LEADER 04730nam 22006255 450 001 996465363103316 005 20240415225310.0 010 $a3-030-44187-3 024 7 $a10.1007/978-3-030-44187-6 035 $a(CKB)4100000011343279 035 $a(DE-He213)978-3-030-44187-6 035 $a(MiAaPQ)EBC6273788 035 $a(PPN)258876581 035 $a(EXLCZ)994100000011343279 100 $a20200709d2020 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data 2.0 Processing Systems$b[electronic resource] $eA Systems Overview /$fby Sherif Sakr 205 $a2nd ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XVI, 145 p. 70 illus., 19 illus. in color.) 311 $a3-030-44186-5 320 $aIncludes bibliographical references. 327 $aIntroduction -- 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. 330 $aThis 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. 606 $aInformation organization 606 $aInformation technology 606 $aBusiness$xData processing 606 $aMachine learning 606 $aDatabase management 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 615 0$aInformation organization. 615 0$aInformation technology. 615 0$aBusiness$xData processing. 615 0$aMachine learning. 615 0$aDatabase management. 615 14$aInformation Storage and Retrieval. 615 24$aIT in Business. 615 24$aMachine Learning. 615 24$aDatabase Management. 676 $a005.7 700 $aSakr$b Sherif$4aut$4http://id.loc.gov/vocabulary/relators/aut$0866736 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465363103316 996 $aBig Data 2.0 Processing Systems$91953983 997 $aUNISA