Agrawal R., Jagadish H.V., "Hybrid transitive closure algorithms", In Proc. 16th International Conference on Very Large Data Bases, Brisbane, Australia 1990.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....programming [SOKO91] For instance, the routine closure objects takes a function describing the closure direction for the semantic net navigation and as a second argument a set of starting objects. Then it computes the closure according to the direction operation using a semi naive method [ULLM88, AGJA90]. In our example, the functions to be applied are stored subclasses and stored instances which are simply built on ISA I and sour resp. IOF I and sour. The routine apply access applies the access function provided as the first parameter to all elements of the set given as the second parameter. The ....

Agrawal R., Jagadish H.V., "Hybrid transitive closure algorithms", In Proc. 16th International Conference on Very Large Data Bases, Brisbane, Australia 1990.

.... p 1 INTRODUCTION HE capability of computing path queries is an essential feature in new database systems for many advanced applications such as navigation systems Geographical Information Systems (GIS) and computer networks [1] 2] [4], 5] 6] 11] 12] 14] 21] 22] 23] 24] 31] For example, one of the primary functionalities of Intelligent Transportation Systems (ITS) 10] 27] 28] 32] 33] is to find routes from the current location of a vehicle to a desired destination with a minimum cost (where cost ....

...., N c , N e and its path weight SPW ae = 9. Thus a tuple e, b, 9 is in the EP a table associated with N a . In this paper, we use a variation of the well known Dijkstra algorithm [9] to generate the path views. However, our solution is general, and any other shortest path algorithms [1] 3] [4], 15] could also be utilized. 2.3 Discussion The computation of the FPV, equal to calculating all pair shortest paths, is computationally expensive, 1 and the space requirement for the FPV is also high. 2 For large maps, computing or updating the FPV may take a long time, therefore can only ....

[Article contains additional citation context not shown here]

 R. Agrawal and H.V. Jagadish, "Hybrid Transitive Closure Algorithms, " Proc. 16th VLDB Conf., Brisbane, Australia, pp. 326--334, 1990.

.... relevant work is done. For certain classes of programs, it is possible to make such transformations more efficient than is generally the case. In particular, the class of linear recursive rules has been much studied ( 12, 13] among others) as have transitive closure algorithms and operators ([1, 2, 3] among others) and there are refinements to the magic set transformation which may be applied in such cases [12] Such methods are designed to make effective use of the constants in the query, and make considerable improvements to the efficiency of evaluation. However, such techniques do not ....

R. Agrawal and H. Jagadish, Hybrid Transitive Closure Algorithms, Proceedings of the 16th Conference on Very Large Database Systems 326-334, Brisbane, August, 1990.

....These can be classified in two broad classes: the iterative methods such as [AgJa87, BaRa86, ChMa89, HAC90, HaQaCh88, IOA86, LU87, VaBo86] These methods compute the TC of a relation with successive iterations until no new tuples are generated. Other algorithms are called direct methods such as [AgJa87, AgJa90, IoRa88, WAR62, and WAR75]. These techniques compute the TC of a relation in a fixed number of passes over the relation. More closely related to our efforts is the work reported by Ullman and Yannakakis [UlYa90] They show that standard algorithms, those that (possibly depending on the data) examine every triplet ....

R. Agrawal and H.V. Jagadish, "Hybrid Transitive Closure Algorithms" VLDB '90.

....the literature that focus on minimizing the I O costs of path computation in a database setting that assumes a fixed size main memory I O buffer. Most of such research has proposed solutions to solve recursive query problems for general databases that focused on pure transitive closure computation [1, 4, 7, 13, 27, 28, 29, 35]. In our work, rather than aiming for generality, we now take an application driven stance by proposing different disk page clustering algorithms for optimizing path query processing for GIS type of applications and then experimentally evaluating their relative advantages and disadvantages. Two ....

Agrawal, R. and Jagadish, H. V., 1990. "Hybrid Transitive Closure Algorithms," Proc. of the 16th VLDB Conf., Brisbane, Australia, 326 - 334.

....of transitive closure for database relations. The performance study given in this paper clearly exhibits the usefulness of this new approach. 1 Introduction There has been considerable research effort in devising algorithms for computing the transitive closure (TC) of a database relation [1, 2, 4, 5, 6, 8]. Very broadly speaking, two fundamental techniques are used in these algorithms to achieve performance. The first is to avoid redundant computation. That is, only the computation that is necessary to produce the result should be performed. This reduces the amount of computation considerably. The ....

R. Agrawal, H.V. Jagadish, "Hybrid Transitive Closure Algorithms", Proc. of 16th Int. Conf. on VLDB, pp 326-344, 1990

....algorithms and the seminaive algorithm when computing the transitive closure, the bill of materials, and the shortest paths of randomly generated graphs. The Warshall derived algorithms were roughly equally efficient, but the semi naive algorithm was much slower. Agrawal and Jagadish [5] compared their hybrid algorithm with a Warshallderived algorithm, a graph based algorithm presented in [24] and the Grid algorithm by Ullman and Yannakakis [44] in computing the bill of materials of randomly generated acyclic graphs. The hybrid algorithm was in all inputs more efficient than the ....

....algorithm [41] when computing the transitive closure of randomly generated graphs. Algorithm btc was in most inputs more efficient than the other two algorithms. Dar and Jagadish [13] compared their spanning tree transitive closure algorithm with the hybrid algorithm by Agrawal and Jagadish [5] when computing the transitive closure of randomly generated acyclic graphs. The spanning tree algorithm was more efficient than the hybrid algorithm in all inputs. Dar and Ramakrishnan [12, 14] compared several algorithms in computing full and partial transitive closures of randomly generated ....

