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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

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835461228
Length 406 pages
Edition 2nd Edition
Languages
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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 (18) Chapters Close

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 17. 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 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 inter-process communication (IPC) format (covered in the next chapter!) and compare that with whatever previous way you passed data around. Which is easier to use? Which...

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