Playground

In directory examples you’ll find two useful notebooks that allows you to test Neo4j and PySpark in a cloud-to-cloud environment using Neo4j sandboxes and Google colab.

Colab/PySpark to Neo4j sandbox architecture

The notebooks

These notebooks contain a set of examples that explain how the Neo4j Spark connector can fit into your data-driven workflow, and mostly important they allow you to test your knowledge with a set of exercises after each section.

If you have any problem feel free to write a post in the Neo4j community forum or in Discord.

If you want more exercises feel free to open an issue in the GitHub repository.

  • neo4j_data_engineering.ipynb file explains how to interact with the Neo4j Spark connector from a Data Engineering perspective, so how to write your Spark jobs and how to read/write data from/to Neo4j;

  • neo4j_data_science.ipynb file explains how to interact with the Neo4j Spark connector from a Data Science perspective, so how to combine Pandas (in PySpark) with the Neo4j Graph Data Science library for highlighting frauds in a banking scenario.

Test your knowledge

After each session you will find an exercise that will test your knowledge as shown in the image below:

An exercise

We provide asserts that will test the output of your code and we also provide a solution that you can check by expanding the text Show a possible solution

Enjoy!