Book Image

In-Memory Analytics with Apache Arrow

By : Matthew Topol
Book Image

In-Memory Analytics with Apache Arrow

By: Matthew Topol

Overview of 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.
Table of Contents (16 chapters)
1
Section 1: Overview of What Arrow Is, its Capabilities, Benefits, and Goals
5
Section 2: Interoperability with Arrow: pandas, Parquet, Flight, and Datasets
11
Section 3: Real-World Examples, Use Cases, and Future Development

Chapter 9: Powered by Apache Arrow

Apache Arrow is becoming the industry standard as more and more projects adopt and/or support it for their internal and external communication formats. In this chapter, we're going to take a look at a few projects that are using Arrow in different ways. With the flexibility that Arrow provides, it is able to serve a variety of use cases in different environments, and many developers are taking advantage of that. Of course, Arrow is used in many different analytical engine projects, but it is also used in other contexts ranging from machine learning (ML) to data visualization in the browser.

With new projects and uses popping up all the time, it only makes sense to give a small overview of a selection of some of those projects. In this chapter, you're going to see a couple of different use cases for how Arrow is being used in the wild. These include the following:

  • A distributed SQL query engine named Dremio Sonar, which we just...