Название: Introducing .NET for Apache Spark: Distributed Processing for Massive Datasets Автор: Ed Elliott
Издательство: Apress
Год: 2021
Формат: true pdf/epub
Страниц: 269
Размер: 12.4 mb
Язык: English
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 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