基于关系数据库的对象数据管理方法研究

面向对象方法在许多领域中已经得到了广泛应用 .对象描述方法可以很方便地描述领域中具有复杂结构的数据 ,但这些复杂数据的存储问题还有待妥善解决 .在数据存储管理方面 ,关系数据库系统一直处于主导地位 .本文提出了一种将对象模型和关系模型有机结合在一起的方法 .该方法将数据存储功能从领域数据对象中分离出来 ,采用专门的对象管理器来处理复杂的对象数据与关系数据库的交互问题 .该方法已经被用于海洋传播模型数据库管理系统的设计开发中 ,并取得较好的效果     

Deriving Object Oriented Federated Databases and Processing Federated Queries

In this paper, we present a federated query processing approach to evaluate queries on an Object-Oriented (OO) federated database. This approach has been designed and implemented in the OO-Myriad project, which is an OO extension to the Myriad FDBS researchmyriad:94. Since data integration is performed as part of federated query processing, we have proposed outerjoin, outer-difference and generalized attribute derivation operations together with the traditional relational operations, to be used for integration purposes. To define an OO federated database as a virtual view on multiple OO export databases, we adopt a database mapping strategy that systematically derives each of the class extents, deep class extents and relationships of the federated database using an operator tree consisting of the integration operations. By augmenting federated database queries with this algebraic mapping information, query execution plans can be generated. Based on the original Myriad query processing framework, we have realized the proposed OO federated query processing approach in the OO-Myriad prototype.     

Incrementally maintained network→relational database mapping

An incrementally maintained mapping from a network to a relational database is presented. This mapping may be established either to support the efficient retrieval of data from a network database through a relational interface, or as the first step in a gradual conversion of data and applications from a network to a relational database system. After the mapping has been established, the only data mapped from the network to the relational database are the increments resulting from updates on the network database. The mapping is therefore an efficient alternative to mappings that repeatedly map the results of retrievals through the relational interface from the network database to the relational database. This is in particular the case when the two databases reside on different hosts. Applications on the network database may, under certain restrictions, gradually be moved to the relational database, while the mapping incrementally maintains the relational database for the applications that remain on the network database. A detailed, but generic, account of how to build such a mapping from a network to a relational database is given, including all the algorithms needed and examples of their use.     

Main memory orientated optimization of OO queries using typedDatalog with foreign predicates

Object-oriented database systems (OODBs) have created a demand for relationally complete, extensible, and declarative object-oriented query languages. Until now, the runtime performance of such languages was far behind that of procedural OO interfaces. One reason is the internal use of a relational engine with magnetic disk resident databases. The authors address the processing of the declarative OO language WS-OSQL, provided by the fully operational prototype OODB called WS-IRIS. A WS-IRIS database is main memory (MM) resident. The system architecture, data structures, and optimization techniques are designed accordingly. WS-OSQL queries are compiled into an OO extension of Datalog called ObjectLog, providing for objects, typing, overloading, and foreign predicates for extensibility. Cost-based optimizations in WS-IRIS using ObjectLog are presented. Performance tests show that WS-IRIS is about as fast as current OODBs with procedural interfaces only and is much faster than known relationally complete systems. These results would not be possible for a traditional disk-based implementation. However, MM residency of a database appears to be only a necessary condition for better performance. An efficient optimization is of crucial importance as well     

Performance analysis of parallel object-oriented query processing algorithms

Advanced application domains such as computer-aided design, computer-aided software engineering, and office automation are characterized by their need to store, retrieve, and manage large quantities of data having complex structures. A number of object-oriented database management systems (OODBMS) are currently available that can effectively capture and process the complex data. The existing implementations of OODBMS outperform relational systems by maintaining and querying cross-references among related objects. However, the existing OODBMS still do not meet the efficiency requirements of advanced applications that require the execution of complex queries involving the retrieval of a large number of data objects and relationships among them. Parallel execution can significantly improve the performance of complex OO queries. In this paper, we analyze the performance of parallel OO query processing algorithms for various benchmark application domains. The application domains are characterized by specific mixes of queries of different semantic complexities. The performance of the application domains has been analyzed for various system and data parameters by running parallel programs on a 32-node transputer based parallel machine developed at the IBM Research Center at Yorktown Heights. The parallel processing algorithms, data routing techniques, and query management and control strategies have been implemented to obtain accurate estimation of controlling and processing overheads. However, generation of large complex databases for the study was impractical. Hence, the data used in the simulation have been parameterized. The parallel OO query processing algorithms analyzed in this study are based on a query graph approach rather than the traditional query tree approach. Using the query graph approach, a query is processed by simultaneously initiating the execution at several object classes, thereby, improving the parallelism. During processing, the algorithms avoid the execution of time-consuming join operations by making use of the object references among the objects. Further, the algorithms do not generate any temporary data, thereby, reducing disk accesses. This is accomplished by marking the selected objects and by employing a two-phase query processing strategy.     

