Don’t you hate when you need to do something you had done before, but cannot remember how exactly? I’ve been in that situation several times and sometimes looking up for a correct method turned out considerably harder than it should. To alleviate the need for future Googling, here’s a bag of notes I can reference easily:

• Getting past Chrome certificate error
• ‘Compressing’ git repository
• Changing commits author
• How to start a letter in English
• Summing numbers in a column in Emacs

Looking for Python stuff? Those are now in separate post:

• Converting date to timestamp
• Re-rising Python exception preserving back-trace
• Flattening a list in Python

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.