Flare - Optimizing Apache Spark for Scale-Up Architectures and Medium-Size Data

Explore a conference talk that delves into Flare, an accelerator module designed to optimize Apache Spark for scale-up architectures and medium-size data processing. Learn how Flare addresses the performance limitations of Spark in scenarios where data can fit into the main memory of a single powerful server. Discover how this innovative approach incorporates code generation techniques inspired by main-memory database systems to deliver significant speedups for a wide range of applications. Gain insights into the challenges of processing medium-size workloads that require high performance, frequent execution on changing data, or integration with external libraries and systems like TensorFlow. Understand the potential benefits of Flare in enhancing Spark's capabilities for users who value its familiar interface and tooling but need improved performance for computationally intensive tasks on scale-up architectures.

"Flare: Optimizing Apache Spark for Scale-Up Architectures and Medium-Size Data" by Gregory Essertel