基于等价变换的分布式查询优化方法研究

分析了分布式数据库的查询准则、代价估算及分布式查询的层次结构,并利用关系操作与SQL描述存在对应关系的特点,将分布式查询转换关系代数表达式,对关系代数表达式进行等价变换实现查询的优化,最后以实例对基于关系代数等价变换的分布式数据库查询优化方法进行验证。     

支持属性粒度数据库加密的查询重写算法

DAS(database as a service)模型数据库中采用加密方案的关键问题之一是针对密文关系的查询处理.DAS模型特有的体系结构和信任模型决定了加密解密操作只能在客户端进行,目前的方案普遍在元组粒度加密的基础上进行查询重写,不可避免地造成了加密效率的损失.为此,提出一种支持属性粒度加密方案的查询重写算法,利用关系代数公式对查询语句进行等价变换,将涉及加密属性的条件谓词与其他条件谓词分离,重构查询语句,支持任意层次的相关子查询.实验显示,算法能够降低客户端与服务器间的网络传输数据量,从而有效地缩短加密DAS模型数据库的查询执行时间.     

SPARQL查询的关系代数表示与转换方法

为解决基于本体的数据集成系统中的查询转换问题,提出SPARQL查询的关系代数表示和转换方法。引入RDF图模式的关系代数,定义了五种基本的关系运算,给出了SPARQL查询的关系代数表示;提出了SPARQL到SQL的查询转换方法,将基于本体的SPARQL查询转换为可在关系数据库上直接执行的SQL查询,从而实现关系数据库的集成。系统实现表明,该方法能够有效地实现查询语言的转换。     

含有空值关系数据库的查询处理

本文在深刻理解空值语义的基础上，给出一种处理占位型空值的方法，空值环境下关系数据库的查询策略，定义了含三种查询操作的关系代数最小完备集中的关系代数运算，并对查询计算的有效性和完备性进行了分析。     

基于二阶基调的时空查询代数形式化定义

提出了一种基于对象关系数据库和中间件技术的时空数据库系统实现与查询处理框架，着重论述了其中的时空查询代数。引入了二阶基调用于时空查询代数的形式化定义，给出了时宅数据库的逻辑结构定义、类型系统定义以及查询操作定义。     

OODB模型的形式定义和查询代数

近十年来,面向对象数据库(CK)DB)的研究已越来越深入,对于类、对象标识、类继承性、查询操作等的研究也很多.本文介绍OODB中一个新的概念—对象继承性,这个概念发展了OODB类继承性概念,使(X)DB的形式定义和查询代数发生变化,而且更符合实际和易于存储操作.     

PAR平台数据库查询优化方案

数据库系统的查询优化技术是提高数据库系统效率的重要技术。当今Java和C＋＋等主流程序设计语言依靠SQL语句,造成数据库系统中查询复杂、繁琐、效率低下、可靠性得不到保证等。针对上述问题,在PAR（Partition And Recur）平台数据库关系代数实现机制基础上,提出和实现基于关系代数的查询优化规则设计方法。这种设计不仅提高了数据库查询效率,也为高可靠数据库的形式化开发提供了依据。     

XML形式数据模型及其查询代数

提出了XML的形式数据模型及其查询代数,主要包括以下几个方面：构造先后序关系、引入带根连通有向图、建立XML形式数据模型(XFDM)和XML查询代数(XFQA)。它形成了一个较为完整的XML数据库管理系统的理论基础,可以作为XML以及其它半结构化数据库管理系统查询存储、查询分解、查询优化和查询实现的形式化基础。     

Skyline查询处理数据立方体代数

维空间的Skyline查询处理技术是近年来数据库技术领域的一个研究重点和热点.目前所有的研究工作都是直接在原始数据表上执行关系查询代数操作来获得最终的结果集,然而,随着原始数据表的数据量和维目标个数的增大,这些研究工作将不再适用.基于此,首次研究Skyline集合上的查询代数操作,使得Skyline查询处理的输入数据来自于小规模的Skyline结果集,而非海量的原始数据表.并且,首次给出一个集成多维对象集合和该对象集合上的Skyline结果集的形式化模型,该模型适合目前Skyline查询计算的应用,并在该模型的实例上研究Skyline集合的查询代数操作.同时,给出查询代数体系的代价评估模型.实验表明,给出的数据模型和查询代数体系具有有效性和实用性.     

SQL查询到扩充的元组关系表达式变换

SOL是标准的关系数据库查询语言,本文在关系代数和元组演算的基础上,定义了一种扩充的元组关系表达式,它能表达SOL 的聚集函数、分组运算、嵌套子查询。将SQL 变换为扩充的元组关系表达式,使我们可以用扩充的元组关系表达式来研究SQL 的语义和查询优化。     

Query Processing Techniques for Multimedia Presentations

A multimedia presentation is a synchronized, and possibly interactive, delivery of multimedia data to users. We expect that, in the future, multimedia presentations will be stored into and queried from multimedia databases. In an earlier work, we have designed a graphical query language, called GVISUAL, that allows users to query multimedia presentations based on content information. In this paper, we discuss GVISUAL query processing techniques for multimedia presentations. More specifically, we discuss the translation of GVISUAL queries into an operator-based language, called O-Algebra, with three new operators, and efficient implementations of the new O-Algebra operators using a coding system called nodecodes.     

