Apache Spark with Scala

"With the rise in popularity of the term 'Big Data', there is an increasing need to process large amounts of data in real-time, with maximum efficiency. This has led to Apache Spark gaining popularity in the Big Data market very quickly. The Spark ecosystem allows you to process large...

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Bibliographic Details
Main Author: Kane, Frank
Format: eBook
Language:English
Published: [Place of publication not identified] Packt Publishing 2016
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:"With the rise in popularity of the term 'Big Data', there is an increasing need to process large amounts of data in real-time, with maximum efficiency. This has led to Apache Spark gaining popularity in the Big Data market very quickly. The Spark ecosystem allows you to process large streams of data in real-time. As Spark is built on Scala, knowledge of both has become vital for data scientists and data analysts today. This comprehensive 7 hour course will empower you to build efficient Spark applications to fulfill your Big Data needs.You will start with quickly understanding the basics of Scala and proceed to set up the development environment for Apache Spark and Scala for Big Data processing. You will understand the different modules of Spark like Spark SQL, Spark Streaming and GraphX, along with when and how to use them. While doing so, you will build practical, real-world Spark applications in Scala and see how you can deploy them on the cloud. You will also learn how to perform machine learning in real time using Spark's MLlib module. Finally, you will learn how to run Spark on Hadoop clusters along with best practices and troubleshooting techniques.With over 20 carefully selected examples and abundant explanation to explain even the most difficult concepts, this course will ensure your success in taming your Big Data challenges using Spark with Scala."--Resource description page
Item Description:Title from resource description page (Safari, viewed January 10, 2017)
Physical Description:1 streaming video file (7 hr., 19 min., 18 sec.) digital, sound, color