{"product_id":"introducing-net-for-apache-spark-distributed-processing-for-massive-datasets-paperback","title":"Introducing .Net for Apache Spark: Distributed Processing for Massive Datasets - Paperback","description":"\u003cp\u003eby \u003cb\u003eEd Elliott\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003eGet 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.\u003cbr\u003eThis 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. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cb\u003eWhat You Will Learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eInstall and configure Spark .NET on Windows, Linux, and macOS \u003c\/li\u003e\n\u003cli\u003eWrite Apache Spark programs in C# and F# using the .NET bindings\u003c\/li\u003e\n\u003cli\u003eAccess and invoke the Apache Spark APIs from .NET with the same high performance as Python, Scala, and R\u003c\/li\u003e\n\u003cli\u003eEncapsulate functionality in user-defined functions\u003c\/li\u003e\n\u003cli\u003eTransform and aggregate large datasets \u003c\/li\u003e\n\u003cli\u003eExecute SQL queries against files through Apache Hive\u003c\/li\u003e\n\u003cli\u003eDistribute processing of large datasets across multiple servers\u003c\/li\u003e\n\u003cli\u003eCreate your own batch, streaming, and machine learning programs\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cbr\u003e.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\u003cbr\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003eGet 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.\u003cbr\u003eThis 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. \u003cbr\u003eYou will: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eInstall and configure Spark .NET on Windows, Linux, and macOS \u003c\/li\u003e\n\u003cli\u003eWrite Apache Spark programs in C# and F# using the .NET bindings\u003c\/li\u003e\n\u003cli\u003eAccess and invoke the Apache Spark APIs from .NET with the same high performance as Python, Scala, and R\u003c\/li\u003e\n\u003cli\u003eEncapsulate functionality in user-defined functions\u003c\/li\u003e\n\u003cli\u003eTransform and aggregate large datasets \u003c\/li\u003e\n\u003cli\u003eExecute SQL queries against files through Apache Hive\u003c\/li\u003e\n\u003cli\u003eDistribute processing of large datasets across multiple servers\u003c\/li\u003e\n\u003cli\u003eCreate your own batch, streaming, and machine learning programs\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003cb\u003eEd Elliott\u003c\/b\u003e 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.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 262\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.59 x 10 x 7 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e April 14, 2021\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42100346224775,"sku":"9781484269916","price":75.58,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/9d6d5339efc97a4a990a8cfda4c48cbd.webp?v=1732383780","url":"https:\/\/booksby.splitshops.com\/products\/introducing-net-for-apache-spark-distributed-processing-for-massive-datasets-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}