[Article contains additional citation context not shown here]

R. Agrawal and H.V. Jagadish. Hybrid transitive closure algorithms. In Proceedings of the 16h International VLDB Conference, pages 326--334, Brisbane, Australia, 1990.

....on centralized a route guidance system where TMCs can possess large main memory and high computation power, making the main memory path view approach feasible. Recently, there has been a body of literature on transitive closure computation and recursive query processing in the database community [1, 3, 4, 5, 6, 13, 14, 15]. While their works focus on secondary storage solutions, the benchmark studies in [3, 15] showed that the I O in computing all pair shortest paths becomes intolerable when the underlying graphs are cyclic with more than 300 nodes. If Shekar et al. s finding in [19] demonstrates that the current ....

....that the I O in computing all pair shortest paths becomes intolerable when the underlying graphs are cyclic with more than 300 nodes. If Shekar et al. s finding in [19] demonstrates that the current database technology can not satisfy the real time constraint for ITS path query, the results in [4, 15] predict that the database technology in the near future will not either. For this reason, we must explore the main memory solution in order to satisfy the stringent time requirement on ITS path query computation. In this paper, we present an in memory solution which is particularly suited to the ....

Rakesh Agrawal, H. V. Jagadish, "Hybrid Transitive Closure Algorithms," Proc. of the 16th VLDB Conf., Brisbane, Australia, 1990, pp. 326 -- 334.

....element (tuple, node or edge) a constant number of times and terminate after processing is complete. The number of iterations they perform is independent of the underlying database. Transitive closure algorithms are furthermore distinguished in matrix (e.g. War75] graph [Ita88] or hybrid [AJ90] algorithms depending on the representation and the techniques used. Hybrid algorithms utilize the optimizing features of graph algorithms in a matrix framework. Most algorithms on graphs solve a variety of problems involving path computations such as, critical path, shortest path, bill of ....

R. Agrawal and H. Jagadish. Hybrid Transitive Closure Algorithms. In Proceedings of VLDB-90, pages 326--334, 1990.

.... especially as it may still be adjusted according to changing conditions during the travel period. 1. 2 Path Query Optimization: Related Work While much research has been conducted by both the theory and database communities on path finding, many suggested transitive closure algorithms [1, 3, 12] do not effectively handle path computation on large graphs in real time application domains such as ITS (Intelligent Transportation Systems) systems. With new computer architectures and networks, the traditional algorithms were adapted to parallel and distributed transitive closure algorithms [7, ....

R. Agrawal and H. V. Jagadish, "Hybrid Transitive Closure Algorithms," Proc. of the 16th VLDB Conf., 1990, pp. 326 -- 334.

....[17] Ioannidis et al. 8] and Nuutila and Soisalon Soininen [12, 13, 14, 15] In [13] we showed that algorithm comptc [12] has the smallest worst case execution time of these algorithms. Several performance evaluations of transitive closure algorithms have been presented in the literature [2, 3, 4, 8, 9, 10]. In most of the studies, the iterative algorithms were less efficient than the matrix based algorithms, and the matrix based algorithms were less efficient than the graph based and the hybrid algorithms. Algorithm btc seemed to be the best competitor; thus we selected it for our comparison. To ....

R. Agrawal and H.V. Jagadish. Hybrid transitive closure algorithms. In Proceedings of the 16h International VLDB Conference, pages 326--334, Brisbane, Australia, 1990.

....Algorithms for ITS We use the shortest path transitive closure concept to model the path view. Because ITS graphs are cyclic, algorithms solving the ITS shortest path problem must be cycle indifferent. Many such shortest path transitive closure algorithms have been presented in the literature [2, 3, 6, 12, 13, 22, 23]. Classic ones such as the Warshall and Warren 0 s algorithms, that are matrix based [22, 23] and the Dijkstra 0 s algorithm, that traverses the graph based on priorities [6] work better in main memory environments. Recently proposed transitive closure algorithms [2, 3, 12, 13] provide ....

....[2, 3, 6, 12, 13, 22, 23] Classic ones such as the Warshall and Warren 0 s algorithms, that are matrix based [22, 23] and the Dijkstra 0 s algorithm, that traverses the graph based on priorities [6] work better in main memory environments. Recently proposed transitive closure algorithms [2, 3, 12, 13] provide disk based solutions that can be adopted to solve linear recursive queries in relational databases [14] Among these, Ioannidis et al. s Path BTC algorithm is based on depth first graph traversal [13] Agrawal et al. s hybrid algorithms is a combination of matrix based and graph traversal ....

[Article contains additional citation context not shown here]

Agrawal, R. and Jagadish, H. V., "Hybrid Transitive Closure Algorithms," Proc. of the 16th VLDB Conf., Brisbane, Australia, 1990, pp. 326 -- 334.

....radius) We discuss how to form domains in Section 2.6. For now let us assume that such domains have somehow been created. The shortest distance between all domain centers is precomputed and compressed using the techniques described in [2, 3, 21] Efficient techniques, such as those described in [4, 5], may be used for computing the shortest distances. In addition, the shortest distance between each node and its domain center (and vice versa, if different 4 ) is precomputed and stored. 2.2 A Lower Bound Given the data organization described above, we first derive a lower bound on the ....

R. Agrawal and H. V. Jagadish, "Hybrid Transitive Closure Algorithms," Proc. 16th Int'l Conf. Very Large Data Bases, Brisbane, Australia, Aug. 1990, pp. 326-334.

No context found.

R. Agrawal and H.V. Jagadish. "Hybrid Transitive Closure Algorithms". In Proc. of Intl Conference on Very Large Data Bases, 1990.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC