O. Gunther et al. Benchmarking Spatial Joins A La Carte. SSDBM'98, pp. 32--41. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
A Framework for Generating Network-Based Moving Objects - Brinkhoff (2002) (8 citations) (Correct)
....operations and spatial queries as well as of different real datasets including raster data, point data, polygon data, and directed graph data. Primary goal of the benchmark is to target the needs of earth scientists but also other engineering and scientific users should be addressed. Gnther et al. [5] propose a WWW based data generator in order to benchmark spatial joins. Apart from synthetic data, also real data from the SEQUOIA 2000 Storage Benchmark are added to this benchmark. 5 2.2 Generating Spatiotemporal Objects The experimental investigation of spatiotemporal database systems is a ....
O. Gnther, V. Oria, P. Picouet, and J.-M. Saglio, M. Scholl. Benchmarking Spatial Joins La Carte, in Proceedings 10 International Conference on Scientific and Statistical Database Management, Capri, Italy, pp. 32-41, 1998.
R-Tree Based Indexing of General Spatio-Temporal Data - Saltenis, Jensen (1999) (1 citation) (Correct)
....intervals meet, yielding at most one spatial value at each point in time, and for the transaction time intervals, TT a = UC. The spatial value associated with the first valid time interval in a history is taken from a set of spatial values generated using the A La Carte spatial data generator [5]. This set contains 2000 rectangles generated in an area spanning 20000 units in the x and y dimensions. The spatial density is set to 1, and the distribution of the bottom left corners of the rectangles is uniform. Point data is obtained by taking the bottom left corners of the rectangles. The ....
O. Gunther et al. Benchmarking Spatial Joins A La Carte. SSDBM'98, pp. 32--41.
The Sort/Sweep Algorithm: A New Method for R-tree Based.. - Gurret, Rigaux (Correct)
....a LRU buffer whose size ranges from 400K (100 pages) to 2.8MB (700 pages) We use synthetic and real life datasets (see below) each being indexed with an R tree. The fanout (maximum number of entries page) of an R tree node is 169. Synthetic datasets were created with the ENST rectangle generator [14]. This tool 2 generates a set of rectangles according to a statistical model whose parameters (size, coverage, distribution) can be specified. The 2 following statistical models were used sharing the same 2D universe (map) 1. Counties simulates a map of counties; rectangles have a shape and ....
O. Gunther, V. Oria, P. Picouet, J.-M. Saglio, and M. Scholl. Benchmarking Spatial Joins A La Carte. In Proc. Intl. Conf. on Scientific and Statistical Databases, 1998.
Generating Spatiotemporal Datasets on the WWW - Theodoridis, Nascimento (2000) (4 citations) (Correct)
....of possible scenarios. Moreover, we presented the WWW environment that we developed to facilitate the use of the GSTD algorithm. Although extended related work is found in traditional database benchmarks and data generators (e.g. 1, 2] in the field of spatial databases it is very limited [10, 3]. In particular, when motion is introduced to support spatiotemporal databases, to our knowledge the single related work is the Oporto generator [8] but for specific purposes (it actually generates scenarios with harbors, fishing ships, spots and shoals of fish) An interesting issue that arises ....
O. Gnther, V. Oria, P. Picouet, J.-M. Saglio, M. Scholl, "Benchmarking Spatial Joins A La Carte", Proceedings of the 10th Int'l Conference on Scientific and Statistical Database Management (SSDBM), 1998.
Generating Semantics-Based Trajectories of Moving Objects - Pfoser, Theodoridis (2000) (9 citations) (Correct)
....processors, with a thousand discs. The data generated here is alphanumeric. A generator for Web data, i.e. tables and Web pages, is introduced in [14] Soo [18] presents a temporal data generator. This work can be seen as the one dimensional case of spatial data generators such as presented in [6]; a web based spatial data generator that produces sets of rectangles. The generator uses statistical distributions to compute the size, shape, and location of the data. Examples of spatiotemporal data generators are GSTD [20] and Oporto [17] The Oporto generator uses a driving application, the ....
Gnther, O., Oria, V., Picouet, P., Saglio, J.-M., and Scholl, M.: Benchmarking spatial joins La Carte. In Proceedings of the 10th International Conference on Scientific and Statistical Database Management, pp. 32-41, 1998.
On the Generation of Spatiotemporal Datasets - Theodoridis, Silva, Nascimento (1999) (30 citations) (Correct)
....aims to make a fair performance study or experimentation without the dilemma of building his her own datasets for this purpose. Although extended related work is found in traditional database benchmarks and data generators (e.g. 2, 5] in the field of spatial databases it is very limited [20, 6, 15]. Moreover, 4 Linear interpolation assumes that a linear function represents boundary points motion, i.e. intermediate locations are linear to the start and end points. Higher order polynomials are hardly modeled. when motion is introduced to support spatiotemporal databases, to our ....
