Lectures related to Stream Processing and Fault Tolerance

Explores fault tolerance and DStreams in Spark Streaming for real-time big data analysis.

Covers the Spark runtime architecture, including RDDs, transformations, actions, and caching for performance optimization.

Explores the Spark ecosystem, Resilient Distributed Datasets, and the storage layer abstraction in Spark.

Explores big data challenges, distributed computing with Spark, RDDs, hardware requirements, MapReduce, transformations, and Spark DataFrames.

Explores the challenges of big data processing and introduces Spark as a solution.