S. Rao, A. Badia, D. Van Gucht, Providing Better Support for a Class of Decision Support Queries, SIGMOD Conf., Montreal, 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....queries, i.e. those for which the quantifier s range constitutes a closed formula. Furthermore, the division is a relational algebra operator tailored for the flat relational model; in a data model supporting multi valued relationships via set attributes one can usually do much better. [HP95, RBG96, Car86, WMSB90] propose generalized universal quantifiers in different variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quantifiers using special data structures (bit ....

....multi valued relationships via set attributes one can usually do much better. HP95, RBG96, Car86, WMSB90] propose generalized universal quantifiers in different variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quantifiers using special data structures (bit matrices) Jarke and Koch [JK83] and Bry [Bry89a, Bry89b] devised rules to move selections into the quantifier range definition in order to reduce the number of tuples that have to be evaluated. ....

S. G. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In Proc. of the ACM SIGMOD Conf. on Management of Data, pages 217--227, Montreal, Canada, June 1996.

....SELECT t.studentId FROM TRANSCRIPT t GROUP BY t.studentId HAVING COUNT(t.courseNo) SELECT COUNT(courseNo) FROM COURSE) Obviously, these formulations are not intuitive and in addition difficult to optimize. Language extensions have already been proposed in the literature [12] [19] and meanwhile considered as additional predicates in the SQL:1999 standardization [9] In this paper, we concentrate on the support provided by relational query processors. Since all quantification can be seen as a division operation, there is a direct relationship from StreamJoin to a division ....

....range constitutes a closed formula [6] In [7] generalized join and aggregation operators are presented. However, the scope of the paper is restricted only to traditional aggregation operations over groups, such as average, max, count etc. and is not applicable for all quantification. [19] proposes a generalized quantifier framework that defines a completely new query subsystem. Thus, it requires significant changes within the query execution system, since special indexes and multidimensional structures have to be built for all relations. Moreover, the results are not directly ....

S. Rao, A. Badia, D. v. Gucht. Providing Better Support for a Class of Decision Support Queries. Proc. SIGMOD, Montreal, 1996.

....We thus see that decision support queries, which usually are more associated with OLAP, also have a role to play in the KDD process. In general, non standard query processing and optimization techniques are required to allow efficient execution of decision support queries on large databases [14, 5]. Much research has still to be done here, and will be done given that current interest in OLAP and decision support is tremendous. However, the ideal platform for implementation of our approach is not relational at all, but is rather provided by OQL, the standard query language of ....

S. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, volume 25:2 of SIGMOD Record, pages 205-- 216. ACM Press, 1996.

....functions taking a set of tuples as argument and producing a single value as result. Our approach is more general than Klug s one, since the MultiDimensional model subsumes the relational one. Furthermore we consider, in addition to aggregate functions, also scalar functions. Many authors [5,11,19,23] claim that SQL is unsuited to data analysis applications, since some aggregate and grouping queries are difficult to express and optimize. They thus consider the problem of extending SQL with aggregation and analysis oriented operators that are more powerful, but also specific to particular ....

....et al. 11] propose cube as an operator generalizing group by. Chatziantoniou and Ross [5] extend both SQL and the relational algebra with an operator, dealing with aggregation variables , to succinctly express common queries, providing also a basis for improved query optimization. Rao et al. [19] consider the issue of supporting quantified queries, a class of queries that is difficult to deal with in SQL; they introduce a number of generalized quantifiers , that is, aggregate set predicates such as some, all, and at least. Many of the features considered in such proposals can be easily ....

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S. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In ACM SIGMOD International Conf. on Management of Data, pages 217--227, 1996.

....quanti ed queries, i.e. those for which the quanti er s range constitutes a closed formula. Furthermore, the division is a relational algebra operator tailored for the AEat relational model; in a data model supporting multi valued relationships via set attributes one can usually do much better. [HP95, RBG96, Car86, WMSB90] propose generalized universal quanti ers in dioeerent variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quanti ers using special data structures (bit ....

....multi valued relationships via set attributes one can usually do much better. HP95, RBG96, Car86, WMSB90] propose generalized universal quanti ers in dioeerent variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quanti ers using special data structures (bit matrices) Jarke and Koch [JK83] and Bry [Bry89b, Bry89a] devised rules to move selections into the quanti er range de nition in order to reduce the number of tuples that have to be evaluated. ....

S. G. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In Proc. of the ACM SIGMOD Conf. on Management of Data, pages 217227, Montreal, Canada, June 1996.

....quantified queries, i.e. those for which the quantifier s range constitutes a closed formula. Furthermore, the division is a relational algebra operator tailored for the flat relational model; in a data model supporting multi valued relationships via set attributes one can usually do much better. [HP95, RBG96, Car86, WMSB90] propose generalized universal quantifiers in different variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quantifiers using special data structures (bit ....

....multi valued relationships via set attributes one can usually do much better. HP95, RBG96, Car86, WMSB90] propose generalized universal quantifiers in different variations for relational languages, e.g. as SQL extensions. These works are at the conceptual (i.e. language) level except for [RBG96] which includes work on evaluating such generalized quantifiers using special data structures (bit matrices) Jarke and Koch [JK83] and Bry [Bry89a, Bry89b] devised rules to move selections into the quantifier range definition in order to reduce the number of tuples that have to be evaluated. ....

S. G. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In Proc. of the ACM SIGMOD Conf. on Management of Data, pages 217--227, Montreal, Canada, June 1996.

