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- ZeitschriftenartikelIterative Computation of Connected Graph Components with MapReduce(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Kolb, Lars; Sehili, Ziad; Rahm, ErhardThe use of the MapReduce framework for iterative graph algorithms is challenging. To achieve high performance it is critical to limit the amount of intermediate results as well as the number of necessary iterations. We address these issues for the important problem of finding connected components in large graphs. We analyze an existing MapReduce algorithm, CC-MR, and present techniques to improve its performance including a memory-based connection of subgraphs in the map phase. Our evaluation with several large graph datasets shows that the improvements can substantially reduce the amount of generated data by up to a factor of 8.8 and runtime by up to factor of 3.5.
- ZeitschriftenartikelUnleashing XQuery for Data-Independent Programming(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Bächle, Sebastian; Sauer, CaetanoThe XQuery language was initially developed as an SQL equivalent for XML data, but its roots in functional programming make it also a perfect choice for processing almost any kind of structured and semi-structured data. Apart from standard XML processing, however, advanced language features make it hard to efficiently implement the complete language for large data volumes. This work proposes a novel compilation strategy that provides both flexibility and efficiency to unleash XQuery’s potential as data programming language. It combines the simplicity and versatility of a storage-independent data abstraction with the scalability advantages of set-oriented processing. Expensive iterative sections in a query are unrolled to a pipeline of relational-style operators, which is open for optimized join processing, index use, and parallelization. The remaining aspects of the language are processed in a standard fashion, yet can be compiled anytime to more efficient native operations of the actual runtime environment. This hybrid compilation mechanism yields an efficient and highly flexible query engine that is able to drive any computation from simple XML transformation to complex data analysis, even on non-XML data. Experiments with our prototype and state-of-the-art competitors in classic XML query processing and business analytics over relational data attest the generality and efficiency of the design.
- ZeitschriftenartikelDissertationen(Datenbank-Spektrum: Vol. 14, No. 2, 2014)
- ZeitschriftenartikelA Real-time Materialized View Approach for Analytic Flows in Hybrid Cloud Environments(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Qu, Weiping; Dessloch, StefanNext-generation business intelligence (BI) enables enterprises to quickly react in changing business environments. Increasingly, data integration pipelines need to be merged with query pipelines for real-time analytics from operational data. Newly emerging hybrid analytic flows have been becoming attractive which consist of a set of extract-transform-load (ETL) jobs together with analytic jobs running over multiple platforms with different functionality.In traditional databases, materialized views are used to optimize query performance. In cross-platform, large-scale data transformation environments, similar challenges (e.g. view selection) arise when using materialized views. In this work, we propose an approach that generates materialized views in hybrid flows and maintains these views in a query-driven, incremental manner. To accelerate data integration processes, the location of a materialization point in a transformation flow varies dynamically based on metrics like source update rates and maintenance cost in terms of flow operations. Besides, by picking up the most suitable platform for accommodating views, for example, materializing and maintaining intermediate results of Hadoop jobs in relational databases, better performance has been shown.
- ZeitschriftenartikelDatenbank-Forschung am Lehrstuhl für Informatik 6 (Datenmanagement) der Friedrich-Alexander-Universität Erlangen-Nürnberg(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Meyer-Wegener, Klaus; Lenz, RichardDer Lehrstuhl für Informatik 6 (Datenmanagement) an der FAU Erlangen-Nürnberg beschäftigt sich mit evolutionären Informationssystemen, Datenqualität, Multimedia-Datenbanken, Datenstromverarbeitung und Ereigniserkennung. Er wird geleitet von den beiden Profs. Meyer-Wegener und Lenz. In der Lehre deckt er das Gebiet der Datenbanksysteme in seiner ganzen Breite ab und bezieht verschiedene Anwendungsbereiche ein, nicht zuletzt die Medizin.
- ZeitschriftenartikelDatenbanken ohne Schema?(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Klettke, Meike; Scherzinger, Stefanie; Störl, UtaIn der Entwicklung von interaktiven Web-Anwendungen sind NoSQL-Datenbanksysteme zunehmend beliebt, nicht zuletzt, weil sie flexible Datenmodelle erlauben. Das erleichtert insbesondere ein agiles Projektmanagement, das sich durch häufige Releases und entsprechend häufige Änderungen am Datenmodell auszeichnet. In diesem Artikel geben wir einen Überblick über die besonderen Herausforderungen der agilen Anwendungsentwicklung gegen schemalose NoSQL-Datenbanksysteme. Wir stellen Strategien für die Schema-Evolution aus der Praxis vor, und postulieren unsere Vision einer eigenen Schema-Management-Komponente für NoSQL-Datenbanksysteme, die für eine kontinuierliche und systematische Schema-Evolution ausgelegt ist.
- ZeitschriftenartikelCloud-Technologien in der Hochschullehre – Pflicht oder Kür?(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Scherzinger, Stefanie; Thor, AndreasEin eigenes Themenheft zum Datenmanagement in der Cloud dient uns als Anlass, die Präsenz von Cloud-Themen in der akademischen Datenbanklehre zu erfassen. In diesem Artikel geben wir die Ergebnisse einer Umfrage innerhalb der Fachgruppe Datenbanksysteme durch den Arbeitskreis Datenmanagement in der Cloud wieder. Dozentinnen und Dozenten von über zwanzig Hochschulen nahmen an der Umfrage teil. Es zeigt sich deutlich, dass sich das Thema „Cloud“ in der Hochschullehre zunehmend etabliert, jedoch überwiegend als ergänzendes Angebot, und seltener in der grundständigen Lehre verankert. Wir fassen die Ergebnisse unserer Umfrage zusammen und wagen Deutungsversuche.
- ZeitschriftenartikelNews(Datenbank-Spektrum: Vol. 14, No. 2, 2014)
- ZeitschriftenartikelEditorial(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Thor, Andreas; Scherzinger, Stefanie; Specht, Günther
- ZeitschriftenartikelDatabase Backend as a Service: Automatic Generation, Deployment, and Management of Database Backends for Mobile Applications(Datenbank-Spektrum: Vol. 14, No. 2, 2014) Gropengießer, Francis; Sattler, Kai-UweManaging data in the Cloud is a challenging task, especially scaling resources in order to prevent under- and over-provisioning. In this paper, we consider a specific domain of applications, namely mobile applications for events like conferences or festivals, where automatic managing and scaling the backend part of the application would be beneficial in terms of efficient resource utilization as well as a good end-user experience. In order to achieve this, we make the following contributions. We automate generation, deployment, operation, and management of the backend in an Infrastructure as a Service Cloud. Thereby, we address the fluctuating load characteristics of mobile applications for events by applying our monitoring and autoscaling framework based on data stream processing and complex event processing.