基于遗传算法的多连接表达式进行查询优化

多连接表达式的并行查询优化是提高数据库性能的关键问题之一，提出了使用遗传算法来解决多连接表达式的并行查询优化问题。为了提高查询处理器的执行效率，采用启发式规则来搜索最优的多连接表达式并行调度执行计划。文中给出了详细的测试结果和性能分析。实验结果表明，结合启发式知识的遗传算法是解决多连并行查询优化的有效途径，对提高数据库 的性能起到重要作用。     

GHMC_一种混合的数据库多连接查询优化算法

如何排列多连接表达式的连接顺序,是优化并行查询和提高数据库性能的关键技术之一．但多连接最优顺序是NPC问题。本文章研究了数据库多连接的特征,提出一种结合启发式和穷举搜索的Ghme算法,结合启发式和穷举搜索处理多连接查询,并从实验和理论证明其有效性。     

并行数据库基于多连接的查询优化算法的研究

多表连接查询是并行数据库中的一种常用且重要的操作,然而基于传统遗传算法所制定的多表连接查询计划,往往存在查询响应时间长的缺陷。根据无共享并行数据库的特点,将一种新的代价估计模型引入到传统遗传算法中,并对传统遗传算法进行了改进。实验证明改进后的遗传算法能制定出更优的查询计划,从而减少多表连接时的查询响应时间。     

结合哈希过滤的一种改进多连接查询优化算法

多连接查询优化是提高数据库性能的关键问题之一。Chiang Lee提出了一种启发式多连接查询优化算法MVP，分析发现该算法并没有考虑减小执行计划的计算代价。该文结合哈希过滤的特点提出一种改进的多连接查询优化算法，与MVP算法相比该算法降低了执行计划的计算代从，从而使查询响应时间更短。     

一种改进的数据库查询优化算法

数据库查询优化技术对提高数据库的查询效率,增强数据库性能有重要作用。针对大型数据库中多表连接查询效率低的问题,提出了一种基于粒子群算法的改进查询优化算法。针对多表连接查询的特征,对粒子采用树形编码的方式,并提出了一种计算数据库查询执行代价的模型。实验表明,使用粒子群算法优化后的查询策略比原始查询策略的查询执行代价低,有效提高了系统的查询效率。     

一种改进的数据库查询优化算法

数据库查询优化技术对提高数据库的查询效率,增强数据库性能有重要作用。针对大型数据库中多表连接查询效率低的问题,提出了一种基于粒子群算法的改进查询优化算法。针对多表连接查询的特征,对粒子采用树形编码的方式,并提出了一种计算数据库查询执行代价的模型。实验表明,使用粒子群算法优化后的查询策略比原始查询策略的查询执行代价低,有效提高了系统的查询效率。     

数据库查询优化技术的历史、现状与未来

传统的查询树优化方法,即基于左线性树、右线性树、浓密树、操作森林的并行数据库查询优化方法,各有优劣,对其的研究比较深入、成熟;基于多重加权树的查询优化方法,研究了其并行查询计划模型、并行查询计划的复杂性模型和查询优化算法;语义查询优化方法将一个查询变换成一个或数个语义等价的查询,进而寻找并执行这些等价查询中具有较好实现策略的一个;基于Agent的并行数据库查询优化采用Multi-Agent技术自动查找与给定查询有关的完整性约束条件,使得多个关系间连接操作的效率得到很大的提高;基于遗传算法的并行优化算法,深入研究了基于机群并行数据库中关系存储的选择、多连接查询优化和查询处理等关键技术。     

Sybase ASE新特性表分区和并行查询的应用

Sybase ASE (Adaptive Server Enterprise)数据库的新特性表分区和并行查询,提供了新的优化数据库性能的途径和手段.阐述如何在Sybase ASE中建立表分区,如何配置Sybase ASE数据库并行查询参数来做基于分区的并行查询,在会话级(Session)和查询语句级进行并行查询控制和表分区及页面统计数据的维护,综合应用表分区和并行查询技术来提高系统响应速度.最后与其他数据库同类技术进行了比较.     

