网格环境下多数据源的协同查询

伴随网格技术的日益发展，作为对数据应用需求的快速回应，在数据网格之后又出现了网格数据库的概念，其中查询又是数据库应用中一个使用频繁的核心功能，由于每个节点上的数据库可能只包含所需信息的一部分，而且查询操作还涉及到数据库异构性、通信开销等问题，这些都给网格环境下的数据库查询性能带来了新的困难。为了提高网格环境下数据库查询的性能，提出了一种运用协同（CSCW）机制来协调网格用户的查询操作的方法，这不仅体现了系统的协同性，而且降低了数据传输开销，还提高了查询效率。     

网格环境下的数据库访问和集成

为了集成网格环境中的数据库资源,促进网格应用支持现有数据库的访问,提出一种基于服务的数据库访问和集成系统(GridDBAdmin)。GridDBAdmin为用户提供了虚拟的全局逻辑数据库视图,支持用户使用现有的SQL语言同时访问多个数据库。系统由元数据服务和网格虚拟数据库服务构成。其中元数据服务负责发现含有用户所需数据的数据库,网格虚拟数据库服务提供全局逻辑视图,通过分布式查询机制将用户的SQL请求分解到具体的数据库中并进行结果合并。对基于Globus和OGSA-DAI工具包开发的原型系统进行了测试,得到了较好的结果。     

基于数据网格面向服务的查询算法

面向服务的框架（SOA）为用户的服务提供了一个标准的平台,实现服务的提供、发现、配置和集成,以帮助用户查询和处理信息．数据网格是面向服务的架构,为用户进行分布式远程数据查询服务提供了保障．对网格环境下Hidden Web数据库的研究与开发逐渐成为人们关注的焦点问题．要回答用户的查询,数据集成系统需要解决网格上的需求语义分析和关键字查询、建立数据查询模型．将数据库抽象为无向图,节点对应数据库中的元组,边对应“主-外码”的关系．查询的结果是与元组连接的答案树,它与查询的关键字相匹配．针对以上这些问题提出了一个新的查询算法,将改进的动态规划算法用于查询模型,保证Top-1答案树最优,Top-K答案树近似最优;给出了实验测试和评估结果．     

浅析网格数据库的访问与查询技术

网格环境下的数据库研究是一个比较新的研究领域。针对高度异构的网格环境，研究了网格数据库访问与查询的设计与实现，使用户可以更方便、更高效地使用网格中的数据库资源。     

一种空间数据仓库动态物化视图选择算法

物化视图能够有效地提高空间数据仓库的查询效率,但由于空间操作的复杂性,传统数据仓库中物化视图的选择算法不能很好地应用于空间数据仓库。为了在存储空间约束下选择查询进行物化,并动态调整物化视图集,以适应用户查询的时变性和即席查询,提出了空间物化视图选择算法SMVS。实验结果表明该算法是有效可行的,不仅能够提高查询性能,而且解决了查询响应性能随用户查询分布变化而下降的问题。     

基于适应性的网格数据库中子查询的节点优化调度

网格数据库是数据库技术和网格技术相结合后新的研究领域，网格的动态变化特性对数据库查询优化技术提出了适应性的要求。本文提出了基于Petri网描述的子查询计划模型TNSN，通过扩展子查询及其节点的数据关联关系的描述，建立了子查询进行适应性优化调度的查询计划模型；进一步提出了考虑变化的参数在内的耗费估算模型，并在TNSN和耗费模型的基础上提出了适应性优化算法，保证了查询处理过程中可以根据网格参数的变化情况对查询进行适应性调整，最后给出了实验验证。     

基于Oracle物化视图的查询性能优化

Oracle物化视图作为由查询结果构成的数据库对象,可以在本地镜像远程数据库的查询结果,从而有效提高查询效率.介绍了物化视图的概念和作用,物化视图的创建和使用,给出了通过物化视图进行数据库设计的案例说明.     

AnyQuery:网格环境下基于服务的分布式查询处理系统

AnyQuery是一种适用于网格环境、基于服务的分布式查询处理系统，使用统一的数据格式（可扩展标记语言）来表示和传输数据，所有组成模块以网格服务的形式实现，网格服务之间通过标准的接口进行通信．这种接口和实现分离技术屏蔽了不同数据库及其运行节点的差异，为用户提供一致的虚拟关系数据视图和分布式数据查询支持．在分析和研究已有的并行数据库和分布式数据库查询技术的基础上，AnyQuery提出和实现了一种适用于动态网格环境的分布式查询计划生成和执行算法，该算法能够根据网格环境中各节点及其连接网络的实际情况确定查询计划，支持跨数据库的连接查询．基于Globus 3．0开发了AnyQuery的原型系统，性能测试表明该系统具有较好的可扩展性，尤其适合计算密集型的复杂查询．     

网格环境下数据集成模型研究

基于OGSA—DAI给出了一个用于解决网格环境下异构数据源数据集成和分布式查询处理的数据集成模型,在此基础上利用客户端元数据库解决了用户对目标数据库信息了解匮乏的问题,从而为用户的分布式查询处理提供了一种直观透明的、可视化的虚拟数据库视图环境。     

IBFS:一种基于模式匹配索引路由的广度优先的资源搜索机制

目前,大多数的网格数据服务都是采用集中式注册和查找管理机制,容易导致服务器单点失败和访问瓶颈问题.随着网格规模的扩大,P2P对等模式将成为网格的主要框架结构.针对纯分布式无结构P2P网络框架的数据库网格的服务资源搜索机制进行研究,将网格数据服务描述信息的存储、数据服务的搜索以及查询结果的集成都分散到P2P网络中的各个节点上,充分利用了网络资源.结合已有改进的搜索机制和数据库网格服务的特点,提出了一种基于模式匹配索引路由的广度优先资源搜索机制IBFS,在查询数据服务过程中最早缩减查询路由分支,削减访问节点数量,缓解了P2P网络带宽吞噬问题,达到了快速而有效地为用户提供满意的查询结果的目的.     

