C. Beeri, P. C. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. on Principles of Database Systems, pages 214--226. ACM Press, 1987.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....database prototypes. As discussed next, however, there still remains room for major extensions and improvements. In this paper, we shall deal with chain queries, i.e. queries where bindings are propagated from arguments in the head to arguments in the tail of the rule, in a chain like fashion [7, 9, 35]. For these queries, general optimization methods, such as the magic set method [31] do not take advantage of the chain structure, thus resulting in rather ine#cient query executions. Therefore, as chain queries are rather frequent in practice (e.g. graph applications) there is a need for ....

....thus resulting in rather ine#cient query executions. Therefore, as chain queries are rather frequent in practice (e.g. graph applications) there is a need for specialized optimization methods. Indeed, several specialized methods for chain queries have been proposed in the literature (e.g. in [1, 7, 9, 11, 35, 36]) Unfortunately, these methods do not fully exploit the query bindings. On the other hand, the counting method is very e#ective for chain queries with bindings, for many chain queries whose recursive rules are linear; however, this method, although proposed in the context of general queries [29] ....

[Article contains additional citation context not shown here]

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrisnhan. Bounds on the Propagation of Selection into Logic Programs, J. of Computer and System Science, Vol. 41, No. 2, Oct. 1990, pages 157--180.

....in several deductive database prototypes. However, there still remains room for major extensions and improvements. In this paper we shall deal with chain queries, i.e. queries where bindings are propagated from arguments in the head to arguments in the tail of the rules, in a chain like fashion [5, 8]. For these queries, insisting on general optimization methods (e.g. the magic set method [18] does not allow to take advantage of the chain structure, thus resulting in rather ine#cient query executions. Therefore, as chain queries are rather frequent in practice (e.g. graph applications) ....

....thus resulting in rather ine#cient query executions. Therefore, as chain queries are rather frequent in practice (e.g. graph applications) there is a need for ad hoc optimization methods. Indeed, various specialized methods for chain queries have been proposed in the literature (e.g. in [1, 5, 8, 22]) Unfortunately, these methods do not fully exploit possible bindings. To find a method that is particularly specialized for bound chain queries, we have to go back to the counting method; however, this method, although proposed in the context of general queries [17] preserves the original ....

[Article contains additional citation context not shown here]

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrisnhan. Bounds on the Propagation of Selection into Logic Programs, JCSS, Vol. 41, No. 2, 1990, pages 157--180.

....boundedness problem for regular path expressions. We show that it is decidable whether a given regular path query is equivalent to a path query without recursion, assuming that a given set of equalities among words is satisfied. Related work Path queries in graphs have been studied formally in [10, 12, 8, 24]. The language Graphlog, introduced in [12] expresses queries using graph patterns, where paths are specified by regular expressions. Graphlog is shown equivalent to stratified linear Datalog and other languages. The complexity of path queries in graphs is studied in [24] Specifically, the ....

....in Section 2. In particular, the processing of Datalog programs with one sided recursion [26] discussed in [8] is in the spirit of our evaluation of path queries using Datalog. The connection between path queries and recursive query processing in deductive databases is also discussed in [10], which relates regular path queries to chain programs in Datalog where the recursive predicates 1 2 expspace denotes the functions computable in space bounded by 2 2 n k for some k, where n is the size of the input. 3 are monadic. Query languages for semistructured data that include path ....

C. Beeri, P.C. Kanellakis, F.Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. ACM Symp. on Principles of Database Systems, pages 214--226, 1987.

....NP. Thus, connectivity seems to have a special significance. Directed reachability is an interesting problem because it is known in some senses to be a more difficult problem to deal with than connectivity. For instance, a surprising result of Kanellakis (private communication, 1986; see also [BKBR87]) says that undirected reachability (where we consider only undirected graphs) is in monadic NP. In contrast, undirected connectivity is not in monadic NP, as mentioned above. Furthermore, Cosmadakis has shown that connectivity does not reduce in his sense to directed reachability. This ....

C. Beeri, P. C. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. on Principles of Database Systems, pages 214--226, 1987. 21

....computing the recursive relations) Variants of the magic set method have been described in many other papers on this subject. While several of the extensions dealt with more complex than linear recursive queries, two other papers have simplified the magic set idea to produce magic envelopes ([28], 29] The idea used in these papers was to minimize the complexity of the magic set rules in order to minimize computation overhead. This regularization of the magic set rules has been discussed first in [28] and implemented in [29] Precedence reducer programs implement a similar idea (cmp. ....

....two other papers have simplified the magic set idea to produce magic envelopes ( 28] 29] The idea used in these papers was to minimize the complexity of the magic set rules in order to minimize computation overhead. This regularization of the magic set rules has been discussed first in [28] and implemented in [29] Precedence reducer programs implement a similar idea (cmp. the splitting of recursive predicates into bound and free part) to allow set oriented processing and to compute the magic set completely (as good as possible) before computing the recursive relations. On the ....

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrishnan, "Bounds on the propagation of selection into logic programs," in Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1987.

....recursion. # 5. Constraint Based Query Evaluation 5.1. Incorporation of query constraints in recursive query evaluation A popular heuristic of query optimization in both traditional and deductive database systems is to push selection as deeply as possible into a relational expression [3, 27]. Since a selection is often represented by a query constraint, the heuristic can be simply rephrased as pushing query constraints as deeply as possible into a compiled expression in the query evaluation. However, the realization of this heuristic for the evaluation of compiled chains may not be ....

