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

Example use cases

One significant proposed benefit of having the C Data API was to allow applications to implement the API without requiring a dependency on the Arrow libraries. Let's suppose there is an existing computational engine written in C++ that wants to add the ability to return data in the Arrow format without adding a new dependency or having to link with the Arrow libraries. There are many possible reasons why you might want to avoid adding a new dependency to a project. This could range from the development environment to the complexity of deployment mechanisms, but we're not going to focus on that side of it.

Using the C Data API to export Arrow-formatted data

Do you have your development environment all set up for C++? If not, go and do that and come back. You know the drill; I'll wait.

We'll start with a small function to generate a vector of random 32-bit integers, which will act as our sample data. You know how to do that? Well, good....