A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases, pages 294-- 305, 1990.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... tries to make the data independence concept even more flexible, by allowing more complicated physical storage schemas in addition to the base relations and indexes: relational materialized views [LMSS95, Lev, CKPS95] join indexes [Val87] access support relations for OO databases [KM90a, KM90b] sources with limited capabilities [RSU95, LRO96, FLMS99] GMAPs [TSI96] etc. In all these cases, the elements of the physical schema are defined as queries (views) over the logical schema. The advantage is that the logical schema is then fixed while the physical schema can be easily changed in ....

....from the ability of expressing index lookup in our language. We can therefore fully describe a join index by a triple consisting of a materialized binary relation view and two indexes. In our example, the join index for joining Dept with Proj is (Dept, I, JI) Access support relations [KM90a, KM90b] generalize path indexes [MS86, Ber94, BK89] and translate the join index idea from the relational to the object model, generalizing it from binary to n ary relations. An access support relation (ASR) for a given path is a separate precomputed relation that explicitly stores the oids of objects ....

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A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. VLDB, Brisbane, Australia, 1990.

....by scanning JRS and using the surrogates to index into the relations. We can therefore fully describe a join index by a triple consisting of a materialized binary relation view and two indexes. In our example, the join index for joining Dept with Proj is (Dept, I, JI) Access support relations [28, 29] generalize path indexes [34, 10, 11] and translate the join index idea from the relational to the object model, generalizing it from binary to n ary relations. An access support relation (ASR) for a given path is a separate precomputed relation that explicitly stores the oids of objects related ....

.... [42, 43, 19, 18] and in fact including the very comprehensive work by Beeri and Kornatzky [8] Use of referential integrity constraints to eliminate dependent joins is implicit in Orion optimizations [26] and the type based approach of [19] This, and the use of precomputed ASR s appear in [28, 29]. Precomputed join indexes are proposed in [46] An approach to semantic query optimization using a translation into Datalog appears in [13, 24] The idea of using semantic constraints as rewrite rules is introduced and exploited systematically in [21, 22] When the physical schema contains only ....

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. VLDB, Brisbane, Australia, 1990.

....do so in the abstract data types for cost etc. in the Volcano optimizer generator) but we have found it extremely hard to maintain encapsulation of all desirably separate concerns in an actual implementation. Kemper and Moerkotte designed a rule based query optimizer for the Generic Object Model [KeM90a]. The rules operate almost entirely on path expressions (e.g. employee.department.floor) by extending and cutting them to permit effective use of access support relations [KeM90b] While the use of rules makes the optimizer extensible, it is not clear to what extent these techniques can be used ....

A. Kemper and G. Moerkotte, Advanced Query Processing in Object Bases Using Access Support Relations, Proc. Int'l. Conf.onVery Large Data Bases,Brisbane, Australia, August 1990, 290.

....a virtual document. This physical storage design decision can be hidden from the user by differentiating among the corresponding document types in the catalog. ToXin the ToX indexing mechanism. ToXin is a main memory indexing mechanism inspired by DataGuides [12] and Access Support Relations [14]. It was designed for allowing fast access to elements in the XML tree both for forward and backward navigation. It consists of two separate indices: a path index, for allowing the efficient evaluation of regular path expressions, and a value index, used for efficiently locating nodes in the ....

Alfons Kemper, and Guido Moerkotte. Advanced query processing in object bases using access support relations. In Proceedings of the 17th International Conference on Very Large Databases, pages 294-305, Brisbane, Australia, August 1990.

.... x algebra [19] On the other hand, much research e ort has already been devoted to query algebras for complex data types [16, 11, 24] which have been used successfully as a formal basis for various optimization techniques for object oriented and object relational databases, such as path indexing [23] and query decorellation [13] However, very few of these algebras can handle tree data structures, such as those implicit to schema less XML data. But if an XML schema is provided, then XML data can be easily mapped to complex data, while XML queries can be translated into algebraic forms in one ....

A. Kemper and G. Moerkotte. Advanced Query Processing in Object Bases Using Access Support Relations. In Proceedings of the Sixteenth International Conference on Very Large Databases, Brisbane, Australia, pages 290-301. Morgan Kaufmann Publishers, Inc., Aug. 1990.

....systems, queries are typically optimized by either access method cost models or rule based methods. Access methods constitute an index structure (or an efficient plan) for executing a user s declarative query. The rule based methods generate an evaluation plan for a query. Some researchers [3, 4, 10, 13] have used heuristic rules to optimize queries. Rules are used to determine efficient search strategies. It is difficult to associate rules to a query for efficient processing. To lessen this difficulty, a few researchers have developed so called semantic query reformulation [2, 3, 7] ....

Alfons Kemper and Guido Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Intl. Conf. on Very Large Data Bases, pages 290--301, Brisbane, Australia, 1990.

....queries often involve pointer chasing operations through the different components of the database objects. This kind of operations may imply numerous input output operations (I O) One way to minimize I O is to consider class extents in order to transform navigation into algebraic join operations [13, 15]. Another technique consists in having a specialized module in the optimizer whose task is to avoid an object at a time reading of the various components needed in the evaluation of the query [14] Secondly, a component of an object may be a nested structure. This leads, for instance, to ....

