工程数据库管理系统OSCAR的页面服务器

为了适应工程应用的特点，工程数据库管理系统OSCAR采用了页面服务器体系结构．OSCAR的页面服务器集中实现了数据库管理系统核心的事务管理，即并发控制和恢复功能．它向客户端提供支持多用户共享的、可靠的数据页面服务，客户端模块在此基础上构建一个功能完备的工程数据库管理系统．介绍了设计与实现OSCAR页面服务器过程中碰到的问题及其解决方法，包括OSCAR页面服务器的功能在物理层、缓冲层和事务层的分配，客户／服务器环境中ARIES恢复策略的改进以及先写日志文件原则的实现方案。     

Data structures and DBMS for computer-aided design systems

The structures for the storage of data in CAD systems influence to a large extent the effectiveness of the system. This paper reviews the wide range of data structures and database management systems (DBMS) available for structuring CAD data. Examples of basic data types are drawn from the MODULA-2 language. The relationship between these basic data types, their composite structures and the classical data models (on which many DBMS are based) is discussed, and the limitations of existing DBMS in modelling CAD data highlighted. A set of requirements for CAD database management systems is drawn up and the emerging role of product models (which seek to encapsulate the totality of data elements required to define fully an engineering artefact) is explored.     

一种数据库加密及密钥管理方法

数据庠中敏感数据的防窃取和防篡改问题是信息安全的一个重要方面,在数据库管理系统（DBMS）中加入安全特性已迫在眉睫。提出一种方法,对DBMS实现进行修改,在不影响DBMS功能的情况下使其支持数据库加密,并且对DBMS性能的影响也很小。给出了一个与之相关的密钥管理体系结构,使得密钥的管理既安全又高效。最后,在TPC—H数据集上对数据库加密后的性能进行了评估。     

一种基于关系数据库的友好查询语言GBD

数据库管理的主要功能之一是查询处理，查询功能的完备性和操作界面的友好性是数据库应用的基本要求。ＧＢＤ查询语言即是以这一基本要求为目标，以ＦＯＸ数据库的应用为背景，并借鉴ＳＱＬ语言的查询功能特点进行研制的。ＧＢＤ语言以可交互式函数方式定义关系集合运算，以表格形式将查询语言的结构与查询交互界面相统一，以数学运算的递归原理实现语言对查询问题的处理过程。ＧＢＤ语言的设计独立于具体的数据库管理系统，可在多种关系数据库上实现。     

计算机集成制造的数据管理策略

本文论述了计算机集成制造（CIM）的数据管理策略。首先从CIM的信息集成角度提出数据管理、全局数据与局部数据等基本概念，阐明数据管理应具备的两个关键功能，即总体的数据规划与全局数据的标准化。结合我国CIMS重点应用工厂的实际，提出了工厂开发总体数据规划的具体内容。最后，建议数据库专题分组开展全局数据标准化的研究与实施，以促进重点应用工厂从中近期到无景数据管理的过渡。     

移动空间数据类型和操作的初步研究

1 引言移动空间对象是随时间变化的空间数据,由时空数据库(Spatio-Temporal Databases)进行管理和处理。一个空间点可能随时间而改变其位置,为了完整地反映该点的信息,数据库中应该存储该点的全部历史信息,这个空间对象就是一个移动点。同理,一个区域也可能随时间移动、扩大或缩小。时空现象在现实生活中非常普遍,如飞机航行时随着时间变化而改变它的空间位置,这飞机就是一个移动点;当森林中某处发生火灾时,火灾区就是一个空间对象:区域。该区域可能     

A Framework for Management of Semistructured Probabilistic Data

This paper describes the theoretical framework and implementation of a database management system for storing and manipulating diverse probability distributions of discrete random variables with finite domains, and associated information. A formal Semistructured Probabilistic Object (SPO) data model and a Semistructured Probabilistic Query Algebra (SP-algebra) are proposed. The SP-algebra supports standard database queries as well as some specific to probabilities, such as conditionalization and marginalization. Thus, the Semistructured Probabilistic Database may be used as a backend to any application that involves the management of large quantities of probabilistic information, such as building stochastic models. The implementation uses XML encoding of SPOs to facilitate communication with diverse applications. The database management system has been implemented on top of a relational DBMS. The translation of SP-algebra queries into relational queries are discussed here, and the results of initial experiments evaluating the system are reported. Work performed while a Ph.D. student at the University of Kentucky.     

