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Month: July 2024

Plotting Individual Values and Means of Multiple Groups in R

Ali Oghabian builds a graph:

In this post I show how groupScatterPlot(), function of the rnatoolbox R package can be used for plotting the individual values in several groups together with their mean (or other statistics). I think this is a useful function for plotting grouped data when some groups (or all groups) have few data points ! You may be wondering why to include such function in the rnatoolbox package ?! Well ! I happen to use it quit a bit for plotting expression values of different groups of genes/transcripts in a sample or expression levels of a specific gene/transcript in several sample groups.

Click through for the sample code and output. H/T R-Bloggers.

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Comparing Configuration of Two SQL Server Instances

Jana Sattainathan checks the labels on these bottles:

A lot of times, you have nearly identical database servers for an application running in Production, Test and Development but you may notice performance differences between them for the same data/queries that you could not attribute to any reason since CPU, Memory, Disk etc., may all be identical.

This is, strictly speaking, a comparison of configurations rather than data differences, indexing, and the like. Nonetheless, it’s useful to make this sort of comparison just to ensure that your instances have your desired state configuration.

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Shared Library Preloading in PostgreSQL

David Wheeler talks pre-loading:

Recently I’ve been trying to figure out when a Postgres extension shared libraries should be preloaded. By “shared libraries” I mean libraries provided or used by Postgres extensions, whether LOADable libraries or CREATE EXTENSION libraries written in C or pgrx. By “preloaded” I mean under what conditions should they be added to one of the Shared Library Preloading variables, especially shared_preload_libraries.

The answer, it turns out, comes very much down to the extension type. Read on for details.

Read on for an interesting discussion of what pre-loading means and the circumstances you should consider along the way.

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Microsoft Purview Classifications and Sensitivity Labels

James Serra labels the data:

I see a lot of confusion on how classifications and sensitivity labels work in Microsoft Purview. This blog will help to clear that up, but I first must address the confusion with Purview now that multiple products have been renamed to Microsoft Purview. I decided to use a question-and-answer format that will hopefully clear up the confusion (I was very confused too!):

Purview is a fantastic product. I just wish it cost about 10% as much as it does; then I could heartily recommend it to people.

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Finding Multiple Substrings in R

Steven Sanderson is looking for two things:

Hello, fellow R programmers! Today, we’re looking at a practical topic that often comes up when dealing with text data: how to check if a string contains multiple substrings. We’ll cover how to do this in base R, as well as using the stringr and stringi packages. Each approach has its own advantages, so let’s explore them together.

Read on for three separate examples.

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The Importance of Exploratory Testing

Thuy covers why exploratory testing is important:

Exploratory Testing is a software testing method that testers use to explore, find, and test features, bugs, or issues in an application freely and without the need for a prior testing plan. In exploratory testing, the tester will focus on freely working with the app as a real user and trying to find bugs and issues without following a specific test scenario.

Exploratory testing is a type of testing in which test cases are not created beforehand, but testers can test the system quickly. They can jot down ideas about what needs to be checked before performing the test. The focus of exploratory testing focuses more on testing as a “thinking” activity that explores new cases that do not follow the mainstream activity.

It’s amazing (and dismaying) how many bugs you can find simply by clicking around. The tricky part about exploratory testing is not actually finding bugs, but keeping track of your actions so that a developer knows how to fix the bugs you’ll inevitably find.

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Forms and Filters in Streamlit

I have a new video:

In this video, I extend the Streamlit app that we’ve been working on even more. We’ll convert a set of drop-down lists into a form, change the behavior of these drop-down lists, and add date picker logic.

Click through for the video, the code to date, and links to additional resources. I’m pretty happy so far with this series, and we’re about to kick it up to another level with the next video.

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A Comparison of Backup Types between SQL Server and Oracle

Sergey Gigoyan compares two sets of backups:

It is a well-known fact that backing up databases is one of the most common tasks for any database administrator (DBA), regardless of the relational database management system (RDBMS) used. However, the definition, naming, and structure of backup types can differ for each RDBMS. Therefore, if a DBA switches from one RDBMS to another, dealing with backup types can sometimes be very confusing. For instance, switching to Oracle databases after working with SQL Server databases for a long time can cause some difficulties. DBAs can work through these challenges by understanding the differences in database backup types.

Click through for the comparison. This a good reminder that, just because two things have the same name, doesn’t mean they do the same thing.

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Using Query Store on Azure Database for PostgreSQL

Marisa Mathews covers an episode of Data Exposed with Anna Hoffman and Grant Fritchey:

Capturing query metrics in PostgreSQL can be a challenge. Add in running that PostgreSQL database on Azure and things get even more challenging. However, Microsoft has a great addition to PostgreSQL when running in Azure Database, Query Store. This session will show the great query information available within the Query Store and how to query it.

Click through for a link to the video and additional links.

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Testing Postgres Configuration Parameter Performance Changes

Semab Tariq follows up on a prior blog post:

In a previous blog post, we configured an EC2 instance and installed PostgreSQL on it. After the initial setup, we ran pgbench to measure the initial TPS (transactions per second). Then, we tuned PostgreSQL and reran pgbench to see how much we could improve the TPS. To tune PostgreSQL, we adjusted various parameters based on the system’s available resources. In this blog, we will identify which of those parameters contributed the most to the performance improvements.

If you want to read the initial blog post, you can find it here: Key PostgreSQL Configuration Parameters for Enhanced Performance.

We will use the same instance size on AWS EC2 as before, which is t2.large.

I suppose it shouldn’t matter very much if you’re running a performance test over a significant timespan, though it was an interesting choice to use a burstable VM type for the test.

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