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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 Matthew Topol
Profile icon Matthew Topol

Table of Contents (16) Chapters

Preface Section 1: Overview of What Arrow Is, its Capabilities, Benefits, and Goals
Chapter 1: Getting Started with Apache Arrow Chapter 2: Working with Key Arrow Specifications Chapter 3: Data Science with Apache Arrow Section 2: Interoperability with Arrow: pandas, Parquet, Flight, and Datasets
Chapter 4: Format and Memory Handling Chapter 5: Crossing the Language Barrier with the Arrow C Data API Chapter 6: Leveraging the Arrow Compute APIs Chapter 7: Using the Arrow Datasets API Chapter 8: Exploring Apache Arrow Flight RPC Section 3: Real-World Examples, Use Cases, and Future Development
Chapter 9: Powered by Apache Arrow Chapter 10: How to Leave Your Mark on Arrow Chapter 11: Future Development and Plans Other Books You May Enjoy

Find your interest and expand on it

In the first section of this chapter, Contributing to open source projects, we looked at a bunch of ideas about how and why you could, or should, contribute to an open source project. At this point, I'd like to provide just a bit of friendly advice about finding a good place to start if you want to contribute to the Arrow project specifically. Yes, there's the obvious case of looking at the implementation in your preferred programming language. But most of the code bases are still quite large, even when limited to only looking at code relevant to one language. My first piece of advice is to figure out what you are interested in. I've put a small flowchart together in Figure 10.6 to help with some ideas:

Figure 10.6 – A flowchart of ideas

Of course, it doesn't cover everything. It's not supposed to. The Arrow libraries house many different ideas and different ways of doing things. If you&apos...

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