Improving Bridge Four, a simple, functional, effectful, single-leader, multi worker, distributed compute system optimized for embarrassingly parallel workloads by providing consistency guarantees and improving overall code quality (or something like that).
How to move a Proxmox host to a new m.2 SSD when using a LSI SAS HBA card to realize PCI passthrough for HDDs for zfs + TrueNAS.
QGIS is incredible: You can build maps that make use of the absolute wealth of public data out there and put Google Maps to absolute shame. This article is doing just that.
Tracking vehicle location offline with a Raspberry Pi, Part 2: Apache Flink, scala, Kafka, and road-testing.
Building custom Linux images, dealing with a 40 year old GPS standard, & trying to shoehorn functional programming into Python: Tracking vehicle location offline with a Raspberry Pi. (Part 1)
Types, type classes, implicits, tagless-final, effects, and other things: Not everything in the world of functional programming is bleak and overly academic. A view on FP & scala concepts someone who loves to complain actually likes.
Reviewing 'Essential Scala' and 'Functional Programming Simplified', while explaining why Spark has nothing to do with Scala, and asking why learning Functional Programming is such a pain. A (maybe) productive rant (or an opinionated essay).
How I build what is essentially a self-service Data Lake at home to narrow down the search area for a new house, instead of using Zillow like a normal person, using Spark, Iceberg, and Python.
A quick project to write a Telegram chat bot that can control a camera, connected to a Raspberry Pi, to take pictures of things; or: Why I refuse to trust IoT vendors and do everything myself
Part 2 of throwing Raspberry Pis at the pepper plants in my garden: On the topics of 3D printing, more bad solder jobs, I2C, SPI, Python, go, SQL, and failures in CAD.
On how growing vegetables is more complicated than it looks, why bad soldering still works, on moving individual bits around, and what I learned about using technology where one probably does not need technology.
On the joy of inheriting a rather bad dataset - dissecting ~120GB of terrible Google Takeout data to make it usable, using Dataflow/Beam, go, Python, and SQL.
One question I do get in earnest quite frequently is why I put up with running GNU/Linux distributions for development work. An attempt at a simple response.
Responding to an article on using Rust for throw away code and prototyping: Making a case for go over Rust, Python, and perl.
In Part 2 of our comparison of Python and go from a Data Engineering perspective, we'll finally take a look at Apache Beam and Google Dataflow and how the go SDK and the Python SDK differ, what drawbacks we're dealing with, how fast it is by running extensive benchmarks, and how feasible it is to make the switch
Exploring golang - can we ditch Python for go? And have we finally found a use case for go? Part 1 explores high-level differences between Python and go and gives specific examples on the two languages, aiming to answer the question based on Apache Beam and Google Dataflow as a real-world example.
Ditching WordPress for a static site generator
How a broken memory module hid in plain sight – and how I blamed the Linux Kernel and two innocent hard drives
The amount of time my outdoor cameras are being set off by light, wind, cars, or anything other than a human is insane. Overly cautious security cameras might be a feature, but an annoying one at that...
In 2017, I wrote about how to build a basic, Open Source, Hadoop-driven Telematics application (using Spark, Hive, HDFS, and Zeppelin) that can track your movements while driving, show you how your driving skills are, or how often you go over the speed limit - all without relying on 3rd party vendors processing and using that data on your behalf...
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