Recommending XML physical designs for XML databases

Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures for a given database. XML database systems are increasingly being used to manage semi-structured data, and XML support has been added to commercial database systems. In this paper, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a database and a query workload. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system, and they rely on the optimizer for enumerating and evaluating physical designs. We have implemented our advisors in a prototype version of IBM DB2 V9, and we experimentally demonstrate the effectiveness of their recommendations using this implementation.     

Dynamic Query Optimization Approach for Semantic Database Grid

Fundamentally, semantic grid database is about bringing globally distributed databases together in order to coordinate resource sharing and problem solving in which information is given well-defined meaning, and DartGrid II is the implemented database gird system whose goal is to provide a semantic solution for integrating database resources on the Web. Although many algorithms have been proposed for optimizing query-processing in order to minimize costs and/or response time, associated with obtaining the answer to query in a distributed database system, database grid query optimization problem is fundamentally different from traditional distributed query optimization. These differences are shown to be the consequences of autonomy and heterogeneity of database nodes in database grid. Therefore, more challenges have arisen for query optimization in database grid than traditional distributed database. Following this observation, the design of a query optimizer in DartGrid II is presented, and a heuristic, dynamic and parallel query optimization approach to processing query in database grid is proposed. A set of semantic tools supporting relational database integration and semantic-based information browsing has also been implemented to realize the above vision.     

基于物化视图的查询系统研究与实现

在数据库领域,如何加快查询的执行速度非常重要。查询重写技术能透明地利用物化视图回答查询,避免了直接访问大量的原始记录以及耗时的连接和聚集计算,提高了查询 的执行速度。本文讨论了基于数据库中的外键连接关系进行扩展的查询重写方法,以此为核心研究了针对小型数据库的物化视图查询系统,并通过实验证明了物化视图策略的有效性。     

Using object deputy model to prepare data for data warehousing

Providing integrated access to multiple, distributed, heterogeneous databases and other information sources has become one of the leading issues in database research and the industry. One of the most effective approaches is to extract and integrate information of interest from each source in advance and store them in a centralized repository (known as a data warehouse). When a query is posed, it is evaluated directly at the warehouse without accessing the original information sources. One of the techniques that this approach uses to improve the efficiency of query processing is materialized view(s). Essentially, materialized views are used for data warehouses, and various methods for relational databases have been developed. In this paper, we first discuss an object deputy approach to realize materialized object views for data warehouses which can also incorporate object-oriented databases. A framework has been developed using Smalltalk to prepare data for data warehousing, in which an object deputy model and database connecting tools have been implemented. The object deputy model can provide an easy-to-use way to resolve inconsistency and conflicts while preparing data for data warehousing, as evidenced by our empirical study.     

一种实化视图的合并算法

对于拥有大量实化视图的实际数据库应用系统,提出了视图合并的方法以减少整个视图 的数量,缩减实化视图的搜索空间;还提出了归并树和基于归并树的快速有效的合并算法。实验表 明,实化视图的合并是快速寻找可能响应查询的实化视图的一种有效途径,可以显著改进查询处理的 性能。     

Synchronous incremental update of materialized views for PostgreSQL

Materialized views are logically excess stored query results in SQL-oriented databases. This technology can significantly improve the performance of database systems. Although the idea of materialized views came up in the 1980s, only three database management systems, i.e. DB2, Oracle, SQL Server, have been successfully developed completely enough with materialized views so far. The barrier lies in building a module that can incrementally update the materialized views automatically, which corresponds to data changes in the base tables. This paper presents the algorithm to incrementally update the materialized views with inner join, focusing on one with aggregate functions, and building of a program that automatically generates codes inPL/pgSQL for triggers, which can undertake synchronous incremental updates of the materialized views in PostgreSQL.     

静态物化视图的动态Cache优化算法

针对静态物化视图集动态适应能力的不足,提出一种动态cache优化算法DCO(dynamic cacheoptimization).它在保持静态算法获取最优物化集能力的基础上,将cache机制直观、快速的动态特性结合进来,以提高数据仓库的动态自适应性能.在cache机制具体实现中提出了一种新颖的空间申请方法,可以充分利用系统剩余空间提高查询响应性能.实验结果在表明算法有效、可行的同时,也显示出该算法可以在一定程度上克服静态物化集存在的空间-性能饱和效应(space-performance saturation effect,简称SPSE),使通过增加物化空间进一步提高数据仓库对查询的响应速度成为可能.     

一种改进的MDX查询优化算法

近年来数据仓库成为数据库研究领域中最活跃的一个分支,而该领域的一个核心就是OLAP查询优化问题.多维表达式(MDX)为多条相关的OLAP查询语句同时查询提供了接口.如何利用数据仓库中大量的冗余实化视图去加速OLAP的查询,国外学者对该问题进行了大量分析并提出了一些优化算法.本文对上述算法进行了研究,发现其对实化视图的利用并不充分,于是提出了改进算法并进行了验证.实验表明本算法对查询性能有明显提高.     

使用模式树和物化视图进行XML查询

使用模式树解析XQuery查询，将经常被查询的XML节点信息存储到物化视图中，利用物化视图和用户查询的交叉部分，直接从物化视图中获取用户的查询内容。对于两者不完全匹配的部分，使用补充规则，使得能部分使用物化视图，以提高查询效率。文章还给出了模式树的匹配算法。     

Answering queries using views: A survey

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results. Received: 1 August 1999 / Accepted: 23 March 2001 Published online: 6 September 2001