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Curated SQL Posts

Detecting Schema and Data Drift via SSDT

Andy Brownsword goes back to SQL Server Data Tools:

Schema drift is an inevitable part of environments where database changes are applied manually. Sometimes it’s dev-ing in production, other times it’s lax change control. Either way you’ve got a problem, and SSDT comparisons may be the solution.

In this post I want to look at how using the Schema Compare and Data Compare features of SSDT can compare different environments to detect movements in schema and core data. The key points are consistency and specificity

The engine that the Visual Studio extension uses for schema and data comparisons is pretty solid, though my recollection was that it was difficult to script these comparisons or make them work across a number of databases that should be equivalent. Back in the day, we ended up purchasing Redgate tooling for that reason, because it had an API for its schema and data comparison features. But if you’re doing a one-off comparison, the free version built into Visual Studio is pretty good.

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Index Rebuild Completion Percentages in SQL Server

Andrea Allred goes searching for the truth:

I truly don’t know when it happened, but over the last while I have noticed that the percentage complete on indexes has disappeared when I run sp_whoisactive. It makes me so sad! I used that functionality often to track how things were progressing in my databases. At first I thought it was a version thing and it would come back, then I wondered if it was only when I use “ONLINE = ON”, but I am seeing it blank more and more. It has left me feeling like I am missing something and today, I finally did the digging to learn how to get that visibility back.

Click through to see how.

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Settings and Configurations to Avoid in SQL Server

Jeff Iannucci has a list:

SQL Server has quite a few instance and database configuration options, which is great if you need to make changes for different business workloads. But some of these configurations can do more harm than good, especially with modern version of the product.

As a consultant, I’ve had the opportunity to work with many clients who have a diverse range of configurations for their instances. And every now and then I see some that have been configured for what I can only presume is a predilection for danger. I mean, little to no good can come of them.

So today I wanted to share with you a few that I have seen used or changed, and to recommend to you with all the influence that I may have, that you DON’T TOUCH THEM – THEY’RE EVIL!

The contrarian in me wants to poke holes at some of these, though all of his database-level settings are defensible. On the instance level, I do have some gripes, specifically with fill factor (at least if you’re following Jeff Moden’s strategy). I thought about having a gripe around min server memory, but that’s reasonable—it’s max server memory that tends to be much more important to change.

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What Comes Next for SQL Server 2016

Debbi Lyons lays it out:

As of today, July 14, 2026, SQL Server 2016 has reached end of support.

For the past decade, SQL Server 2016 has helped organizations run mission-critical applications and support the data needs of their business. Whether it was end-to-end encryption with Always Encrypted or performance improvements with In-Memory OLTP, SQL Server 2016 was shaped by evolving data platform needs and what we heard directly from customers like you.

Last year, we shared guidance on how to prepare for this milestone: Protect and modernize SQL Server 2016 workloads with Microsoft. Now, after 10 years of powering innovation, the focus shifts to what comes next.

It basically comes down to “Pay Microsoft a lot more money for one-off security fixes or upgrade to a version that isn’t a decade old.”

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Replacing Item IDs and Connection Strings with Variable Libraries

Gilbert Quevauvilliers makes use of variable libraries in Microsoft Fabric:

In this blog post I’m going to show you how you can use variable libraries with connection strings as well as items.

This approach allows you to manage environment-specific configuration when deploying Fabric items across development, test, and production workspaces

If you’re looking to move your fabric capacities across workspaces or regions, you can do this quickly and easily without having to re-Plumb a lot of the work.

Click through for a working example.

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Subqueries in the SELECT Clause

Louis Davidson tries out a few query forms:

The post states that a query such as:

SELECT soh.SalesOrderID,(SELECT  C.AccountNumberFROM    Sales.Customer AS CWHERE   C.CustomerID = SOH.CustomerID)AS CustomerAccountNumberFROM   Sales.SalesOrderHeader SOH;

will, by definition, execute that subquery on the Customer object one time per row in the SalesOrderHeader table.

But is this true?

Click through as Louis tests a few variants of this using SQL Server.

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Ways to Find a Query Plan

Deborah Melkin has a list:

I’m very excited for this because I’ve wanted to put something together about this topic for a long time.

What inspired me is that I’ve really come to appreciate that there’s different pieces of information collected with the execution plan itself depending on where I get the plan from. Understanding what’s collected, where, and why can help make a difference when trying to troubleshoot and performance tune.

I get most of my query plans from a shady vendor with an unmarked van in a Walmart parking lot.

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Dealing with linger.ms in Apache Kafka

Jack Vanlightly covers a common performance optimization:

Recently I was curious to see if there was any general performance improvement since Kafka 3.X. So I ran a suite of benchmarks with Dimster against 3.7.2 and 4.3.0. I saw two common patterns:

Those two patterns involved higher latency for the newer version of Kafka, but better scale. Click through to understand what changed between these two versions that had such a big impact.

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Applying Different Formatting Rules at Levels of a Hierarchy

Marco Russo and Alberto Ferrari format things differently:

A challenging requirement in Power BI reports is that of applying different formatting rules based on the level of aggregation. At the year level, the background shade may reflect each year’s share of the grand total. At the quarter level, a status color may indicate whether the quarter is above or below the average. At the month level, the color may flag exceptional values, like months that contribute more than a defined threshold to their year. Each level has its own logic; what the conditional expression of the measure needs to know is which level the current cell belongs to.

Read on to see how you can pull this off.

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Bad Query Signals

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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