High Performance Analytics R3 Cache by Sayeed Ruhan (6 results)

Taschenbuch. Condition: Neu. High performance analytics with the R3-cache | Data-warehouse caching using Relational OLAP | Ruhan Sayeed | Taschenbuch | 104 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838376127 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Contemporary data warehouses now represent some of the world's largest databases. As these systems grow in size and complexity, however, it becomes increasingly difficult for brute force query processing approaches to meet the performance demands of end users. In this paper, we describe the R3-cache, a natively multi-dimensional caching framework designed specifically to support sophisticated warehouse/OLAP environments. R3-cache is based upon an in-memory version of the R-tree that has been extended to support buffer pages rather than disk blocks. A key strength of the R 3-cache is that it is able to utilize multi-dimensional fragments of previous query results so as to significantly minimize the frequency and scale of disk accesses. Moreover, the new caching model directly accommodates the standard relational storage model and provides mechanisms for pro-active updates that exploit the existence of query 'hot spots'. The current prototype has been evaluated as a component of the Sidera DBMS, a 'shared nothing' parallel OLAP server designed for multi-terabyte analytics. Experimental results demonstrate significant performance improvements relative to simpler alternatives. 104 pp. Englisch.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sayeed RuhanRuhan Sayeed is currently working as a Software Engineer in Montreal, Canada. Before joining the software industry, he completed his Masters thesis under the supervision of Professor Todd Eavis from Concordia University. .…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Contemporary data warehouses now represent some of the world''s largest databases. As these systems grow in size and complexity, however, it becomes increasingly difficult for brute force query processing approaches to meet the performance demands of end users. In this paper, we describe the R3-cache, a natively multi-dimensional caching framework designed specifically to support sophisticated warehouse/OLAP environments. R3-cache is based upon an in-memory version of the R-tree that has been extended to support buffer pages rather than disk blocks. A key strength of the R 3-cache is that it is able to utilize multi-dimensional fragments of previous query results so as to significantly minimize the frequency and scale of disk accesses. Moreover, the new caching model directly accommodates the standard relational storage model and provides mechanisms for pro-active updates that exploit the existence of query 'hot spots'. The current prototype has been evaluated as a component of the Sidera DBMS, a 'shared nothing' parallel OLAP server designed for multi-terabyte analytics. Experimental results demonstrate significant performance improvements relative to simpler alternatives.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Contemporary data warehouses now represent some of the world's largest databases. As these systems grow in size and complexity, however, it becomes increasingly difficult for brute force query processing approaches to meet the performance demands of end users. In this paper, we describe the R3-cache, a natively multi-dimensional caching framework designed specifically to support sophisticated warehouse/OLAP environments. R3-cache is based upon an in-memory version of the R-tree that has been extended to support buffer pages rather than disk blocks. A key strength of the R 3-cache is that it is able to utilize multi-dimensional fragments of previous query results so as to significantly minimize the frequency and scale of disk accesses. Moreover, the new caching model directly accommodates the standard relational storage model and provides mechanisms for pro-active updates that exploit the existence of query 'hot spots'. The current prototype has been evaluated as a component of the Sidera DBMS, a 'shared nothing' parallel OLAP server designed for multi-terabyte analytics. Experimental results demonstrate significant performance improvements relative to simpler alternatives.…