基于属性相关性的SPARQL查询优化方法

目前主流的RDF存储系统都是基于关系数据库的,其查询引擎都是将SPARQL转换为SQL,然后由数据库的查询引擎来执行查询.但是,目前的数据库查询优化器对于连接查询的选择度估计都是基于属性独立假设的,这往往导致估计错误而选择了效率低的执行计划,所以属性相关性信息对于SPARQL查询优化器能否找到效率高的执行计划是非常重要的.针对SPARQL转换为SQL后,因连接操作没有优化导致查询效率不高的问题,提出了利用本体信息自动计算属性相关性的方法,从而调整连接操作的选择度估计值,调整连接顺序,提高SPARQL查询中基本图模式的连接查询效率.     

一种自底向上的静态语义查询优化算法

演绎数据库语义查询优化是运用数据库中的语义知识，即完整性约束条件，将用户提交的一种查询转换为能有效执行，并与原查询等价的查询的一种优化方法．至今在这一领域已有了许多的算法，但大多是基于自顶向下的查询计算模式．而本文提出的静态语义查询优化算法及其改进算法是在优化“并”和“连接”操作的过程中进行自底向上的查询计算，因此相对自顶向下的计算方式更有效地提高了查询执行效率．     

网格环境下基于流水线的多重相似查询优化

提出一种网格环境下基于流水线技术的分布式多重相似查询的优化算法(pipeline-based distributed similarity query processing,简称pGMSQ).首先,当用户提交若干个查询请求时,采用基于代价的动态层次聚类策略(dynamic query clustering,简称DQC)对其进行合并.然后在数据结点层,采用索引支持的向量集缩减方法快速过滤无关向量.最后,在执行结点层对候选向量执行求精操作返回结果向量.由于本查询采用了流水线技术,实验结果表明,该方法在提高查询性能的同时也提高了系统的吞吐量.     

基于粒子群算法的数据库查询优化

研究粒子群算法在数据库查询优化中的应用问题。为了解决大型数据库信息检索困难、查询效率低的问题,提出了一种基于粒子群算法优化数据库查询技术方案。算法提出了一种数据库查询执行计划代价模型,主要包括了查询多链接次序以及副本的选择问题,准确定义了数据库查询执行代价,采用提出的粒子群算法来优化并求解该执行代价问题,从而使得分组数目更少、数据定位更精确。实例验证结果表明,通过属性表现和违规行为任何教师都可以被准确定位,减少了分组,为数据库查询提供了优化。     

DETECTOR:基于关系数据库通用的在线关键词查询系统

关系数据库上的现有数据库关键词检索系统可分为在线和离线两大类,它们都难以兼顾查询效率和效果:在线系统能够获得数据库最新结果,但速度较慢;离线系统使用预处理提高查询速度,但若数据库更新就要重新执行预处理.在离线系统DETECTOR基础上,设计并实现增量更新方案,在不影响查询效率的前提下最大程度地保证了查询结果的准确性.另一个贡献是实现了通用的预处理模块,使得普通用户也能顺利进行预处理操作.     

SQL Server查询优化器原理与优化实例分析

查询是数据库的核心操作,随着数据库技术的发展以及数据量急剧增加,对查询性能的要求越来越高,查询优化成为数据库管理系统亟待解决的重要问题。文中针对应用最广泛的SQL Server数据库的查询优化器进行研究。通过图形研究查询优化器的工作原理,并深入分析提交SQL语句、解析、代数化、查询优化、编译、执行、结果等查询优化器的工作步骤;进行实例分析,运用图形表示了逻辑树和经过优化后得到的查询执行计划。结果表明,SQL语句是查询优化的基础,实际应用时需要写出符合查询优化器规则的SQL语句     

SQL Server查询优化器原理与优化实例分析

查询是数据库的核心操作,随着数据库技术的发展以及数据量急剧增加,对查询性能的要求越来越高,查询优化成为数据库管理系统亟待解决的重要问题。文中针对应用最广泛的SQL Server数据库的查询优化器进行研究。通过图形研究查询优化器的工作原理,并深人分析提交SQL语句、解析、代数化、查询优化、编译、执行、结果等查询优化器的工作步骤;进行实例分析,运用图形表示了逻辑树和经过优化后得到的查询执行计划。结果表明,SQL语句是查询优化的基础,实际应用时需要写出符合查询优化器规则的SQL语句。     