The MurMur project: Modeling and querying multi-representation spatio-temporal databases

Successful information management implies the ability to design accurate representations of the real world of interest, in spite of the diversity of perceptions from the applications sharing the same database. Current database management systems do not provide representation schemes that preserve each perception while fully supporting their diversity and maintaining their consistency. This is a major hindrance for building an all-embracing view of the world while serving multiple applications, whether it is by developing a single database or by providing transparent access (e.g., via the Web) to several heterogeneous data sources (that would typically hold a great diversity of stored representations). This paper reports on results from the multiple representations and multiple resolutions in geographical databases project,¹ funded by the European Commission under the 5th Framework Programme. The objective of the project has been to enhance GIS (or DBMS) by adding functionality that supports multiple coexisting representations of the same real-word phenomena (semantic flexibility), including representations of geographic data at multiple resolutions (cartographic flexibility). The new functionality enables a semantically meaningful management of multi-scale, integrated, and temporal geo-databases.     

网格环境下的数据库系统

网格计算是一种重要的新技术，网格上的大量数据需要使用数据库系统来管理。在介绍了与网格环境下数据库系统相关的研究工作之后，讨论了网格数据库的研究内容，包括网格数据库管理系统、网格数据库集成和网格应用的新需求。建议数据库研究人员对网格数据库作更多的研究，致力于从网格应用中发现并解决网格数据库面临的新问题。     

一种基于对象关系模型的时空数据库管理系统体系结构

时空数据库的关键与难点在于其实现技术．本文提出了一种基于对象关系模型的优化型时空数据库管理系统体系结构，该体系结构采用时空数据类型扩展和时空操作扩展技术对数据库管理系统的内核进行扩充，使其具有内建的时空数据管理能力，同时以时空查询优化层实现时空查询的逻辑优化，解决了底层数据库管理系统的查询优化问题。     

一种基于对象的复杂数据管理系统的实现

数据应用环境的演变和数据模式的越来越复杂,促使系统实现者在数据（库）管理系统中引入了面向对象的概念。本文描画了在非面向对象的底层数据库管理系统上实现基于对象的复杂数据管理系统的可能,尤其详细阐述了系统数据模块ｃｒｉｐｔ模块如何实现复杂语义的生成,以及用户数据模块如何提供复杂数据的统一接口和完成复杂行为的执行。     

电动汽车充电站管理系统

以北京市电动汽车充电站管理系统为例,描述了基于485网络的MIS(信息管理系统)的设计和实现。该系统充分分析了电动汽车充电站的系统需求,介绍了一种数据库系统的开发方法,实现了对充电机参数的设置和充放电控制,完成了人机界面对话和对数据库的管理和打印,并能对充电机的状态进行判断及故障诊断。     

支持工作流的DBMS模型

本文提出支持工作流的数据库管理系统模型,目的在于借助DBMS对数据管理的成熟技术和对DBMS的扩展,使数据库能够为工作流管理系统的任务恢复提供相关数据一致性服务,从而为工作流一致性管理做出贡献。     

一种基于SQL的层次查询方法

关系型数据库管理系统不适合表达层次模型问题,标准的SQL语言无法满足复杂的层次查询要求,但有许多实际应用系统,其结构和查询要求都呈现很强的层次特征。本文提出了一种在ORACLE DBMS环境下,利用C和SQL语言实现的层次查询方法,可广泛应用于工程数据管理信息系统的设计过程。     

Query triggers for XML DBMS: Efficient implementation based on shadow mechanism

Active database systems extend functionality of traditional database systems with powerful mechanisms of triggers (or active rules) support. Triggers provide a uniform and convenient base that can be used for realization of internal DBMS functions, such as support of integrity constraints, representations, access authorization, statistics gathering, monitoring and notifications and for higher efficiency of external applications. Among representative examples of external applications that can be based on the usage of properties of active DBMS are data-intensive expert systems and workflow management systems. Today, the majority of industrial relational DBMS already support triggers, while XML DBMS, which are comparatively new, lack such functionality. Expansion of the XML DBMS application field and its usage in constructing complex application system stimulates appearance of new research works aimed at extending the functionality of XML DBMS by trigger support.In this paper, the authors define a special type of triggers for XML DBMS—XML triggers responding to data retrieval—and propose methods for their implementation. The paper also discusses examples of applications where XML query triggers occur to be useful and gives review of existing research works in this area.     

