90 research outputs found
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An effective data placement strategy for XML documents
As XML is increasingly being used in Web applications, new
technologies need to be investigated for processing XML documents with high
performance. Parallelism is a promising solution for structured document
processing and data placement is a major factor for system performance
improvement in parallel processing. This paper describes an effective XML
document data placement strategy. The new strategy is based on a multilevel
graph partitioning algorithm with the consideration of the unique features of
XML documents and query distributions. A new algorithm, which is based on
XML query schemas to derive the weighted graph from the labelled directed
graph presentation of XML documents, is also proposed. Performance analysis
on the algorithm presented in the paper shows that the new data placement
strategy exhibits low workload skew and a high degree of parallelism
The Sloan Digital Sky Survey Science Archive: Migrating a Multi-Terabyte Astronomical Archive from Object to Relational DBMS
The Sloan Digital Sky Survey Science Archive is the first in a series of
multi-Terabyte digital archives in Astronomy and other data-intensive sciences.
To facilitate data mining in the SDSS archive, we adapted a commercial database
engine and built specialized tools on top of it. Originally we chose an
object-oriented database management system due to its data organization
capabilities, platform independence, query performance and conceptual fit to
the data. However, after using the object database for the first couple of
years of the project, it soon began to fall short in terms of its query support
and data mining performance. This was as much due to the inability of the
database vendor to respond our demands for features and bug fixes as it was due
to their failure to keep up with the rapid improvements in hardware
performance, particularly faster RAID disk systems. In the end, we were forced
to abandon the object database and migrate our data to a relational database.
We describe below the technical issues that we faced with the object database
and how and why we migrated to relational technology
Prefetching techniques for client server object-oriented database systems
The performance of many object-oriented database applications suffers from the page fetch latency which is determined by the expense of disk access. In this work we suggest several prefetching techniques to avoid, or at least to reduce, page fetch latency. In practice no prediction technique is perfect and no prefetching technique can entirely eliminate delay due to page fetch latency. Therefore we are interested in the trade-off between the level of accuracy required for obtaining good results in terms of elapsed time reduction and the processing overhead needed to achieve this level of accuracy. If prefetching accuracy is high then the total elapsed time of an application can be reduced significantly otherwise if the prefetching accuracy is low, many incorrect pages are prefetched and the extra load on the client, network, server and disks decreases the whole system performance. Access pattern of object-oriented databases are often complex and usually hard to predict accurately. The ..
Three Denerations of DBMS
This paper describes the evolution of data base technology from early computing to the sophisticated systems of today. It presents an overview of the most popular data base management systems architectures such as hierarchical, network, relational and object-oriented. The last section of this paper presents a view of the factors that will influence the future of data base technology
VOODB: A Generic Discrete-Event Random Simulation Model to Evaluate the Performances of OODBs
International audiencePerformance of object-oriented database systems (OODBs) is still an issue to both designers and users nowadays. The aim of this paper is to propose a generic discrete-event random simulation model, called VOODB, in order to evaluate the performances of OODBs in general, and the performances of optimization methods like clustering in particular. Such optimization methods undoubtedly improve the performances of OODBs. Yet, they also always induce some kind of overhead for the system. Therefore, it is important to evaluate their exact impact on the overall performances. VOODB has been designed as a generic discrete-event random simulation model by putting to use a modelling approach, and has been validated by simulating the behavior of the O2 OODB and the Texas persistent object store. Since our final objective is to compare object clustering algorithms, some experiments have also been conducted on the DSTC clustering technique, which is implemented in Texas. To validate VOODB, performance results obtained by simulation for a given experiment have been compared to the results obtained by benchmarking the real systems in the same conditions. Benchmarking and simulation performance evaluations have been observed to be consistent, so it appears that simulation can be a reliable approach to evaluate the performances of OODBs
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