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Author: Kevin Feasel

Preventing Accidental Azure Changes with Resource Locks

Published 2023-06-28 by Kevin Feasel

Khushbu Ghandi puts a padlock on it:

Resource locks are just locks that we can associate to different scopes in Azure allowing us to override permissions at that resource scope and down. When we talk about the scope of the resource lock, we can lock subscriptions, we can lock resource groups and individual resources, and the lock restrictions that we have based off the type of lock we select will apply to all users and roles that have access to that resource. Also, it’s worth noting that locks are inherited by child resources. So, if we apply a lock on a subscription, it is inherited by all the resource groups that have been created under that subscription along with the resources that will be created under the resource groups.

Resource locks come with their own considerations, and Khushbu dives into those. This is a concept I like more in theory than in practice, save for pretty stable systems where you keep things running 24/7.

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When Statistics Updates Happen

Published 2023-06-28 by Kevin Feasel

Matthew McGiffen gives us the numbers:

SQL Server has had the ability to automatically update statistics since version 7.0. Nonetheless for a long part of my career working with SQL Server, whenever a performance issue raised its head everyone’s knee-jerk response would be “Update Statistics!” In most cases though the people shouting that didn’t really understand what the “Statistics” were, or what mechanisms might already be in place for keeping them up to date.

Of course SQL Server isn’t perfect and sometimes it is helpful for human intelligence to intervene. But to provide intelligent intervention one has to understand how things work.

Read on to learn what triggers automatic stats updates in various versions of SQL Server.

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Context and Auditors

Published 2023-06-28 by Kevin Feasel

Martin Schoombee shares a learning experience:

When you’re young and inexperienced you may have the determination to succeed (read: youthful exuberance), but the lack of experience (or understanding of the context) may get you in a lot of trouble because you may see something as black or white when in reality it’s a shade of grey.

This story is how my inexperience (almost) got me into a whole heap of trouble, and how it defined the rest of my career.

Read on for Martin’s story. Some advice I received early in my career is, give the auditors exactly what they ask for, no more and no less. Don’t assume they have detailed technical expertise—some do, but many don’t. And don’t assume they have the full story—they have what you’re saying and (typically) a built-in assumption that you’re soft-shoeing them.

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Stopping a Resumable Index

Published 2023-06-28 by Kevin Feasel

Andrea Allred doesn’t want that index to resume:

It had been building for about 10 minutes, when I realized I had the fields in the wrong order. No big deal, I just canceled it, corrected it and tried to start it again. “Tried” was the keyword here. I got an error because I had set RESUMABLE = ON but hadn’t properly cleared it out of the system. I started to furiously dig through articles about how to clear out an index that was resumable but had been canceled.

Read on to see what Andrea found.

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Detecting AI-Generated Profile Photos

Published 2023-06-27 by Kevin Feasel

Shivansh Mundra, et al, report on some research:

With the rise of AI-generated synthetic media and text-to-image generated media, fake profiles have grown more sophisticated. And we’ve found that most members are generally unable to visually distinguish real from synthetically-generated faces, and future iterations of synthetic media are likely to contain fewer obvious artifacts, which might show up as slightly distorted facial features. To protect members from inauthentic interactions online, it is important that the forensic community develop reliable techniques to distinguish real from synthetic faces that can operate on large networks with hundreds of millions of daily users, like LinkedIn. 

There are some interesting findings here.

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Bootstrap Resampling in R

Published 2023-06-27 by Kevin Feasel

Steven Sanderson makes a list and checks it twice (or n number of times with replacement):

Bootstrap resampling is a powerful technique used in statistics and data analysis to estimate the uncertainty of a statistic by repeatedly sampling from the original data. In R, we can easily implement a bootstrap function using the lapply, rep, and sample functions. In this blog post, we will explore how to write a bootstrap function in R and provide an example using the “mpg” column from the popular “mtcars” dataset.

Read on for the process.

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Cache Recommendations for Azure Data Explorer

Published 2023-06-27 by Kevin Feasel

Guy Reginiano notes an update:

A new generation of cache recommendations for Azure Data Explorer is now available in the Azure portal! 
This update introduces significant improvements, including enhanced logic, additional statistics for end users, an improved user interface, and a streamlined process for reviewing and applying recommendations. In this blog post, we will explore the new features and benefits offered by this latest update. 

Read on to see where you can find these cache recommendations, as well as the types of recommendations you’re liable to receive.

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Using Subqueries in a SELECT Statement

Published 2023-06-27 by Kevin Feasel

Greg Larsen builds a subquery:

Did you know you can include a SELECT statement within another SELECT statement? When a SELECT statement is embedded within another statement it is known as a subquery. There are two types of subqueries: basic subquery and correlated subquery.

In this article I will be discussing both types of subqueries and will be providing examples of how to use a subquery in different places within in a SELECT statement.

Greg has a good write-up on the topic of subqueries and does well to separate correlated from non-correlated subqueries.. And if you want to learn more about those, as well as common table expressions, I put out a video on the topic just last week.

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Indexing Multiple Columns in Oracle with DBMS_SEARCH

Published 2023-06-27 by Kevin Feasel

Brendan Tierney rounds up the usual suspects:

This type of index is a little different to your traditional index. With DBMS_SEARCH we can create an index across multiple schema objects using just a single index. This gives us greater indexing capabilities for scenarios where we need to search data across multiple objects. You can create a ubiquitous search index on multiple columns of a table or multiple columns from different tables in a given schema. All done using one index, rather than having to use multiples. Because of this wider search capability, you will see this (DBMS_SEARCH) being referred to as a Ubiquitous Search Index. A ubiquitous search index is a JSON search index and can be used for full-text and range-based searches.

This is an interesting approach to the problem, though as I think about it, it makes me wonder, if you’re constantly searching in A+B+C+D, is that really four separate attributes or has something gone wrong in the design? It’s early enough in the morning for me that I’m willing to accede to there being use cases in a well-designed database.

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