Dear Postgres, Why won’t you use my covering index?

Lately I’ve been learning to tune queries running against PostgreSQL, and it’s pretty delightful. One fun question that I worked through struck me something that most Postgres users probably encounter one way or another: sometimes you may create the perfect index that covers a given query, but the query planner will choose to ignore it and scan the base table.

Why in the world would it do that?

Forcing plans with Query Store can be a powerful tool—until it mysteriously fails. In real production systems, plan forcing sometimes just… doesn’t work. One common culprit is the cryptic OPTIMIZATION_REPLAY_FAILED error.

If you’re hitting OPTIMIZATION_REPLAY_FAILED, try re-forcing the plan using @disable_optimized_plan_forcing=1.

Statistics in SQL Server are simple in theory: they help the optimizer estimate how many rows a query might return. In practice? Things get weird fast. Especially when you start filtering on multiple columns, or wondering why the optimizer thinks millions of rows are coming back when you know it’s more like a few hundred thousand. In this post, I’ll walk through examples using single-column, multi-column, and filtered statistics—and show where estimates go off the rails, when they get back on track, and why that doesn’t always mean you need to update everything with FULLSCAN.

The biggest lesson I’ve learned from helping folks manage data in Azure is this: if you’ve got a truly terrible problem you’d rather people didn’t notice, a great way to hide it is by educating your support staff and users about something bad but not AS terrible— something with a small mitigation—and constantly refocusing them on that.

The user base— and even your own support staff— will think that anyone who talks about the bigger issue just doesn’t understand how to fix the “known” problem.

This is the story of Azure General Purpose storage for Azure SQL Managed Instance and Azure SQL Database.

Joins are essential. The SQL Corgs introduce you to INNER joins in this animated short.

Why do we “normalize” relational databases, and what are the basics? Awkward Unicorn explains, with a little help from their friends.

Freyja the corgi shares her tips for learning SQL: SELECT, FROM, and WHERE.

Now that I’m getting the hang of this, I think I’m going to do a whole series of shorts on SQL syntax essentials, plus tips and tricks!

I learned to make short form videos with my drawings this week, and, well… things are about to get weirder.