Performance evaluation of the object-relational transformation methodology

The emergence of the object-oriented (OO) methodology has shown its capabilities in modelling the real world better than the earlier relational methodology. However, object-oriented databases (OODBs) are still considered immature in comparison with relational databases (RDBs) which have existed for many years. RDBs still continue to dominate the implementation of databases constituting more than 90% of all database implementations [28]. It was felt worthwhile to exploit the great modelling power of OO methodology, while still facilitating relational implementations. These reasons have led us to develop an object-relational transformation methodology [20, 21, 22, 23, 24 and 25] which allows us to use the OO methodology for data modelling and to transform it into a relational logical model for implementation in relational database management systems (RDBMSs). The main purpose of this paper is to present a performance evaluation of the transformation methodology. The evaluation covers I/O cost models of different types of queries. The type of evaluation is basically comparison-based, in which the performance of SQL operations upon a set of tables derived from the relational data model is compared with the tables derived from the OO data model using the transformation methodology. The results of the evaluation show that the performance of the RDB implementation transferred from an OO conceptual model using our object-relational transformation methodology is better than the relational implementation using a conventional relational modelling. Moreover, in many cases, the relational modelling is not applicable since it cannot capture the design semantics particularly relating to collection types. Our object-relational methodology solves this problem.     

Query processing over object views of relational data

This paper presents an approach to object view management for relational databases. Such a view mechanism makes it possible for users to transparently work with data in a relational database as if it was stored in an object-oriented (OO) database. A query against the object view is translated to one or several queries against the relational database. The results of these queries are then processed to form an answer to the initial query. The approach is not restricted to a ‘pure’ object view mechanism for the relational data, since the object view can also store its own data and methods. Therefore it must be possible to process queries that combine local data residing in the object view with data retrieved from the relational database. We discuss the key issues when object views of relational databases are developed, namely: how to map relational structures to sub-type/supertype hierarchies in the view, how to represent relational database access in OO query plans, how to provide the concept of object identity in the view, how to handle the fact that the extension of types in the view depends on the state of the relational database, and how to process and optimize queries against the object view. The results are based on experiences from a running prototype implementation. Edited by: M.T. ?zsu. Received April 12, 1995 / Accepted April 22, 1996     

Qualitative and quantitative temporal constraints and relationaldatabases: theory, architecture, and applications

Many different applications in different areas need to deal with both: databases, in order to take into account large amounts of structured data; and quantitative and qualitative temporal constraints about such data. We propose an approach that extends: temporal databases and artificial intelligence temporal reasoning techniques and integrate them in order to face such a need. Regarding temporal reasoning, we consider some results that we proved recently about efficient query answering in the Simple Temporal Problem framework and we extend them in order to deal with partitioned sets of constraints and to support relational database operations. Regarding databases, we extend the relational model in order to consider also qualitative and quantitative temporal constraints both in the data (data expressiveness) and in the queries (query expressiveness). We then propose a modular architecture integrating a relational database with a temporal reasoner. We also consider classes of applications that fit into our approach and consider patient management in a hospital as an example     