....locations are linear to the start and end points. Higher order polynomials are hardly modeled. when motion is introduced to support spatiotemporal databases, to our knowledge, no related work exists. Relaxing this constraint, the most relevant to our work is the A La Carte benchmark [6]. It is a WWW based tool consisting of a rectangle generator that builds datasets based on user defined parameters (cardinality, coverage, coordinates distributions) and an experimentation module that runs experiments on either user built or stored sample datasets (including parts of the Sequoia ....
O. Gnther, V. Oria, P. Picouet, J.-M. Saglio, M. Scholl, "Benchmarking Spatial Joins A La Carte", Proceedings of the 10th International Conference on Scientific and Statistical Database Management (SSDBM), 1998.
On the Generation of 2-Dimensional Index Workloads - Hellerstein, Hellerstein.. (1999) (Correct)
....sometimes conflicting results. Significantly absent from many of these studies is a crisp description of the distribution of queries that were used for testing the index. The need for rigorous empirical performance methodologies in this domain has been noted with increasing urgency in recent years [20, 6]. Recent work on generalized indexing schemes presents software and analytic frameworks for indexing that are domain independent, i.e. applicable to arbitrary sets of data and queries [11, 10] As noted in [10] there is a simple logical characterization of the space of queries supported by an ....
O. Gunther, V. Oria, P. Picouet, J.-M. Saglio, and M. Scholl. Benchmarking Spatial Joins A la Carte. In J. Ferriee (ed.), Proc. 13e Journees Bases de Donnees Avancees, Grenoble, 1997.
Oporto: A Realistic Scenario Generator for Moving Objects - Saglio, Moreira (2000) (15 citations) Self-citation (Saglio) (Correct)
....pieces of data access methods and optimisers rather than whole DBMS, following the Wisconsin tradition , developed various spatial data set generators. In order to minimise development e orts and facilitate measurement comparisons, the ENST database lab has proposed the A la carte benchmark (Gunther et al. 1998) which o ers, through a Web interface, to generate spatial data sets according to pertinent size and spatial distribution parameters. 3. Spatio temporal benchmarking 3.1. Taxonomy of spatio temporal applications The elds of application of spatio temporal systems are vast and heterogeneous. ....
O. Gunther, V. Oria, P. Picouet, J-M Saglio and M. Scholl. Benchmarking Spatial Joins \A la Carte". In Proceedings of the 10th International Conference on Scientic and Statistical Database Management (SSDBM), 1998, pp. 32-41.
A Performance Evaluation of Spatial Join Processing.. - Papadopoulos, Rigaux.. Self-citation (Scholl) (Correct)
No context found.
O. Gunther, V. Oria, P. Picouet, J.-M. Saglio, and M. Scholl. Benchmarking Spatial Joins ` A La Carte. In Proc. Intl. Conf. on Scientific and Statistical Databases, 1998.
R-Tree Based Indexing of General Spatio-Temporal Data - Saltenis, Jensen (1999) (1 citation) (Correct)
No context found.
O. Gunther et al. Benchmarking Spatial Joins A La Carte. SSDBM'98, pp. 32--41.
Generating Semantics-Based Trajectories of Moving Objects - Pfoser, Theodoridis (2000) (9 citations) (Correct)
No context found.
Gnther, O., Oria, V., Picouet, P., Saglio, J.-M., and Scholl, M. (1998). Benchmarking spatial joins La Carte. In Proceedings of the 10th International Conference on Scientific and Statistical Database Management (pp. 32-41).
The BASIS System: a Benchmarking Approach for.. - Gurret.. (1999) (Correct)
No context found.
O. Gunther, V. Oria, P. Picouet, J-M. Saglio and M. Scholl: "Benchmarking Spatial Joins A la Carte", Proceedings International Conference on Scientific and Statistical Databases (SSDBM '98), 1998.
The Sort/Sweep Algorithm: A New Method for R-tree Based.. - Gurret, Rigaux (Correct)
No context found.
O. Gunther, V. Oria, P. Picouet, J.-M. Saglio, and M. Scholl. Benchmarking Spatial Joins ` A La Carte. In Proc. Intl. Conf. on Scientific and Statistical Databases, 1998.
On the Generation of Spatiotemporal Datasets - Theodoridis, al. (1999) (30 citations) (Correct)
No context found.
O. Günther, V. Oria, P. Picouet, J.-M. Saglio, M. Scholl, "Benchmarking Spatial Joins A La Carte", Proceedings of the 10 th International Conference on Scientific and Statistical Database Management (SSDBM), 1998.
On the Generation of 2-Dimensional Index Workloads - Hellerstein, Hellerstein.. (1999) (Correct)
No context found.
O. Gunther, V. Oria, P. Picouet, J.-M. Saglio, and M. Scholl. Benchmarking Spatial Joins A la Carte. In J. Ferriee (ed.), Proc. 13e Journees Bases de Donnees Avancees, Grenoble, 1997.
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