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|a Web-Scale Data Management for the Cloud; Preface; Acknowledgements; Contents; Chapter1 Data Cloudification; 1.1 Big Data, Big Problems; 1.2 Classic Database Solutions as an Alternative; 1.3 Cloud Computing; 1.4 Data Management and Cloud Computing; 1.5 Summary; References; Chapter2 Virtualization for Data Management Services; 2.1 Core Concepts of Virtualization; 2.1.1 Limits of Virtualization; 2.1.2 Use Cases for Virtualization; 2.1.3 Summary; 2.2 Virtualization Stack; 2.3 Hardware Virtualization; 2.3.1 Machine Virtualization; 2.3.2 Virtual Storage; 2.4 Schema Virtualization; 2.4.1 Sharing
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|a 2.4.2 Customization2.5 Configuring the Virtualization; 2.6 Summary; References; Chapter3 Transactional Data Management Services for the Cloud; 3.1 Foundations; 3.1.1 Transaction Processing; 3.1.2 Brewer's CAP Theorem and the BASE Principle; 3.2 Consistency Models; 3.3 Data Fragmentation; 3.3.1 Classification of Fragmentation Strategies; 3.3.2 Horizontal Versus Vertical Fragmentation; 3.3.3 Consistent Hashing; 3.4 Data Replication; 3.4.1 Classification of Replication Strategies; 3.4.2 Classic Replication Protocols; 3.4.3 Optimistic Replication; 3.4.4 Conflict Detection and Repair
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|a 3.4.5 Epidemic Propagation3.5 Consensus Protocols; 3.6 Summary; References; Chapter4 Web-Scale Analytics for BIG Data; 4.1 Foundations; 4.1.1 Query Processing; 4.1.2 Parallel Data Processing; 4.1.3 Fault Tolerance; 4.2 The MapReduce Paradigm; 4.2.1 The MapReduce Programming Model; 4.2.1.1 Basic MapReduce Programming; 4.2.2 The MapReduce Execution Model; 4.2.3 Expressing Relational Operators in MapReduce; 4.2.4 Expressing Complex Operators in MapReduce; 4.2.5 MapReduce Shortcomings and Enhancements; 4.2.6 Alternative Model: DAG Dataflows; 4.3 Declarative Query Languages; 4.3.1 Pig; 4.3.2 JAQL
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|a 4.3.3 Hive4.4 Summary; References; Chapter5 Cloud-Specific Services for Data Management; 5.1 Service Level Agreements; 5.1.1 The Notion of QoS and SLA; 5.1.2 QoS in Data Management; 5.1.3 Workload Management; 5.1.4 Resource Provisioning; 5.2 Pricing Models for Cloud Systems; 5.2.1 Cost Types; 5.2.2 Subscription Types; 5.3 Security in Outsourced Data Management; 5.3.1 Secure Joins; 5.3.2 Secure Aggregation and Selection; 5.3.3 Secure Range Queries; 5.4 Summary; References; Chapter6 Overview and Comparison of Current Database-as-a-Service Systems; 6.1 Infrastructure-as-a-Service
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|a 6.1.1 Amazon Elastic Compute Cloud6.1.2 Further IaaS Solutions; 6.2 Platform-as-a-Service; 6.2.1 Amazon S3, DynamoDB, and RDS; 6.2.2 Amazon Elastic MapReduce; 6.2.3 Microsoft Windows Azure; 6.3 Software- and Data-as-a-Service; 6.3.1 The Open Data Trend; 6.3.2 Data Markets and Pricing models; 6.3.3 Beyond ``Data-as-a-Service''; 6.4 Summary; References; Chapter7 Summary and Outlook; 7.1 Outlook, Current Trends, and Some Challenges; 7.2 … the End; References
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|a The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and se
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Web-Scale Data Management for the Cloud; Preface; Acknowledgements; Contents; Chapter1 Data Cloudification; 1.1 Big Data, Big Problems; 1.2 Classic Database Solutions as an Alternative; 1.3 Cloud Computing; 1.4 Data Management and Cloud Computing; 1.5 Summary; References; Chapter2 Virtualization for Data Management Services; 2.1 Core Concepts of Virtualization; 2.1.1 Limits of Virtualization; 2.1.2 Use Cases for Virtualization; 2.1.3 Summary; 2.2 Virtualization Stack; 2.3 Hardware Virtualization; 2.3.1 Machine Virtualization; 2.3.2 Virtual Storage; 2.4 Schema Virtualization; 