Implementação de um sistema temporal em um banco de dados orientado a objetos

Orientador: Claudia Bauzer MedeirosDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Ciencia da ComputaçãoResumo: Vários modelos têm sido propostos para incorporar o conceito de Tempo em Banco de Dados. A maioria destes modelos limita-se a incorporar as facilidades temporais em Sis­temas de Bancos de Dados Relacionais. Contudo, a maioria das aplicações que requerem um gerenciamento temporal de dados apresenta uma natureza orientada a objeto. As pesquisas sobre a incorporação de Tempo em Bancos de Dados Orientado a Objetos ainda estão em uma fase inicial. Este trabalho apresenta mais uma contribuição para o desenvolvimento das pesquisas nesta área. A contribuição consiste na implementação de um sistema de gerenciamento de tempo para um banco de dados orientados a objetos. Este sistema, a Camada de Gerenciamento Temporal, foi implementado sobre o sistema O2 e permite a definição e gerenciamento de dados temporais orientado a objetos, bem como o processamento de consultas temporais.Abstract: Many temporal data models have been suggested. A great number of these models is based on incorporating time only for relational databases systems. However, the applications that require temporal data management presents a object-oriented nature. Research on object-oriented database systems is still in its initial phase. This work presents a practical contribution to the research in this area. This contribution consists in the development of a temporal data management system for an object oriented database. This system - The Temporal Management Layer - was built on top of the O2 database system and allows the definition and management of object oriented temporal data, as well as the processing of temporal queries.MestradoMestre em Ciência da Computaçã

Query processing in temporal object-oriented databases

This PhD thesis is concerned with historical data management in the context of objectoriented databases. An extensible approach has been explored to processing temporal object queries within a uniform query framework. By the uniform framework, we mean temporal queries can be processed within the existing object-oriented framework that is extended from relational framework, by extending the existing query processing techniques and strategies developed for OODBs and RDBs. The unified model of OODBs and RDBs in UmSQL/X has been adopted as a basis for this purpose. A temporal object data model is thereby defined by incorporating a time dimension into this unified model of OODBs and RDBs to form temporal relational-like cubes but with the addition of aggregation and inheritance hierarchies. A query algebra, that accesses objects through these associations of aggregation, inheritance and timereference, is then defined as a general query model /language. Due to the extensive features of our data model and reducibility of the algebra, a layered structure of query processor is presented that provides a uniforrn framework for processing temporal object queries. Within the uniform framework, query transformation is carried out based on a set of transformation rules identified that includes the known relational and object rules plus those pertaining to the time dimension. To evaluate a temporal query involving a path with timereference, a strategy of decomposition is proposed. That is, evaluation of an enhanced path, which is defined to extend a path with time-reference, is decomposed by initially dividing the path into two sub-paths: one containing the time-stamped class that can be optimized by making use of the ordering information of temporal data and another an ordinary sub-path (without time-stamped classes) which can be further decomposed and evaluated using different algorithms. The intermediate results of traversing the two sub-paths are then joined together to create the query output. Algorithms for processing the decomposed query components, i. e., time-related operation algorithms, four join algorithms (nested-loop forward join, sort-merge forward join, nested-loop reverse join and sort-merge reverse join) and their modifications, have been presented with cost analysis and implemented with stream processing techniques using C++. Simulation results are also provided. Both cost analysis and simulation show the effects of time on the query processing algorithms: the join time cost is linearly increased with the expansion in the number of time-epochs (time-dimension in the case of a regular TS). It is also shown that using heuristics that make use of time information can lead to a significant time cost saving. Query processing with incomplete temporal data has also been discussed