The query language OVAL which is intended for the integration with the databaseprogramming language based on C++ is proposed in this paper. The work addresses the impedance mismatch problem [1] between the syntax and...
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The query language OVAL which is intended for the integration with the databaseprogramming language based on C++ is proposed in this paper. The work addresses the impedance mismatch problem [1] between the syntax and the semantics of the programming and query language. The query language OVAL is based on the functional query language FQL [3] extending it for the manipulation of complex objects. The salient features of the OVAL query language are: (i) functional nature of the query language, which makes the language suitable for the integration with the procedural programminglanguages and provides modular style of query definition, (ii) the use of schema information for expressing queries and (iii) recursive evaluation of the algebraic operations on set structured complex objects.
View materialization is a well-known optimization technique of relational database systems. In this work, we present a similar, vet more powerful, optimization concept for object-oriented data models: function materia...
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View materialization is a well-known optimization technique of relational database systems. In this work, we present a similar, vet more powerful, optimization concept for object-oriented data models: function materialization. Exploiting the object-oriented paradigm-namely, classification, object identity, and encapsulation-facilitates a rather easy incorporation of function materialization into (existing) object-oriented systems. Only those types (classes) whose instances are involved in some materialization are appropriately modified and recompiled, thus leaving the remainder of the object system invariant. Furthermore, the exploitation of encapsulation (information hiding) and object identity provides for additional performance-tuning measures that drastically decrease the invalidation and rematerialization overhead incurred by updates in the object base. First, it allows us to cleanly separate the object instances that are irrelevant for the materialized functions from those that are involved in the materialization of some function result, and thus to penalize only those involved objects upon update. Second, the principle of information hiding facilitates fine-grained control over the invalidation of precomputed results. Based on specifications given by the data type implementor, the system can exploit operational semantics to better distinguish between update operations that invalidate a materialized result and those that require no rematerialization. The paper concludes with a quantitative analysis of function materialization based on two sample performance benchmarks obtained from our experimental object base system GOM.
This paper introduces a model that combines and extends capabilities of relational and object oriented systems. Within a simple, statically-typed framework, the model supports abstract data types (ADTs), a multiple in...
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