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Discover how to efficiently combine `MAX` and `SUM` in Oracle ROLLUP without excessive SQL nesting. Improve your query structure and maintainability today!
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Mastering MAX and SUM in Oracle ROLLUP: A Clear Solution

Handling data in SQL can sometimes be more complex than we anticipate, especially when it comes to aggregation functions like MAX and SUM in combination with the ROLLUP clause in Oracle. If you've ever faced a scenario where the output of your SQL query didn't match your expectations, you're not alone! In this guide, we will explore a common problem and provide a straightforward solution for combining MAX and SUM using ROLLUP in Oracle SQL.

The Problem

Consider this SQL statement that you might be using:

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Expected Output

When run, the output might look something like this:

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However, you expected to aggregate the maximum weights correctly, and the output doesn't reflect your initial expectations. You wanted the total weight for each food type, which should include summed values rather than just the maximum values found.

The Challenge

The challenge arises because the ROLLUP operation as typically used computes the maximum of all maximums in the food-type category, rather than summing the maximum weights from each food after grouping. Thus, there is a need to rethink the approach without unnecessarily complicating the SQL with additional nesting, which often makes the query harder to maintain.

The Solution

After some refinement, here’s a solution that effectively addresses the problem without additional SQL nesting:

[[See Video to Reveal this Text or Code Snippet]]

Breakdown of the Solution

CTE Definition: The Common Table Expression (CTE) source1 is defined as before, combining various fruit and vegetable data with their weights.

Group By and Rollup: We apply the GROUP BY clause along with ROLLUP to aggregate the hierarchy of food types and food items.

CASE Statement:

We utilize a CASE statement to differentiate between regular rows and summary rows created by the ROLLUP.

If a summary row is detected (grouping(s.food) = 1), we proceed to use the cumulative sum of maximum weights; otherwise, we show the maximum weight.

Window Function: The OVER(PARTITION BY s.foodtype ORDER BY s.food) clause allows us to calculate running total weight for summary rows effectively.

Conclusion

This approach offers a more manageable SQL query solution without the need for excessive nesting while ensuring that the aggregation meets your requirements. Despite its complexity, the final result is both efficient and easier to maintain, offering a clean way to summarize your data using MAX and SUM within a ROLLUP context.

Feel free to implement this solution in your work and witness how effective SQL can be when it's properly structured! If you have any further questions or need clarification on any points, feel free to reach out in the comments below.