Introducing .Net for Apache Spark : distributed processing for massive datasets / Ed Elliott.
Elliott, Ed, author.
2021
QA76.9.D5
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title Introducing .Net for Apache Spark : distributed processing for massive datasets / Ed Elliott.
Author Elliott, Ed, author.
ISBN 9781484269923 (electronic bk.)
1484269926 (electronic bk.)
9781484269916
1484269918
DOI https://doi.org/10.1007/978-1-4842-6992-3
Published [Berkeley] : Apress, [2021]
Language English
Description 1 online resource
Item Number 10.1007/978-1-4842-6992-3 doi
Call Number QA76.9.D5
Dewey Decimal Classification 004/.36
Summary 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.
Note Includes index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 28, 2021).
Available in Other Form Introducing .Net for Apache Spark.
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
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.

Browse Subjects

Show more subjects...

Statistics

from
to
Export