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In-Memory Analytics with Apache Arrow

You're reading from   In-Memory Analytics with Apache Arrow Perform fast and efficient data analytics on both flat and hierarchical structured data

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781801071031
Length 392 pages
Edition 1st Edition
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Author (1):
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Matthew Topol Matthew Topol
Author Profile Icon Matthew Topol
Matthew Topol
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 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: 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

Technical requirements

For the portion of the chapter describing how to set up a development environment for working with the Arrow libraries, you'll need the following:

  • Your preferred Integrated Development Environment (IDE): For example, VSCode, Sublime, Emacs, and Vim
  • Plugins for your desired language (optional but highly recommended)
  • Interpreter or toolchain for your desired language(s):
    • Python 3+: pip and venv and/or pipenv
    • Go 1.16+
    • C++ Compiler (capable of compiling C++11 or newer)
You have been reading a chapter from
In-Memory Analytics with Apache Arrow
Published in: Jun 2022
Publisher: Packt
ISBN-13: 9781801071031
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