Decision support for management of parallel database systems

Howard Williams, Shaoyu Zhou, Hamish Taylor, Neven Tomov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
36 Downloads (Pure)

Abstract

Parallel database systems are generally recognised as one of the most important applications areas for commercial parallel systems. However, the task of managing the performance of a parallel database system is exceedingly complex. The initial choice of hardware configuration to support a particular DBMS application and the subsequent task of tuning the DBMS to improve the performance rely not only on the way in which the data is structured, but also on how it is fragmented, replicated and distributed across the processing elements of the system. To understand the behaviour of a particular application requires the study of large volumes of performance data. To simplify this process it is essential to provide some means of presenting performance data in a comprehensible form which will aid visualisation. This paper explores some of the issues relating to decision support for the performance management of parallel database systems and describes an analytical planning tool to assist users in this task.
Original languageEnglish
Title of host publicationProceedings of High Performance Computing and Networking
PublisherSpringer
Pages164-169
Number of pages6
VolumeLNCS 1067
ISBN (Print)3-540-61142-8
DOIs
Publication statusPublished - 1996

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag

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