In-memory analytics with Apache Arrow

• Verfasst von: Topol, Matthew [VerfasserIn]
• Titel: In-memory analytics with Apache Arrow
• Titelzusatz: accelerate data analytics for efficient processing of flat and hierarchical data structures
• Mitwirkende: McKinney, Wes [MitwirkendeR]
• Verf.angabe: Matthew Topol ; foreword by Wes McKinney
• Ausgabe: Second edition.
• Verlagsort: Birmingham, UK
• Verlag: Packt Publishing Ltd.
• Jahr: 2024
• Umfang: 1 online resource (406 pages)
• Illustrationen: illustrations
• Fussnoten: Includes index
• ISBN: 978-1-83546-122-8
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Exploration de données (Informatique)
• K10plus-PPN: 190788842X
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m4611004457
• Lokale URL Inst.: Zum Volltext

Abstract

Apache Arrow is an open source, columnar in-memory data format designed for efficient data processing and analytics. This book harnesses the author’s 15 years of experience to show you a standardized way to work with tabular data across various programming languages and environments, enabling high-performance data processing and exchange. This updated second edition gives you an overview of the Arrow format, highlighting its versatility and benefits through real-world use cases. It guides you through enhancing data science workflows, optimizing performance with Apache Parquet and Spark, and ensuring seamless data translation. You’ll explore data interchange and storage formats, and Arrow's relationships with Parquet, Protocol Buffers, FlatBuffers, JSON, and CSV. You’ll also discover Apache Arrow subprojects, including Flight, SQL, Database Connectivity, and nanoarrow. You’ll learn to streamline machine learning workflows, use Arrow Dataset APIs, and integrate with popular analytical data systems such as Snowflake, Dremio, and DuckDB. The latter chapters provide real-world examples and case studies of products powered by Apache Arrow, providing practical insights into its applications. By the end of this book, you’ll have all the building blocks to create efficient and powerful analytical services and utilities with Apache Arrow.