To calculate running totals in MySQL, use window functions like SUM() OVER(). 1. Use SUM() OVER (ORDER BY column) for cumulative sums across rows. 2. Add PARTITION BY to compute separate running totals for groups. 3. Ensure correct ordering, handle NULLs with COALESCE(), and index columns used in ORDER BY and PARTITION BY for performance. 4. Avoid window functions in MySQL 5.x or opt for simpler variable-based methods when appropriate.
When you need to calculate running totals in MySQL, window functions are the go-to solution. They let you compute cumulative sums across rows related to the current one—without needing complicated joins or subqueries.
What Is a Cumulative Sum?
A cumulative sum (or running total) adds up values as you move through rows. For example, if you're tracking daily sales, a cumulative sum would show the total sales from the first day up to each subsequent day.
In MySQL, doing this used to require self-joins or session variables, which could get messy and hard to read. But with window functions introduced in MySQL 8.0, it's clean and straightforward.
How to Use SUM() OVER() for Running Totals
The core function you'll use is SUM() OVER(). This tells MySQL to apply a window frame to your data and return the sum up to that point.
Here’s a basic example:
SELECT
date,
sales,
SUM(sales) OVER (ORDER BY date) AS running_total
FROM daily_sales;This query orders rows by date and calculates a running total of the sales column. The key part is OVER (ORDER BY date)—that defines how the window moves through your data.
If you want the total partitioned by another field—like per store—you can add PARTITION BY:
SELECT
store_id,
date,
sales,
SUM(sales) OVER (PARTITION BY store_id ORDER BY date) AS running_total
FROM daily_sales;Now, each store has its own separate running total.
Common Pitfalls and Tips
There are a few gotchas when using window functions for cumulative sums:
- Order matters: If you forget
ORDER BYinside theOVER()clause, the result might not be what you expect—or it may default to an arbitrary row order. - NULLs can throw things off: Make sure your numeric fields don’t have unexpected NULLs. You can wrap them with
COALESCE()to treat missing values as zero. - Partitioning is optional but often needed: Without
PARTITION BY, the entire dataset will be treated as one group. That’s fine for overall totals, but usually, you’ll want to break it down by category, user, or time period.
Also, keep in mind that performance can degrade on very large datasets if you’re not careful. Indexes on the columns used in ORDER BY and PARTITION BY can help a lot.
When Not to Use Window Functions
Window functions are powerful, but they aren’t always the best fit:
If you're stuck on MySQL 5.x, you can't use them at all.
For very simple reports, sometimes a quick variable-based approach might be easier:
SELECT date, sales, @total := @total sales AS running_total FROM daily_sales CROSS JOIN (SELECT @total := 0) AS init ORDER BY date;This method works, but it's more fragile and harder to maintain, especially when partitioning comes into play.
So yes, for modern versions of MySQL, window functions are the way to go when calculating cumulative sums. They’re clearer, safer, and scale better than older methods. Just remember to define your ordering, think about partitioning, and make sure your data is clean before diving in.
That’s pretty much it.
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