Christian Hollinger

Software Engineering, GNU/Linux, Data, ML, and other things

11 Jun 2020

A Data Engineering Perspective on Go vs. Python (Part 1)

5,340 words, ~21 min read

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.
21 May 2020

Goodbye, WordPress - Hello, Hugo & nginx

2,555 words, ~10 min read

Ditching WordPress for a static site generator
25 Feb 2020

How a broken memory module hid in plain sight

1,956 words, ~7 min read

How a broken memory module hid in plain sight – and how I blamed the Linux Kernel and two innocent hard drives
09 Dec 2019

Tensorflow on edge, or – Building a “smart” security camera with a Raspberry Pi

1,919 words, ~7 min read

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...
07 Aug 2019

How I built a (tiny) real-time Telematics application on AWS

3,822 words, ~15 min read

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...
01 Jul 2019

A look at Apache Hadoop in 2019

2,380 words, ~9 min read

In this article, we'll take a look at whether Apache Hadoop still a viable option in 2019, with Cloud driven data processing an analytics on the rise...
11 Apr 2019

Building a Home Server

3,306 words, ~13 min read

In this article, I’ll document my process of building a home server - or NAS - for local storage, smb drives, backups, processing, git, CD-rips, and other headless computing...
27 Oct 2018

Analyzing Reddit’s Top Posts & Images With Google Cloud (Part 2 - AutoML)

2,470 words, ~9 min read

In the last iteration of this article we analyzed the top 100 subreddits and tried to understand what makes a reddit post successful by using Google’s Cloud ML tool set to analyze popular pictures.
12 Jun 2018

Analyzing Reddit’s Top Posts & Images With Google Cloud (Part 1)

3,040 words, ~12 min read

In this article (and its successors), we will use a fully serverless Cloud solution, based on Google Cloud, to analyze the top Reddit posts of the 100 most popular subreddits. We will be looking at images, text, questions, and metadata...
18 Mar 2018

Analyzing Twitter Location Data with Heron, Machine Learning, Google's NLP, and BigQuery

3,487 words, ~13 min read

In this article, we will use Heron, the distributed stream processing and analytics engine from Twitter, together with Google’s NLP toolkit, Nominatim and some Machine Learning as well as Google’s BigTable, BigQuery, and Data Studio to plot Twitter user's assumed location across the US.