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Key benefits

Learn about Apache Arrow's data types and interoperability with pandas and Parquet

Work with Apache Arrow Flight RPC, Compute, and Dataset APIs to produce and consume tabular data

Reviewed, contributed, and supported by Dremio, the co-creator of Apache Arrow

Description

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.

Who is this book for?

This book is for developers, data analysts, and data scientists looking to explore the capabilities of Apache Arrow from the ground up. This book will also be useful for any engineers who are working on building utilities for data analytics and query engines, or otherwise working with tabular data, regardless of the programming language. Some familiarity with basic concepts of data analysis will help you to get the most out of this book but isn't required. Code examples are provided in the C++, Go, and Python programming languages.

What you will learn

Use Apache Arrow libraries to access data files both locally and in the cloud

Understand the zero-copy elements of the Apache Arrow format

Improve read performance by memory-mapping files with Apache Arrow

Produce or consume Apache Arrow data efficiently using a C API

Use the Apache Arrow Compute APIs to perform complex operations

Create Arrow Flight servers and clients for transferring data quickly

Build the Arrow libraries locally and contribute back to the community

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Frequently bought together

Machine Learning for Streaming Data with Python

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Amazon verified reviews

Francesco Lacopo Jul 02, 2022

This is a great book for anyone who needs to move and analyze data consistently in their day-to-day workflow.If you're someone who's building a distributed system, this book is an excellent gateway into Arrow and really sells you on its uses and benefits. Even if you're unsure if Arrow would be a good fit for your use case, the book provides excellent examples to give you a better frame of reference. It even goes into detail on Arrow in several, popularly-used programming languages that will cover most people's area of usage.You can definitely feel the author's genuine interest and enthusiasm for the technologies mentioned. The tone is fun, friendly, and conversational, and I enjoyed the pun chapter titles. I also think the fact that Topol included a large section specifically for how to contribute back to the open-source project goes to show that he really wants to see the technology thrive and succeed.I can definitely see myself referring back to this book in the future whenever I need to develop a new piece of a system and want to use or consider using Arrow as my data exchange format. It provides setup steps along with plenty of examples on how to use Arrow in a project, and the plentiful code snippets help keep each passage in the context of how you would use the concepts in practice.If you've ever been interested in learning more about Arrow, have only heard the name in passing, or have never heard of it but deal with processing on large data sets, this is a great book to pick up.

Amazon Verified review

Wilson Jul 06, 2022

There aren't a lot of other books right now on Apache Arrow at the moment, and this book fills a nice void in cutting edge tech. Couple that with the fun prose that Matt uses, it was entertaining as well as met the needs for a data geek like me.The book focused on the Arrow libraries quite a bit and as a whole section on contributing to the open-source Arrow community. It wasn't my particular specialty but was able to understand and follow. The git repos helped as well if you wanted to reference examples out of book like I did.I found the chapter on Real World Applications most useful for those looking to modernize and where we could actually apply the concepts and for ideas on the book. This was the most helpful to me and I found myself referencing this section for some of my firm's future projects.Overall, learned many things and this book does a great job promoting to you on the benefits of Arrow and Flight in your data stack. As someone new to Apache Arrow, this book does a great job explaining the benefits over the "legacy" technologies. It has definitely sold me on the analytics modernization that's to come!

Amazon Customer May 18, 2023

Apache arrow is a massive project to follow through. Matthew had done an incredible job in putting out content in easy to follow manner. He actually contributes to arrow project from golang perspective. So it's always a delightful experience to understand from practitioner's viewpoint.You must grab a copy if you desire to find out nitty-gritty of the overall apache arrow domain. Mind you, apache arrow is the next big thing in technology. Period.

Jennifer Ma Jun 25, 2022

This book makes a very dense subject matter accessible. Topol's conversational tone and frequent quips made it a fun read.The book goes into depth on many Arrow libraries in multiple languages. It also discusses memory management in detail to explain the pros and cons of Arrow and other formats, such as Profobuf, JSON, CSV, and FlatBuffers. And it also provides examples of integrating with other common data platforms, such as Spark and ElasticSearch.While all of the book is insightful, I'd recommend picking and choosing the chapters that are most relevant for your use case. I've read through it all once, but I think I'll need to read it again to let some of the more advanced topics sink in.

John Murray Jun 28, 2022

The book is logically structured starting, as a course in Arrow, with basic concepts, data types, I/O, filesystems and interaction with other libraries, such as Pandas, leading on to more advanced features such as compute functions and Flight.The book is illustrated throughout with example code, in both C++ and Python, which can be downloaded from the publisher's Github site to try yourself (see screenshot).By following through the text, and examples, a user with an understanding of C++ and/or Python can quickly get up to speed with Apache Arrow and start writing efficient in-memory analytical code.Highly recommended for beginners and intermediate level Arrow programmers who want to develop their skills.

In-Memory Analytics with Apache Arrow: Perform fast and efficient data analytics on both flat and hierarchical structured data

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