How to Correctly Aggregate SUM Values Across Multiple Database Tables?

Database Aggregation across Multiple Tables: Correcting Sum Calculations

When dealing with multiple tables in a database, aggregation functions like SUM require careful handling to ensure accurate results. This is exemplified by a query attempting to calculate the sum of values from two tables, AP and INV, both having columns [PROJECT] and [Value]. The desired output should resemble:

PROJECT | SUM_AP | SUM_INV

However, the provided query exhibited incorrect results due to an error in summation:

SELECT AP.[PROJECT],
SUM(AP.Value) AS SUM_AP, 
SUM(INV.Value) AS SUM_INV
FROM AP INNER JOIN INV ON (AP.[PROJECT] =INV.[PROJECT])
WHERE AP.[PROJECT] = 'XXXXX'
GROUP BY AP.[PROJECT]

The issue lies in the grouping of values. The GROUP BY clause combines duplicate values, which leads to incorrect sums.

To rectify this, sub-selects can be employed:

SELECT 
    AP1.[PROJECT],
    (SELECT SUM(AP2.Value) FROM AP AS AP2 WHERE AP2.PROJECT = AP1.PROJECT) AS SUM_AP,
    (SELECT SUM(INV2.Value) FROM INV AS INV2 WHERE INV2.PROJECT = AP1.PROJECT) AS SUM_INV
FROM AP AS AP1 
    INNER JOIN INV AS INV1 
        ON (AP1.[PROJECT] =INV1.[PROJECT])
WHERE AP1.[PROJECT] = 'XXXXX'
GROUP BY AP1.[PROJECT]

This approach calculates the sums separately for each [PROJECT] using sub-selects, resulting in accurate aggregation.

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