The PARTITION BY clause of a Window Function – with an example in MySQL.

In this blog post, I will look at a couple of interesting result sets using the PARTITION BY clause as part of the OVER() clause of a Window Function with an example using MySQL.

Note: All data, names or naming found within the database presented in this post, are strictly used for practice, learning, instruction, and testing purposes. It by no means depicts actual data belonging to or being used by any party or organization.

OS and DB used:

• Xubuntu Linux 16.04.5 LTS (Xenial Xerus)
• MySQL 8.0.15

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I’ll be using the table structure below, containing close to 90 rows of data:

We can apply aggregate functions (E.g., SUM(), AVG(), etc …) in conjunction with the OVER() clause of a window function, producing some interesting query results.

I’ll start with the SUM() function and the OVER() clause filtering for just those walks in the month of ‘July’:

Note that on the 3rd row of the result set, the ‘amt_per_trail’ value of 739.7, is the total sum of the preceding (2) rows ‘burned_calories’ column values, in addition to the current row value (i.e., 93.1 + 322.9 + 323.7 = 739.7). This pattern continues throughout the remainder of the results with the combined total of all rows making up the last value of 8718.9.

Although that query does give us basically a nice running total, through-and-through, we can leverage specific clauses and retrieve even more detailed and interesting query results.

One of the 3 optional clause arguments allowed in the OVER() clause, PARTITION BY – with ordering and windowing being the other 2 – breaks the rows into individual sub-groups (i.e., rows of data). Let’s see with an example:

An important differentiator in this query is that the ‘amt_per_trail’ running total values resets for each distinct group of ‘trail_hiked’ values since that column is specified in the PARTITION BY clause (and further separated into those sub-groups). Here’s the breakdown.

First, the 3rd row is the sum of all the rows for the ‘Sandy Trail-Drive’ trail_hiked column. Then on the immediately following row, trail ‘West Boundary’ group begins, ending on the 4th row from the end of the result set. And finally, ‘Yard Mowing’ values begin at the 3rd from the end of the result set continuing through the remaining rows left.

The ending row value for each sub-group is the aggregated total (via SUM()) for that entire group’s ‘burned_calories’ values.

I am still learning about the power of Window Functions. Through these examples, I hope to help both you and I understand them even better.

Like what you have read? See anything incorrect? Please comment below and thanks for reading!!!

Explore the official MySQL 8.0 Online Manual for more information.

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Josh Otwell has a passion to study and grow as a SQL Developer and blogger. Other favorite activities find him with his nose buried in a good book, article, or the Linux command line. Among those, he shares a love of tabletop RPG games, reading fantasy novels, and spending time with his wife and two daughters.

Disclaimer: The examples presented in this post are hypothetical ideas of how to achieve similar types of results. They are not the utmost best solution(s). The majority, if not all, of the examples provided, is performed on a personal development/learning workstation-environment and should not be considered production quality or ready. Your particular goals and needs may vary. Use those practices that best benefit your needs and goals. Opinions are my own.