A Fine Slice Of SQL Server
David Smith notes important changes in R 4.0.2:
R 4.0.2 is now available for download for Windows, Mac and Linux platforms. This update addresses a few minor bugs included in the R 4.0.0 release, and also a significant bug introduced in R 4.0.1 on the Windows platform.
Read on for the rest of David’s report.
Comments closedPhil Seamark continues a discussion on single-column fusion:
You may notice the [Package – Bag] measure uses the * (multiplication) operator in line 4 between a measure and what looks like a column filter.
The [base measure] performs a simple COUNTROWS aggregation and returns an INTEGER. This side of the equation makes sense, so let’s see what is going on with the DAX on the right-hand side of the * operator? The filter statement is encompassed with parenthesis, which automatically converts the expression to a TRUE/FALSE boolean value – which is then implicitly converted to an INTEGER value of either 0 or 1. It can’t be anything else.
The result of this double conversion is that we end up with a INTEGER * INTEGER to produce the number we see in the visual.
Click through for plenty more where that came from.
Comments closedRandolph West finds a need and fills it:
Last year when Windows Server 2019 was released I wanted to see which versions of SQL Server I could run on it, testing more the unwritten backward compatibility promise Microsoft has maintained over the last 45 years, rather than what the documentation says.
Speaking of documentation, Glenn Berry has a nifty compatibility matrix to show what versions of SQL Server are supported on each version of Windows Server. For official purposes, this is the list you should refer to:
But I know you’re not here for supported versions, because this post is about what Randolph managed to get running on Windows Server 2019, which as you know is a 64-bit operating system.
SQL Server 6.5 surprised me. This idea also nets my most coveted category.
Comments closedI wrote some other posts on this topic in the past, you can find them here and here. In the first post I explain how to create “Time” dimension with time bands at minutes granularity. Then one of my customers required the “Time” dimension at seconds granularity which encouraged me to write the second blogpost. In the second blogpost though I didn’t do time bands, so here I am, writing the third post which is a variation of the second post supporting time bands of 5 min, 15 min, 30 min, 45 min and 60 min while the grain of the “Time” dimension is down to second. in this quick post I jump directly to the point and show you how to generate the “Time” dimension in three different ways, using T-SQL in SQL Server, using Power Query (M) and DAX. Here it is then:
Click through for the code, which includes several sample bands (e.g., 5 minutes, 15 minutes) that you can also control.
Comments closedGlenn Berry explains how to get yourself out of a pickle in Standard Edition:
Ok, that is bad enough, but it gets worse. Unless you fix it, SQL Server 2019 Standard Edition will use 32 logical cores on NUMA node 0, but only 16 logical cores on NUMA node 1. This can have a significant negative effect on performance. What you want is for SQL Server to use 24 logical cores on each NUMA node.
Glenn then explains how to pull this off.
Comments closedKamil Nowinski shares how to deploy Azure Data Factory flows via Azure DevOps:
Struggling with #ADF deployment? adf_publish branch doesn’t suit your purposes? Don’t have skills with PowerShell? I have good news for you. There is a new tool in the market. It’s a task for Azure DevOps Release Pipeline to deploy whole ADF from code (JSON files) to ADF instance in Azure. Behind the scenes, it runs the PowerShell module which does all job for you.
Sounds unbelievable? But it’s real! Check it out for yourself.
Click through for a video.
Comments closedI’ve heard many times incorrectly over the years that CTEs somehow materialize data.
But a new one to me was that CTEs execute procedurally, and you could use that to influence plan shapes by always doing certain things first.
Unfortunately, that’s not true of them either, even when you use TOP.
Read the whole thing. Though I do chain common table expressions for readability’s sake, but that’s usually because I’m performing a series of repetitive calculations that I can’t simplify via APPLY.
Lionel Hertzog continues a series on spatial regression:
INLA is a package that allows to fit a broad range of model, it uses Laplace approximation to fit Bayesian models much, much faster than algorithms such as MCMC. INLA allows for fitting geostatistical models via stochastic partial differential equation (SPDE), a good place for more background informations on this are these two gitbooks: spde-gitbook and inla-gitbook.
This is not the gentlest introduction, so if you’re new to the concept go back and read part 1.
Comments closedDavid Stelfox takes us through some thoughts on provisioning instances of Snowflake:
For this example, I’ve chosen an open dataset of 2017 taxi rides in New York City. There are a few options for interacting with Snowflake: a dialog box approach in the web-based GUI, using SQL statements in the Worksheets tab in the GUI or a CLI called SnowSQL. For this example, I used SQL statements as I find them easier to follow what’s happening. Once you have set up your account (or trial) and logged in, you need to create your first database.
Click through for some how-to as well as thoughts about cost and performance.
Comments closedJason Hall takes a look at how much tempdb space Accelerated Database Recovery might use:
You might have heard me talk about tempdb parasites in the past, or maybe you’ve read my blog post on the same topic, “Be Mindful of SQL Server Tempdb Use (aka Tempdb Parasites!).” I know that at least one person did, because they recently asked a great question.
In that blog post, I reviewed how triggers use the version store in tempdb for access to the “special” trigger tables we can use from within the trigger code to access the previous and new versions of data being modified. One person on Twitter was wondering if that is still the case for triggers on databases using Accelerated Database Recovery (ADR) in SQL Server 2019. I really wasn’t sure, so I decided to find out.
Click through for the answer.
Comments closed