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Day: August 30, 2024

Composite Indexes in MySQL

Published 2024-08-30 by Kevin Feasel

Lukas Vileikis needs more than one column:

Indexes in MySQL are one of the primary ways to enhance query performance and they are especially useful when the primary use case of our project refers to reading data stored in a database. We‘ve already told you about the nuanced world of indexes in MySQL – and there we‘ve mentioned that MySQL has multiple types of SQL indexes available for you to choose from.

The primary index type available within MySQL is the B-Tree index which we‘ve already covered in one of our previous articles. If you know your way around MySQL though, you will certainly be aware of other nuances of indexes, too – and one of those nuances has to do with the fact that B-Tree indexes can also consist of multiple columns (commonly referred to as composite indexes). In this example, we’re using MariaDB as our DBMS of choice. Percona Server for MySQL and MySQL Server will act identically.

Find the queries recreating the table structure and composite indexes in the appendix, and let’s get started.

Read on to see how composite indexes work in MySQL. On the whole, it’s quite similar to how they work in SQL Server, though it’s interesting to catch the differences at the edges.

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Computed Columns and Wide Index Updates

Published 2024-08-30 by Kevin Feasel

Paul White takes us through a performance scenario:

Update execution plans are not something the T-SQL statement writer has much control over. You can affect the data reading side of the plan with query rewrites and hints, but there’s not nearly as much tooling available to affect the writing side of the plan.

Update processing can be extremely complex and reading data-changing execution plans correctly can also be difficult. Many important details are hidden away in obscure and poorly documented properties, or simply not present at all.

In this X article, I want to you show a particularly bad update plan example. It has value in and of itself, but it will also give me a chance to describe some less well-known SQL Server details and behaviours.

Read on for the full story.

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Understanding the EXISTS Keyword in SQL

Published 2024-08-30 by Kevin Feasel

Eric Blinn probably exists:

I’ve seen the EXISTS keyword in Microsoft SQL Server T-SQL code and don’t understand it well. What does it do? How do I use it? Are there best practices around SQL EXISTS?

This SQL tutorial will explain what the keyword EXISTS does and show several different use cases.

Read on to see how you can use EXISTS and its complement, NOT EXISTS, in a variety of use cases. One important part of why EXISTS can be useful compared to other ways of writing a particular query is that the performance profile of an EXISTS clause is a semi-join: we proceed until we find the first result matching our clause. If that happens to be in the first row, we can stop there as we’ve fulfilled the requirement. By contrast, an alternative using IN or something else like using SELECT COUNT(*) would likely need to read more pages of data than EXISTS.

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Planning Statistics Updates

Published 2024-08-30 by Kevin Feasel

Andy Mallon makes the case:

Let’s talk about the trade-offs.

Auto-updated stats are triggered by queries needing to access a table with “stale” stats. (It doesn’t matter how we define stale, so lets not think about it.) With the exception of very small tables, auto-updated stats use a random small data sample of the table data; in contrast scheduled jobs that usually have a larger sample size defined—I always say “FULLSCAN if you can!”

Read on for Andy’s thesis.

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