基于混合遗传算法的关系型数据库多连接查询优化

本文分析了关系型数据库的查询优化问题，针对多连接查询提出将遗传算法和爬山法结合，从而构造了关系型数据库多连接查询优化问题的混合遗传算法，并进行了实验计算。结果表明，用混合遗传算法解决多连接查询优化问题，可以发挥遗传算法和爬山法的不同优势，从而得到较满意的查询优化性能。     

一种基于多连接属性划分的查询优化算法

查询操作是数据库中最常用的操作,由于分布式数据库的数据分布性和冗余性,使得查询优化处理成为分布式数据库研究的核心问题之一。为了提高分布式数据库查询效率,分析讨论了基于直接连接的常见执行策略和查询优化算法,同时针对分布式数据库应用中多表连接时存在多连接属性,提出一种改进的直接连接查询优化策略。改进后的算法提高了查询执行的并行性,缩短了查询处理时间,提高了查询效率。     

基于半连接的并行查询处理算法的研究

多元连接查询的并行执行是并行数据库的研究重点,传统的并行查询处理算法没有利用面向对象数据库及其查询的特点,算法效率较低.借鉴分布式数据库查询处理中基于半连接的优化思想,提出了基于半连接的并行查询处理算法.性能评价表明了其实用性和有效性.     

Dataflow query execution in a parallel main-memory environment

In this paper, the performance and characteristics of the execution of various join-trees on a parallel DBMS are studied. The results of this study are a step into the direction of the design of a query optimization strategy that is fit for parallel execution of complex queries.Among others, synchronization issues are identified to limit the performance gain from parallelism. A new hash-join algorithm is introduced that has fewer synchronization constraints than the known hash-join algorithms. Also, the behavior of individual join operations in a join-tree is studied in a simulation experiment. The results show that the introduced Pipelining hash-join algorithm yields a better performance for multi-join queries. The format of the optimal join-tree appears to depend on the size of the operands of the join: A multi-join between small operands performs best with a bushy schedule; larger operands are better off with a linear schedule. The results from the simulation study are confirmed with an analytic model for dataflow query execution.     

基于机群环境的并行多连接存储分布技术

基于机群系统的数据存储分布是并行数据库领域的一个重要问题。已有的研究工作多集中在基于单个关系的存储分布,不能有效支持复杂多连接查询处理。文章提出了多个关系整体分布方法,给出分布属性选择和处理机分配算法。实验结果表明,算法具有良好的性能,有助于提高并行多连接查询效率。     

退火遗传算法的多连接查询应用

多连接查询的优化是数据库查询的关键问题之一,遗传算法与模拟退火算法的结合有利于全局最优解的搜索。提出了一种混合算法,并将其应用到多连接优化问题中,改进了获得最优查询计划的性能。     

基于LBT树的并行数据库查询优化方法

本文提出了一种基于LBT(Linear-Bushy-Tree)树的查询优化方法，它是对基于浓密树(Bushy-Tree)查询优化方法的一种改进。这种优化方法大大地缩减了查询执行计划空间，确保了并行查询执行计划的优化性。这种优化方法已经在我们自主研制的并行数据库管理系统PDBMS^[1,4]中得到实现。     

Performance evaluation of a parallel cascade semijoin algorithm for computing path expressions in object database systems

