A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In pages 88--99, 1988.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....results on a shared memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images. 1 Introduction Multi query optimization is becoming increasingly important in many application domains, such as relational databases [9, 14, 15, 20, 21, 22, 23], deductive databases [7] decision support systems [27] and data intensive analytical applications (or data analysis applications) 3] In a collaborative environment, multiple clients may submit queries to the data server. There may be a large number of overlapping regions of interest and ....

Anant Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proceedings of the 14th VLDB Conference, pages 88--99, 1988.

....processing has been studied widely in previous literature. The benefit of this technique is obtained from saving (part of) the subsequent query computations by utilizing the previous cached (intermediate) results. Applications of this technique can be found in [Fin82, LY85, DR92, Sel87, Rou91, Jhi88, HS93, AL80] In [Fin82, LY85, Rou91] cached query results were used in relational database systems to avoid repeated computations. Sel87, Jhi88] addressed the problem This research was sponsored partially by NSF under grant IRI 9057573 and GDR 85 00108 and by NASA USRA under contract ....

....computations by utilizing the previous cached (intermediate) results. Applications of this technique can be found in [Fin82, LY85, DR92, Sel87, Rou91, Jhi88, HS93, AL80] In [Fin82, LY85, Rou91] cached query results were used in relational database systems to avoid repeated computations. Sel87, Jhi88] addressed the problem This research was sponsored partially by NSF under grant IRI 9057573 and GDR 85 00108 and by NASA USRA under contract FCPO 550 81. This paper also appears in Proceedings of the 4th International Conference on Extending Database Technology, 1994. 1 of caching query results ....

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A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Procs. of 14th VLDB, 1988.

....(e.g. the same magnification level for microscopy images, or use of the same transfer functions to convert scalar values into color values) among the clients. Optimizations for the execution of multiple queries have been extensively investigated in the context of relational databases [7, 8, 10, 11, 12, 14]. Common optimization techniques include detection of common subexpressions in query plans, use of materialized views (or intermediate results) and data prefetching and caching. Once common subexpressions are detected for a batch of queries, individual query plans are merged or modified and ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In 14th International Conference on Very Large Data Bases, pages 88--99, 1988.

....data transfer to the client over the network. Given the focus on efficiency, most research on UDFs has investigated the interaction between database query optimization and UDFs. Specifically, cost based query optimization algorithms have been developed to place UDFs within query plans [Hel95, Jhi88] Some recent research has explored the possibility of evaluating queries partially at the server and partially at the client (this has been called hybrid shipping ) FJK96] However, this work has not been applied to extensible systems. Portability and ease of extensibility have largely been ....

Anant Jhingran. A Performance Study of Query Optimization Algorithms on a Database System Supporting Procedures. In Proceedings of the Fourteenth International Conference on Very Large Databases, pages 88--99, 1988.

....predicate caching should be avoided. This optimization is planned for Montage, but has not been implemented yet. Other alternatives exist to our predicate caching implementation, though ours seems to perform reasonably well for our purposes. One can do per function caching instead, as proposed in [Jhi88] and [HS93a] Function or predicate caches can be limited in size, using any of a variety of replacement schemes. Queries can be rewritten with Magic Sets techniques [BMSU86, MFPR90] to avoid the issue of caching entirely, at the expense of extra joins and common subexpressions. Such alternatives ....

Anant Jhingran. A Performance Study of Query Optimization Algorithms on a Database System Supporting Procedures. In Proc. 14th International Conference on Very Large Data Bases, Los Angeles, AugustSeptember 1988.

....provided. Unlike LNC R, the proposed algorithms do not maximize query execution cost savings. The performance of the algorithms is not studied either analytically or experimentally. Caching of retrieved sets of queries containing either procedures or method invocations was subsequently studied in [Jhi88, Hel94, KKM94] However, the work concentrates primarily on cache organization, integration with query optimization, and update handling rather than on the design of cache replacement and admission algorithms. Keller and Basu propose a cache replacement algorithm for materialized predicates which ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proceedings of the International Conference on Very Large Databases, 1988.

....extended relational models, in particular the POSTGRES data model [21] In POSTGRES an attribute of type POSTQUEL may consist of a relational query that has to be evaluated upon referencing. Much work has been spent on optimizing the evaluation of queries accessing such POSTQUEL attributes, e.g. [6, 7, 9, 18, 19, 20], by caching the results. The above cited work is similar to ours with respect to the general idea of precomputing results. However, exploiting object oriented features facilitates a much finer grained control over rematerialization requirements of precomputed results in our approach than is ....

