Tag: Golang

A Revelation in Algorithm Form

Thanks to an article from System Design Academy that came my way this week, I’ve been reflecting on something I find curious and simple at the same time: how to sort massive datasets in a distributed manner. And you know what? These patterns are so elegant that they can be applied to so many other problems we face day to day.

As a developer who has gone from JavaScript to PHP, then Python, and is now fully immersed in Golang, I’m struck by how certain patterns transcend languages and frameworks. Distributed sorting is one of those cases where architecture matters more than implementation.

I’ve always liked to see and try different technologies, and within these, of course, programming languages.

An example of this was the intensive use I gave at the time, at Arrakis, to Rebol, an interpreted cross-platform language, with everything you could need to perform great data cleaning scripts, in a “strange” syntax, but beautiful in its approach.

The case of Go was a bit different, because just like what happened to me with Angular, at the time (several years ago) I tried to give it a chance, but all the information and examples I found were “very small” blocks of code, I didn’t see in that (at a bird’s eye view) that it was finished, it seemed like a more academic/conceptual language than something for real use.

The first one is the very simple, but not limited, Go interface system.

How to use interfaces in Go

The second, no less important, making it clear and showing C# vs Go code.

Statements are statements, and expressions are expressions (in Go)

As always, we’ll need some debugging:

Scheduler Tracing In Go

A project, green, but promising, for (among other things) distributed execution:

hyflow-go: A geo-replicated, main-memory, highly consistent datastore

Every day we hear about Big Data, IoT, Smart Data, Machine Learning, semantic data, etc. Many times out of context or simply used because they’re “trendy”.

One of the best examples is “Big Data”, where we always talk about huge amounts of information, systems, platforms, queries, but with the error, from my point of view, of taking that as information, no, no it’s not information, they’re data, raw data or processed data, information is what is extracted from that data. Many times, with the term “Big Data”, we get lost in only the part of storing huge amounts of data, replicated and in astronomical volumes. That’s not “Big Data”, that’s only talking about one part, the most mechanical one, and the one that contributes least to what we’re looking for “Information”, it’s only “data storage and management”, one leg of a much broader table.