Big Data Processing Using Spark in Cloud / edited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar.

Format:

Book

Contributor:

Mittal, Mamta, editor.

Balas, Valentina Emilia, editor.

Goyal, Lalit Mohan, editor.

Kumar, Raghvendra, 1987- editor.

SpringerLink (Online service)

Series:

Engineering (Springer-11647)

Studies in big data 2197-6503 ; 43.

Studies in Big Data, 2197-6503 ; 43

Language:

English

Subjects (All):

Big data.

Computer security.

Big Data.

Systems and Data Security.

Big Data/Analytics.

Local Subjects:

Big Data.

Systems and Data Security.

Big Data/Analytics.

Physical Description:

1 online resource (XIII, 264 pages) : 89 illustrations, 62 illustrations in color.

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

Singapore : Springer Singapore : Imprint: Springer, 2019.

System Details:

text file PDF

Summary:

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.

Contents:

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. .

Other Format:

Printed edition:

ISBN:

978-981-13-0550-4

9789811305504

OCLC:

1041108960

Access Restriction:

Restricted for use by site license.