2.4.1 Sharing, 2.4.2 Customization2.5 Configuring the Virtualization; 2.6 Summary; References; Chapter3 Transactional Data Management Services for the Cloud; 3.1 Foundations; 3.1.1 Transaction Processing; 3.1.2 Brewer's CAP Theorem and the BASE Principle; 3.2 Consistency Models; 3.3 Data Fragmentation; 3.3.1 Classification of Fragmentation Strategies; 3.3.2 Horizontal Versus Vertical Fragmentation; 3.3.3 Consistent Hashing; 3.4 Data Replication; 3.4.1 Classification of Replication Strategies; 3.4.2 Classic Replication Protocols; 3.4.3 Optimistic Replication; 3.4.4 Conflict Detection and Repair, 3.4.5 Epidemic Propagation3.5 Consensus Protocols; 3.6 Summary; References; Chapter4 Web-Scale Analytics for BIG Data; 4.1 Foundations; 4.1.1 Query Processing; 4.1.2 Parallel Data Processing; 4.1.3 Fault Tolerance; 4.2 The MapReduce Paradigm; 4.2.1 The MapReduce Programming Model; 4.2.1.1 Basic MapReduce Programming; 4.2.2 The MapReduce Execution Model; 4.2.3 Expressing Relational Operators in MapReduce; 4.2.4 Expressing Complex Operators in MapReduce; 4.2.5 MapReduce Shortcomings and Enhancements; 4.2.6 Alternative Model: DAG Dataflows; 4.3 Declarative Query Languages; 4.3.1 Pig; 4.3.2 JAQL, 4.3.3 Hive4.4 Summary; References; Chapter5 Cloud-Specific Services for Data Management; 5.1 Service Level Agreements; 5.1.1 The Notion of QoS and SLA; 5.1.2 QoS in Data Management; 5.1.3 Workload Management; 5.1.4 Resource Provisioning; 5.2 Pricing Models for Cloud Systems; 5.2.1 Cost Types; 5.2.2 Subscription Types; 5.3 Security in Outsourced Data Management; 5.3.1 Secure Joins; 5.3.2 Secure Aggregation and Selection; 5.3.3 Secure Range Queries; 5.4 Summary; References; Chapter6 Overview and Comparison of Current Database-as-a-Service Systems; 6.1 Infrastructure-as-a-Service, 6.1.1 Amazon Elastic Compute Cloud6.1.2 Further IaaS Solutions; 6.2 Platform-as-a-Service; 6.2.1 Amazon S3, DynamoDB, and RDS; 6.2.2 Amazon Elastic MapReduce; 6.2.3 Microsoft Windows Azure; 6.3 Software- and Data-as-a-Service; 6.3.1 The Open Data Trend; 6.3.2 Data Markets and Pricing models; 6.3.3 Beyond ``Data-as-a-Service''; 6.4 Summary; References; Chapter7 Summary and Outlook; 7.1 Outlook, Current Trends, and Some Challenges; 7.2 … the End; References, The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and se |
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Lehner, Wolfgang aut, Web-scale data management for the cloud Wolfgang Lehner; Kai-Uwe Sattler, New York [u.a.] Springer 2013, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, EBL-Schweitzer, Description based upon print version of record, Web-Scale Data Management for the Cloud; Preface; Acknowledgements; Contents; Chapter1 Data Cloudification; 1.1 Big Data, Big Problems; 1.2 Classic Database Solutions as an Alternative; 1.3 Cloud Computing; 1.4 Data Management and Cloud Computing; 1.5 Summary; References; Chapter2 Virtualization for Data Management Services; 2.1 Core Concepts of Virtualization; 2.1.1 Limits of Virtualization; 2.1.2 Use Cases for Virtualization; 2.1.3 Summary; 2.2 Virtualization Stack; 2.3 Hardware Virtualization; 2.3.1 Machine Virtualization; 2.3.2 Virtual Storage; 2.4 Schema Virtualization; 2.4.1 Sharing, 2.4.2 Customization2.5 Configuring the Virtualization; 2.6 Summary; References; Chapter3 Transactional Data Management Services for the Cloud; 3.1 Foundations; 3.1.1 Transaction Processing; 3.1.2 Brewer's CAP Theorem and the BASE Principle; 3.2 Consistency Models; 3.3 Data Fragmentation; 3.3.1 Classification of Fragmentation Strategies; 3.3.2 Horizontal Versus Vertical Fragmentation; 3.3.3 Consistent Hashing; 3.4 Data Replication; 3.4.1 Classification of Replication Strategies; 3.4.2 Classic Replication Protocols; 3.4.3 Optimistic Replication; 3.4.4 Conflict Detection and Repair, 3.4.5 Epidemic Propagation3.5 Consensus Protocols; 