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Category: T-SQL Tuesday

Bad Query Signals

Published 2026-07-14 by Kevin Feasel

Mala Mahadevan takes advantage of an extra week:

I just managed to get a post in for this landmark T-SQL Tuesday, hosted by Brent Ozar. Brent was kind enough to keep the submission window open for two weeks instead of the usual one, and I was able to sneak a post in last – minute.

His invitation is to write about the things that immediately stand out as “bad signs” when reviewing a SQL query.

Click through for Mala’s list. It’s a good list. While some items Mala calls out are defensible and quite reasonable, there are some of them (such as a LEFT OUTER JOIN whose columns show up in the WHERE clause for filtering) that are simply not.

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Two Pain Points in SQL Server Code

Published 2026-07-10 by Kevin Feasel

Steve Jones digs up a pair:

There are two things that immediately stand out to me when I see a query and create concern.

  1. cross joins
  2. functions in the where/on clause

While there are other things I might see, these two stand out and usually I can guess there will be issues.

Steve specifically calls out ANSI-89 style joins, which are awful. Before continuing, I agree with Steve’s points, but I figure I’d do a “yes, and” for this one.

When it comes to cross joins, there are specific circumstances in which I’ve written cross joins to great effect. The one that comes to mind most readily is when I need to create the raw data that will let you generate a matrix in a reporting tool.

Let’s say you want to know, for each sales territory and month, the number of new customers that month, the prior month, and the next month. The LAG() and LEAD() functions only work on rows, not intervals. Therefore, LAG() on the July row will show you the row prior to July. That might be June or it might be March, depending on how much data you have.

The solution, then, is to get the full set of months you care about from, say, a calendar table. Then, get the full set of sales territories. Cross join those two and you’ll have the entire range of relevant data. You can then left outer join to the actual data and fill in the gaps.

I have an example of this as a demo script on my Analyzing Business Data with T-SQL talk.

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Red Flags in Query Design

Published 2026-07-09 by Kevin Feasel

Thomas Williams has a list:

Nowadays I look after 3rd-party databases more than internally-developed ones, so I accept there’s a whole lot of ex-best practices, vendor preferences, and possibly shortcuts in queries I might come across – whether it’s a poorly-performing query, a blocker, or an error.

(Although, when I developed software more frequently, I was guilty of all the gripes below. My start in SQL, last century, was poring over a big yellow “For Dummies” book. I was the dummy.)

Click through for the list. I particularly hate tibbling, a rather derisive term for the malformed version of Hungarian notation. This would just lead me down a rant about how systems Hungarian notation was a mess, whereas apps Hungarian notation can be useful in certain circumstances. Tibbling provides no semantically valuable information, which is why I dislike it so much.

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T-SQL Code Smells

Published 2026-07-09 by Kevin Feasel

Rob Farley has a few:

I feel like I should preface this with a disclaimer. I added “potentially-” to the title, because there are many queries that might seem bad but can actually perform just fine. There are queries that on the surface can be great, but are nasty without a particular index, and there are queries that make me cringe a little when looking at them, but are actually okay. Brent Ozar is asking about signs of bad code for this month’s T-SQL Tuesday (the 200th – and I have a response for all 200 if you look back through my history of posts), and he wants us to write this for 2004 Brent, rather than 2026 Brent.

Click through for what Rob has come up with. I agree with all of Rob’s examples and do appreciate his usage of the APPLY operator as a way of solving one common problem.

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Traits of Sketchy Queries

Published 2026-07-09 by Kevin Feasel

Louis Davidson has a list of red flags in code:

I still feel like garbage, so I decided just a simple list would do. I will also preface this by saying each item could include “without a coherent comment.”

Everything on this list fills me with dread unless I read someone say: “Such and such was needed because the optimizer wouldn’t….” and then I at least know why they believed needed it.

Click through for Louis’s list. Most of these aren’t bad things per se, but they do serve as signs of a potential deeper issue.

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The Never-Ending Query

Published 2026-07-09 by Kevin Feasel

Andy Yun doesn’t like it:

You know THE ONE I’m talking about… it has numerous sub-queries and CTEs… JOIN after JOIN after JOIN… predicates within predicates. Or maybe it’s just an obscene MERGE statement. 

These are particularly painful to deal with because it’s hard to test the pieces in isolation and ensure that an issue earlier in the process doesn’t bite you later.

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When All Joins are Left

Published 2026-07-08 by Kevin Feasel

Hugo Kornelis gives an example of a red flag:

This anniversary edition is hosted by Brent Ozar. And his chose topic is: query red flags. Things that make you groan when you open a query and see them in the code. I’m sure there will be a ton of posts, because there are so many. I myself could probably fill a book with things I consider a red flag (and someone else would then point out that my queries have things that they consider red flags, but that is another discussion).

But let’s focus on just one thing in this post.

Hugo selects the case when all query joins are LEFT OUTER joins. Especially when the logic of the query mandates INNER joins.

Meanwhile, if all of your query joins are RIGHT OUTER joins, you’re just chaotic evil.

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Red Flags in Database Code

Published 2026-07-08 by Kevin Feasel

Tom Zika has a list and starts with AI-generated code:

This one didn’t exist three years ago. Now it’s the first thing I look for.

To be clear, I’m not anti-AI. If the AI wrote clean code, I probably wouldn’t even notice. The red flag isn’t that AI generated it – it’s the patterns that give it away. I recently saw a real case where someone needed to update a set of values. Simple enough, right? Here’s what the AI-generated solution did:

Click through for a laugh, as well as several other red flags.

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Starting Points for Query Tuning

Published 2026-07-08 by Kevin Feasel

Deborah Melkin shares some tips:

This one is really timely for me as I just started a new job. Performance tuning was part of the interview process so I’m really excited to dive back into doing more of that day-to-day. In fact, I just got added to the email reports with the top SQL results for the worst performers. Here’s some of what I’ll start looking at in that list and why:

Click through for Deborah’s red flag list. Of note, a red flag is not necessarily a bad thing. But it does merit further inspection and comment. For example, there may be specific instances in which join hints are necessary—you know you’re joining from a very small filtered subset to grab a tiny percentage of a bigger table (and you have an appropriate index on said bigger table), and so you slap on a LOOP join hint because the optimizer keeps trying to sort and merge join. But it’s worth explaining why and figuring out if there’s a better way, especially considering the consequences of slapping on that join hint.

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