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.     

QQL: A DB&;IR Query Language

Traditional database query languages are based on set theory and crisp first order logic. However, many applications require retrieval-like queries which return result objects associated with a degree of being relevant to the query. Historically, retrieval systems estimate relevance by exploiting hidden object semantics whereas query processing in database systems relies on matching select-conditions with attribute values. Thus, different mechanisms were developed for database and information retrieval systems. In consequence, there is a lack of support for queries involving both retrieval and database search terms. In this work, we introduce the quantum query language (QQL). Its underlying unifying theory is based on the mathematical formalism of quantum mechanics and quantum logic. Van Rijsbergen already discussed the strong relation between the formalism of quantum mechanics and information retrieval. In this work, we interrelate concepts from database query processing to concepts from quantum mechanics and logic. As result, we obtain a common theory which allows us to incorporate seamlessly retrieval search into traditional database query processing.     

并行查询下查询执行计划的选择

查询是数据库系统的主要负载,其效率决定了数据库性能的好坏。一个查询存在多种执行计划,当前,查询优化器只能按照数据库系统的配置参数,静态地为查询选择一个较优的执行计划。并行查询间存在复杂多变的资源争用,很难通过配置参数准确反映,而且同一执行计划在不同情景下的效率并不一致。并行查询下执行计划的选择需考虑查询间的相互影响——查询交互。基于此,提出了一种在并行查询下度量查询受查询交互影响大小的标准QIs。针对并行查询下查询执行计划的选择,还提出了一种动态地为查询选择执行计划的方法TRating,该方法通过比较查询组合中按不同执行计划执行的查询受查询交互影响的大小,选择受查询交互影响较小的执行计划作为该查询的较优执行计划。实验结果表明,TRating方法为查询选择较优执行计划的准确率达61%,相比查询优化器提高了25%;而且在为查询选择次优执行计划时,其准确率也高达69%。     

Functional Query Optimization over Object-Oriented Views for Data Integration

AMOS is a mediator system that supports passive (non-intrusive) integration of data from heterogeneous and autonomous data sources. It is based on a functional data model and a declarative functional query language AMOSQL. Foreign data sources, e.g., relational databases, text files, or other types of data sources can be wrapped with AMOS mediators, making them accessible through AMOSQL. AMOS mediators can communicate among each other through the multi-database constructs of AMOSQL that allow definition of functional queries and OO views accessing other AMOS servers. The integrated views can contain both functions and types derived from the data sources. Furthermore, local data associated with these view definitions may be stored in the mediator database. This paper describes AMOS' multi-database query facilities and their optimization techniques. Calculus-based function transformations are used to generate minimal query expressions before the query decomposition and cost-based algebraic optimization steps take place. Object identifier (OID) generation is used for correctly representing derived objects in the mediators. A selective OID generation mechanism avoids overhead by generating in the mediator OIDs only for those derived objects that are either needed during the processing of a query or have associated local data in the mediator database. The validity of the derived objects that are assigned OIDs and the completeness of queries to the views are guaranteed by system generated predicates added to the queries.     

基于代数的Transform查询优化策略

XQuery/Update中定义了一种特殊的查询--Transform查询.Transform查询类似于关系数据库中的假设查询,可以表示成假设查询的一般形式:"Q when{U}",即查询Q的查询结果是假设数据库执行了更新操作{U}以后的结果,而更新操作U实际不修改数据库的状态.Transform查询需要拷贝XML数据库中的结点,并对拷贝的结点执行更新操作,所以不影响数据库的状态.但该操作通常拷贝和更新了大量与查询结果无关的结点,因此如何减少拷贝与更新操作的代价是Transform查询处理优化的关键.提出了基于OrientXA的Transform查询优化方法,并在NativeXML数据库系统OrientX 3.0里实现和验证了该方法.     

应用分布式索引提高海量数据查询性能

在电信领域的精准化营销、即席查询业务中,存在着大量针对一张宽表或几张宽表（超过50字段）的随机查询场景. 传统处理模式（直接查询数据库）在数据量不大（〈;1000万）时,查询响应时间可优化到几秒至数十秒级,而当数据量到达几千万、上亿甚至十亿记录以上时,此处理模式无论如何优化或更改索引机制,都无法满足秒级并发查询要求.新的处理模式通过引入分布式Solr索引层解决上述问题.索引层预先对数据库记录建立索引,查询不再作用于数据库而直接查询索引层,如此,可大幅提高查询性能.经过对两种处理模式的对比验证,在相同环境下,数据量到达5000万,每秒20并发访问的宽表查询场景,传统处理模式的查询全部超时失败,而使用分布式索引层的查询可以在2秒以内返回,查询全部成功.     

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).     

语义缓存的聚集查询匹配研究

为提高海量数据库系统的查询效率,围绕海量数据库系统中的聚集查询技术,把通常应用于小型数据库查询的语义缓存技术拓展到海量数据库的聚集查询中．首先研究了面向聚集查询的语义缓存形式化描述,在此基础上讨论了利用缓存处理查询的条件并对查询匹配进行了分类,提出并实现了包含匹配判定算法和相交匹配判定算法,最后给出了相应的实验结果．在某大型实际工程中的应用表明上述判定算法是有效的．