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Day: February 24, 2025

Defining “Laziness” in R

Published 2025-02-24 by Kevin Feasel

Maëlle Salmon, Athanasia Mo Mowinckel, and Hannah Frick are quite studious:

In the programming world, laziness can often be a good thing: it is both a human quality that can motivate automation efforts, and a programming concept that avoids wasting resources such as memory. Now, when reading code or documentation, seeing the word “lazy” can be confusing, because of its polisemy: it carries several meanings. In this post, we will enumerate the different possible definitions of “lazy” in R code.

Read on for a variety of contexts around “lazy,” including lazy evaluation, lazy database queries, lazy loading, and more.

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Building Sparklines in R Shiny

Published 2025-02-24 by Kevin Feasel

Osheen MacOscar needs a series of tiny visuals:

All of the plots from this package use the sparkline function, and we pass the type of chart we want as the type argument (default is line). The function will take a vector or list for the values argument, depending on the type of chart we are creating this can be either data to plot or specifications for the plot.

Click through for a list of the sparkline-esque visuals you can create as well as how you can use the sparkline package and some examples of outputs.

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Microsoft Fabric Permissions Models for Sharing Data with End Users

Published 2025-02-24 by Kevin Feasel

Jon Vöge builds a list:

Consider the following scenario:

  • I am building a data platform on Microsoft Fabric, using Lakehouses as the primary storage engine.
  • My end users need to consume data from the data platform as users of Power BI reports which connects to data from the Lakehouses, as developers of ad hoc models and report using data from the Lakehouses, and through ad hoc SQL queries on the Lakehouses.
  • I want to use DirectLake for Power BI reports to take advantage of frequency data ingestion and transformation, and improve the actionability of my reports.
  • My data is sensitive, and users, regardless of whether they consume reports or develop their own, need to be restricted by Row Level Security to only see some of the data.

Read on for eight different approaches to the problem and Jon’s thoughts on each approach.

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The Challenge of TDE in PostgreSQL

Published 2025-02-24 by Kevin Feasel

Bruce Momjian shares an update:

I first blogged about Transparent Data Encryption (tde) in 2019, which was more thoroughly analyzed in a blog post in 2023. An email exchange in December 2024 summarized the most up-to-date status of this feature:

When I started focusing on tde, it was going to require changes to buffer reads/writes, wal, and require a way to store secret keys. I thought those changes would be acceptable given tde’s security value. Once file I/O changes were required, I think the balance tilted to tde requiring too many code changes given its security value (not policy compliance value).

Read on for Bruce’s take now. Coming from the SQL Server world, where TDE has been in the product since 2008, I generally agree that there are better ways to ensure regulatory compliance. It’s not like TDE is actively harmful or anything, but considering that all of the relevant keys and certificates need to be on the local server to begin with, this prevents a limited number of situations from exposing your data, and there tend to be less resource-intensive alternatives for those situations.

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Point in Time Database Restoration in SQL Server

Published 2025-02-24 by Kevin Feasel

Andy Brownsword rolls back the clock:

A few weeks ago I demonstrated the simplicity of performing point-in-time database restored in Azure Managed Instance. Whilst that has a lovely front-end, it can be just as easy with a proc call on your traditional SQL instance.

Let’s see how to use two open source tools to achieve this simplicity.

Click through for Andy’s solution. I would also make mention of Minion Backup, which does a great job of the database backup portion and about 90% of the database restoration portion well.

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