....determined by the location of the argument objects. Therefore, we chose to store materialized results in a separate data structure disassociated from the argument objects. This decision is also backed by a quantitative analysis undertaken in the extended relational system POSTGRES by A. Jhingran [9] where separate caching (CS) of precomputed POSTQUEL attributes proved to be almost always superior to caching within the tuples (CT) If several functions are materialized which share all argument types, the results of these functions may be stored within the same data structure. This provides ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proc. of The Conf. on Very Large Data Bases (VLDB), pages 88--99, L.A., CA, Sep 1988.

....and rematerialization overhead upon update operations. In this respect function materialization is related to relational view materialization [1, 3, 4] Analogous work exists for the POSTGRES data model to optimize the evaluation of queries accessing (virtual) POSTQUEL attributes, e.g. [6, 7, 8, 13, 14, 15]. The above cited work is similar to ours with respect to the general idea of precomputing (caching) results. However, the exploitation of object oriented features, especially the classification of objects into types , object identity , and the principle of encapsulation facilitates a much ....

....determined by the location of the argument objects. Therefore we chose to store materialized results in a separate data structure disassociated from the argument objects. This decision is also backed by a quantitative analysis undertaken in the extended relational system POSTGRES by A. Jhingran [8] where separate caching of precomputed POSTQUEL attributes proved to be almost always superior to caching within the tuples. If several functions are materialized which share all argument types the results of these functions may be stored in the same data structure. This provides for more ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proc. of The Conf. on Very Large Data Bases, pages 88--99, L.A., CA, Sep 1988.

....set of queries, including queries on a single relation. The scheme presented here does not cause traditional optimizers to exhibit this exponential growth in optimization time. Caching the return values of function calls will prove to be vital to the techniques presented in this paper. Jhingran [Jhi88] has explored a number of the issues involved in caching procedures for query optimization. Our model is slightly different, since our caching scheme is value based, simply storing the results of a function on a set of argument values. Jhingran s focus is on caching complex object attributes, and ....

Anant Jhingran. A Performance Study of Query Optimization Algorithms on a Database System Supporting Procedures. In Proc. VLDB 88 [Pro88].

....set of queries, including queries on a single relation. The scheme presented here does not cause traditional optimizers to exhibit this exponential growth in optimization time. Caching the return values of function calls will prove to be vital to the techniques presented in this paper. Jhingran [Jhi88] has explored a number of the issues involved in caching procedures for query optimization. Our model is slightly different, since our caching scheme is value based, simply storing the results of a function on a set of argument values. Jhingran s focus is on caching complex object attributes, and ....

Anant Jhingran. A Performance Study of Query Optimization Algorithms on a Database System Supporting Procedures. In Proc. VLDB 88 [Pro88].

....extended relational models, in particular the POSTGRES data model [19] In POSTGRES an attribute of type POSTQUEL may consist of a relational query that has to be evaluated upon referencing. Much work has been spent on optimizing the evaluation of queries accessing such POSTQUEL attributes, e.g. [6, 7, 9, 16, 17, 18], by caching the results. The above cited work is similar to ours with respect to the general idea of precomputing results. However, exploiting object oriented features facilitates a much finer grained control over rematerialization requirements of precomputed results in our approach than is ....

....is determined by the location of the argument objects. Therefore we chose to store materialized results in a separate data structure disassociated from the argument objects. This decision is also backed by a quantitative analysis undertaken in the extended relational system POSTGRES by A. Jhingran [9] where separate caching (CS) of precomputed POSTQUEL attributes proved to be almost always superior to caching within the tuples (CT) If several functions are materialized which share all argument types, the results of these functions may be stored within the same data structure. This provides ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proc. of The Conf. on Very Large Data Bases, pages 88--99, L.A., CA, Sep 1988.

....provided. Unlike LNC R, the proposed algorithms do not maximize query execution cost savings. The performance of the algorithms is not studied either analytically or experimentally. Caching of retrieved sets of queries containing either procedures or method invocations was subsequently studied in [Jhi88, Hel94, KKM94] However, the work concentrates primarily on cache organization, integration with query optimization, and update handling rather than on the design of cache replacement and admission algorithms. Keller and Basu propose a cache replacement algorithm for materialized predicates which ....

A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In Proceedings of the International Conference on Very Large Databases, 1988.

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A. Jhingran. A performance study of query optimization algorithms on a database system supporting procedures. In pages 88--99, 1988.

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Anant Jhingran. A Performance Study of Query Optimization Algorithms on a Database System Supporting Procedures. In Proceedings of the Fourteenth International Conference on Very Large Databases, pages 88--99, 1988.

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