3.6 Summary; References; Chapter4 Web-Scale Analytics for BIG Data; 4.1 Foundations; 4.1.1 Query Processing; 4.1.2 Parallel Data Processing; 4.1.3 Fault Tolerance; 4.2 The MapReduce Paradigm; 4.2.1 The MapReduce Programming Model; 4.2.1.1 Basic MapReduce Programming; 4.2.2 The MapReduce Execution Model; 4.2.3 Expressing Relational Operators in MapReduce; 4.2.4 Expressing Complex Operators in MapReduce; 4.2.5 MapReduce Shortcomings and Enhancements; 4.2.6 Alternative Model: DAG Dataflows; 4.3 Declarative Query Languages; 4.3.1 Pig; 4.3.2 JAQL, 4.3.3 Hive4.4 Summary; References; Chapter5 Cloud-Specific Services for Data Management; 5.1 Service Level Agreements; 5.1.1 The Notion of QoS and SLA; 5.1.2 QoS in Data Management; 5.1.3 Workload Management; 5.1.4 Resource Provisioning; 5.2 Pricing Models for Cloud Systems; 5.2.1 Cost Types; 5.2.2 Subscription Types; 5.3 Security in Outsourced Data Management; 5.3.1 Secure Joins; 5.3.2 Secure Aggregation and Selection; 5.3.3 Secure Range Queries; 5.4 Summary; References; Chapter6 Overview and Comparison of Current Database-as-a-Service Systems; 6.1 Infrastructure-as-a-Service, 6.1.1 Amazon Elastic Compute Cloud6.1.2 Further IaaS Solutions; 6.2 Platform-as-a-Service; 6.2.1 Amazon S3, DynamoDB, and RDS; 6.2.2 Amazon Elastic MapReduce; 6.2.3 Microsoft Windows Azure; 6.3 Software- and Data-as-a-Service; 6.3.1 The Open Data Trend; 6.3.2 Data Markets and Pricing models; 6.3.3 Beyond ``Data-as-a-Service''; 6.4 Summary; References; Chapter7 Summary and Outlook; 7.1 Outlook, Current Trends, and Some Challenges; 7.2 … the End; References, The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and se, Online-Ausg. [S.l.] eblib 2013 Online-Ressource |2013||||||||||, Cloud computing, Computer science, Database management, Information systems, Electronic books, s (DE-588)4113276-2 (DE-627)105830550 (DE-576)209475145 Datenbanksystem gnd, s (DE-588)7623494-0 (DE-627)577000314 (DE-576)285431765 Cloud Computing gnd, s (DE-588)4839180-3 (DE-627)497288176 (DE-576)217076009 Virtualisierung gnd, s (DE-588)7666250-0 (DE-627)605282293 (DE-576)308898303 SaaS Software gnd, s (DE-588)4274324-2 (DE-627)104467525 (DE-576)21070585X Computersicherheit gnd, (DE-627), Sattler, Kai-Uwe 1968- (DE-588)120420392 (DE-627)080664091 (DE-576)17884845X oth, 9781461468561, Druckausg. Lehner, Wolfgang, 1969 - Web-scale data management for the cloud New York, NY [u.a.] : Springer, 2013 XV, 193 S. (DE-627)74396537X (DE-576)381789187 9781461468554, http://swb.eblib.com/patron/FullRecord.aspx?p=1205361 Verlag Volltext, https://swbplus.bsz-bw.de/bsz381789187inh.htm V:DE-576;B:DE-Mit1 application/pdf 20150616155251 Inhaltsverzeichnis |
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Lehner, Wolfgang, Web-scale data management for the cloud, Web-Scale Data Management for the Cloud; Preface; Acknowledgements; Contents; Chapter1 Data Cloudification; 1.1 Big Data, Big Problems; 1.2 Classic Database Solutions as an Alternative; 1.3 Cloud Computing; 1.4 Data Management and Cloud Computing; 1.5 Summary; References; Chapter2 Virtualization for Data Management Services; 2.1 Core Concepts of Virtualization; 2.1.1 Limits of Virtualization; 2.1.2 Use Cases for Virtualization; 2.1.3 Summary; 2.2 Virtualization Stack; 2.3 Hardware Virtualization; 2.3.1 Machine Virtualization; 2.3.2 Virtual Storage; 2.4 Schema Virtualization; 2.4.1 Sharing, 2.4.2 Customization2.5 Configuring the Virtualization; 2.6 Summary; References; Chapter3 Transactional Data Management Services for the Cloud; 3.1 Foundations; 3.1.1 Transaction Processing; 3.1.2 Brewer's CAP Theorem and the BASE Principle; 3.2 Consistency Models; 3.3 Data Fragmentation; 3.3.1 Classification of Fragmentation Strategies; 3.3.2 Horizontal Versus Vertical Fragmentation; 3.3.3 Consistent Hashing; 3.4 Data Replication; 3.4.1 Classification of Replication