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In-Memory Analytics with Apache Arrow - Matthew Topol

In-Memory Analytics with Apache Arrow

Accelerate data analytics for efficient processing of flat and hierarchical data structures

(Autor)

Buch | Softcover
406 Seiten
2024 | 2nd Revised edition
Packt Publishing Limited (Verlag)
978-1-83546-122-8 (ISBN)
CHF 66,30 inkl. MwSt
Harness the power of Apache Arrow to optimize tabular data processing and develop robust, high-performance data systems with its standardized, language-independent columnar memory format

Key Features

Explore Apache Arrow's data types and integration with pandas, Polars, and Parquet
Work with Arrow libraries such as Flight SQL, Acero compute engine, and Dataset APIs for tabular data
Enhance and accelerate machine learning data pipelines using Apache Arrow and its subprojects
Purchase of the print or Kindle book includes a free PDF eBook

Book DescriptionApache 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.What you will learn

Use Apache Arrow libraries to access data files, both locally and in the cloud
Understand the zero-copy elements of the Apache Arrow format
Improve the read performance of data pipelines by memory-mapping Arrow files
Produce and consume Apache Arrow data efficiently by sharing memory with the C API
Leverage the Arrow compute engine, Acero, to perform complex operations
Create Arrow Flight servers and clients for transferring data quickly
Build the Arrow libraries locally and contribute to the community

Who this book is forThis book is for developers, data engineers, and data scientists looking to explore the capabilities of Apache Arrow from the ground up. Whether you’re building utilities for data analytics and query engines, or building full pipelines with tabular data, this book can help you out regardless of your preferred programming language. A basic understanding of data analysis concepts is needed, but not necessary. Code examples are provided using C++, Python, and Go throughout the book.

Matthew Topol is a member of the Apache Arrow Project Management Committee (PMC) and a staff software engineer at Voltron Data, Inc. Matt has worked in infrastructure, application development, and large-scale distributed system analytical processing for financial data. At Voltron Data, Matt's primary responsibilities have been working on and enhancing the Apache Arrow libraries and associated sub-projects. In his spare time, Matt likes to bash his head against a keyboard, develop and run delightfully demented fantasy games for his victims—er—friends, and share his knowledge and experience with anyone interested enough to listen.

Table of Contents

Getting Started with Apache Arrow
Working with Key Arrow Specifications
Format and Memory Handling
Crossing the Language Barrier with the Arrow C Data API
Acero: A Streaming Arrow Execution Engine
Using the Arrow Datasets API
Exploring Apache Arrow Flight RPC
Understanding Arrow Database Connectivity (ADBC)
Using Arrow with Machine Learning Workflows
Powered by Apache Arrow
How to Leave Your Mark on Arrow
Future Development and Plans

Erscheinungsdatum
Vorwort Wes McKinney
Verlagsort Birmingham
Sprache englisch
Maße 191 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Software Entwicklung User Interfaces (HCI)
Mathematik / Informatik Informatik Theorie / Studium
ISBN-10 1-83546-122-0 / 1835461220
ISBN-13 978-1-83546-122-8 / 9781835461228
Zustand Neuware
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