GROUP BY queries allow you to partition a table into groups based on the values of one or more columns. Its purpose is to let you easily retrieve aggregate results at the database level, and it is typically used in conjunction with SQL aggregate functions, such as COUNT(), MAX(), MIN(), SUM(), or AVG(). Particularly, read this real-world case article on how SQL aggregate functions to increase the performance of a backend.

The main problem with GROUP BY is that queries involving it are usually slow, especially when compared with WHERE-only queries. Luckily, by defining the right SQL index you can effortlessly make them lightning fast.

Let's now delve into the how.

The Perfect Index for a GROUP BY Query in 4 Steps

As described here, optimizing a GROUP BY query can be tricky and involves many operations and adjustments. This means that finding the best possible solution to make your queries more performant can easily become a grueling task. That being said, the simple procedure that follows should allow you to achieve remarkable results and be enough in most cases.

First, make sure to rewrite your query so that the columns used in the GROUP BY clause appears in your SELECT clause at the beginning and in the same order. Keep in mind that column order is critical when defining a SQL index.

Then, define an index involving the following columns as described in these instructions:

1. columns in the same order as they appear in the WHERE clause (if present)

2. remaining columns in the same order as they appear in the GROUP BY clause

3. remaining columns in the same order as they appear in the ORDER BY clause (if present)

4. remaining columns in the same order as they appear in the SELECT clause

This 4-step approach derives from this StackOverflow answer, and it has helped my team make GROUP BY queries up to 10x faster on several occasions.

Now, let's see how to define it through an example. Let's say you are dealing with the following GROUP BY MySQL query:

SELECT city, AVG(age) AS avg_age, school 
FROM fooStudent 
WHERE LENGTH(name) > 5
GROUP BY city, school

First, you have to rewrite your query as follows:

SELECT city, school, AVG(age) AS avg_age
FROM fooStudent 
WHERE LENGTH(name) > 5
GROUP BY city, school

Then, according to the 4 aforementioned rules, this is what your performance-improving index definition should look like:

CREATE INDEX fooStudent_1 ON fooStudent(name, city, school, age)

Et voilà! Your GROUP BY query will now be faster than ever.

Conclusion

GROUP BY is a powerful statement, but it tends to slow down queries. Over time, my team and I have used it many times and defined SQL indexes to avoid the performance issues introduced by the GROUP BY clause, especially when dealing with large tables. Specifically, a simple 4-step procedure is enough to define an efficient SQL index that will make your GROUP BY queries up to 10 times faster, and presenting it is what this article was about.

Thanks for reading! I hope that you found my story helpful.

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