Strategies; 3.4.2 Classic Replication Protocols; 3.4.3 Optimistic Replication; 3.4.4 Conflict Detection and Repair, 3.4.5 Epidemic Propagation3.5 Consensus Protocols; 3.6 Summary; References; Chapter4 Web-Scale Analytics for BIG Data; 4.1 Foundations; 4.1.1 Query Processing; 4.1.2 Parallel Data Processing; 4.1.3 Fault Tolerance; 4.2 The MapReduce Paradigm; 4.2.1 The MapReduce Programming Model; 4.2.1.1 Basic MapReduce Programming; 4.2.2 The MapReduce Execution Model; 4.2.3 Expressing Relational Operators in MapReduce; 4.2.4 Expressing Complex Operators in MapReduce; 4.2.5 MapReduce Shortcomings and Enhancements; 4.2.6 Alternative Model: DAG Dataflows; 4.3 Declarative Query Languages; 4.3.1 Pig; 4.3.2 JAQL, 4.3.3 Hive4.4 Summary; References; Chapter5 Cloud-Specific Services for Data Management; 5.1 Service Level Agreements; 5.1.1 The Notion of QoS and SLA; 5.1.2 QoS in Data Management; 5.1.3 Workload Management; 5.1.4 Resource Provisioning; 5.2 Pricing Models for Cloud Systems; 5.2.1 Cost Types; 5.2.2 Subscription Types; 5.3 Security in Outsourced Data Management; 5.3.1 Secure Joins; 5.3.2 Secure Aggregation and Selection; 5.3.3 Secure Range Queries; 5.4 Summary; References; Chapter6 Overview and Comparison of Current Database-as-a-Service Systems; 6.1 Infrastructure-as-a-Service, 6.1.1 Amazon Elastic Compute Cloud6.1.2 Further IaaS Solutions; 6.2 Platform-as-a-Service; 6.2.1 Amazon S3, DynamoDB, and RDS; 6.2.2 Amazon Elastic MapReduce; 6.2.3 Microsoft Windows Azure; 6.3 Software- and Data-as-a-Service; 6.3.1 The Open Data Trend; 6.3.2 Data Markets and Pricing models; 6.3.3 Beyond ``Data-as-a-Service''; 6.4 Summary; References; Chapter7 Summary and Outlook; 7.1 Outlook, Current Trends, and Some Challenges; 7.2 … the End; References, The efficient management of a consistent and integrated database is a central task in modern IT and highly relevant for science and industry. Hardly any critical enterprise solution comes without any functionality for managing data in its different forms. Web-Scale Data Management for the Cloud addresses fundamental challenges posed by the need and desire to provide database functionality in the context of the Database as a Service (DBaaS) paradigm for database outsourcing. This book also discusses the motivation of the new paradigm of cloud computing, and its impact to data outsourcing and se, Cloud computing, Computer science, Database management, Information systems, Electronic books, Datenbanksystem, Cloud Computing, Virtualisierung, SaaS Software, Computersicherheit |
| title |
Web-scale data management for the cloud |
| title_auth |
Web-scale data management for the cloud |
| title_full |
Web-scale data management for the cloud Wolfgang Lehner; Kai-Uwe Sattler |
| title_fullStr |
Web-scale data management for the cloud Wolfgang Lehner; Kai-Uwe Sattler |
| title_full_unstemmed |
Web-scale data management for the cloud Wolfgang Lehner; Kai-Uwe Sattler |
| title_short |
Web-scale data management for the cloud |
| title_sort |
web-scale data management for the cloud |
| title_unstemmed |
Web-scale data management for the cloud |
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Cloud computing, Computer science, Database management, Information systems, Electronic books, Datenbanksystem, Cloud Computing, Virtualisierung, SaaS Software, Computersicherheit |
| topic_facet |
Cloud computing, Computer science, Database management, Information systems, Electronic books, Datenbanksystem, Cloud Computing, Virtualisierung, SaaS, Computersicherheit |
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http://swb.eblib.com/patron/FullRecord.aspx?p=1205361, https://swbplus.bsz-bw.de/bsz381789187inh.htm |
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AT lehnerwolfgang webscaledatamanagementforthecloud, AT sattlerkaiuwe webscaledatamanagementforthecloud |