A Fine Slice Of SQL Server
Jameson Marriott fixes a spacing issue:
I recently noticed that ggplot2 spaces date axes literally even when grouped by month. I’ve been using ggplot2 extensively for years and I don’t remember noticing before, so this is not really a big deal, but now that I know it bugs me a lot. Take a look below.
I don’t think I had noticed this before either, though now that Jameson has pointed it out, it certainly is annoying. H/T R-Bloggers.
Leave a CommentThomas Sobolik and Leopold Boudard talk model drift:
Regardless of how much effort teams put into developing, training, and evaluating ML models before they deploy, their functionality inevitably degrades over time due to several factors. Unlike with conventional applications, even subtle trends in the production environment a model operates in can radically alter its behavior. This is especially true of more advanced models that use deep learning and other non-deterministic techniques. It’s not enough to track the health and throughput of your deployed ML service alone. In order to maintain the accuracy and effectiveness of your model, you need to continuously evaluate its performance and identify regressions so that you can retrain, fine-tune, and redeploy at an optimal cadence.
In this post, we’ll discuss key metrics and strategies for monitoring the functional performance of your ML models in production […]
Click through for the article. There’s a Datadog pitch at the end, but the info is useful regardless of which tool you’re using for monitoring.
Leave a CommentNicky van Vroenhoven shares a public service announcement:
In case you missed the official blog post 2 months ago, I suggest you read my blog post 🙂
Or if you want you can refer to the official blog here: Announcing the retirement of legacy Power BI Apps (pre-audiences).
Already on March 6, 2023(!), Power BI apps with multiple audiences went Generally Available.
Read on for more information, with the note that these things will disappear soon—May 1, 2004 is the date of retirement.
Leave a CommentVlad Drumea doesn’t need no steenkin’ transaction log backups:
This brief post contains a script that can help switch a whole SQL Server instance, model and all user databases, to SIMPLE recovery.
The script is useful in case of dev/test/QA/UAT instances that have been left by accident to use the default FULL recovery model, yet do not have or need transaction log backups.
Read on for the script. It also shrinks the transaction log file after the switch-over.
Leave a CommentAfter a lengthy period in Public Preview it seems, the boffins at Microsoft have finally pushed Elastic Jobs for SQL Azure DB to general availability. Hooray!
But what are Elastic Jobs? And why would I want to use them in SQL Azure DB?
That’s one of the things you’ll learn in this post.
Leave a CommentPavel Borisov explains the importance of vacuuming your tables:
By default, all table data in Postgres are physically stored using the “heap” method. So every database is a set of 1Gb files (”segments”) and each file is logically split into 8Kb pages. Actual table rows are put into any page with enough free space.
When the row data is updated, a new version of a whole row is constructed and written (to any free space). The old one remains because, at the time of the update, the transaction is not completed and can be rolled back in the future. When the transaction is completed we’ll have two or several versions of the same row in the table. Cleaning old ones is by an asynchronous process called vacuum (and autovacuum).
Read on for more information about how this works and what you can (or should) do to help it along.
Leave a CommentSteven Sanderson performs feature selection:
As an R programmer, one of the fundamental tasks you’ll encounter is manipulating data frames. Whether you’re cleaning messy data or preparing it for analysis, knowing how to drop unnecessary columns is a valuable skill. In this guide, we’ll walk through the process of dropping columns from data frames in R, using simple examples to demystify the process.
Read on for three ways of doing this.
Leave a CommentMike Robbins shows off one feature of gh cli:
Checking out someone else’s pull request (PR) on GitHub is essential in collaborative software development, enabling thorough code reviews, local testing, and detailed feedback. This process allows developers to ensure the quality and functionality of the code before integration, identify and resolve potential conflicts, and maintain consistency across the project. By reviewing changes locally, team members can collaborate more effectively, offering insights and improvements that enhance the overall quality of the project. Additionally, local reviews support security audits and performance evaluations, ensuring that the code is not only functional but also optimized and secure.
I don’t use gh cli as much as I should (in part because 95+ percent of the time, I’m committing into one-man repos and use GitHub Desktop), but every time I do use it, I remember that it’s a nice CLI.
Leave a CommentDavid Seis shares tips from an upcoming talk:
PowerShell is an essential tool for SQL Server database administrators looking to streamline their workflow and automate repetitive tasks. When it comes to troubleshooting your SQL Server instances, PowerShell is an essential tool for the DBA toolbox.
As a versatile scripting language and command-line shell, PowerShell enables seamless integration of commands, arguments, variables, and modules with an interface and logic that SQL users would find pleasantly familiar. This blog post will guide you through the basics of PowerShell, demonstrate how to implement simple automation for routine database tasks, and explore advanced automation strategies to optimize your database management.
The post starts as a basic primer on Powershell but also includes plenty of notes on good ways to make use of the language as a DBA.
Leave a CommentErik Darling has Blondie stuck in my head:
The OR operator is a perfectly valid one to use in SQL statements. If you use an IN clause, there’s a reasonable chance that the optimizer will convert it to a series of OR statements.
For example,
IN(1, 2, 3)could end up being= 1 OR = 2 OR = 3without you doing a darn thing. Optimizers are funny like that. Funny little bunnies.The problem generally isn’t when asking for IN or OR for a single column, with a list of literal values, the problem is usually when you:
- Use OR across multiple where clause columns
- Use OR in a join clause of any variety
- Use OR to handle NULL parameters or variables
This is an excellent, detailed article and well worth the read.
Leave a Comment