....supports heuristics in order to reduce the optimization rewriting phase. There exist two main approaches to query rewriting in the object oriented context: the algebraic approach [17, 6, 18] and the one, that we call the type based approach, which transform pointer chasing into join operations [13, 15]. We unify these two appoaches in one formalism. We show that it is just the lack of type information (membership to class extents) that makes it impossible to perform type based transformations using algebraic equivalences. Accordingly, we extend the algebraic approach by reducing and typing the ....

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A. Kemper and G. Moerkotte. Advanced Query Processing in Object Bases Using Access Support Relations. In proc. VLDB, Brisbane, Australy, 1990.

....head) which cannot be unnested without using outer joins and grouping. There is an increasing number of recent proposals on OODB query optimization. Some of them are focused on handling nested collections [Ozsoyoglu and Wang 1992; Colby 1989] others on converting path expressions into joins [Kemper and Moerkotte 1990; Cluet and Delobel 1992] others on unnesting nested queries [Cluet and Moerkotte 1995b; Cluet and Moerkotte 1995a] while others are focused on handling encapsulation and methods [Daniels et al. 1991] Query decorrelation was rst introduced in the context of relational queries [Kim 1982; ....

Kemper, A. and Moerkotte, G. 1990. Advanced Query Processing in Object Bases Using Access Support Relations. In Proceedings of the Sixteenth International Conference on Very Large Databases, Brisbane, Australia (Aug. 1990), pp. 290-301. Morgan Kaufmann Publishers, Inc.

....or the comprehension head) which cannot be unnested without using outer joins and grouping. There is an increasing number of recent proposals on OODB query optimization. Some of them are focused on handling nested collections [OW92, Col89] others on converting path expressions into joins [KM90, CD92] others on unnesting nested queries [CM95b, CM95a] while others are focused on handling encapsulation and methods [DGK 91] Query decorrelation was rst introduced in the context of relational queries [Kim82, GW87, Mur92] mostly in the form of source to source transformations. There ....

A. Kemper and G. Moerkotte. Advanced Query Processing in Object Bases Using Access Support Relations. In Proceedings of the Sixteenth International Conference on Very Large Databases, Brisbane, Australia, pages 290-301. Morgan Kaufmann Publishers, Inc., August 1990.

.... system maintained references, or tuples in a relation, as shown in [Rum87] Furthermore, database research has shown that references are not as efficient when it comes to sets of objects: they need to be supported by relation like structures like path indexes [LLOW91] or access support relations [KM90] 3 Mixed cases are possible and can be seen as an optimization. 3.1 Relationship Classes References link one object to another one, and can therefore only model binary, hierarchical relationships with no attributes adequately; to model general relationships, one has to create relationship ....

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Databases, pages 290--301, 1990.

....traversal approach [Jenq90] enables a long path to be traversed forward and backward. A variant approach is the typed algebra [Cluet92] which allows the Jenq et al. traversals to be described as binary algebra expressions. Another approach uses path indexes to directly achieve a whole navigation [Kemper90]. A more general approach proposes using not only path indexes but also the physical information in linked objects to accelerate the navigation [Orenstein92] This corresponds to pipelined (i.e. one object at a time or depth first pointer chasing ) traversals of multiple collections. Pipelined ....

....the external collection definition. The traversal functions encapsulate the storage organization of the collection. Definition 1: Abstract Collection A container of objects encapsulated by a finite set of behavioral and traversal functions. Indexes essential in all optimization strategies [Kemper90, Orenstein92, Finance94] are integrated into the language as common abstract collections. Indeed, conventional indexes can be seen as collections where an object or a set of objects is related to an atomic value [Kemper90] In object oriented databases, path indexes can be seen as collections providing a direct ....

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Kemper A., Moerkotte G., "Advanced Query Processing in Object Bases Using Access Support Relations", Intl. Conf. on VLDB, Brisbane, Australia 1990.

....than what we have considered. 7] reports on join elimination in star queries that are still less complex than our experiments with EC2. Examples of SQO for OO systems appear in [28, 10, 9, 3, 14, 13, 17, 8] Use of referential integrity constraints to eliminate dependent joins is implicit in [19, 10, 20, 21]. A general framework for SQO using rewrite rules expressed using OQL appears in [16, 15] Techniques for using materialized views in query optimization are discussed in [33, 31, 6, 15, 16, 30, 12] A survey of the area appears in [22] From our perspective, the work on join indexes [32] and ....

.... rewrite rules expressed using OQL appears in [16, 15] Techniques for using materialized views in query optimization are discussed in [33, 31, 6, 15, 16, 30, 12] A survey of the area appears in [22] From our perspective, the work on join indexes [32] and precomputed access support relations [20, 21] belongs here too. The general problem is forced by data independence: how to reformulate a query written against a user level schema into a plan that also only uses physical access structures and materialized views eciently. The GMAP approach [31, 30] works with a special case of conjunctive ....

