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Author: Kevin Feasel

Deploying SQL Server with Availability Groups via HPE Serviceguard for LInux and Ansible

Published 2023-11-06 by Kevin Feasel

Amit Khandelwal packs a lot into a post:

It’s time for a new blog on how Ansible can simplify SQL Server deployment, configuration, and availability. If you’ve read my previous blogs on Ansible for SQL Server installation and configuration, and the pacemaker-based Always On availability group, you know how powerful Ansible can be. Now, let’s talk about HPE Serviceguard for Linux (SGLX), a high availability/disaster recovery solution that provides business continuity for critical applications like SQL Server.

Deploying SQL Server Always On availability groups on HPE SGLX is a fully supported solution for production workloads.

Today, let’s look at how you can configure Always On availability group based on HPE SGLX via Ansible. We have collaborated with our friends in HPE to enable the Ansible based deployment for HPE SGLX with SQL Server. This feature is now available for HPE SGLX 15.10. For this demonstration, you can download the evaluation bits from the ‘My HPE Software Center‘. The Ansible bits with the scripts are available on GitHub: 

Read on for instructions and what you need to make it all work.

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Run-Length Encoding in Power BI

Published 2023-11-06 by Kevin Feasel

Chris Webb performs some experiments:

Recently I was involved in an interesting discussion on Twitter X about how partitioning a table in a Power BI dataset semantic model can affect compression and therefore its size and query performance. You can read the thread here. It got me thinking: is there a way to get more detail on how well compression, and in particular run-length encoding (RLE from hereon), is working for a column when you’re using Import mode or Direct Lake? After a bit of research I found out there is, so let’s see some examples that illustrate what I learned.

The results are interesting and Chris explains why we see what we do.

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Triangular Distributions and R

Published 2023-11-03 by Kevin Feasel

Steven Sanderson unleashes the power of the triangle:

The Triangular Distribution is a continuous probability distribution with a triangular shape, hence the name. It is defined by three parameters: min, max, and mode. These parameters determine the range of values the distribution can take and the most likely value within that range. In mathematical terms, the probability density function (PDF) of the Triangular Distribution is given by:

Read on to see the definition, as well as how you can use the four functions around the Triangular Distribution.

By the way, the best-known case of the Triangular Distribution is combining the results of two fair dice, which gives us a peak at the number 7 (1/6 of the time) for a pair of fair, six-sided dice and moving symmetrically down from there, so p(6) = p(8), p(5) = p(9), and so on.

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Optimizing Shared Buffers in Postgres

Published 2023-11-03 by Kevin Feasel

Salman Ahmed explains how shared buffers work in Postgres:

PostgreSQL is known for its robustness and performance right out of the box. However, different applications and different scales of data demand fine-tuning of various parameters to achieve optimum performance. One such significant parameter is shared_buffers, which, when configured correctly, can notably enhance the performance of your PostgreSQL database.

Read on to see what shared buffers are, why they are so important to Postgres, and how to figure out the right value to use.

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Automated Alerts for Query Store Usage in Azure SQL DB

Published 2023-11-03 by Kevin Feasel

Jose Manuel Jurado Diaz doesn’t want to run out of disk space:

In this article, we will introduce a PowerShell script that helps monitor the usage of Query Data Store (QDS) in SQL Server databases. The script automatically sends an email alert when the storage space used by the Query Data Store reaches or exceeds 80% of its maximum allocated space. This can be particularly useful for database administrators to proactively manage and optimize their database storage.

Before we dive into the details, it’s essential to note that the script provided is a recommendation and should be adapted according to your specific environment and requirements. The responsibility of ensuring its compatibility and the impact on your system lies solely with the user.

Click through for the script. A quick glance of the code makes me think it will also work with on-premises SQL Server.

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A PBIX Report for Microsoft Fabric’s Support Page

Published 2023-11-03 by Kevin Feasel

Gilbert Quevauvilliers checks the status of Microsoft Fabric services:

What I wanted to show you is that I have created a Power BI report which shows the Microsoft Fabric Support page details.

I created one for Power BI which I receive daily, and it is great to get the subscription so that I am aware of any potential issues or changes affecting the Power BI Service.

I now have done the same thing for the Microsoft Fabric Support page; I have enabled the report subscription which I get daily.

Click through to see what it looks like and how you can get a copy of it for your own nefarious purposes.

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Fun with Tables in the Microsoft Fabric Lakehouse

Published 2023-11-03 by Kevin Feasel

Nikola Ilic dives into tables:

Probably the biggest confusion is: should I use a lakehouse or warehouse in Fabric? Or, what is the difference between Direct Lake and DirectQuery mode for Power BI reports?

And, while these two points mentioned above are of paramount importance to clarify, in this article I’ll focus on explaining another potential caveat, which is relevant when working with the lakehouse in Microsoft Fabric.

If only Nikola dove onto tables, I could make him an honorary Buffalo Bills fan.

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Building a Multinomial Distribution in R

Published 2023-11-02 by Kevin Feasel

Steven Sanderson isn’t satisfied with the binomial:

The multinomial distribution is a probability distribution that describes the probability of obtaining a specific number of counts for k different outcomes, when each outcome has a fixed probability of occurring.

In R, we can use the rmultinom() function to simulate random samples from a multinomial distribution, and the dmultinom() function to calculate the probability of a specific outcome.

Click through to see how you can build a multinomial distribution and what the difference is between rmultinom() and dmultinom().

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Using SQL Doc to Find Object Dependencies

Published 2023-11-02 by Kevin Feasel

Steve Jones looks for links:

In the SQL Doc application, you can dive down into the various objects in your database. As I’ve shown below, I navigated on the left side down to a specific object.

This gives me the basics of this object, but I can scroll down and see more. The lower part below the script shows what this object depends on (Uses) and what other objects depend this one (Used By). In this case, this object depends on dbo.ErrorLog and dbo.uspPrintError.

Read on to learn more about how it works and some tips from Steve.

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An Overview of Data Lake Operations with Apache NiFi

Published 2023-11-02 by Kevin Feasel

Lav Kumar gives us a 10,000 foot view:

In the world of data-driven decision-making, ETL (Extract, Transform, Load) processes play a pivotal role. The effective management and transformation of data are essential to ensure that businesses can make informed choices based on accurate and relevant information. Data lakes have emerged as a powerful way to store and analyze massive amounts of data, and Apache NiFi is a robust tool for streamlining ETL processes in a data lake environment.

Read on for a brief primer on NiFi and how some of its capabilities can assist in ETL and ELT processing.

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