Central Library

Big Data Processing Using Spark in Cloud (Record no. 75512)

000 -LEADER
fixed length control field 04137nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-981-13-0550-4
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801213719.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180616s2019 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9789811305504
-- 978-981-13-0550-4
082 04 - CLASSIFICATION NUMBER
Call Number 005.7
245 10 - TITLE STATEMENT
Title Big Data Processing Using Spark in Cloud
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2019.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIII, 264 p. 89 illus., 62 illus. in color.
490 1# - SERIES STATEMENT
Series statement Studies in Big Data,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 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 ## - SUMMARY, ETC.
Summary, etc 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.
700 1# - AUTHOR 2
Author 2 Mittal, Mamta.
700 1# - AUTHOR 2
Author 2 Balas, Valentina E.
700 1# - AUTHOR 2
Author 2 Goyal, Lalit Mohan.
700 1# - AUTHOR 2
Author 2 Kumar, Raghvendra.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-981-13-0550-4
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2019.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big data.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data protection.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Quantitative research.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Big Data.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data and Information Security.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Analysis and Big Data.
700 1# - AUTHOR 2
-- (orcid)0000-0003-0490-4413
-- https://orcid.org/0000-0003-0490-4413
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2197-6511 ;
912 ## -
-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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