基于MySql的查询优化技术研究

查询优化研究是数据库设计与应用中重点考虑问题,在研究MySql数据库查询优化技术基础上,对配置参数中的数据缓存区和日志缓存区的参数进行优化设置,提高查询效率。针对MySql查询重用技术的特点及存在不规范化sql语言等重用性不高问题,通过设计相关模块改进查询重用功能;增加查询缓冲区的查询执行计划模块来解决查询缓存区大数据量结果集存储问题,并通过实验进行验证,从而改进查询优化效率。     

多源异构数据库数据查询处理研究

针对多源敖据库之间的异构差异,分析和研究查询执行过程中的查询预处理、查询分解、查询优化相关问题,提出中间件体系结构的多教据库系统解决方法.查询预处理完成时全局查询语句的等价修改,辅助查询分解执行,提高其效率,查询分解将全局查询分解为可在局部数据库上执行的局部查询,同时尽可能保证取回全局查询相关数据,井给出查询分解方法及优化算法.     

基于模拟退火的查询优化算法的设计与实现

提出了一种基于模拟退火方法的查询优化算法，在查询策略的状态空间上构造了模拟退火处法的一个原型，利用模拟退火算法对联结操作进行了优化。实验说明，该算法得到的执行策略优于传统算法得到的执行策略。     

Query optimization in XML structured-document databases

While the information published in the form of XML-compliant documents keeps fast mounting up, efficient and effective query processing and optimization for XML have now become more important than ever. This article reports our recent advances in XML structured-document query optimization. In this article, we elaborate on a novel approach and the techniques developed for XML query optimization. Our approach performs heuristic-based algebraic transformations on XPath queries, represented as PAT algebraic expressions, to achieve query optimization. This article first presents a comprehensive set of general equivalences with regard to XML documents and XML queries. Based on these equivalences, we developed a large set of deterministic algebraic transformation rules for XML query optimization. Our approach is unique, in that it performs exclusively deterministic transformations on queries for fast optimization. The deterministic nature of the proposed approach straightforwardly renders high optimization efficiency and simplicity in implementation. Our approach is a logical-level one, which is independent of any particular storage model. Therefore, the optimizers developed based on our approach can be easily adapted to a broad range of XML data/information servers to achieve fast query optimization. Experimental study confirms the validity and effectiveness of the proposed approach.     

Indexing and querying XML using extended Dewey labeling scheme

Finding all the occurrences of a tree pattern in an XML database is a core operation for efficient evaluation of XML queries. The Dewey labeling scheme is commonly used to label an XML document to facilitate XML query processing by recording information on the path of an element. In order to improve the efficiency of XML tree pattern matching, we introduce a novel labeling scheme, called extended Dewey, which effectively extends the existing Dewey labeling scheme to combine the types and identifiers of elements in a label, and to avoid the scan of labels for internal query nodes to accelerate query processing (in I/O cost). Based on extended Dewey, we propose a series of holistic XML tree pattern matching algorithms. We first present TJFast to answer an XML twig pattern query. To efficiently answer a generalized XML tree pattern, we then propose GTJFast, an optimization that exploits the non-output nodes. In addition, we propose TJFastTL and GTJFastTL based on the tag + level data partition scheme to further reduce I/O costs by level pruning. Finally, we report our comprehensive experimental results to show that our set of XML tree pattern matching algorithms are superior to existing approaches in terms of the number of elements scanned, the size of intermediate results and query performance.     

Optimizing complex queries based on similarities of subqueries

As database technology is applied to more and more application domains, user queries are becoming increasingly complex (e.g. involving a large number of joins and a complex query structure). Query optimizers in existing database management systems (DBMS) were not developed for efficiently processing such queries and often suffer from problems such as intolerably long optimization time and poor optimization results. To tackle this challenge, we present a new similarity-based approach to optimizing complex queries in this paper. The key idea is to identify similar subqueries that often appear in a complex query and share the optimization result among similar subqueries in the query. Different levels of similarity for subqueries are introduced. Efficient algorithms to identify similar queries in a given query and optimize the query based on similarity are presented. Related issues, such as choosing good starting nodes in a query graph, evaluating identified similar subqueries and analyzing algorithm complexities, are discussed. Our experimental results demonstrate that the proposed similarity-based approach is quite promising in optimizing complex queries with similar subqueries in a DBMS.     

