Scaling Up with R and Apache Arrow: Bigger Data, Easier Workflows by Nic Crane H

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
ISBN-13
9781032663203
Book Title
Scaling Up with R and Apache Arrow
ISBN
9781032663203
Category

About this product

Product Identifiers

Publisher
CRC Press LLC
ISBN-10
1032663200
ISBN-13
9781032663203
eBay Product ID (ePID)
2343784870

Product Key Features

Number of Pages
168 Pages
Publication Name
Scaling Up with Rand Apache Arrow : Bigger Data, Easier Workflows
Language
English
Subject
Computer Science, Data Processing, Databases / General
Publication Year
2025
Type
Textbook
Subject Area
Computers
Author
Neal Richardson, Jonathan Keane, Nic Crane
Format
Hardcover

Dimensions

Item Weight
16 Oz
Item Length
9.2 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
005.7
Table Of Content
Acknowledgements Foreword 1. Introduction 2. Getting Started 3. Data Manipulation 4. Files and Formats 5. Datasets 6. Cloud 7. Advanced Topics 8. Sharing Data and Interoperability References Appendices
Synopsis
Analyze large datasets directly from R. Scaling Up With R and Arrow provides a guide to working efficiently with larger-than-memory datasets using the arrow R package. As data grows in size and complexity, traditional data analysis methods in R often hit technical limitations. In this book, you'll learn how to overcome these hurdles without needing to set up complex infrastructure. You'll learn about the Apache Arrow project's origins, goals, and its significance in bridging the gap between data science and big data ecosystems. You'll also learn how to leverage the arrow R package to work directly with files in various formats, such as CSV and Parquet, using familiar dplyr syntax. This book explores practical topics like data manipulation, file formats, working with larger datasets, and optimizing workflows for data in cloud storage. Advanced chapters examine user-defined functions, integration with other tools like DuckDB, and extending Arrow's capabilities to work with geospatial data. Written by developers of the Arrow R package, this guide is essential for anyone looking to scale their data processing capabilities in R., This book provides a guide to working efficiently with larger-than-memory datasets using the arrow R package. You'll learn how to overcome these hurdles without needing to set up complex infrastructure. Written by developers of the Arrow R package, this guide is essential for anyone looking to scale their data processing capabilities in R.

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