intro
SQL aggregate functions allow developers to perform operations across entire columns. Here’s what they are, how they work, and how to tame them.
Functions are tools that are essential to many database administrators, developers, or even those taking their first steps on how to build applications. SQL functions don’t come alone — they have a lot of things you should consider, and SQL aggregate functions are no exception to the rule either.
With that being said, not all functions are built equal — aggregate functions in SQL allow developers to run operations by performing calculations on a set of values and after these calculations are performed, a singular value is returned. In this blog, we dig into what they can offer !
What Are SQL Aggregate Functions?
In the database world, SQL aggregate functions are just what they sound like — they are SQL functions that aggregate multiple values and return a singular value. In other words, SQL aggregate functions are functions that are used to let your database act on data in the form of a function and return the necessary results.
Popular Aggregate Functions in SQL
Here are some of the most common SQL aggregate functions you can encounter (the list is DBMS-agnostic): AVG(), COUNT(), MIN(), MAX(), and SUM().
Depending on who you ask, you may be told that there may also be other aggregate functions of interest, but the five functions (depicted above) is a good starting point. Here’s what they do:
Not rocket science, right? We think so too. However, for many applications, these 5 functions serve as the primary point of contact when running analytical queries because:
A few use cases utilizing these functions are depicted above, but I’m certain you can think of many more use cases that these functions would help complete.
Why so? That’s because SQL aggregate functions are simple but universal — these kinds of SQL functions don’t walk alone, but once they have a friend (your data) by their side, they help developers achieve numerous analytics-related goals if they’re used properly.
Properly Using SQL Aggregate Functions
Right, you got it — aggregate functions help you achieve analytics-related goals by working in conjunction with SQL queries. The question is how do you make these SQL functions work in conjunction with those queries?
Everything becomes more simple after you keep a couple of things in mind:
Example
Here’s an example of using an aggregate function in SQL with INTO OUTFILE:
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SELECT SUM(`column_name`) FROM `data_table` INTO OUTFILE '/tmp/data/data_table_output.csv' FIELDS TERMINATED BY '\t';
Nothing complex, right? Yet, this is where SQL aggregate functions depicted above can indeed shine the most. From the most trivial things like counting the number of rows in an InnoDB table using SUM():
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SELECT SUM(`id`) FROM `demo`
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INTO OUTFILE 'C:/wamp64/tmp/demo_table_output.csv' FIELDS TERMINATED BY '\t';
To more advanced use cases like counting the number of rows from the left side of a certain character (negative values mean the left side, positives go towards the right):
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SELECT
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SUBSTRING_INDEX(username, ' ', -1) AS substr, -- everything to the left of a space
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COUNT(id) -- number of rows
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FROM
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demo -- table name
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INTO
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OUTFILE 'C:/wamp64/tmp/demodata2.txt' LINES TERMINATED BY '\n';
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-- file name and determining how to terminate columns/lines
Once you get the gist of SQL aggregate functions, it starts to get fun. Very fun. You see, there are people building applications that do just that, and then there’s you doing the same thing with just the click of a button. Interesting, no?
Note: in some cases when using SQL aggregate functions, you can safely disregard the number of returned rows. Sometimes we purposefully set things up for our database to return few rows: that’s the row with a result set derived from the data we gave our database.
Beyond SQL Aggregate Functions
As powerful as aggregate functions may be, they’re not worth their salt if you don’t have any data for them to act on. And once you have a lot of data for them to act on, you have to manage it accordingly.
You have a lot of things to care about as-is: your server and its infrastructure, your database architecture, replication, tasks given by your manager/team lead, and so on. Oh, and aggregate functions too. All of these things affect your database, and once you hear fellow developers saying “Hmm, this query is slow. Wonder why”, it’s often too late to wonder.
That happens because no matter what kind of application your database might be supporting, your database will undergo incidents all the time: those incidents must be accounted for, and it’s hard to account for them without a reliable partner by your side.
Partners of this nature often come in the form of SQL clients such as DbVisualizer: you’ve seen an example of DbVisualizer writing data into text/excel files in this blog, but it can do much more than that, and with the recent updates to the tool it became further equipped to help you deal with your most precious data no matter what problems you may be facing.
Grab a free trial of DbVisualizer for 21 days, take care of your SQL aggregate functions and other intricacies surrounding your database, make sure to read books to educate yourself on how to work with databases both now and in the future, and until next time.
Summary
SQL aggregate functions often refer to 5 functions — AVG(), COUNT(), MIN(), MAX(), and SUM() — that let us act on data to influence our end goal in data analytics. They’re far from a revolution, but at the same time, data analytics wouldn’t be the same without them. Sure, there are alternatives to these functions (SQL clients like DbVisualizer can provide you with the same results after just a couple of clicks), but these alternatives take time to get acquainted with.
Regardless of what path you choose, we hope that this blog helped you to achieve your database goals — stay humble, and until next time!
FAQ
What are SQL aggregate functions?
SQL aggregate functions refer to 5 functions — AVG(), COUNT(), MIN(), MAX(), and SUM(). These functions compute a result set from a set of multiple values.
Will a query using SQL aggregate functions be slower than usual?
Not necessarily. Queries using SQL aggregate functions may be slower than usual if they act on tens or hundreds of millions of rows (or beyond that), but here, a factor that you don’t have to wait until your database returns results on a screen may be at play. Act upon your data with aggregate functions in conjunction with INTO OUTFILE or other clauses, and you will be good to go!
Where can I learn more about databases or the SQL language?
Consider attending conferences and workshops, watching YouTube videos, reading blogs, or, if you have no time for either of those, grab a book on a database topic and read up now. There are no wrong paths here — there’s just the path you choose.