With the emerging of new applications,especially in Web,Such as E-Commerce,Digital Library and DNA Bank,object database systems show their stronger funcitons than other kinds of database systems due to their powerful representation ability on complex semantics and relationshiop.One distinguished feature of object database systems is path expression,and most queries on an object database ar based on path expression because it is the most natural and convenient way to access the object databse,for example,to navigate the hyper-links in a web-based database,The execution of path expression is usually extremely expensive on a very large database.Therefore,the improvement of path expression eecution efficiency is critical for the performance ofobject databases.As an importan approach realizing high-performance query processing ,the parallel processing of path expression on distributed object databases is explored in this paper.Up to now,some algorithms about how to compute path expressions and how to optimize path expression processing have been proposed for centralizedenvironments.But,few approaches have been presented for computing path expressions in parallel.In this paper,a new paralle algorithm for computing path expression named Parallel Cascade Semijoin(PCSJ)is proposed.Moreover,a new scheduling strategy called right-deep zigzag tree is designed to further improve the performance of the PCSJ algorithm.The exper-iments have been implemented in an NOW distributed and parallel environment.The results show that the PCSJ algorithm outperforms the other two parallel algorithms(the parallel version of forward pointer chasing algorithm(PFPC)and the index splitting parallel algorithm(IndexSplit) when computing path expressions with restrictive predicates and that the right-deep zigzage tree scheduling strategy has better performance than the right-deep tree scheduling strategy.     

基于遗传算法的多数据源连接查询优化方法

主要从查询处理自适应性方面进行研究,在已经存在的适应性查询处理技术基础之上,将自适应性与遗传算法相结合,提出一种基于遗传算法的多数据源连接查询优化问题的方法以及与此相适应的交叉变异概率、编码方法、交叉算子和变异算子,并对算法的性能进行了分析。     

An efficient query optimization strategy for spatio-temporal queries in video databases

The interest for multimedia database management systems has grown rapidly due to the need for the storage of huge volumes of multimedia data in computer systems. An important building block of a multimedia database system is the query processor, and a query optimizer embedded to the query processor is needed to answer user queries efficiently. Query optimization problem has been widely studied for conventional database systems; however it is a new research area for multimedia database systems. Due to the differences in query processing strategies, query optimization techniques used in multimedia database systems are different from those used in traditional databases. In this paper, a query optimization strategy is proposed for processing spatio-temporal queries in video database systems. The proposed strategy includes reordering algorithms to be applied on query execution tree. The performance results obtained by testing the reordering algorithms on different query sets are also presented.     

Graph-Based Parallel Query Processing and Optimization Strategies for Object-Oriented Databases

Much work has been accomplished in the past on the subject of parallel query processing and optimization in parallel relational database systems; however, little work on the same subject has been done in parallel object-oriented database systems. Since the object-oriented view of a database and its processing are quite different from those of a relational system, it can be expected that techniques of parallel query processing and optimization for the latter can be different from the former. In this paper, we present a general framework for parallel object-oriented database systems and several implemented query processing and optimization strategies together with some performance evaluation results. In this work, multiwavefront algorithms are used in query processing to allow a higher degree of parallelism than the traditional tree-based query processing. Four optimization strategies, which are designed specifically for the multiwavefront algorithms and for the optimization of single as well as multiple queries, are introduced. The query processing algorithms and optimization strategies have been implemented on a parallel computer, nCUBE2; and the results of a performance evaluation are presented in this paper. The main emphases and the intended contributions of this paper are (1) data partitioning, query processing and optimization strategies suitable for parallel OODBMSs, (2) the implementation of the multiwavefront algorithms and optimization strategies, and (3) the performance evaluation results.     

内存存储模型上的多表连接优化技术研究

分析了面向先进硬件平台上的数据库优化技术,提出了基于内存存储模型的多表连接查询处理优化技术,采用内存存储模型存储维表并对维表主键进行顺序化,从而使维表的主键与内存维表记录的内存偏移地址相一致,实现对维表记录的内存直接访问。通过列存储技术减少维表记录的访问宽度,进一步优化维表访问的cache性能。与基于SQL Server 2005的查询执行计划的连接算法、join index连接算法以及基于列存储模型的优化连接算法进行了实验比较和性能分析,结果表明:基于内存存储模型的多表连接算法在处理星型结构数据仓库多谓词、多连接的复杂查询时具有很好的性能,与join index相比不需要额外的空间开销,与列存储数据模型相比具有更好的兼容性和性能。