LEFT JOIN with SUM Not Returning Correct Values: A SQL Solution

As a developer, we have all been there at some point or another - staring at a confusing error message from our database system, trying to figure out why a seemingly simple query is returning incorrect results. In this article, we’ll explore the concept of LEFT JOIN and SUM in SQL, and provide a solution to the problem described in the provided Stack Overflow post.

Understanding LEFT JOIN

A LEFT JOIN (also known as LEFT OUTER JOIN) is used to combine rows from two tables based on a related column between them. The basic idea behind a LEFT JOIN is to return all records from the left table (left_table), and the matched records from the right table (right_table). If there are no matches, the result will contain NULL values for the right table’s columns.

The syntax for a LEFT JOIN varies depending on the SQL dialect being used. In this article, we’ll use the SQL syntax:

SELECT * FROM left_table
LEFT JOIN right_table ON left_table.column_name = right_table.column_name;

Understanding SUM in SQL

The SUM function is used to calculate the total value of a column in a table. It takes one argument - the column for which we want to calculate the sum.

For example, if we have a table with the following structure:

We can use the SUM function to get the total salary as follows:

SELECT SUM(salary) FROM employees;

This would return 120000.

The Problem

The problem described in the Stack Overflow post is a common gotcha when working with LEFT JOINs and SUM. When we join two tables using a LEFT JOIN, we need to be careful not to multiply the values in the left table by the number of rows found in the right table.

In the provided query, the user tries to use the following query:

SELECT  SUM(ad.labour_cost) AS LABOUR,
    SUM(ad.part_cost) AS PARTS,
    SUM(ad.pol_cost) AS POLS,
    SUM(ad.sublet_cost) AS SUBLET,
    SUM(am.misc_sales_amt)  AS MISC
FROM AdvisorSalesData ad 
LEFT JOIN AdvisorMiscSalesData am 
  ON (ad.customer_id=am.customer_id AND ad.invoice_no=am.invoice_no)
WHERE ad.customer_id IN (3)

This query will return incorrect results because the SUM function is applied to each row in the left table, not just the actual sum of the values.

The Solution

To fix this issue, we need to apply the SUM function before joining the two tables. We can do this by using a subquery or by applying the SUM function at the beginning of our query.

The correct solution is to use a subquery with the SUM function:

SELECT 
    SUM(ad.labour) AS LABOUR,
    SUM(ad.parts) AS PARTS,
    SUM(ad.pols) AS POLS,
    SUM(ad.sublet) AS SUBLET,
    SUM(am.misc)  AS MISC
FROM (
  SELECT customer_id, invoice_no,
         SUM(ad.labour_cost) AS labour,
         SUM(ad.part_cost) AS parts,
         SUM(ad.pol_cost) AS pols,
         SUM(ad.sublet_cost) as sublet
  FROM AdvisorSalesData ad 
  GROUP BY customer_id, invoice_no
) ad
LEFT JOIN (
  SELECT customer_id, invoice_no,
          SUM(am.misc_sales_amt) AS misc
  FROM AdvisorMiscSalesData am 
  GROUP BY customer_id, invoice_no
) am
ON ad.customer_id = am.customer_id AND    
    ad.invoice_no = am.invoice_no
WHERE ad.customer_id IN (3);

This query first calculates the sum of each column in the AdvisorSalesData table using a subquery. Then it joins this subquery with the AdvisorMiscSalesData table, and finally applies the SUM function to calculate the total value.

Example Use Case

Let’s say we have two tables: orders and order_items. The orders table has the following structure:

And the order_items table has the following structure:

We want to calculate the total value of each order.

SELECT 
    SUM(o.order_date) AS total_orders,
    SUM(oi.quantity * p.price) AS total_value
FROM orders o
LEFT JOIN (
  SELECT order_id, quantity
  FROM order_items
) oi ON o.id = oi.order_id
LEFT JOIN products p ON oi.product_id = p.id;

This query first calculates the sum of each column in the orders table using a subquery. Then it joins this subquery with the order_items and products tables, and finally applies the SUM function to calculate the total value.

Conclusion

In conclusion, when working with LEFT JOINs and SUM, we need to be careful not to multiply the values in the left table by the number of rows found in the right table. By applying the SUM function before joining the two tables, or using a subquery to calculate the sum, we can avoid this issue and get the correct results.

We hope this article has helped you understand how to use LEFT JOINs with SUM in SQL, and provided you with a solution to the problem described in the Stack Overflow post. If you have any further questions or need additional clarification, please don’t hesitate to ask.

Last modified on 2023-08-16