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Big data processing using Spark in cloud

Mittal, Mamta.

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Big data processing using Spark in cloud

Record Type:	Electronic resources : Monograph/item
Title/Author:	Big data processing using Spark in cloud/ edited by Mamta Mittal ... [et al.].
other author:	Mittal, Mamta.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	xiii, 264 p. :ill., digital ;24 cm.
[NT 15003449]:	Concepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies.
Contained By:	Springer eBooks
Subject:	Big data. -
Online resource:	http://dx.doi.org/10.1007/978-981-13-0550-4
ISBN:	9789811305504

Big data processing using Spark in cloud
Big data processing using Spark in cloud[electronic resource] /edited by Mamta Mittal ... [et al.]. - Singapore :Springer Singapore :2019. - xiii, 264 p. :ill., digital ;24 cm. - Studies in big data,v.432197-6503 ;. - Studies in big data ;v.43..

Concepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies.

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.

ISBN: 9789811305504

Standard No.: 10.1007/978-981-13-0550-4doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45 / B543 2019

Dewey Class. No.: 005.7

Big data processing using Spark in cloud
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245 0 0 $a Big data processing using Spark in cloud $h [electronic resource] / $c edited by Mamta Mittal ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xiii, 264 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.43
505 0 $a Concepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies.
520 $a 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.
650 0 $a Big data. $3 2045508
650 0 $a SPARK (Computer program language) $3 3300294
650 0 $a Cloud computing. $3 1016782
650 0 $a Electronic data processing $x Distributed processing. $3 548601
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Systems and Data Security. $3 898223
650 2 4 $a Big Data/Analytics. $3 2186785
700 1 $a Mittal, Mamta. $3 3378265
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830 0 $a Studies in big data ; $v v.43. $3 3378266
856 4 0 $u http://dx.doi.org/10.1007/978-981-13-0550-4
950 $a Engineering (Springer-11647)