When you have set up Apache Spark and use Jupyter to run analyses on it, you’ll need to connect to the Jupyter notebooks by forwarding the port the notebooks run on to your local machine.
Depending on how the server that runs Spark is secured, you might need to do that through a “jump box”, a server that is hardened to prevent unauthorized access and let’s you access a network that’s otherwise not directly accessible from the Internet.
Whether it’s for social science, marketing, business intelligence or something else, the number of times data analysis benefits from heavy duty parallelization is growing all the time.
Apache Spark is an awesome platform for big data analysis, so getting to know how it works and how to use it is probably a good idea. Setting up your own cluster, administering it etc. etc. is a bit of a hassle to just learn the basics though (although Amazon EMR or Databricks make that quite easy, and you can even build your own Raspberry Pi cluster if you want…), so getting Spark and Pyspark running on your local machine seems like a better idea.