I have read quite a bit this week, I’m also preparing a summary of the
Christopher Dresser’s Studies in Design
I summarised the Delta Lake paper. Most people who have read it have enjoyed it, which is pretty great.
This almost made me understand trampolines. I suspect a couple reads and I’ll have it.
This is a very old post, and I don’t think I can use anything here for my
generative, but it was a very interesting read.
There are many good resources here. Even if the subject is trite and you don’t care, the resources here are interesting just for their own sake.
These look interesting, but given the minimal size/cost of a RA3 cluster, it does not exactly fill SMB (small/medium businesses) level of data.
I’m not sure I get how I’d use it, but since neither does Hillel (or did), I don’t feel as bad.
This is a very well-written post about best practices to introduce Haskell. I don’t think I disagree (or at least strongly disagree, I may argue some choice) with anything here.
Yet another product from Amazon. At least they don’t “do a Google” with them.
At first it looks as if the post is dismissive of the new syntax, but surprisingly, it is in favour. Personally, I like whitespace-based indentation. It feels correct.
This is an interesting approach to lightweight distributed data. In short, it’s SQLite with Raft.
What can I say, it’s a classic in data visualization. There’s also a very cool t-shirt for Scala lovers, by 47 degrees.
This is intended as a joke, but I wonder how much of a joke it really needs to be. I have tweaked them into my own version (I like fonts and margins):
serif, monospace. You need to open them in a new tab manually (no idea why), and you can bookmark them afterwards (or just copy the link).
This sounds like a very good data discovery platform. I need to know more!
My biggest time sink is juggling development time and keeping on top of everything that is going on in the data area.
This is probably the clearest explanation of monads ever. Or at least, the one that best matches how I’d explain it.
At one point I had a Plan9 cluster with my Macbook (with Plan 9 from User Space), a very old laptop and a Raspberry Pi sharing a Venti fileserver. That was some serious yak shaving. This post has no Plan9 on it by the way.
This is about frameworks for evaluation and avoiding post-fact rationalisation. Worth reading if you like changing methods and self-improvement.
Not much more to add. It’s fascinating, would have never guessed.
Autoloader from Databricks looks interesting.
What’s in the title. And with examples, very
Buy me a coffee