Contents
Context
As part of a Data Engineering course, I’m currently exploring Apache Spark in depth – a powerful framework for distributed data processing in the Big Data ecosystem. This interactive mind map serves as a visual summary of the key concepts, components, and application areas of Spark – both to reinforce my own learning and to act as a compact reference guide.
The mind map was created using Markmap, a tool that transforms Markdown structures into interactive mind maps. You can navigate and use the map as follows:
Mindmap Usage & Features
- Expand/Collapse Nodes: Click on a node with an arrow to show or hide its subtopics.
- Zoom & Pan: Use your mouse or touch gestures to zoom in/out and move around the map.
- Fullscreen View: Right-clicking on the map or using the menu (depending on the Markmap setup) may allow fullscreen display.
- Linked Elements: Some nodes contain links to documentation or external resources – simply click to follow.
Note: This mind map doesn’t cover all topics, but it’s more than enough for an initial deep dive. I’ve kept it in German because it made managing my notes easier during the learning process.
For my long-term, networked learning, I’ve since switched to using Obsidian with its graph view, which allows me to organize and access notes quickly across different projects.
References
[1] Apache Spark – Apache Software Foundation. (2025). “Apache Spark™ – Unified Analytics Engine for Big Data.” https://spark.apache.org/
[2] GitHub Pages – GitHub, Inc. (2025). “GitHub Pages – Websites for you and your projects.” https://pages.github.com/
[3] Hugo – The Hugo Authors. (2025). “Hugo: The world’s fastest framework for building websites.” https://gohugo.io/
[4] Markmap – Markmap Team. (2025). “Markmap: Visualize your Markdown as mindmaps.” GitHub. https://github.com/markmap/markmap
[5] Obsidian – Obsidian.md. (2025). “Obsidian – A powerful knowledge base that works on local Markdown files.” https://obsidian.md/
[6] PySpark – Apache Software Foundation. (2025). “PySpark: Python API for Apache Spark.” https://spark.apache.org/docs/latest/api/python/
License
CC BY-NC-SA 4.0 Licence
With this licence, you may use, modify and share the work as long as you credit the original author. However, you may not use it for commercial purposes, i.e. you may not make money from it. And if you make changes and share the new work, it must be shared under the same conditions.