Managing the US Navy's first OO digital mapping project

In the late 1980s the Defense Mapping Agency began converting their paper maps into digital format. A military standard known as Vector Product Format emerged as the format for storing digital vector data. The VPF relational data model, however, has problems representing complex spatial data. In 1991, the US Navy, a DMA database user, began investigating how object technology could improve its digital maps. This research led to the development of the Object Vector Product Format, an object-oriented approach to viewing and editing digital maps and charts. By combining multiple relational databases into a single OO database, OVPF offers users such key advantages as the ability to immediately update and modify the content of the original data. Over the course of developing OVPF we have also learned some valuable lessons about managing OO projects. Our experiences have given us insight into some important risk-management techniques, including how to manage the expectations of decision-makers and sponsors and how to implement effective training methods. Managing the OVPF project was much more rewarding than most due to the greatly increased productivity offered by an OO approach     

Mining multiple-level spatial association rules for objects with a broad boundary

Spatial data mining, i.e., mining knowledge from large amounts of spatial data, is a demanding field since huge amounts of spatial data have been collected in various applications, ranging from remote sensing to geographical information systems (GIS), computer cartography, environmental assessment and planning. The collected data far exceeds people's ability to analyze it. Thus, new and efficient methods are needed to discover knowledge from large spatial databases. Most of the spatial data mining methods do not take into account the uncertainty of spatial information. In our work we use objects with broad boundaries, the concept that absorbs all the uncertainty by which spatial data is commonly affected and allows computations in the presence of uncertainty without rough simplifications of the reality. The topological relations between objects with a broad boundary can be organized into a three-level concept hierarchy. We developed and implemented a method for an efficient determination of such topological relations. Based on the hierarchy of topological relations we present a method for mining spatial association rules for objects with uncertainty. The progressive refinement approach is used for the optimization of the mining process.     

Export database derivation in object-oriented wrappers

Wrappers export the schema and data of existing heterogeneous databases and support queries on them. In the context of cooperative information systems, we present a flexible approach to specify the derivation of object-oriented (OO) export databases from local relational databases. Our export database derivation consists of a set of extent derivation structures (EDS) which defines the extent and deep extent of export classes. Having well-defined semantics, the EDS can be readily used in transforming wrapper queries to local queries. Based on the EDS, we developed a wrapper query evaluation strategy which handles OO queries on the export databases. The strategy is unique in that it considers the limited query processing capabilities of local database systems as well as the language constraints on the local query languages.     

Integrating relational and object-oriented database systems using a metaclass concept

This paper presents a specific approach of integrating a relational database system into a federated database system. The underlying database integration process consist of three steps: first, the external database systems have to be connected to the integrated database system environment and the external data models have to be mapped into a canonical data model. This step is often called syntactic transformation including structural enrichment and leads to component schemas for each external DBMS. Second, the resulting schemas from the first step are used to construct export schemas which are then integrated into global, individual schemas or views in the third step. In this paper we focus on the first step for relational databases, i.e., the connection of a relational database system and the mapping of the relational model into a canonical data model. We take POSTGRES as the relational database system and the object-oriented federated database system VODAK as the integration platform which provides the open, object-oriented data model as the canonical data model for the integration. We show different variations of mapping the relational model. By exploiting the metaclass concept provided by VML, the modelling language of VODAK, we show how to tailor VML such that the canonical data model meets the requirements of integrating POSTGRES into the global database system VODAK in an efficient way.     

Translating update operations from relational to object-oriented databases

In migrating a legacy relational database system to the object-oriented (OO) platform, when database migration completes, application modules are to be migrated, where embedded relational database operations are mapped into their OO correspondents. In this paper we study mapping relational update operations to their OO equivalents, which include UPDATE¹, INSERT and DELETE operations. Relational update operation translation from relational to OO faces the touchy problem of transformation from a value-based relationship model to a reference-based model and maintaining the relational integrity constraints. Moreover, with a relational database where inheritance is expressed as attribute value subset relationship, changing of some attribute values may lead to the change of the position of an object in the class inheritance hierarchy, which we call object migration. Considering all these aspects, algorithms are given mapping relational UPDATE, INSERT and DELETE operations to their OO correspondents. Our work emphasize in examining the differences in the representation of the source schema's semantics resulting from the translation process, as well as differences in the inherent semantics of the two models.     

