A Fine Slice Of SQL Server
Sean Gallardy has a video for us:
The first video olved stery! In this one we look at an FCI node that will not come online after patching.
Click through for that video, which is a great learning instrument for in-depth analysis of a SQL Server problem.
Comments closedHugo Gruson draws some comparisons:
The debate regarding the use of
forloops versus theapply()function family (apply(),lapply(),vapply(), etc., along with their purrr counterparts:map(),map2(),map_lgl(),map_chr(), etc.), has been a longstanding one in the R community.While you may occasionally hear that
forloops are slower, this notion has already been debunked in other posts. When utilized correctly, aforloop can achieve performance on par withapply()functions.However, there are still lesser-known reasons to prefer
apply()functions overforloops, which we will explore in this post.
Read on for an important caveat, and then several reasons to prefer apply() (or purrr’s counterparts). H/T R-Bloggers.
Sebastian Sauer draws a graph:
Let’s visualize the quantiles of a normal distribution.
Not much to snag in the graf, as Sebastian goes straight to code. Read on to see how to set this up in R, how to draw randomized data points from a normal distribution, and then how to plot and animate the solution.
Comments closedMarco Russo and Alberto Ferrari show off their intelligence:
Time intelligence functions such as month-to-date (MTD), quarter-to-date (QTD), and year-to-date (YTD) in DAX operate relative to the current filter context. Their outcome depends on the filter applied, making them both adaptable for various periods and useful for comparisons. But, if you wish to showcase the most recent data – for the “current” period – there is a complication: without the proper filter, you may not get the data you aim for.
Read on to see what they mean and how you can avoid this issue.
Comments closedSo what’s up this time. Our client has moved to Azure in classic lift and shift scenario. Well, almost. They’ve deployed new VM’s and installed SQL Server 2019 Standard in nice DTAP setting. The VM’s are standard E16-4as-v4 SKU. 4 vcpus and 128 GB memory. The disks are Premium SSD LRS ones with 2300 Max IOPS.
Their on-premises environment was a SQL Server 2016 standard edition running on a virtualisation layer with 128 GB of memory and 8 cores.
In both cases there are 2 numa nodes dividing the amount of cores between them.
Read on to learn more about the problem and what Reitse & co did to resolve it. Also check out the comments—Daniel Hutmacher, in particular, I think has the reason nailed.
Comments closedSteve Jones links to Steve Jones talking about Steve Jones:
I had written about a FK in a CREATE TABLE statement recently, but the second half of this was that after the original question, the person asked if this would also work for a self-referencing FK. It does, and I wrote this to show that.
Click through for an example of how to do this.
Comments closedRod Edwards shares some hard-earned guidance:
Some organisations are more strict on security than others. Thats just the way of the world, whether it be local policy, industry policy, paranoia or worryingly…just not considering it a priority.
This is why Microsoft have to offer BYOK, no, not the famous Icelandic singer from the 90’s and beyond either. I’m (very) tenuously referring to “Bring Your Own Key” which allows customers to let the encryption key to be handled by Microsoft for their encryption purposes, but create and use one of their own.
Read on to learn more about how it works, as well as a couple of important warnings you should keep in mind.
Comments closedBryan Shalloway explains how odds and probabilities intertwine:
However human understanding of odds predates our formal understanding of probability. You can find references to odds dating back to Shakespeare:
Knew that we ventured on such dangerous seas
That if we wrought out life ’twas ten to one;
– Shakespeare’s Henry IV, Part II, 1597Yet, in most common settings, modern society has largely supplanted odds for probabilities. You can imagine if Shakespeare were writing today the line might end “’twas ten out of eleven.”
Read the whole thing.
Comments closedLouis Davidson shares some notes:
As I have dealt with other platforms, PostgreSQL has stood out to me as the platform I am most interested in because it feels like the one that is most competitive with SQL Server’s platform (Oracle is out there too, as is MySQL, and many others, but PostgreSQL feels like the balance of affordability and features that it has a similar feel enough to get started.)
There are a few high-level differences that can be confusing. A cluster is really just a server (or in SQL Server, an instance). Second, the way you execute a batch of code is very different, and sometimes this is based on the tool you are using. As you dig into how PostgreSQL works, some things will feel really normal, and some stuff will be very different from the other servers you have used.
Read on for the first post in the series, covering setup and connection.
Comments closedSteven Sanderson tests a distribution fit:
There are two main ways to fit a gamma distribution to a dataset in R:
- Maximum likelihood estimation (MLE): This method estimates the parameters of the gamma distribution that are most likely to have produced the observed data.
- Method of moments: This method estimates the parameters of the gamma distribution by equating the sample mean and variance to the theoretical mean and variance of the gamma distribution.
Click through to see which technique Steven uses and an example of how it all works.
Comments closed