一种有效的XQuery更新操作

XQuery是XML查询语言的推荐标准。正如其它数据查询语言一样,XQuery也有自己的更新操作,XQuery更新操作就是用插入、替换、删除等操作对XML文档树进行修改,本文依照W3C组织7月草案[1]对XQuery更新操作提出了一些新的想法。诸如:对上述操作进行完善,使之更易读写,还设想了一个update操作符用来进行集中式更新操作,可以提高执行效率。当然这些都符合草案关于XQuery更新操作的规范[2]。     

数据集成中XML数据查询语义重写

查询重写是数据库研究的一个基本问题，它和查询优化，数据仓库，数据集成，语义缓存等数据库问题密切相关，为提高集成系统的查询效率，系统选择提交频率较高的XML查询物化为中间层视图，用户提交查询后，系统尽可能利用中间视图层中视图，而不是访问数据源来回答查询，这个问题实际可以归结为半结构化查询重写问题，考虑到中间视图层空间的有限性，已有视图应当尽可能回答更多的查询，传统查询重写方法有考虑半结构化数据之间的约束，而根据约束可以等价变换查询，从而提高中间视图层中的表达能力，提出了一种新的半结构化查询重写的方法，该方法在保证算法正确性和完备性的基础上，利用上半结构化数据中的约束，尤其是XML文件中的路径依赖，来增强中间层物化视图的表达能力，理论分析和初步原型实验证明方法的有效性。     

路径分区编码优化小枝查询

有效地存储查询XML文档已经成为当今数据库领域的研究热点。从XML文档的路径统计出发,提出了路径分区存储编码方案,并依此消除了小枝查询的后裔边和通配符。针对这类不含//和*的小枝查询,利用路径分区编码的特性,给出了基于结构约束节点的Twig查询算法,极大地减少了结构连接次数。实验表明,该算法能有效滤除无关元素,提高小枝查询效率。     

Foundations for object-oriented query processing

A minimal framework for an object-oriented query language standard should (1) include a formal definition of a high-level data model and the syntax and semantics of associated query languages, (2) provide the functionality of relational query languages, and (3) support proofs of correctness of transformations for logical query optimization. In this paper, a high-level conceptual model for object-oriented query processing is discussed; the model includes widely-used structural abstractions such as the isa relationship, associations (properties) between complex objects and complex objects/values, and inheritance of properties. A formal, algebraic query language for the model, inspired by relational algebra, is presented. Operators of the algebra allow queries based on values, queries that manipulate entire objects, and queries that construct new objects from existing objects/values. All queries retain connections to existing database objects, providing logical access paths to data. Each query result is a class, so the algebra has the closure property. The intensional and extensional results of query operators are summarized. Two forms of logical query optimization supported by the query algebra are outlined: algebraic transformations and classifier-based optimizations (optimizations which employ inclusion and exclusion dependencies between classes).     

DVQ: Towards Visual Query Processing of XML Database Systems

XML has been recognized as a promising language for data exchange over the Internet. A number of query languages have been proposed for querying XML data. Most of those languages are path-expression based. One difficulty in forming path-expression based queries is that users have to know the structure of XML data against which the queries were issued. In this paper, we describe a DTD-driven visual query interface for XML database systems. With such an interface, a user can easily form path-expression based queries by clicking elements in the DTD tree displayed on the screen and supplying conditions if necessary. The interface and the query generation process are described in detail.     

一种支持高效XML 路径查询的自适应结构索引

提出了一种新的自适应结构索引:AS-Index(adaptive structural index),能够克服现有静态索引和自适应索引的缺陷,具备高效的查询和调整性能.AS-Index 建立在F&B-Index 的基础之上,其索引结构包括F&B-Index,Query-Table 和Part-Table.Query-Table 能够记录频繁查询,避免了查询过程中的冗余操作.并且,在Query-Table 的基础上提出了自底向上的查询处理过程,能够充分利用现有的频繁查询高效地回答非频繁查询.Part-Table 用于优化包含祖先后裔边的查询,进一步提高了查询性能.现有的自适应结构索引的调整粒度是XML 元素节点,调整过程往往需要遍历整个文档.而AS-Index 是基于F&B-Index 节点的增量调整,其过程是局部的,高效的,并且能够支持复杂分支查询的调整.实验结果表明,AS-Index 在查询和调整性能上优于现有的XML 结构索引.同时,相比于现有的自适应结构索引,AS-Index 针对大规模文档具有更加优良的可扩展性.     

基于直方图的空间查询选择率估计研究

空间查询优化是空间数据库中的关键问题之一,以查询代价估算为基础的查询优化技术是提高查询效率的一种重要方法,而估算代价的主要问题是估算查询结果(选择率)的大小。针对空间数据库中最常用的两种查询—空间选择和空间连接,阐述了几种主要用于查询选择率佑计的直方图算法,并对各算法的优缺点做了分析,最后对空间查询选择率估计的研究方向进行了展望。