Press "Enter" to skip to content

Category: Indexing

Making Leading Wildcard Searches Faster

Published 2025-08-07 by Kevin Feasel

Brent Ozar flips everything around:

99.9% of you are never gonna need this.

But let’s say you need to run queries with leading (not trailing) wildcards, like this search for all the different national versions of the Encabulator, each of which has different prefixes depending on which government it’s being sold to:

This is indeed a pretty uncommon scenario. I’m pretty sure I’ve only ever needed to do this once. Well, twice, but in one case I couldn’t actually use the REVERSE() function because the column was itself an awful non-deterministic function and this solution wouldn’t work.

Leave a Comment

PostgreSQL and Covering Indexes

Published 2025-06-30 by Kevin Feasel

Kendra Little does a bit of index management:

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?

Read on to learn why.

Comments closed

Index Maintenance for Large Databases

Published 2025-06-27 by Kevin Feasel

Jon Russell shares some thoughts:

Most database administrators are comfortable with the daily tasks of backup, CHECKDB, index maintenance, and statistics updates. The available guidance for those topics is extensive. Much less has been written about caring for estates that contain hundreds of databases—or a single database large enough to strain conventional maintenance windows. This post will focus on options that help when individual tables or complete databases grow beyond the point where “standard” maintenance jobs finish in a reasonable time.

Click through for Jon’s advice. My big thing is to stop worrying and learn to love the bomb fragmentation. Index fragmentation was very important back in the days of spinning disk, where accessing pages took much longer if you needed to move the disk head. With NVMe storage, all-flash arrays, and even more prosaic solid state drives, random access is typically at least as fast as sequential access, so there’s no real benefit to having pages of data be contiguous.

Comments closed

Using Filtered Indexes in SQL Server

Published 2025-05-28 by Kevin Feasel

Stephen Planck explains the value (and limitations) of filtered indexes:

When a table holds millions of rows yet most queries touch only a small, well-defined subset, a traditional non-clustered index feels like using a searchlight to find something sitting under a desk lamp: the index still stores an entry for every row even though the workload rarely needs most of them. SQL Server’s answer is the filtered index—introduced in SQL Server 2008 and still under-used today—allowing you to index just the rows that match a predicate you supply in a WHERE clause.

I always thought I would get more value out of filtered indexes. Instead, they’re very useful for specific circumstances, but not the all-purpose performance dynamos you’d want them to be, particularly because of the limitations.

Comments closed

JSON Indexes in SQL Server 2025 CTP 2.0

Published 2025-05-20 by Kevin Feasel

Daniel Hutmacher gives it a try:

Starting today, the public preview of SQL Server 2025 is available to download!

One really interesting new feature that got my attention was the addition of JSON indexes. I’m a big fan of everything that makes working with JSON easier, since JSON blobs are so much easier to work with than table variables when you’re moving data from point A to point B. This is especially true when you’re working with complex, relational data.

Daniel lays out some of the limitations of JSON index creation and also some of the performance gains you might see from it. This will be most helpful in data engineering scenarios, shredding JSON from various services, but the normalization purist in me says that if you’re shredding JSON enough to need indexes, it’s probably time to normalize that data.

1 Comment

Thoughts on Index Rebuilds

Published 2025-05-19 by Kevin Feasel

Kevin Hill shares some thoughts:

Here’s the truth: if you’re doing this daily on indexes smaller than 10,000 pages, you might be chewing up CPU, bloating your logs, and annoying your users  for zero gain.

Let’s fix that.

I disagree with Kevin on index reorganization, in that I would never perform index reorgs—there’s no there there. Even so, I firmly agree with the thrust of Kevin’s argument and believe that, in the majority of cases, companies with DBAs (or people who have stumbled through maintenance plans before) are maintaining indexes too much rather than not enough.

Comments closed

Hash Indexes in MySQL

Published 2025-05-13 by Kevin Feasel

Lukas Vileikis explains how hash indexes work in MySQL:

In MySQL, hash indexes are indexes that are used in queries that use the equality operators like = or <=> (which is the MySQL NULL safe equality operator, equivalent to the SQL Standard IS NOT DISTINCT FROM). Hash indexes are not used in other situations, so they can be useful for things like random or generated PRIMARY KEY values where you are looking up single rows and not needing to order rows or searching for a range of values.

Just like in SQL Server hash indexes only work for in-memory tables, and some of the mechanisms look very similar.

Comments closed

SQL Server Performance Office Hours Episode 10

Published 2025-05-06 by Kevin Feasel

Erik Darling has some doozies today:

Many of our Tables have 15 plus guid s from other tables, but not declared as Foreign Key. Plus Foreigne Keys. When I add a Index on for every Foreign Key plus Indexes for declared foreign keys we end up with tables with 30 plus indexes for fks only. We don’t have write performance issues. would you index every fk for every possible join?

Click through for the answer to this and four other questions.

Comments closed