t1.quantity > 5
) > 1;

Here’s a step-by-step explanation of this query:

• The subquery counts the number of rows in mytable (t1) that have the same customer_id, product_id, and quantity greater than 5.
• The outer query selects all columns from mytable (t) where the count is greater than 1, indicating multiple purchases of the product with a quantity greater than 5.

Using Window Functions

Another approach is to use window functions to calculate the cumulative count of customers who have purchased the same product with a quantity greater than 5.

SELECT *
FROM (
    SELECT t.*,
        SUM(CASE WHEN t.quantity > 5 THEN 1 ELSE 0 END) OVER (PARTITION BY t.customer_id, t.product_id) AS cnt
    FROM mytable t
) t
WHERE cnt > 1;

Here’s a step-by-step explanation of this query:

• The inner query uses the SUM window function to calculate the cumulative count of customers who have purchased the same product with a quantity greater than 5.
• The outer query selects all columns from the inner query where the cumulative count is greater than 1, indicating multiple purchases of the product with a quantity greater than 5.

Comparing Subqueries and Window Functions

Both subqueries and window functions can be used to solve this problem. However, there are some differences between the two approaches:

• Performance: Subqueries can be slower than window functions because they require multiple passes over the data.
• Flexibility: Window functions offer more flexibility in terms of calculating aggregated values and performing joins.
• Readability: Subqueries can be easier to read and understand, especially for complex queries.

In general, window functions are a good choice when you need to perform aggregate calculations or joins, while subqueries might be preferred when the calculation is simple and straightforward.

Conclusion

Writing an efficient SQL query to filter customers who have purchased the same product multiple times with a quantity greater than 5 requires careful consideration of the available data and the performance requirements. Both subqueries and window functions can be used as solutions, depending on your specific needs and preferences.

In this article, we explored the use of both subqueries and window functions to solve this problem. We also discussed the pros and cons of each approach and provided example queries to illustrate the concepts. By following these guidelines, you can write efficient SQL queries that meet your requirements.

Last modified on 2025-01-23