In-Memory Analytics with Apache Arrow
Whether you’re a developer or a data scientist, working with large amounts of data can be a challenge. This book focuses on describing Apache Arrow’s format and data types and the benefits of using it to accelerate data manipulation. You’ll get to grips with topics such as Spark, Jupyter, Arrow Flight, and FlightSQL.
Offered by
Difficulty Level
Intermediate
Completion Time
13h4m
Language
English
About Book
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.
In-Memory Analytics with Apache Arrow
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 13h4m total length
Getting Started with Apache Arrow
Working with Key Arrow Specifications
Data Science with Apache Arrow
Format and Memory Handling
Crossing the Language Barrier with the Arrow C Data API
Leveraging the Arrow Compute APIs
Using the Arrow Datasets API
Exploring Apache Arrow Flight RPC
Powered By Apache Arrow
How to Leave Your Mark on Arrow
Future Development and Plans
Related Resources
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