Introducing .NET for Apache Spark: Distributed Processing for Massive Datasets b

Description: Introducing .NET for Apache Spark by Ed Elliott Intermediate-Advanced user level FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET bindings. Readers new to Apache Spark will get up to speed quickly using Spark for data processing tasks performed against large and very large datasets. You will learn how to combine your knowledge of .NET with Apache Spark to bring massive computing power to bear by distributed processing of extremely large datasets across multiple servers.This book covers how to get a local instance of Apache Spark running on your developer machine and shows you how to create your first .NET program that uses the Microsoft .NET bindings for Apache Spark. Techniques shown in the book allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes. You will learn to process data using both batch mode and streaming mode so you can make the right choice depending on whether you are processing an existing dataset or are working against new records in micro-batches as they arrive. The goal of the book is leave you comfortable in bringing the power of Apache Spark to your favorite .NET language. What You Will LearnInstall and configure Spark .NET on Windows, Linux, and macOS Write Apache Spark programs in C# and F# using the .NET bindingsAccess and invoke the Apache Spark APIs from .NET with the same high performance as Python, Scala, and REncapsulate functionality in user-defined functionsTransform and aggregate large datasets Execute SQL queries against files through Apache HiveDistribute processing of large datasets across multiple serversCreate your own batch, streaming, and machine learning programsWho This Book Is For.NETdevelopers who want to perform big data processing without having to migrate to Python, Scala, or R; and Apache Spark developers who want to run natively on .NET and take advantage of the C# and F# ecosystems Back Cover Get started using Apache Spark via C# or F# and the .NET for Apache Spark bindings. This book is an introduction to both Apache Spark and the .NET bindings. Readers new to Apache Spark will get up to speed quickly using Spark for data processing tasks performed against large and very large datasets. You will learn how to combine your knowledge of .NET with Apache Spark to bring massive computing power to bear by distributed processing of extremely large datasets across multiple servers. This book covers how to get a local instance of Apache Spark running on your developer machine and shows you how to create your first .NET program that uses the Microsoft .NET bindings for Apache Spark. Techniques shown in the book allow you to use Apache Spark to distribute your data processing tasks over multiple compute nodes. You will learn to process data using both batch mode and streaming mode so you can make the right choice depending on whether you are processing an existing dataset or are working against new records in micro-batches as they arrive. The goal of the book is leave you comfortable in bringing the power of Apache Spark to your favorite .NET language. You will: Install and configure Spark .NET on Windows, Linux, and macOS Write Apache Spark programs in C# and F# using the .NET bindings Access and invoke the Apache Spark APIs from .NET with the same high performance as Python, Scala, and R Encapsulate functionality in user-defined functions Transform and aggregate large datasets Execute SQL queries against files through Apache Hive Distribute processing of large datasets across multiple servers Create your own batch, streaming, and machine learning programs Author Biography Ed Elliott is a data engineer who has been working in IT for 20 years and has focused on data for the last 15 years. He uses Apache Spark at work and has been contributing to the Microsoft .NET for Apache Spark open source project since it was released in 2019. Ed has been blogging and writing since 2014 at his own blog as well as for SQL Server Central and Redgate. He has spoken at a number of events such as SQLBits, SQL Saturday, and the GroupBy conference. Table of Contents Part I. Getting Started.- 1. Understanding Apache Spark.- 2. Setting up Spark.- 3.- Programming with .NET for Apache Spark.- Part II. The APIs.- 4. User-Defined Functions.- 5. The DataFrame API.- 6. Spark SQL and Hive Tables.- 7. Spark Machine Learning API.- Part III. Examples.- 8. Batch Mode Processing.- 9. Structured Streaming.- 10. Troubleshooting.- 11. Delta Lake.- Part IV. Appendices.- Appendix A. Running in the Cloud.- Appendix B. Implementing .NET for Apache Spark Code. Feature Helps .NET developers use Apache Spark without needing Python or Scala Shows you how to use the power of Apache Spark to efficiently process big data Provides examples in C# and F# Details ISBN1484269918 Author Ed Elliott Short Title Introducing . NET for Apache Spark Language English Year 2021 ISBN-10 1484269918 ISBN-13 9781484269916 Format Paperback DOI 10.1007/978-1-4842-6992-3 Publisher APress Edition 1st Imprint APress Place of Publication Berkley Country of Publication United States Pages 262 Publication Date 2021-04-14 AU Release Date 2021-04-14 NZ Release Date 2021-04-14 US Release Date 2021-04-14 UK Release Date 2021-04-14 Illustrations 41 Illustrations, black and white; XV, 262 p. 41 illus. Subtitle Distributed Processing for Massive Datasets Edition Description 1st ed. DEWEY 005.72 Audience Professional & Vocational We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:137939071;

Price: 96.28 AUD

Location: Melbourne

End Time: 2024-11-05T01:17:57.000Z

Shipping Cost: 0 AUD