There a dozen of statusline plugins for neovim: express_line, galaxyline, lualine, statusline, windline and possibly more. Each with different goals and feature sets. This article isn’t about any of them, instead we look at the built-in statusline option and how you can use it to create a boring but functional status line.
I am pretty certain that the whole web 3.0 story is a mind-bogglingly stupid idea, but I like to challenge my own views. I thought one way to do that is to explore how I’d build a web 3.0 twitter clone. This post is this exploration. I’ll try to suppress my bias as best I can.
This article is for you if you either:
I started learning Haskell a couple of years ago. My usual reason to learn a programming language is because I have a concrete use-case - a project I want to contribute to. With Haskell it was different. My primary motivation wasn’t a concrete use-case, but instead I thought studying the language would be worth it for the sake of learning. It does things different than other mainstream languages and I wanted to become familiar with concepts I hadn’t seen before.
Writing a couple of iterations of “Hello World” applications wasn’t going to get me far. Utilizing it in a project at work wasn’t an option - instead I started using it for my ad-hoc and utility scripts. Before, Python was my go-to language for such things, but Haskell ended up replacing it. In this article I will show why.
In this article we’ll take a look at the circuit breaker mechanism in CrateDB. CrateDB uses circuit breakers to prevent a node from running out of memory or stalling due to high garbage collection load.
In this post we’ll look at how CrateDB distributes GROUP BY queries. This is the fourth post in a series about CrateDB internals.
I assume that you’ve read the first and second post of the series. You may also be interested in the third post, but it is not necessary to read it to follow this article.
This is the third post in a series about CrateDB internals. This time I’ll introduce the Query Then Fetch execution strategy. Similar to the previous posts, this focuses on the distribution aspect.
This is the second post of a series about CrateDB internals. In the first post I introduced relational algebra, the optimizer and outlined how the execution works on a very high level. In this post I’ll explore the execution of a simple SELECT statement in more detail. This post focuses on the distribution aspect of the query execution.
This post is the first of a series that explains how CrateDB executes queries. This first post focuses on the optimizer, logical plan and execution plan.
Over the last couple of years I’ve developed an intuition that shallow functions can be problematic and here I’d like to share some thoughts on why that is the case.