How to Correctly Summarize Data from Multiple SQL Tables and Avoid Incorrect Results?

Summarizing Data from Multiple Tables in SQL: Addressing Incorrect Results

In the realm of data analysis, it's often necessary to combine information from multiple tables to gain a comprehensive understanding. One common task is to calculate the sum of values across these tables, grouped by a common column. However, as evident from the provided code, incorrect results can arise if the data is not handled appropriately.

The initial query provided:

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]

attempts to calculate the sum of values from two tables, AP and INV for a specific PROJECT. However, the issue lies in the use of the GROUP BY clause. Grouping the results by AP.PROJECT causes duplicate values to be included in the sum, leading to incorrect totals.

To rectify this, a more robust approach utilizing sub-queries is required:

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 enhanced query employs sub-queries to calculate the sum of values for each PROJECT individually. By isolating the calculations within sub-queries, we eliminate the problem of duplicate values being included in the sums. The result is an accurate and meaningful summary of data from multiple tables, grouped by the desired column.

The above is the detailed content of How to Correctly Summarize Data from Multiple SQL Tables and Avoid Incorrect Results?. For more information, please follow other related articles on the PHP Chinese website!