Introducing .NET for Apache Spark
Apress (Verlag)
978-1-4842-6991-6 (ISBN)
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 Learn
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
Who 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
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.
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.
Erscheinungsdatum | 28.04.2021 |
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Zusatzinfo | 41 Illustrations, black and white; XV, 262 p. 41 illus. |
Verlagsort | Berkley |
Sprache | englisch |
Maße | 178 x 254 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
Mathematik / Informatik ► Informatik ► Software Entwicklung | |
Schlagworte | Apache Hive • Apache Spark • Azure Analytics • Big Data • C# • DataFrame .NET • Distributed Computing • F# • Microsoft .NET Framework • .NET Spark Machine Learning (ML) • Scala API • Sparkcode • Spark .NET • SparkSession .NET • Spark SQL • Streaming data • stream processing • U-SQL |
ISBN-10 | 1-4842-6991-8 / 1484269918 |
ISBN-13 | 978-1-4842-6991-6 / 9781484269916 |
Zustand | Neuware |
Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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