Lecture

Introduction to Spark runtime architecture

Description

This lecture introduces Apache Spark, a unified analytics engine for large-scale data processing, highlighting its key features like interactive data exploration, in-memory data processing, and fault-tolerance. It covers the history of Spark, its usage in various applications, and its flexibility in deployment. The lecture explains Resilient Distributed Datasets (RDDs), the primary interface of Spark applications, and their importance in fault-tolerant and efficient iterative algorithms. It also delves into Spark's architecture, including the roles of the Driver and Worker nodes. Additionally, it explores RDD operations, transformations, actions, caching, and partitioning, providing insights into Spark's distributed computing framework.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.