面向税控收款机应用的嵌入式数据库的设计

针对税控收款机应用对数据存储和查询操作的要求,设计了一种基于Flash文件系统的关系型嵌入式数据库系统,该数据库系统采取模块化和层次化的设计方式,将系统划分成接口处理层、数据库引擎层、数据存取层、数据库维护模块和数据存储模块,并具有开销小、可移植性强、执行效率高等特点,特别适合于税控收款机应用的数据管理领域。     

PARADISE: Big data analytics using the DBMS tightly integrated with the distributed file system

There has been a lot of research on MapReduce for big data analytics. This new class of systems sacrifices DBMS functionality such as query languages, schemas, or indexes in order to maximize scalability and parallelism. However, as high functionality of the DBMS is considered important for big data analytics as well, there have been a lot of efforts to support DBMS functionality in MapReduce. HadoopDB is the only work that directly utilizes the DBMS for big data analytics in the MapReduce framework, taking advantage of both the DBMS and MapReduce. However, HadoopDB does not support sharability for the entire data since it stores the data into multiple nodes in a shared-nothing manner—i.e., it partitions a job into multiple tasks where each task is assigned to a fragment of data. Due to this limitation, HadoopDB cannot effectively process queries that require internode communication. That is, HadoopDB needs to re-load the entire data to process some queries (e.g., 2-way joins) or cannot support some complex queries (e.g., 3-way joins). In this paper, we propose a new notion of the DFS-integrated DBMS where a DBMS is tightly integrated with the distributed file system (DFS). By using the DFS-integrated DBMS, we can obtain sharability of the entire data. That is, a DBMS process in the system can access any data since multiple DBMSs are run on an integrated storage system in the DFS. To process big data analytics in parallel, our approach use the MapReduce framework on top of a DFS-integrated DBMS. We call this framework PARADISE. In PARADISE, we employ a job splitting method that logically splits a job based on the predicate in the integrated storage system. This contrasts with physical splitting in HadoopDB. We also propose the notion of locality mapping for further optimization of logical splitting. We show that PARADISE effectively overcomes the drawbacks of HadoopDB by identifying the following strengths. (1) It has a significantly faster (by up to 6.41 times) amortized query processing performance since it obviates the need to re-load data required in HadoopDB. (2) It supports query types more complex than the ones supported by HadoopDB.     

Spatial Data Handling for ITS: Perspective, Issues and Approaches

This paper studies problems related to spatial data handling in intelligent transportation systems (ITS) and it investigates solution approaches. The discussion focuses on three areas: (1) data management and processing, (2) dynamic data integration, and (3) data exchange and communications. For data management and processing, the paper considers the approach of the combined use of GIS and database management systems (DBMS). The framework under which GIS and DBMS are integrated and the interoperability requirements related to this framework are discussed. Unified location referencing systems, location referencing message specification, and ITS datum are major strategies proposed to address problems arising from dynamic data integration in ITS applications. The paper provides a review on the research associated with the development of these strategies and recommends the use of reference maps in places where data collection or reconciliation efforts can be coordinated. To facilitate data exchange and communications, the paper investigates the use of data dictionaries, data coding, and data models. Key issues related to their development are identified, and potential approaches to address these issues are suggested.     

Multiversion views: Constructing views in a multiversion database

Commercial DBMS offer mechanisms for views and for versions. Research and development efforts in these directions are, however, characterized by concentration on either the one or the other mechanism, very seldom trying to take advantage of their complementary properties. This paper presents the multiversion view mechanism, which allows these orthogonal concepts to be managed together, taking advantage of their combined characteristics. Unlike previous efforts to combine views and versions, multiversion views create views over versions of data, thereby offering users coherent logical units of the versioned world. They allow a wide range of (virtual) data reorganization possibilities, which encompass, among others, operations found in temporal databases and OLAP. Multiversion views are illustrated and motivated by needs from a real life large case study of complex configuration management, described at the end of the paper.     

数据库负载自适应的体系结构研究*

随着网络应用对数据库的访问量日益增大,数据库管理系统（DBMS）受到越来越多的关注。自主计算的研究解决了DBMS内部资源管理的问题,但是无法解决外部负载的管理问题;不同的负载具有不同的商业价值,具有重要商业价值的负载其性能要求应当优先得到满足。将针对负载自适应技术开展研究,提出一个改进的数据库负载自适应体系结构框架并作出了测试。结果表明该框架起到了提高用户满意率的作用。