Outside of functional programming context, map-reduce refers to a technique for processing data. Thanks to properties of map and reduce operations, computations which can be expressed using them can be highly parallelised, which allows for faster processing of high volumes of data.

If you’ve ever wondered how tools such as Apache Hadoop work, you’re at the right page. In this article I’ll explain what map and reduce are and later also introduce a shuffle phase.

Same as my previous article written in Polish, this text will describe some steps I take after installing Slackware Linux. I try to strike a balance between performance, security and usability, but not everything written here may work for everyone. You have been warned.