Big Data 2.0 Processing Systems (Record no. 174087)

MARC details
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001 - CONTROL NUMBER
control field 978-3-030-44187-6
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125103.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
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fixed length control field 200709s2020 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030441876
-- 978-3-030-44187-6
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-44187-6
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA75.5-76.95
072 #7 - SUBJECT CATEGORY CODE
Subject category code UNH
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Subject category code UND
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM030000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UNH
Source thema
072 #7 - SUBJECT CATEGORY CODE
Subject category code UND
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 025.04
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Sakr, Sherif.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Big Data 2.0 Processing Systems
Medium [electronic resource] :
Remainder of title A Systems Overview /
Statement of responsibility, etc by Sherif Sakr.
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2020.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2020.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 145 p. 70 illus., 19 illus. in color.
Other physical details online resource.
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505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- General-Purpose Big Data Processing Systems -- Large-Scale Processing Systems of Structured Data -- Large-Scale Graph Processing Systems -- Large-Scale Stream Processing Systems -- Large-Scale Machine/Deep Learning Frameworks -- Conclusions and Outlook.
520 ## - SUMMARY, ETC.
Summary, etc This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information storage and retrieval systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Business information services.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Database management.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Information Storage and Retrieval.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element IT in Business.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Database Management.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030441869
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030441883
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030441890
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-44187-6">https://doi.org/10.1007/978-3-030-44187-6</a>
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Koha item type eBooks-CSE-Springer

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