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Introducing .NET for Apache Spark - Distributed Processing for Massive Datasets (Paperback, 1st ed.)
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Introducing .NET for Apache Spark - Distributed Processing for Massive Datasets (Paperback, 1st ed.)
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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 Who This Book Is For .NET developers 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
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