Summary  
This chapter explains the architecture of a distributed processing framework by detailing how a cluster is organized into a master node for coordination and worker nodes for executing tasks, and how they interact to manage resources and schedule work.  

General domain of usage  
Distributed data processing

Learn the essentials of PySpark for big data analysis using real-world flights data. Explore Spark architecture, RDDs, DataFrames, and practical data processing techniques.

Core concepts and hands-on practice with PySpark using flights data.

Spark Architecture: Cluster, Master, and Workers