Typically, the advice on fill factor is “if it ain’t broke, don’t fix it”. But occasionally, you’ll find a database or even a server with a crazy default setting that just fills your disk and buffer pool without any real benefit. Here’s a nifty script to rebuild any tables and indexes to a fill factor of 100%.
Regular readers of my blog will know that I occasionally share some useful scripts on my Downloads page. And even though I update some of those scripts regularly when new versions of SQL Server come out, or if I run into a bug feature, there really hasn’t been a practical way for readers to subscribe to those updates or to contribute with good ideas.
I recently attended the annual PASS Summit conference in Seattle, and as part of my personal goal to try to learn new (and scary) things, I took a precon on working with Git.
So as of now, a bunch of downloads are available on GitHub (which is, really, a much better place to host scripts than a shared Dropbox link). You can download them as usual, and if you want, you can add your improvements and send me a pull request. I know I’ve received a ton of good ideas and suggestions over the years, but more often than not, I haven’t had the proper environment to test those changes in, or I just haven’t had the time to dig into my old code.
But now you can:
I’m the type of developer that invents wheels. Yes, every wheel I design is unique in its own way, and hand-crafted for a specific purpose. And so it has also been with calendar dimensions (typically when I do data warehousing work).
This got me thinking – why not design the mother of all calendar dimensions? One that includes every conceivable calendar and property that I and others could use and re-use. One that could save me a ton of coding, and lessen the burden of having to validate it each and every time?
And that’s how I got started designing my one calendar script to rule the all.
Everyone has a script, a hack or a checklist they can’t function without. In this edition of T-SQL Tuesday, Bert Wagner challenged us to write about our favorite scripts. This is my take.
With good naming and datatyping conventions, an automated script can help you with the process of creating foreign key constraints across your database, or actually, suggest table relations where you’ve forgotten to implement them.
Probably one of the most common challenges I see when I do ETL and business intelligence work is analyzing a table (or a file) for possible primary keys. And while a bit of domain knowledge, along with a quick eye and some experience will get you really far, sometimes you may need some computational help just to be sure.
Here are some handy tricks to get you started!
I frequently need to look up object definitions when I’m developing or query tuning. You could use Object Explorer in SSMS, but that takes a lot of time and clicking. Then there’s the Alt+F1 shortcut, which will trigger the sp_help stored procedure. That however, comes with a lot of annoying built-in limitations, so a few years ago I started building and maintaining a “better Alt+F1” of sorts.
I decided to call it “Ctrl+3“. But I suppose you could assign it to any keyboard shortcut you want.
AlwaysOn Availability Groups are a reasonably simple way to set up disaster recovery (DR) for your SQL Server environment, and with fairly little effort, you can get a bit of high availability (HA) from it as well. But there are a few gotchas, the most obvious of them being that Availability Groups only synchronize specific user-databases, not the entire server setup.
Things that are not included in AGs include logins, SQL Server Agent jobs, SSIS packages stored in SQL Server, linked servers and server settings. You could sync these manually (as is often the case), but wouldn’t you just love to have an automated process do all this for you?
This is the first post in a series on synchronizing stuff between Availability Groups, and in this installment, we’ll look at logins. For the sake of simplicity, I’ll assume that you have a primary replica with a single AG and any number of secondary replicas. The logic holds true if you have multiple AGs, it just gets trickier.
Whenever you’re building a data warehouse or similar solution, you’ll probably want to have a “calendar dimension”, a table that contains all days in a range of years. A challenge with this type of table is getting all the public holidays right, which could be particularly important if your business depends on this, like financial markets or logistics.
We’ve previously looked at how to calculate recurring public holidays. However, calculating the date of easter sunday is not as simple as you might think, because it involves calculations of lunar phases. This short post contains a T-SQL translation of the popularly used Meeus-Jones-Butcher formula.