C. Beeri, P. Kanellakis, F. Bancilhon and R. Ramakrishnan, Bounds on the Propagation of Selection into Logic Programs, Proc. 6th ACM Symp. Principles of Database Systems, San Diego, CA, March 1987, 214-226.

....performed using the methods discussed in Section 3. Step 2 is necessary and correct since the correct ordering of the predicates will lead to finite and efficient evaluation. Step 3 is correct because the most selective information should be pushed into the rectified chain for initial processing [3]. The iterative query evaluation can be determined by the query binding analysis because the binding information can be passed to the next iteration based on the regularity of the recursion. If there is a portion of the chain not immediately finitely evaluable, the chain split evaluation will be ....

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. Principles of Database Systems, pp. 214--226, San Diego, CA (1987).

.... methods and optimisation techniques exist [24,6] These classes are defined by imposing syntactic restrictions on the Datalog programs belonging to them, following two main approaches: restricting the width (number of arguments) of the predicates defined by the Datalog programs (as, e.g. in [7,9,27]) imposing the linearity condition on the clauses of Datalog programs allowing at most one non database predicate in the body of each clause defined by the Datalog program (as, e.g. in [17,18] As an example, consider the following Datalog program which checks if there CT93 00414 Logic ....

C. Beeri, P. C. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. on Principles of Database Systems, pages 214--226. ACM Press, 1987.

....boundedness problem for regular path expressions. We show that it is decidable whether a given regular path query is equivalent to a path query without recursion, assuming that a given set of equalities among words is satisfied. Related work Path queries in graphs have been studied formally in [8, 10, 6, 20]. The language GraphLog, introduced in [10] expresses queries using graph patterns, where paths are specified by regular expressions. GraphLog is shown equivalent to stratified linear Datalog and other languages. The complexity of path queries in graphs is studied in [20] Specifically, the ....

....in Section 2. In particular, the processing of Datalog programs with one sided recursion [22] discussed in [6] is in the spirit of our evaluation of path queries using Datalog. The connection between path queries and recursive query processing in deductive databases is also discussed in [8], which relates regular path queries to chain programs in Datalog where the recursive predicates are monadic. Query languages for semistructured data that include path expressions are considered in [18, 9, 19, 26] The language UnQL and its optimization are discussed in [9] the optimizations ....

C. Beeri, P.C. Kanellakis, F.Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. ACM Symp. on Principles of Database Systems, pages 214--226, 1987.

....performed using the methods discussed in Section 3. Step 2 is necessary and correct since the correct ordering of the predicates will lead to finite and efficient evaluation. Step 3 is correct because the most selective information should be pushed into the rectified chain for initial processing [3]. The iterative query evaluation can be determined by the query binding analysis because the binding information can be passed to the next iteration based on the regularity of the recursion. If there is a portion of the chain not immediately finitely evaluable, the chain split evaluation will be ....

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. Principles of Database Systems, pages 214--226, San Diego, CA, March 1987.

....same generation query) This gain of a factor of n is not due to better focusing properties of the rewritten factored program; rather, it is due to the fact that the Factoring strategy reduces the arity of the recursively defined predicate. Our results lend credence to the hypothesis, stated in [BKBR87], that using a selection to reduce the arity of the recursion is far more important than using the selection to avoid irrelevant tuples. Related work on the performance of recursive queries and their evaluation algorithms [BMSU86, BR88, GKS91, HN88, HL86, MSPS87, Nau88, SZ87] has considered either ....

Catriel Beeri, Paris Kanellakis, Francois Bancilhon, and Raghu Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proceedings of the ACM Symposium on Principles of Database Systems, pages 214--226, San Diego, California, March 1987.

....evaluation in the evaluation of compiled functional single chain recursions. Rationale. Step 1 is necessary since a query must be finitely evaluable and terminate. Step 2 is necessary and correct since the most selective information should be pushed into the compiled chain for initial processing [3]. Step 3 is correct since if the chain split evaluation is to be performed, partial evaluation should be explored. Step 4 is correct based on the study of constraint based query processing in deductive databases [6] 2 A similar algorithm can be derived for constraint enforced chain split partial ....

C. Beeri, P. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. Principles of Database Systems, pages 214--226, San Diego, CA, March 1987.

No context found.

C. Beeri, P. C. Kanellakis, F. Bancilhon, and R. Ramakrishnan. Bounds on the propagation of selection into logic programs. In Proc. 6th ACM Symp. on Principles of Database Systems, pages 214--226. ACM Press, 1987.

No context found.

Beeri, C., P. Kanellakis, F. Bancilhon, R. Ramakrishnan, "Bound on the Propagation of Selection into Logic Programs", Proc. 6th ACM SIGMOD--SIGACT Symp. on Principles of Database Systems, 1987.

No context found.

Beeri, C., P. Kanellakis, F. Bancilhon, R. Ramakrishnan, "Bound on the Propagation of Selection into Logic Programs", Proc. 6th ACM SIGMOD--SIGACT Symp. on Principles of Database Systems, 1987.

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