In-Memory Analytics with Apache Arrow

By Matthew Topol
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    Chapter 1: Getting Started with Apache Arrow

About this book

Apache Arrow is designed to accelerate analytics and allow the exchange of data across big data systems easily.

In-Memory Analytics with Apache Arrow begins with a quick overview of the Apache Arrow format, before moving on to helping you to understand Arrow’s versatility and benefits as you walk through a variety of real-world use cases. You'll cover key tasks such as enhancing data science workflows with Arrow, using Arrow and Apache Parquet with Apache Spark and Jupyter for better performance and hassle-free data translation, as well as working with Perspective, an open source interactive graphical and tabular analysis tool for browsers. As you advance, you'll explore the different data interchange and storage formats and become well-versed with the relationships between Arrow, Parquet, Feather, Protobuf, Flatbuffers, JSON, and CSV. In addition to understanding the basic structure of the Arrow Flight and Flight SQL protocols, you'll learn about Dremio’s usage of Apache Arrow to enhance SQL analytics and discover how Arrow can be used in web-based browser apps. Finally, you'll get to grips with the upcoming features of Arrow to help you stay ahead of the curve.

By the end of this book, you will have all the building blocks to create useful, efficient, and powerful analytical services and utilities with Apache Arrow.

Publication date:
June 2022


Section 1: Overview of What Arrow Is, its Capabilities, Benefits, and Goals

This section is an introduction to Apache Arrow as a format specification, the benefits it claims, and the goals it's trying to achieve, along with a high-level overview of basic use cases and examples.

This section comprises the following chapters:

  • Chapter 1, Getting Started with Apache Arrow
  • Chapter 2, Working with Key Arrow Specifications
  • Chapter 3, Data Science with Apache Arrow

About the Author

  • Matthew Topol

    Matthew Topol is an Apache Arrow contributor and a principal software architect at FactSet Research Systems, Inc. Since joining FactSet in 2009, Matt has worked in both infrastructure and application development, led development teams, and architected large-scale distributed systems for processing analytics on financial data. In his spare time, Matt likes to bash his head against a keyboard, develop and run delightfully demented games of fantasy for his victims—er—friends, and share his knowledge with anyone interested enough to listen.

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In-Memory Analytics with Apache Arrow
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