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Day: July 9, 2021

Font Choices with ggplot2

Kenneth Tay takes us through font options in R’s ggplot2 package:

I was recently asked to convert all the fonts in my ggplot2-generated figures for a paper to Times New Roman. It turns out that this is easy, but it brought up a whole host of questions that I don’t have the full answer to.

If you want to go all out with using custom fonts, I suggest looking into the extrafont and showtext packages. This post will focus on what you can do without importing additional packages.

A quick word of warning: R’s behavior with respect to fonts differs quite a bit between Windows and Mac/Linux. This becomes especially apparent if you do end up installing something like extrafont. H/T R-Bloggers.

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Running Azure ML On-Premises via Azure Arc

Tsuyoshi Matsuzaki takes us through running Azure Machine Learning via Azure Arc:

First of all, you must run Azure Arc enabled Kubernetes on-premise or on 3rd party cloud. For running Arc-enabled Machine Learning later, use machines with more than 4 CPUs, since Arc-enabled ML requires enough resources.

In this post, I assume that we run KIND (Kubernetes in Docker) cluster on on-premise Ubuntu server. (For test purpose, I have used Ubuntu 18.04 on a single virtual machine in Azure, Standard D3 v2, which has 4 CPUs and 14 GB memory.)

Click through to see how it’s done.

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Event Streaming for Security

Kai Waehner has a new series, and part 1 is all about using Apache Kafka as the backbone for a cybersecurity infrastructure:

This introductory post explored the basics of cybersecurity and how it relates respectively why it requires data in motion powered by Apache Kafka. The rest of the series will go deeper into specific topics that partly rely on each other.

Threat intelligence is only possible with situational awareness. Forensics is complementary. Deployments differ depending on security, safety, and compliance requirements.

Click through for the article.

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Case-Insensitive Collations in Redshift

Mengchu Cai, et al, show us how to change collation with Redshift:

Amazon Redshift is a fast, fully managed, cloud-native data warehouse. Tens of thousands of customers have successfully migrated their workloads to Amazon Redshift. We hear from customers that they need case-insensitive collation for strings in Amazon Redshift in order to maintain the same functionality and meet their performance goals when they migrate their existing workloads from legacy, on-premises data warehouses like Teradata, Oracle, or IBM. With that goal in mind, AWS provides an option to create case-insensitive and case-sensitive collation.

In this post, we discuss how to use case-insensitive collation and how to override the default collation. Also, we specifically explain the process to migrate your existing Teradata database using the native Amazon Redshift collation capability.

Specifically, it appears that they have two collations exposed: one which is case-sensitive and the other which is case-insensitive.

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Extending MDF Files without an Outage

David Klee creates some files:

Do you have quite large MDF files on your database? By large, I mean hundreds of gigabytes (or larger). Have you ever noticed that your SQL Server disk stall metrics for these data files are much higher than the storage latency metrics exhibited on the underlying operating system layer? It could be that your SQL Server data files are being hammered too hard and you don’t have enough data files to help the SQL Server storage engine distribute the load. We do this for tempdb, right? Why don’t we do this enough for our user databases as well? It’s easy for a brand-new database from day zero, but what about existing databases that have grown out of control with a single data file attached? Let me show you how to adjust this for existing databases without an outage!

Check it out. This is a part of database administration I’d never really thought much about, so it often ended up being a blind spot for me.

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SQL Server on Azure Container Instances

Arun Sirpal has a series for us. Part 1 involves spinning up SQL Server on ACI:

This is Microsoft’s serverless technology which allows us to deploy containers without having to worry about managing the underlying hardware. It’s a way to get access to SQL fast (faster than traditional methods like installing a virtual machine) to do things like test code fixes etc.

There a couple of ways of doing this, you can use the portal, PowerShell or Azure CLI, I actually like Azure CLI.

Part 2 gives you an idea of what you get:

In the last post we built an image of SQL server 2019 Linux hosted in Azure Container Instance for fast access to SQL server. So, your next question is probably, lets see some database action?

When you connect to SSMS its not different, the feel and look, is, SQL server. Lets have a tour.

The normal warning with Azure Container Instances is that they’re great for development and testing efforts (in part because of how inexpensive it is compared to alternatives on Azure) but won’t have the same uptime or high availability guarantees that a service like Azure Kubernetes Service will have.

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