Nowadays words like “agile”, “lean”, “scrum” or “kanban” have been abused so many times that some of its initial values or ideas have been lost. Many people think (and say) they are agile because they do stand-ups; some others are trying to come up with new “smart” acronyms (SAFe, LeSS…) for unknown reasons (because the old buzzwords don’t sell anymore?)
Here at Intent HQ we deal with code on a daily basis (is there any software engineering team who doesn’t?). So, when we are about to hire somebody, her ability to write code is probably the skill we will take into account the most. That’s why we do have a coding interview in our process.
Pucket is a Scala library which provides a simple partitioning system for Parquet. But what is Parquet and why does it need partitioning when it already supports filtering? In this post I will attempt to explain Parquet, partitioning in Hadoop, and the motivation and design of Pucket. If you’re not interested in the background, you can skip straight to some simple code examples or go to the GitHub repository.
As programmers, a large portion of our job is to stay aware of, research, and assess new technologies in an industry that evolves at breakneck speed. Being continually bombarded with such information it can seem like an uphill struggle to process this information in a memorable fashion.
Here at Intent HQ we believe how important it is to write good code. Why? First, because writing good code is much cheaper and more fun than writing bad code. Second, because if you write good quality code chances are that the product you are building will be much better. Third, and more important, because writing good quality code is what we are supposed to do: after all, we are getting paid for doing our job well.