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

Spicing up your ML workflows

Among the various fields of engineering that work with very large sets of data, one field that deals with processing some of the largest datasets would be ML and AI workflows. However, if your full-time job isn't ML, and you don't have the support of a dedicated ML team, it can often be very difficult to create an application that can learn and adapt. This is where a group of engineers decided to step in and make it easier for developers to create intelligent and adapting applications. Spice AI (https://spiceai.io) is, at the time of writing, a venture-capital-funded start-up that is working to create a platform to make it easier for developers to create AI-driven applications that can adapt and learn. They've open-sourced a product on GitHub called Spice.ai (https://github.com/spiceai/spiceai). It is currently in alpha development and utilizes Apache Arrow, Arrow Flight, as well as Dremio Sonar for its data processing and transport (https...