DataFusion: Query Execution with Rust and Arrow: The Complete Guide for Developers and Engineers

"DataFusion: Query Execution with Rust and Arrow"

"DataFusion: Query Execution with Rust and Arrow" is a comprehensive exploration into the architecture, execution, and innovation that power modern analytical query engines. This book begins by establishing a solid foundation in advanced Rust programming, data systems engineering, and the transformative role of Apache Arrow’s columnar memory format. Through its in-depth examination of DataFusion’s core architecture, readers gain a clear understanding of how high-performance, safe, and flexible query processing is achieved in cloud-native analytics environments.

Delving deeper, the book covers the full spectrum of query lifecycle stages: from SQL parsing and logical planning to physical execution and advanced optimization. It demystifies the interplay between logical and physical plans, highlighting strategies such as predicate pushdown, schema inference, and cost-based optimization. Detailed discussions of parallelism, vectorized execution, memory management, and the seamless integration of diverse data sources position DataFusion at the forefront of modern large-scale analytics. Chapters dedicated to distributed execution with Ballista, resource-adaptive scheduling, and workload profiling provide practical guidance for building scalable and robust analytical platforms.

With dedicated sections on observability, debugging, security, and extensibility, "DataFusion: Query Execution with Rust and Arrow" equips both practitioners and architects to tackle real-world challenges in analytical data systems. Coverage of Arrow Flight, custom data connectors, auditability, user-defined functions, and future directions ensures readers are prepared for the rapidly evolving landscape of cloud, stream, and real-time analytics. This work is an essential guide for anyone seeking deep technical mastery of the systems powering next-generation, high-performance data analytics.

© 2025 HiTeX Press (Ebook): 6610001065102

Fecha de lanzamiento

Ebook: 12 de julio de 2025