Sum Values Based on Specific Value in a Column Within Group

Introduction

In this article, we will explore how to sum values based on specific conditions within groups. This is particularly useful when working with sequential datasets where you need to group data by distinct groups and then perform calculations based on those groups.

We will use an example from the Stack Overflow community to demonstrate how to achieve this using windowed SUM and aggregate SUM in SQL.

Dataset Description

The dataset consists of customer information, including order columns, names, values, and a distinct group column. The distinct group column indicates whether a new group should be started when a 1 appears in the order column.

Original Table

Query

To solve this problem, we can use a common table expression (CTE) to create a new column called subgrp that indicates whether the current row belongs to the same group as the previous row. We will then use this new column to perform aggregate SUM on the values column.

The query is as follows:

WITH cte AS (
  SELECT *, 
         SUM(Distinct_Group) OVER(Partition by Customer ORDER BY Order_col) AS subgrp
  FROM tab
)
SELECT Customer, Name, subgrp, SUM(Val) AS Sum
FROM cte
GROUP BY Customer, Name, subgrp;

How It Works

Here’s a step-by-step explanation of how the query works:

1. Creating a CTE: We start by creating a CTE called cte. This allows us to perform calculations on the data without having to repeat them in the main query.
2. Summing Distinct Groups: Inside the CTE, we use the SUM function with an OVER clause to sum up the values of the Distinct_Group column for each group. The PARTITION BY clause groups the rows by the Customer column, and the ORDER BY clause orders the rows by the Order_col column.
3. Creating a New Column: We use this sum as a new value in our CTE, assigning it to a new column called subgrp. This effectively tells us whether the current row belongs to the same group as the previous row (if the subgrups are equal) or not (if they’re different).
4. Main Query: We then move on to the main query, which selects the required columns from our CTE.
5. Grouping by Subgrp: Finally, we use this new subgrp column as a grouping criterion when calculating the sum of values.

The Result

When we run the query, it produces the following result:

Conclusion

In this article, we have explored how to sum values based on specific conditions within groups using windowed SUM and aggregate SUM. We created a CTE to calculate the subgrp column and then used it in our main query to perform the desired aggregation.

This approach allows us to effectively handle sequential datasets where we need to group data by distinct groups and then perform calculations based on those groups.

In future articles, we can explore more advanced techniques for handling complex grouping and aggregation scenarios.

Last modified on 2023-10-21