In-Memory Data Management : Technology and Applications

by Hasso Plattner, Alexander Zeier

1. Introduction. Lloyd Strickland, Julia Weckend -- Section 1: Science. 2. Philosophy and science in Leibniz. Maria Rosa Antognazza -- 3. Between learned science and technical knowledge: Leibniz, Leeuwenhoek and the school for microscopists. Alessandro Becchi -- 4. Leibniz, organic matter and astrobiology. Richard T. W. Arthur -- Section 2: Metaphysics. 5. Plenitude and mirrors of God in Leibniz. Nicholas Jolley -- 6. As matter to form so passive to active? The irreducible metaphysics of Leibniz’s Dynamics. Tzuchien Tho -- 7. Conceptual analysis and ontology in the Leibniz - De Volder correspondence. Stefano di Bella -- Section 3: Epistemology. 8. Leibniz’s empirical, not empiricist methodology. Dale Jacquette -- 9. Leibniz on certainty. Julia Weckend -- 10. Leibniz and probability in the moral domain. Chris Meyns -- Section 4: Religion and Theology. 11. How Leibniz would have responded to the Lisbon earthquake. Lloyd Strickland -- 12. Leibniz on the efficacy and economy of divine grace. Agustín Echavarría -- 13. Eternal punishment, universal salvation and pragmatic theology in Leibniz. Paul Lodge -- Biographical conclusion. 14. In the “hinterland” of globalization? Leibniz and the European expansion. Michael Kempe -- Index

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Year of publication:	2012 ; 2nd ed. 2012
Authors:	Plattner, Hasso
Other Persons:	Zeier, Alexander (contributor)
Publisher:	Berlin, Heidelberg : Springer Berlin Heidelberg
Subject:	Betriebliches Informationssystem \| Datenmanagement \| In-Memory-Datenbank
Description of contents:	Abstract [springer.com]

Extent:	Online-Ressource (XXXIV, 267p. 99 illus, digital)
Series:	SpringerLink / Bücher
Type of publication:	Book / Working Paper
Language:	English
Notes:	Description based upon print version of record In-Memory Data Management; In Praise of ''In-Memory Data Management''; Foreword; Preface; The Essence of In-Memory Data Management; Contents; Acronyms; Introduction; Part I An Inflection Point for Enterprise Applications; 1 Desirability, Feasibility, Viability: The Impact of In-Memory; 1.1 Information in Real Time: Anything, Anytime, Anywhere; 1.1.1 Response Time at the Speed of Thought; 1.1.2 Real-Time Analytics and Computation on the Fly; 1.2 The Impact of Recent Hardware Trends; 1.2.1 Database Management Systems for Enterprise Applications; 1.2.2 Main Memory is the New Disk 1.2.3 From Maximizing CPU Speed to Multi-Core Processors1.2.4 Increased Bandwidth Between CPU and Main Memory; 1.3 Reducing Cost Through In-Memory Data Management; 1.3.1 Total Cost of Ownership; 1.3.2 Cost Factors in Enterprise Systems; 1.3.3 In-Memory Performance Boosts Cost Reduction; 1.4 Conclusion; 2 Why Are Enterprise Applications So Diverse?; 2.1 Current Enterprise Applications; 2.2 Examples of Enterprise Applications; 2.3 Enterprise Application Architecture; 2.4 Data Processing in Enterprise Applications; 2.5 Data Access Patterns in Enterprise Applications; 2.6 Conclusion 3 SanssouciDB: Blueprint for an In-Memory Enterprise Database System3.1 Targeting Multi-Core and Main Memory; 3.2 Designing an In-Memory Database System; 3.3 Organizing and Accessing Data in SanssouciDB; 3.4 Conclusion; Part II SanssouciDB: A Single Source of TruthThrough In-Memory; 4 The Technical Foundations of SanssouciDB; 4.1 Understanding Memory Hierarchies; 4.1.1 Introduction to Main Memory; 4.1.2 Organization of the Memory Hierarchy; 4.1.3 Trends in Memory Hierarchies; 4.1.4 Memory from a Programmer's Point of View; 4.2 Parallel Data Processing Using Multi-Core and Across Servers 4.2.1 Increasing Capacity by Adding Resources4.2.2 Parallel System Architectures; 4.2.3 Parallelization in Databases for Enterprise Applications; 4.2.4 Parallel Data Processing in SanssouciDB; 4.3 Compression for Speed and Memory Consumption; 4.3.1 Light-Weight Compression; 4.3.2 Heavy-Weight Compression; 4.3.3 Data-Dependent Optimization; 4.3.4 Compression-Aware Query Execution; 4.3.5 Compression Analysis on Real Data; 4.4 Column, Row, Hybrid: Optimizing the Data Layout; 4.4.1 Vertical Partitioning; 4.4.2 Finding the Best Layout; 4.4.3 Challenges for Hybrid Databases 4.4.4 Application Scenarios4.5 The Impact of Virtualization; 4.5.1 Virtualizing Analytical Workloads; 4.5.2 Data Model and Benchmarking Environment; 4.5.3 Virtual Versus Native Execution; 4.5.4 Response Time Degradation with Concurrent VMs; 4.6 Summarizing the Technical Concepts; 4.7 Conclusion; 5 Organizing and Accessing Data in SanssouciDB; 5.1 SQL for Accessing In-Memory Data; 5.1.1 The Role of SQL; 5.1.2 The Lifecycle of a Query; 5.1.3 Stored Procedures; 5.1.4 Data Organization and Indices; 5.1.5 Any Attributes as Index; 5.2 Increasing Performance with Data Aging 5.2.1 Active and Passive Data
ISBN:	978-3-642-29575-1 ; 978-3-642-29574-4
Other identifiers:	10.1007/978-3-642-29575-1 [DOI]
Classification:	Datenbanken ; Betriebliche Information und Kommunikation
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014015832