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

Exploring Apache Arrow Flight RPC

Distributed systems have always interested me. A distributed system is like a really good puzzle; it’s immensely satisfying once you figure out how all the pieces fit together to achieve your goal. If you’re not familiar with the term, a distributed system is simply a situation where you have various components of a system spread across multiple machines on a network. The idea is to split up the work and coordinate efforts among the components to complete tasks more efficiently. A great example would be Apache Spark.

The goal of distributed systems is generally to provide a robust, scalable, and reliable conglomeration of components that efficiently perform operations by distributing work across a system. This often means large amounts of data flowing between various components so that the data can get processed, manipulated, or otherwise operated on. When it comes to Apache Arrow-formatted data, the Arrow project provides a remote...

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