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In-Memory Analytics with Apache Arrow

You're reading from In-Memory Analytics with Apache Arrow

Product type Book

Published in Jun 2022

Publisher Packt

ISBN-13 9781801071031

Pages 392 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Matthew Topol

Table of Contents (16) Chapters

Preface

1. Section 1: Overview of What Arrow Is, its Capabilities, Benefits, and Goals

2. Chapter 1: Getting Started with Apache Arrow

3. Chapter 2: Working with Key Arrow Specifications

4. Chapter 3: Data Science with Apache Arrow

5. Section 2: Interoperability with Arrow: pandas, Parquet, Flight, and Datasets

6. Chapter 4: Format and Memory Handling

7. Chapter 5: Crossing the Language Barrier with the Arrow C Data API

8. Chapter 6: Leveraging the Arrow Compute APIs

9. Chapter 7: Using the Arrow Datasets API

10. Chapter 8: Exploring Apache Arrow Flight RPC

11. Section 3: Real-World Examples, Use Cases, and Future Development

12. Chapter 9: Powered by Apache Arrow

13. Chapter 10: How to Leave Your Mark on Arrow

14. Chapter 11: Future Development and Plans

15. Other Books You May Enjoy

Summary

At this point, not only should you be fairly well acquainted with a variety of topics and concepts regarding the usage of the Apache Arrow libraries, but you should also know how to start integrating them into your daily workflows. Whether you're taking advantage of the filesystem abstractions, data format conversions, or zero-copy communication benefits, Arrow can slot into a huge number of parts of any data workflow. Make sure you understand the concepts that have been touched on so far involving the formats, communication methods, and utilities provided by the Arrow libraries before moving on. Play around with them and try out different strategies for managing your data and passing it around between tools and utilities. If you're an engineer building out distributed systems, try using the Arrow IPC format (which we will learn about in detail in Chapter 4, Format and Memory Handling) and compare that with whatever previous way you passed data around. Which is easier...

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Authors (1)

Matthew Topol

Matthew Topol is an Apache Arrow contributor and a principal software architect at FactSet Research Systems, Inc. Since joining FactSet in 2009, Matt has worked in both infrastructure and application development, led development teams, and architected large-scale distributed systems for processing analytics on financial data. In his spare time, Matt likes to bash his head against a keyboard, develop and run delightfully demented games of fantasy for his victims—er—friends, and share his knowledge with anyone interested enough to listen.

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