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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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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

Chapter 4: Format and Memory Handling

I've continuously extolled the virtues of using Arrow as a data interchange technology for tabular data, but how does it stack up against the more common technologies that people tend to utilize for transferring data? When does it make sense to use one over the other for your application programming interface (API)? The answer is to know how different technologies utilize memory. Clever management of your memory can be the key to performant processes. To decide which format to use for your data, you need to understand which use cases your options were designed for. With that in mind, you can take advantage of the runtime properties of the most common data transport formats such as Protocol Buffers (Protobuf), JavaScript Object Notation (JSON), and FlatBuffers when appropriate. By understanding how to utilize memory in your program, you can process very large amounts of data with minimal memory overhead.

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