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Big Data Processing Using Spark in Cloud (Studies in Big Data)

By: Lalit Mohan Goyal (Edited by) , Mamta Mittal (Edited by) , Raghvendra Kumar (Edited by) , Valentina E. Balas (Edited by)

Extended Catalogue

Ksh 20,500.00

Format: Paperback or Softback

ISBN-10: 9811344485

ISBN-13: 9789811344480

Collection / Series: Studies in Big Data

Collection Type: Publisher collection

Edition statement: Softcover reprint of the original 1st ed. 2019

Publisher: Springer Verlag, Singapore

Imprint: Springer Verlag, Singapore

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Dec 23rd, 2018

Publication Status: Active

Product extent: 264 Pages

Product Classification / Subject(s): Databases
Computer security
Network security

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The book describes the emergence of big data technologies and the role of Spark in the entire big data stack.

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data''s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data.

The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.


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