Yes, this topic is far from new material. Especially if you consider Cloud tech stack evolution/change speed, it has been a long time since Apache Spark version 2 was introduced (26-07-2016, to be more precise). But moving into the cloud is not an easy solution for all companies, where data volumes can make such a move prohibitive. And in on-premises contexts, the speed of operational change is significantly slower.
This post summarizes the steps for deploying Apache Spark 2 alongside Spark 1 with Cloudera, and install python jupyter notebooks that can switch between Spark versions via kernels. Given that this is a very frequent setup in big data environments, thought I would make the life easier for “on-premise engineers”, and, hopefully, speed up things just a little bit.