PySpark on Windows can be installed using two different ways. Since Spark is a distributed compute engine, it also works stand alone. Most of the developer who are familiar with working jupyter notebood prefer to use jupyter notebook and it has to be integrated with PySpark.

There are other sets of python developers who prefer to use an interactive shell to interact with PySpark. Form them PySpark has REPL (Read, Iterate, Print, Loop) which helps them to start the PySpark session and write their code. Refer this detailed documentation for PySpark interactive shell installation.

Additional PySpark Resource & Reading Material

PySpark Frequentl Asked Question

Refer our PySpark FAQ space where important queries and informations are clarified. It also links to important PySpark Tutorial apges with-in site.

PySpark Examples Code

Find our GitHub Repository which list PySpark Example with code snippet

PySpark/Spark Related Interesting Blogs

Here are the list of informative blogs and related articles, which you might find interesting

1. PySpark Frequently Asked Questions
2. Apach Spark Introduction
3. How Spark Works
4. PySpark Installation on Windows 10
5. PySpark Jupyter Notebook Configuration On Windows
6. PySpark Tutorial
7. Apache Spark 3.0 Release Note (Preview)
8. PySpark Complete Guide