数据仓库中多视图环境下的联机维护

数据仓库的视图联机维护是指数数据仓库中的实体化视图实时地与信息源中的数据库仑保持一致,同时不影响前端用户对数据仓库的正常使用。为了解决多视图环境中视图联机维护与下钻查询的一致性问题,文中在数据仓库体系结构中引入了“基库”模型,并提出了相应的视图维护算法３ＶＰＡ。     

数据仓库视图一致性维护与下查研究

数据仓库是存储供查询和决策分析用的集成化信息仓库。实体化视图作为数据仓库中存储的主要信息实体,是由对上一级或外部数据源进行抽取、转化、传输和上载的数据构成的。当源数据发生变化时,如何进行数据仓库实体化视图的一致性维护以及OLAP查询,是一个有着实际意义的研究课题。论文提出的算法Glide采用版本控制、补偿思想和应答机制来协调源数据库与数据仓库间的数据更新,保证了数据仓库视图维护与下查的一致性,提高了算法的健壮程度和对源数据库端CPU的利用率,是以往同类算法的一个本质改进。论文指出算法Glide是完全一致的,并给出了严格的数学证明。文章还通过一个示例说明了该算法在实际中的具体运用。     

数据仓库实体化视图一致性维护与下查研究

实体化视图作为数据仓库中存储的主要信息实体是由对上一级或外部数据源进行抽取、转化、传输和上载的数据构成的.当源数据发生变化时,如何进行数据仓库实体化视图的一致性维护以及0LAP查询,是一个有着实际意义的研究课题.本文提出一个改进性算法Glide*,该算法采用补偿思想来协调源数据库及实体化视图的一致性,从而对系统内存开销及维护工作量方面都有很大的改进.文章还通过一个示例说明了该算法在实际中的具体运用.     

基于时间戳的实化视图多版本维护

实化视图的一致性维护是数据仓库联机维护的关键问题.本文分析了基于三层数据仓库体系结构的3VWQ算法中潜在不一致性的原因,给出了三层结构的改进方法并引入时间戳作为中间版本实化视图的一致性维护标记;提出一种基于时间戳的补偿算法,实现了增量查询维护过程中不一致更新的本地补偿,从而在保证较好性能的同时解决了维护查询过程中的一致性问题.     

数据仓库的集合刷新维护算法

本文提出了一种版本控制集合刷新算法ＶＳＲＡ,它采用增量维护和批处理思想,首先根据原始数据的变化集合,计算出实体化视图的刷新集合,然后据此集合实体化视图,同时利用版本控制保持数据仓库与当前数据库状态的一致性,达到对数据仓库联机维护的目的。ＶＳＲＡ不但减少了数据仓库与数据库之间的通信开销,而且提高了实体化视
视图的刷新效率。严格的版本控制使用户可以随时使用数据仓库进行联机分析处理（ＯＬＡＰ）,并得到正确一     

数据仓库多源实化视图一致性维护的方法研究

研究了多源单视图下数据仓库实化视图联机维护与查询一致性问题,并对现有算法做了改进.改进后的算法在更改信息中增加时间戳控制数据源端查询的时序,并引入动作列表控制数据仓库端信息提交的顺序,采用补偿思想和应答机制来协调数据源与数据仓库间的数据更新,从而保证了实化视图维护和查询的一致性.     

数据仓库实化视图的联机维护

数据仓库实化视图和联机维护是数据仓库系统维护的一项关键技术,采用这种技术,能够在不影响用户正常业务的情况下,实现数据仓库的实化视图数据的及时更新、联机分析处理（OLAP）作为数据仓库的一个主要应用,在数据仓库实化视图的联机维护的过程中会面临严重的数据不一致问题。为了解决这个问题,本文引入“维护库”（Maintaining Database)的概念,提出基于事务触发的视图维护算法TVM,通过消息应答机制实现实化视图与数据源的数据一致性。     

数据仓库实化视图的联机维护

数据仓库实化视图的联机维护是数据仓库系统维护的一项关键技术,采用这种技术,能够在不影响用户正常业务的情况下,实现数据仓库中实化视图数据的及时更新。但联机分析处理（OLAP）作为数据仓库的一个主要应用,在数据仓库实化视图的联机维护过程中会产生严重的数据不 一致问题。为了解决这个问题,引入“维护库”（Maintaining Database)的概念,提出基于事务触发的视图维护算法TVM,采取应答机制,达到数据的一致性。     

基于时间戳实化视图动态维护技术的研究

由于源数据的不稳定性,其结构和数据的变化必须及时传播到实体化视图中,以保持实体化视图与源数据变化的一致性,否则会降低实体化视图中数据的新鲜度,并影响OLAP查询结果的真实性和有效性.为此,本文提出了基于时间戳的动态视图维护技术.该技术采用版本链控制技术,通过时间戳的控制进一步使视图更新和查询的同步进行,有效地解决了由于OLTP更新事务和OLAP事务同时访问数据所发生冲突的问题,在满足视图联机实时维护的同时,更好的提高了数据仓库的新鲜度和OLAP的查询效率.     

一种数据仓库联机维护的集合刷新算法

提出了一种版本控制集合刷新算法（VSRA）.它采用增量维护、版本控制和批处理机制保证数据仓库的联机维护和数据一致性.VSRA不仅减少了数据库和数据仓库之间的通信流量,而且提高了实体化视图的刷新效率.用户可以随时使用VSRA进行联机分析处理,并能得到正确的结果.     