....Hence OE(p; d) will be (p = 101; d = 3) p = 103; d = 1) This means that patient 101 is free from all symptoms of disease 3 and patient 103 is free from all symptoms of disease 1. 2 The above query can be also expressed in several languages (SQL and others) that do not use constraint databases [Rao 1996]. However, the use of set variables and set order constraints enabled a more compact and higher level expression. The use of SQL for this and similar queries is more awkward (see Figure 2 in [Rao 1996] 5. SAFE STRATIFIED DATALOG QUERIES 5.1 Safe Stratified Datalog for Gap Order Constraint ....

....can be also expressed in several languages (SQL and others) that do not use constraint databases [Rao 1996] However, the use of set variables and set order constraints enabled a more compact and higher level expression. The use of SQL for this and similar queries is more awkward (see Figure 2 in [Rao 1996]) 5. SAFE STRATIFIED DATALOG QUERIES 5.1 Safe Stratified Datalog for Gap Order Constraint Databases We start with some basic definitions. Let C = V; E; j; 6j) be a congraph of a relation over C= 6= g . The transitive closure of C is C = V; E ; j ; 6j) where j is the congruence ....

Rao, A. v. G. D., S.G.and Badia. 1996. Providing better support for a class of decision support systems. In ACM SIGMOD International Conference on Management of Data (1996).

....their techniques are significantly less general than ours; their syntax corresponds roughly with allowing just one grouping variable. Consequently, their extended syntax cannot succinctly express Queries Q2, Q3, or Q4. Rao, Badia and Van Gucht address the issue of supporting quantified subqueries [RBV96] Their work, which was done independently from ours, is motivated by similar concerns that SQL s syntax is cumbersome for expressing and optimizing a natural class of queries. Our syntax can succinctly solve (for a known number of columns) the so called Value to Attribute conflict, a case of ....

Sudhir Rao, Antonio Badia, and Dirk Van Gucht. Providing better support for a class of decision support queries. In ACM SIGMOD, Conference on Management of Data, pages 217--227, 1996.

....Therefore, a differential form of the partial query ppq(Q) can be applied only to that group, where Q is the query defining the materialized view. Extended syntaxes. A number of papers and systems propose extensions of standard SQL in order to more easily express and optimize complex queries [CR96, KS95, RBVG96, Syb94]. Each of these proposals makes the argument that with an extended syntax, complex queries are easier to write and easier to optimize. We did not consider an extended syntax here, because (a) we wanted our work to apply to present day systems, b) we wanted to see how much optimization potential ....

Sudhir Rao, Antonio Badia, and Dirk Van Gucht. Providing better support for a class of decision support queries. In ACM SIGMOD, Conference on Management of Data, pages 217--227, 1996.

....Even though this kind of temporal aggregation is not discussed in the model proposals and systems we surveyed, we believe that it is very important for temporal decisionsupport applications. Quantified temporal aggregates is an adaptation of quantified aggregates proposed in [17] and in [24]. They typically involve phrases, such as all, most frequently, more than five, at least twice as many, not all, etc. Examples follow: ffl For every stock, derive its phases of monotonically increasing closing prices, that lasted at least 30 days. ffl For the IBM stock, report its price ....

S. G. Rao, A. Badia, and D. van Gucht. Providing better support for a class of Decision Support Queries. In Proceedings of the ACM SIGMOD Intl. Conf. on Management of Data, pages 217--227, 1996.

....query processing. This area is starting to receive the attention it deserves. A number of conventional relational query processing approaches have been applied to or extended for answering OLAP queries. Some of this work has concentrated on efficiently performing GROUP BY [8, 9, 20] aggregation [10, 23, 33, 30, 50, 68, 69], join or range queries [32, 60, 64] or supporting incomplete query answers [6, 29, 66] Several approaches have been proposed for supporting the SQL CUBE operator, including [2, 17, 23, 42, 53, 58] Yet another facet of query processing that has received attention in the literature is that of ....

S.G. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In Proc. ACM SIGMOD Intl. Conf. on Management of Data, pages 217--227, Montreal, Quebec, Canada, June 4-6 1996.

....[12] that supports more natural constructs for ad hoc querying. Recently, Hsu and Parker [12] and, independently, Badia, Van Gucht, and Gyssens [1] have shown that generalized quantifiers are an effective and natural way of expressing quantified queries. Furthermore, Rao, Badia, and Van Gucht [20] have demonstrated that a superior performance can be achieved on quantified queries with database system kernels that support generalized quantifier operations directly. Hsu and Parker [12] syntactically extended SQL to support generalized quantifiers and provided a translation mechanism from ....

.... in the query language [8, 7, 3] This approach has led to an easing of the problem of query transformation and optimization [8] We choose this latter approach to solve the query transformation and optimization problem for queries in Hsu and Parker s extended SQL (SQLGQ for short) The work in [20] provides us with a suite of certain basic operators that can be used to efficiently support generalized quantifiers. The main contributions of this paper are as follows: 1) an extended relational algebra that includes operators which can be efficiently implemented in a database system kernel, ....

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Rao, S. G., Badia, A., and Van Gucht, D. Providing Better Support for a Class of Decision Support Queries. In Proc. of ACM-SIGMOD Int'l Conf. on Management of Data (1996). To appear.

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S. Rao, A. Badia, D. Van Gucht, Providing Better Support for a Class of Decision Support Queries, SIGMOD Conf., Montreal, 1996.

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Rao, S., Badia, A., Van Gucht, D., Providing Better Support for a Class of Decision Support Queries. Proc. ACM SIGMOD, Montreal 1996, 217227. 77

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S. Rao, A. Badia, and D. Van Gucht. Providing better support for a class of decision support queries. In ACM SIGMOD International Conf. on Management of Data, pages 217#227, 1996.

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