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. VLDB, Brisbane, Australia, 1990.

....space generation is used. There are several possible alternatives to control rule selection: ffl Fixing the rule ordering by programming also fixes the optimization potential and thus lacks flexibility. For example, this approach is taken by COKO KOLA, Starburst [HFLP89, PHH92] and GOM [KM90] Volcano uses a default ordering that may be overwritten according to a given function. ffl Calculating costs for both the original and all the transformed queries of any rewriting step forms the expensive way. This approach violates the separation of logical and physical level and often lacks ....

....that also has to be programmed and is evaluated online. Thus the rule ordering is heuristical. The system is not flexible because of the lack of statistical elements and the coded rule application order. Extending the rule base can not be done without programming. The rule interpreter of GOM [KM90] is based on forming rule groups like Starburst, thereby grouping rules of same intention. Inside the groups, the rules may be ordered in coherence to their quality (heuristical ordering) The group sequencing is programmed as well as the grouping. Thus, the rule ordering is fixed by programming. ....

A. Kemper and G. Moerkotte. Advanced Query Processing in Object Bases Using Access Support Relations. In Proc. of the 16th VLDB Conference, pages 290--301, Brisbane, Australia, 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases, pages 294-- 305, 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases (VLDB), pages 294--305, 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases, pages 294-- 305, 1990.

....use the notation E[e;A 1 ; A n ] for an extent belonging to object type E. It returns tuples consisting of the object identifier e and projects on the (possibly set valued) attributes A 1 ; A n . The algebraic counterpart of the dot operator in OQL is the expand operator c [KM90], also called, e.g. materialize [BMG93] It may be used both to retrieve attributes and to invoke member functions of a referenced object. In this paper, we only need the attribute access variant (The operator ffi denotes tuple concatenation and g is a newly introduced attribute) c g : e:a (E) ....

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. of the Conf. on Very Large Data Bases (VLDB), pages 290--301, Brisbane, Australia, 1990.

....loop evaluation which may be very inefficient. Hence, the second phase unnests nested algebraic expressions to allow for more efficient evaluation. 1 Introduction Many declarative query languages for object oriented database management systems have been proposed in the last few years (e.g. [3, 5, 2, 18, 14]) To express complex conditions, access nested structure, or produce nested results, an essential feature found in these languages is the nesting of queries, i.e. the embedding of a query into another query. The optimization of object oriented (oo) queries has been intensively studied using ....

....nested results, an essential feature found in these languages is the nesting of queries, i.e. the embedding of a query into another query. The optimization of object oriented (oo) queries has been intensively studied using algebraic rewriting [4, 7, 23, 24, 25] or rewriting of path expressions [7, 13, 14]. However, in spite of the importance of nested queries, we do not know of any research on their optimization. Nested queries in the oo context are usually translated into nested algebraic expressions which are evaluated through rather inefficient nested loops. To a lesser extent, relational ....

[Article contains additional citation context not shown here]

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases, pages 294--305, 1990.

....occur in the form of a sequence of D joins and Map operators have to be transformed (cut and pasted) into a pattern which is indexed by an FTI. The process of cutting and pasting the paths resembles very much the process of cutting and pasting database paths in order to introduce path indexes [km90]. C S P FTI FTI DB myencyclopedia.chapters[C] Sections[S] Paragraphs P ;P contains Polypody R: C.reviewer Map S in C.sections R contains Dupont Select P in S.paragrs Project C,S,P Index join Index join Map FTI R: C.reviewer Map R contains Dupont Select Project ....

A. Kemper G. Moerkotte. Advanced Query Processing in Object Bases Using Access Support Relations. In Proceedings of the International Conference on Very Large Data Bases, pages 294--305, 1990.

....if a DTD is speci ed, disjunction and recursion within an element speci cation lead to a potential in nite set of possible paths. Further, access support relations were not designed to cover generalized path expressions, i.e. those containing wild cards. This is also true for other path indexes [2, 11, 12, 15]. 1 www.goxml.com 2 www.ibm.com xml 3 Xyleme is a joint project between INRIA Rocquencourt and the University of Mannheim. The rest of the paper is organized as follows. Section 2 introduces the Mumpits query language. Section 3 discusses the design and implementation of Mumpits. Section 4 ....

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. Int. Conf. on Very Large Data Bases (VLDB), pages 294-305, 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proceedings of VLDB, pages 290--301, 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proc. of The Conf. on Very Large Data Bases (VLDB), pages 290--301, Brisbane, Australia, Aug 1990.

No context found.

A. Kemper and G. Moerkotte. Advanced query processing in object bases using access support relations. In Proceedings of VLDB, pages 290--301, 1990.

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KEMPER, A., AND MOERKOTTE, G. Advanced Query Processing in Object Bases Using Access Support Relations, Proc. of the 16 VLDB, 1990.

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KM90 Kemper, A., Moerkotte, G.: Advanced Query Processing in Object Bases Using Access Support Relations, Proc. 16th Int. Conf. on Very Large Databases, Sidney, 1990, 290-301.

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