This is the first article in a series of blog posts to help Data Scientists and NLP practitioners learn the basics of Spark NLP library from scratch and easily integrate it into their workflows. During this series, we will do our best to produce high-quality content and clear instructions with accompanying codes both in Python and Scala regarding the most important features of Spark NLP. Through these articles, we aim to make the underlying concepts of Spark NLP library as clear as possible by touching all the practical and pain points with codes and instructions. The ultimate goal is to let the audience get started with this amazing library in a short time and smooth the learning curve. It’s expected that the reader has at least a basic understanding of Python and Spark.