SQL Query to Get Max Value per ID

In this article, we will explore how to write a SQL query that retrieves the maximum value per customer (or user) from three related tables: tblclients, tblhosting, and tblproducts.

Table Structures

Before diving into the query, let’s examine the structure of each table:

Table tblclients

CREATE TABLE tblclients (
  id INT PRIMARY KEY,
  email VARCHAR(255),
  status VARCHAR(20)
);

Table tblhosting

CREATE TABLE tblhosting (
  id INT PRIMARY KEY,
  userid INT,
  packageid INT,
  domainstatus VARCHAR(20),
  FOREIGN KEY (userid) REFERENCES tblclients(id)
);

Table tblproducts

CREATE TABLE tblproducts (
  id INT PRIMARY KEY,
  name VARCHAR(50)
);

The Query

The original query provided in the Stack Overflow post attempts to retrieve the maximum value per customer by using a combination of MAX aggregation and CASE statements. However, this approach has several limitations:

• It only returns one row per customer, instead of retrieving all rows with the maximum quota for each user.
• It uses subqueries to calculate the maximum quota, which can lead to performance issues.

A better approach is to use window functions, specifically MAX OVER (PARTITION BY) to achieve this.

Using Window Functions

Let’s rewrite the query using window functions:

SELECT 
  c.id AS client_id,
  c.email AS client_email,
  h.packageid AS package_id,
  p.name AS product_name,
  MAX(CASE 
    WHEN p.name = 'Basic' THEN 100
    WHEN p.name = 'Silver' THEN 100
    WHEN p.name = 'Gold' THEN 100
    ELSE 10
   END) AS quota
FROM 
  tblclients c
  LEFT JOIN tblhosting h ON c.id = h.userid
  INNER JOIN tblproducts p ON h.packageid = p.id
GROUP BY 
  c.id, c.email, h.packageid, p.name
ORDER BY 
  c.id;

However, this query still has limitations. To get the maximum quota per customer, we need to use window functions.

Using MAX OVER (PARTITION BY)

Here’s the corrected query:

SELECT 
  client_id,
  client_email,
  packageid,
  product_name,
  MAX(quota) OVER (PARTITION BY client_id) AS max_quota
FROM (
  SELECT 
    c.id AS client_id,
    c.email AS client_email,
    h.packageid AS packageid,
    p.name AS product_name,
    MAX(CASE 
      WHEN p.name = 'Basic' THEN 100
      WHEN p.name = 'Silver' THEN 100
      WHEN p.name = 'Gold' THEN 100
      ELSE 10
     END) AS quota
  FROM 
    tblclients c
    LEFT JOIN tblhosting h ON c.id = h.userid
    INNER JOIN tblproducts p ON h.packageid = p.id
  GROUP BY 
    c.id, c.email, h.packageid, p.name
) subquery
ORDER BY 
  client_id;

This query uses a subquery to calculate the maximum quota for each group of rows with the same client_id. The outer query then selects these values and calculates the overall maximum quota per customer using the MAX window function.

Explanation

In this query:

• We first calculate the maximum quota for each group of rows with the same client_id in the subquery.
• Then, we select the original row from the subquery that corresponds to the current row in the outer query.
• Finally, we use the MAX window function to get the overall maximum quota per customer.

Conclusion

In this article, we have explored how to write a SQL query that retrieves the maximum value per customer from three related tables using window functions. The corrected query uses MAX OVER (PARTITION BY) to achieve this, providing a more efficient and accurate solution than the original query.

Recommendations

• Use window functions whenever possible when working with aggregate values.
• Consider normalizing your database schema to reduce data redundancy and improve performance.
• Always use proper indexing and join optimization techniques to improve query performance.

Example Use Cases

• Retrieving top-performing products by sales revenue
• Finding the average rating for each customer
• Identifying the most popular categories in e-commerce

By applying these concepts and techniques, you can write more efficient and effective SQL queries that solve real-world problems.

Last modified on 2024-02-27