SQL Query: 3 Methods for Calculating Cumulative SUM

SQL provides various constructs for calculating cumulative sums, offering flexibility and efficiency in data analysis. In this article, we explore three distinct SQL queries that facilitate the computation of cumulative sums. Each query leverages different SQL constructs to achieve the desired outcome, catering to diverse analytical needs and preferences.

Using Window Functions (e.g., PostgreSQL, SQL Server, Oracle)

SELECT id, value, SUM(value) OVER (ORDER BY id) AS cumulative_sum 

FROM your_table;

This query uses the SUM() window function with the OVER clause to calculate the cumulative sum of the value column ordered by the id column.

Using Subqueries (e.g., MySQL, SQLite):

SELECT t1.id, t1.value, SUM(t2.value) AS cumulative_sum

FROM your_table t1

JOIN your_table t2 ON t1.id >= t2.id

GROUP BY t1.id, t1.value

ORDER BY t1.id;

This query uses a self-join to calculate the cumulative sum. It joins the table with itself, matching rows where the id in the first table is greater than or equal to the id in the second table. It then calculates the sum of the value column for each group of rows with the same ID from the first table.

Using Correlated Subqueries (e.g., MySQL, SQLite):

SELECT id, value, (

    SELECT SUM(value) 

    FROM your_table t2 

    WHERE t2.id <= t1.id

) AS cumulative_sum

FROM your_table t1

ORDER BY id;

This query uses a correlated subquery to calculate the cumulative sum. For each row in the main query, it calculates the sum of the value column for all rows with an id less than or equal to the id of the current row.