Understanding the Problem and the Challenge

When dealing with two tables that have some common columns, but not all of them are identical, it can be challenging to find the difference between these two sets of data. In this scenario, we’re working with SQL Server, and our goal is to calculate the sum of costs for a specific month in both tables.

We’ll begin by examining how to approach this problem using SQL Server and explore different methods to achieve our objective.

Table Structures and Sample Data

For our purposes, let’s consider two sample tables: Table1 and Table2. The table structures are as follows:

CREATE TABLE Table1 (
    Cost2 DECIMAL(10, 2)
);

INSERT INTO Table1 (Cost2) 
VALUES 
    ('500'),
    ('400'),
    ('300'),
    ('600'),
    ('300'),
    ('200'),
    ('400'),
    ('200');

CREATE TABLE Table2 (
    Cost2 DECIMAL(10, 2)
);

INSERT INTO Table2 (Cost2) 
VALUES 
    ('200'),
    ('250'),
    ('195'),
    ('700'),
    ('300'),
    ('200'),
    ('400'),
    ('200');

Both tables contain a single column called Cost2, representing the cost of certain items.

Initial Query Attempt

We’ll start with an initial query that aims to find the difference between the sum of costs in Table1 and Table2 for a specific month. In this case, we’re interested in January:

SELECT 
    a.month,
    (SUM(a.cost2)) - (SUM(b.cost2)) AS difference
FROM 
    Table1 a
LEFT JOIN 
    Table2 b ON a.Month = b.Month
WHERE 
    a.month = 'January'
GROUP BY 
    a.month;

However, this query does not produce the desired result of 300. It returns an incorrect value of 600.

Explanation and Issues with the Initial Query

To understand why our initial query is returning an incorrect result, let’s break down what it’s doing:

• We’re joining Table1 with Table2 on the Month column.
• We’re filtering the results to only include rows where the month is January.
• We’re grouping the results by the Month column.
• We’re calculating the difference between the sum of costs in each group.

The issue arises because we’re performing a left join. This means that all rows from Table1 will be included in our result, even if there’s no matching row in Table2. As a result, when we calculate the difference between the sums, we’re essentially combining the values from both tables as though they were identical.

Alternative Approach: Aggregation and Join

One way to address this issue is by aggregating the costs separately for each table first, before joining them. Here’s how you can modify your query:

SELECT 
    a.month,
    (a_cost2 - b_cost2) AS difference
FROM (
    SELECT month, SUM(Cost2) AS a_cost2
    FROM Table1
    WHERE Month = 'January'
    GROUP BY Month
) a
LEFT JOIN (
    SELECT month, SUM(Cost2) AS b_cost2
    FROM Table2
    WHERE Month = 'January'
    GROUP BY Month
) b
ON a.Month = b.Month;

In this modified query:

• We first calculate the sum of costs for January in Table1 and store it in column a_cost2.
• We do the same for Table2, storing the result in column b_cost2.
• We then perform a left join on these aggregated values, ensuring that we get the correct difference between the two sums.

This approach should give us the desired result of 300, which is the difference between the sum of costs in January for Table1 and Table2.

Conclusion

In this article, we explored how to find the difference between two sets of data stored in separate tables. We examined an initial query that did not produce the correct result due to a left join on common columns.

We then discussed alternative approaches using aggregation and joining individual subqueries for each table. By doing so, we ensured that we were comparing identical sums from both tables correctly.

This technique can be applied to many different scenarios involving multiple tables with overlapping data and requires attention to how you structure your query to achieve the desired result.

Last modified on 2024-03-16