XML数据流基于组着色的XPath查询模型

提出了一种新的XML数据流XPath查询模型GBRender,该模型通过组着色序列来直接处理元素,具有较高的处理效率与较强的适应性.     

基于语义缓存的数据库查询优化研究

为了应用智能化的方法提高数据库访问效率,基于多Agent技术构建了分布式数据库访问平台,研究并解决了平台的结构、各种Agent的设计、Agent间的协作机制、以及数据库系统的包装方法等关键问题.在优化策略方面,研究了分布式环境下的语义缓存技术,并提出了一种Agent平台下的智能预取算法,弥补了传统数据库优化手段缺乏智能性、预动性,以及重用困难等不足.通过在大型数据库系统上进行测试,表明该方案在进行大规模数据库操纵时效率有明显提高.     

A fuzzy extension of the XPath query language

Today the current state of the art in querying XML data is represented by XPath and XQuery, both of which rely on Boolean conditions for node selection. Boolean selection is too restrictive when users do not use or even know the data structure precisely, e.g. when queries are written based on a summary rather than on a schema. In this paper we describe a XML querying framework, called FuzzyXPath, based on Fuzzy Set Theory, which relies on fuzzy conditions for the definition of flexible constraints on stored data. A function called “deep-similar” is introduced to replace XPath’s typical “deep-equal” function. The main goal is to provide a degree of similarity between two XML trees, assessing whether they are similar both structure-wise and content-wise. Several query examples are discussed in the field of XML based metadata for e-learning.     

一种基于图归约的XPath高性能流数据查询方法

作为网络数据交换和数据共享的标准,XML数据越来越多地用于表示应用系统的流数据。然而,受制于流数据处理有限空间开销等特征,如何高效地实现这种查询成为值得探讨的问题。与传统的基于自动机或层次栈方法不同,文中提出了一种基于图归约的XML查询自动机(GRAT),采用一种图结构来表示针对不同XML流元素的子查询任务之间的关系,通过图的归约变化来实现XPath查询。实验结果表明,基于GRAT的查询算法能够高效地完成复杂的XML查询,流数据处理的吞吐量达到了较高水平。     

基于MapReduce的SQL查询优化分析

对SQL翻译成MapReduce程序的性能进行分析,并对影响翻译性能的原因进行阐述。结合MapReduce作业间输入相关性、数据转换相关性和作业流相关性的分析,通过合并冗余的作业,减少资源消耗,从而达到提高SQL查询性能的目的,给出了优化条件和优化规则。通过对优化前后的性能进行对比,证明改进后的SQL过程有更高的执行效率。     

基于贪婪策略的分布式数据库查询优化研究

针对分布式数据库系统复杂的多连接查询问题,分析了查询系统的目标要求,研究了查询优化的代价模型.结合具体实例,通过问题简化,构造出代价模型的查询图,提出了利用贪婪算法实现数据库查询的迭代方案.采用多步决策,按照一定的算法依次优化查询图,使得每一步优化都能得到最小的查询中间代价,从而确保了全局查询的最优.分析比较结果表明,该算法能以最小的代价实现对数据库的查询优化,缩短查询时间,提高查询效率.     

Indexing XML documents for XPath query processing in external memory

Existing encoding schemes and index structures proposed for XML query processing primarily target the containment relationship, specifically the parent–child and ancestor–descendant relationship. The presence of preceding-sibling and following-sibling location steps in the XPath specification, which is the de facto query language for XML, makes the horizontal navigation, besides the vertical navigation, among nodes of XML documents a necessity for efficient evaluation of XML queries. Our work enhances the existing range-based and prefix-based encoding schemes such that all structural relationships between XML nodes can be determined from their codes alone. Furthermore, an external-memory index structure based on the traditional B+-tree, XL+-tree(XML Location+-tree), is introduced to index element sets such that all defined location steps in the XPath language, vertical and horizontal, top-down and bottom-up, can be processed efficiently. The XL+-trees under the range or prefix encoding scheme actually share the same structure; but various search operations upon them may be slightly different as a result of the richer information provided by the prefix encoding scheme. Finally, experiments are conducted to validate the efficiency of the XL+-tree approach. We compare the query performance of XL+-tree with that of R-tree, which is capable of handling comprehensive XPath location steps and has been empirically shown to outperform other indexing approaches.     

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。     

Parametric query optimization

In most database systems, the values of many important run-time parameters of the system, the data, or the query are unknown at query optimization time. Parametric query optimization attempts to identify at compile time several execution plans, each one of which is optimal for a subset of all possible values of the run-time parameters. The goal is that at run time, when the actual parameter values are known, the appropriate plan should be identifiable with essentially no overhead. We present a general formulation of this problem and study it primarily for the buffer size parameter. We adopt randomized algorithms as the main approach to this style of optimization and enhance them with a sideways information passing feature that increases their effectiveness in the new task. Experimental results of these enhanced algorithms show that they optimize queries for large numbers of buffer sizes in the same time needed by their conventional versions for a single buffer size, without much sacrifice in the output quality and with essentially zero run-time overhead. Edited by S. Zdonik / Received June 1993 / Accepted April 1996     

基于Mediato/Wrapper信息集成的查询优化研究

在对Mediato/Wrpper集成系统及其查询特点进行详细分析的基础上,针对涉及多个数据源的连接查询是使用频率较高且是查询代价最高的一种查询方式这一事实,确定了以全局连接查询为主要优化对象,并提出了用半连接方法来优化连接查询.在对半连接执行方案进行优化时,提出了半连接加权有向图的概念,并给出了针对半连接加权有向图的半连接执行方案的快速有效的优化算法.     