Implementing associations among classes in an environment of active databases

The association is a native concept from relational databases, one that has been adapted to object oriented (OO) modelling. It is an interesting operator used to describe links among objects of a system, commonly included in the most popular diagram-based OO methodologies. However, those methodologies sometimes present a lack of formality that may undermine its use. In this paper we formalize the semantics of associations. Firstly, we will describe an OO model based on different kinds of constraints. Some of them will be especially useful for describing the semantics of associations. Finally, we will present some remarks about implementation by means of triggers, a new feature incorporated in databases to specify an inner active behavior. This article was submitted by the authors in English.     

Formal approach for reengineering fuzzy XML in fuzzy object-oriented databases

Since semi-structured documents (e.g., XML) could benefit greatly from database support and more specifically from object-oriented (OO) database management systems, we study the methodology of reengineering XML to object-oriented databases when database migration occurs in this paper. In particular, considering the need of processing the imprecise and uncertain information existing in practical applications, we investigate the problem of migrating fuzzy XML to fuzzy object-oriented databases. To find the object-oriented schema that best describes the existing fuzzy XML schema (DTD), we devise a comprehensive approach centering on a set of mapping rules. Such reengineering practices could not only provide a significant consolidation of the interoperability between fuzzy OO and fuzzy XML modeling techniques, but also develop the practical design methodology for fuzzy OO databases.     

<Emphasis Type="BoldItalic">IRSJ</Emphasis>: incremental refining spatial joins for interactive queries in GIS

An increasing number of emerging web database applications deal with large georeferenced data sets. However, exploring these large data sets through spatial queries can be very time and resource intensive. The need for interactive spatial queries has arisen in many applications such as Geographic Information Systems (GIS) for efficient decision-support. In this paper, we propose a new interactive spatial query processing technique for GIS. We present a family of the Incremental Refining Spatial Join (IRSJ) algorithms that can be used to report incrementally refined running estimates for aggregate queries while simultaneously displaying the actual query result tuples of the data sets sampled so far. Our goal is to minimize the time until an acceptably accurate estimate of the query result is available (to users) measured by a confidence interval. Our approach enables more interactive data exploration and analysis. While similar work has been done in relational databases, to the best of our knowledge, this is the first work using this approach in GIS. We investigate and evaluate different sampling methodologies through extensive experimental performance comparisons. Experiments on both real and synthetic data show an order of magnitude response time improvement relative to the final answer obtained when using a full R-tree join. We also show the impact of different index structures on the performance of our algorithms using three known sampling methods.     

基于XML数据的FP-growth算法挖掘研究

XML是跨平台的数据表示、交换技术,由于其本身在自描述性、开放性等方面的优势,在短短的时间内迅速成为行业标准。大量XML数据的涌现给数据挖掘提出了新的挑战。传统关联规则挖掘是基于关系数据库的,即把XML数据文档映射成关系数据库来完成。给出一个使用FP-growth算法直接从XML文档挖掘关联规则的类接口,并且在J2EE平台下用Java语言实现。     

基于同义词表的异构数据库-本体映射

本体是信息在语义层和知识层的描述。将现有的其它数据形式转换为本体表示将有利于实现数据共享和语义推理。目前计算机系统中的数据大多以关系数据库形式存在,因此基于关系数据库构建本体的研究具有重要意义。本文首先分析了单一数据库-本体映射问题,扩充了Ghawi规则以覆盖更多类型的数据关系,其次针对同质异构数据库-本体映射问题,进一步扩充Ghawi规则,给出了基于同义词表的异构数据库-本体映射规则集,实现了异构数据库-本体映射。     

通用关系数据库访问层的设计与实现

在目前的软件开发中,面象对象技术和关系数据库技术都扮演着重要的角色。但是,这两项技术之间存在着著名的不匹配问题。论文通过引入一种精心设计的持久化层,对解决该问题提供了一种新颖且有效的方法。     

基于本体的关系数据集成的查询处理

为实现异构关系数据库的语义集成,针对传统集成技术存在的问题,在对语义网等相关技术进行分析的基础上,研究基于本体的关系数据集成系统中的查询处理问题,提出了一种基于本体的关系数据库集成框架。设计了基于本体的关系数据的描述方法,使用本体作为集成的全局模式来描述关系模式的语义。设计了查询重写算法,该算法可以将基于全局模式的SPARQL查询重写为针对具体关系数据库的查询,从而实现对异构关系数据库的集成。实验表明,该算法具有良好的可扩展性。