Introduction to Spark Runtime Architecture

This lecture provides an overview of Apache Spark, a unified analytics engine for large-scale data processing, covering its architecture, history, key features, and flexibility. It explains the Spark runtime components, such as RDDs, transformations, actions, and lineage. The lecture also delves into Spark's distributed computing framework, basic data abstraction with RDDs, and the importance of fault tolerance. Additionally, it explores Spark's deployment options, supported languages, data storage, and specialized libraries. Practical exercises using Sparkmagic in Jupyter notebooks are highlighted, along with references for further exploration.