基于网络的数据仓库动态增量维护算法与模型

提出数据仓库动态增量维护算法和模型．文中阐述了动态增量维护算法、模型以及利用该算法对数据仓库视图的维护技术，并以基于网络的数据仓库为例，描述了动态增量维护算法在数据仓库系统中的实现技术．本算法与技术对数据仓库技术的发展及应用有着重要的理论意义和实用价值。     

Analysis of the probability of transaction abort and throughput oftwo timestamp ordering algorithms for database systems

The author analyzes and compares the performance of two timestamp ordering concurrency control algorithms, namely, the basic and multiversion, for database systems. The multiversion algorithm improves the performance of the basic timestamp ordering algorithm by keeping multiple versions of data objects. The author discusses the performance enhancement in the multiversion algorithm over the basic algorithm. The author also discusses the storage overhead due to multiple versions of data objects in the multiversion algorithm. The exact performance model of these algorithms is so complex that it is impossible to find a closed-form solution. The author reduces the complexity of the analysis by analyzing a single transaction in isolation and reflects the presence of other transactions on the isolated transaction by the probability of conflict/abort. The analysis provides useful insight into the performance of these algorithms     

Parallel multisource view maintenance

In a distributed environment, materialized views are used to integrate data from different information sources and then store them in some centralized location. In order to maintain such materialized views, maintenance queries need to be sent to information sources by the data warehouse management system. Due to the independence of the information sources and the data warehouse, concurrency issues are raised between the maintenance queries and the local update transactions at each information source. Recent solutions such as ECA and Strobe tackle such concurrent maintenance, however with the requirement of quiescence of the information sources. SWEEP and POSSE overcome this limitation by decomposing the global maintenance query into smaller subqueries to be sent to every information source and then performing conflict correction locally at the data warehouse. Note that all these previous approaches handle the data updates one at a time. Hence either some of the information sources or the data warehouse is likely to be idle during most of the maintenance process. In this paper, we propose that a set of updates should be maintained in parallel by several concurrent maintenance processes so that both the information sources as well as the warehouse would be utilized more fully throughout the maintenance process. This parallelism should then improve the overall maintenance performance. For this we have developed a parallel view maintenance algorithm, called PVM, that substantially improves upon the performance of previous maintenance approaches by handling a set of data updates at the same time. The parallel handling of a set of updates is orthogonal to the particular maintenance algorithm applied to the handling of each individual update. In order to perform parallel view maintenance, we have identified two critical issues that must be overcome: (1) detecting maintenance-concurrent data updates in a parallel mode and (2) correcting the problem that the data warehouse commit order may not correspond to the data warehouse update processing order due to parallel maintenance handling. In this work, we provide solutions to both issues. For the former, we insert a middle-layer timestamp assignment module for detecting maintenance-concurrent data updates without requiring any global clock synchronization. For the latter, we introduce the negative counter concept to solve the problem of variant orders of committing effects of data updates to the data warehouse. We provide a proof of the correctness of PVM that guarantees that our strategy indeed generates the correct final data warehouse state. We have implemented both SWEEP and PVM in our EVE data warehousing system. Our performance study demonstrates that a manyfold performance improvement is achieved by PVM over SWEEP.Received: 12 November 2001, Accepted: 18 December 2002, Published online: 31 July 2003This work was supported in part by the NSF NYI grant IIS-979624 and NSF CISE Instrumentation grant IRIS 97-29878 and NSF grant IIS-9988776.     

Modular synchronization in distributed, multiversion databases:version control and concurrency control

A version control mechanism is proposed that enhances the modularity and extensibility of multiversion concurrency control algorithms. The multiversion algorithms are decoupled into two components: version control and concurrency control. This permits modular development of multiversion protocols and simplifies the task of proving the correctness of these protocols. A set of procedures for version control is described that defines the interface with the version control component. It is shown that the same interface can be used by the database actions of both two-phase locking and time-stamp concurrency control protocols to access multiversion data. An interesting feature of the framework is that the execution of read-only transactions becomes completely independent of the underlying concurrency control implementation. Unlike other multiversion algorithms, read-only transactions in this scheme do not modify any version-related information, and therefore do not interfere with the execution of read-write transactions. The extension of the multiversion algorithms to a distributed environment becomes very simple     

基于数据挖掘的煤矿安全信息管理模型的研究

基于对数据挖掘技术、粗糙集理论、模糊逻辑与神经网络算法的分析,文章提出了一种基于数据挖掘的煤矿安全信息管理模型的设计方案。该模型应用Web服务器注册技术和XML数据合成技术形成终端数据库,采用数据挖掘技术中的粗糙集理论和模糊逻辑与神经网络算法形成终端数据仓库,并对终端数据仓库进行统一分析、管理和维护,有效地提高了煤矿安全信息管理的效率。     

分布式数据源的实视图维护算法研究

数据仓库作为决策支持系统的集成化数据中心,其数据可以认为是定义在多个不同数据源的实视图集。近年来数据仓库中实视图维护算法的研究激起很多学者的重视。当多个独立的数据源出现并发更新时传统的实视图维护算法可能导致视图维护异常,本文提出了一个双向扫描并行处理实视图维护(BSP)算法,能确保实视图与数据源的完全一致性,并通过实验与其它类似的算法进行了比较,说明本算法具有较高的效率。