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In-Memory Analytics with Apache Arrow

You're reading from In-Memory Analytics with Apache Arrow Accelerate data analytics for efficient processing of flat and hierarchical data structures

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781835461228

Length 406 pages

Edition 2nd Edition

Languages

Python

Tools

Apache arrow

Concepts

Data Engineering

Author (1):

Matthew Topol

View More author details

Table of Contents (18) Chapters

Preface

1. Part 1: Overview of What Arrow is, Its Capabilities, Benefits, and Goals

2. Chapter 1: Getting Started with Apache Arrow FREE CHAPTER

3. Chapter 2: Working with Key Arrow Specifications

4. Chapter 3: Format and Memory Handling

5. Part 2: Interoperability with Arrow: The Power of Open Standards

6. Chapter 4: Crossing the Language Barrier with the Arrow C Data API

7. Chapter 5: Acero: A Streaming Arrow Execution Engine

8. Chapter 6: Using the Arrow Datasets API

9. Chapter 7: Exploring Apache Arrow Flight RPC

10. Chapter 8: Understanding Arrow Database Connectivity (ADBC)

11. Chapter 9: Using Arrow with Machine Learning Workflows

12. Part 3: Real-World Examples, Use Cases, and Future Development

13. Chapter 10: Powered by Apache Arrow

14. Chapter 11: How to Leave Your Mark on Arrow

15. Chapter 12: Future Development and Plans

16. Index

Why subscribe?

17. Other Books You May Enjoy

Technical requirements

As in previous chapters, you’ll need an internet-connected computer with the following software so that you can follow along with the code examples here:

Python 3.8 or higher, with the PyArrow and pandas (or Polars) modules installed
Go 1.21 or higher
A C++ compiler capable of compiling C++17 or higher, with the Arrow libraries installed
Your preferred IDE, such as Emacs, Sublime, or VS Code
A web browser
An Nvidia graphics card and CUDA libraries (optional)

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Authors (1)

Matthew Topol

Matthew Topol

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.

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