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Data warehouse queries pose challenging performance problems that often necessitate the use of parallel database systems (PDBS). Although dynamic load balancing is of key importance in PDBS, to our knowledge it has not yet been investigated thoroughly for parallel data warehouses. In this study, we propose a scheduling strategy that simultaneously considers both processors and disks while utilizing...
In data intensive applications, both programming and declarative query languages have attractions, the former in comprehensiveness and the latter for ease of use. Databases sometimes support the calling of side-effect free user defined functions from within declarative queries. As well as enabling more efficient coding of computationally intensive functions, this provision not only moves computation...
The retrieval of images in remote sensing databases is based on world-oriented information like the location of the scene, the utilised scanner, and the date of acquisition. However, these descriptions are not meaningful for many users who have a limited knowledge about remote sensing but nevertheless have to work with satellite imagery. Therefore a content-based dynamic retrieval technique using...
Decision tree construction is a very well studied problem in data mining, machine learning, and statistics communities [3,2,7,8,9]. The input to a decision tree construction algorithm is a database of training records. Each record has several attributes. An attribute whose underlying domain is totally ordered is called a numerical attribute. Other attributes are called categorical attributes. One...
Using a public domain version of a commercial clustered database server and TPC-H like decision support queries, this paper studies the performance and scalability issues of a Pentium/Linux cluster and an 8-way Linux SMP. The execution profile demonstrates the dominance of the I/O subsystem in the execution, and the importance of the communication subsystem for cluster scalability. In addition to...
The parallel fuzzy c-means (PFCM) algorithm for clustering large data sets is proposed in this paper. The proposed algorithm is designed to run on parallel computers of the Single Program Multiple Data (SPMD) model type with the Message Passing Interface (MPI). A comparison is made between PFCM and an existing parallel k-means (PKM) algorithm in terms of their parallelisation capability and scalability...
Increasingly the datasets used for data mining are becoming huge and physically distributed. Since the distributed knowledge discovery process is both data and computational intensive, the Grid is a natural platform for deploying a high performance data mining service. The focus of this paper is on the core services of such a Grid infrastructure. In particular we concentrate our attention on the design...
In this paper, we devise a “temporally reordering” mechanism of supporting update transactions that are impacted by delays (e.g., network delays) to the extent that they cannot be executed because of the irreversible progress of other conflicting transactions (i.e., data dependent and temporally dependant) extend this scheme with a delayed-initiation mechanism. This mechanism allows (a) the impacted...
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