Ilya Sorokin silarr

Knowledge Space

— Draft —

Link for sharing: https://w3id.org/knowledge-space/

Vision

You might sometimes ask yourself questions like this:

Disclaimer

I'm still very new to Kafka, eventsourcing, stream processing, etc. I'm in the middle of building my first production system with this stuff and am writing this at the request of a few folks on Twitter. So if you do have experience, please do me and anyone else reading this a favor by pointing out things I get wrong :)

Inspirations

The Log — http://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying
Turning the database inside out — http://www.confluent.io/blog/2015/03/04/turning-the-database-inside-out-with-apache-samza/
Why local state is a fundamental primitive in stream processing — http://radar.oreilly.com/2014/07/why-local-state-is-a-fundamental-primitive-in-stream-processing.html
Samza
Various functional systems been exposed to over past year or so, React, Flux, RX, etc.

	#!/usr/bin/python

	import os
	import subprocess
	import time
	import yaml
	import re

	user_name = os.environ.get("DOCKERHUB_USER")

	"""
	This script is designed to export a mass amount of MagicaVoxel .vox files
	to .obj. Unlike Magica's internal exporter, this exporter preserves the
	voxel vertices for easy manipulating in a 3d modeling program like Blender.

	Various meshing algorithms are included (or to be included). MagicaVoxel
	uses monotone triangulation (I think). The algorithms that will (or do)
	appear in this script will use methods to potentially reduce rendering
	artifacts that could be introduced by triangulation of this nature.