基于蚁群算法的分布式数据库查询优化方法

在分布式数据库查询优化中,数据传输和多连接次序往往决定了查询执行速度,以通信代价最小为目标的代价模型一直是研究的重点。随着大数据时代的到来,如何提高数据库的查询效率成为我们所要面对的首要问题。为此,利用蚁群算法优化查询计划,以多元连接查询操作为例,进行了模型建立和算法实现。在Oracle数据库中进行了仿真实验,实验结果表明该算法有较好的寻优效果,并对分布式数据库的查询优化具有实际意义。     

基于多核的Rijndael算法的并行优化与实现

为提高Rijndael算法的执行效率,从对Rijndael算法的核心部分-轮变换的分析入手,在多核平台下提出了一种基于数据流分解的方式对Rijndael算法进行并行优化.采用的主要方法是将轮变换的各构成变换对整个状态的作用分割成对状态的每个组成单元的作用,使得各构成变换可以并行进行.实验结果表明,采用基于数据流的分解方式对Rijndael算法分解可有效的提高其执行效率.     

基于Mediator/Wrapper信息集成的查询优化研究

在对Mediator/Wrapper集成系统及其查询特点进行详细分析的基础上,针对涉及多个数据源的连接查询是使用频率较高且是查询代价最高的一种查询方式这一事实,确定了以全局连接查询为主要优化对象,并提出了用半连接方法来优化连接查询。在对半连接执行方案进行优化时,提出了半连接加权有向图的概念,并给出了针对半连接加权有向图的半连接执行方案的快速有效的优化算法。     

基于2-阶段成本优化的多播容量供应

针对媒体内容提供商采用网络编码的多播最优化容量供应问题,提出一种基于2-阶段的成本优化方案.在第一阶段,网络容量购买基于对未来客户集的预测,这相当于内容提供商在与因特网服务提供商进行初始服务级协议谈判期间预定的容量;在第二阶段,一旦明确知道客户集,就追加购买服务所有客户所要求的额外容量;为指导第一阶段的容量购买决策,提出2种有效的近似算法,使两个阶段的总体成本在预期中最小化.仿真结果表明,该成本优化算法有效,且非常接近甚至优于最优解.     

A bi-labeling based XPath processing system

We present BLAS, a Bi-LAbeling based XPath processing System. BLAS uses two labeling schemes to speed up query processing: P-labeling for processing consecutive child (or parent) axis traversals, and D-labeling for processing descendant (or ancestor) axis traversals. XML data are stored in labeled form and indexed. Algorithms are presented for translating XPath queries to SQL expressions. BLAS reduces the number of joins in the SQL query translated from a given XPath query and reduces the number of disk accesses required to execute the SQL query compared with the traditional XPath processing using D-labeling alone. We also propose an approximate P-labeling scheme and the corresponding query translation algorithm to handle XML data trees that contain a large number of distinct tag names, and/or are very deep. This extension captures a spectrum of XPath-to-SQL query translation schemes, ranging from existing schemes that do not use P-labels to the one that uses exact P-labels. Experimental results demonstrate the efficiency of the BLAS system.     

Parallel complexity of logical query programs

We consider the parallel time complexity of logic programs without function symbols, called logical query programs, or Datalog programs. We give a PRAM algorithm for computing the minimum model of a logical query program, and show that for programs with the polynomial fringe property, this algorithm runs in time that is logarithmic in the input size, assuming that concurrent writes are allowed if they are consistent. As a result, the linear and piecewise linear classes of logic programs are inN C. Then we examine several nonlinear classes in which the program has a single recursive rule that is an elementary chain. We show that certain nonlinear programs are related to GSM mappings of a balanced parentheses language, and that this relationship implies the polynomial fringe property; hence such programs are inN C Finally, we describe an approach for demonstrating that certain logical query programs are log space complete forP, and apply it to both elementary single rule programs and nonelementary programs.Supported by NSF Grant IST-84-12791, a grant of IBM Corporation, and ONR contract N00014-85-C-0731.     

并行数据库查询优化技术的最新进展

传统的查询树及基于多重加权树的查询优化方法,研究得比较成熟,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,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地提高.并行数据库的查询优化领域的3个重要方向为基于机群系统的并行数据库查询优化研究,将MAS技术及专家系统引入本领域,将模拟退火算法及神经网络算法引入本领域.     

Semantic query optimization for query plans of heterogeneousmultidatabase systems

New applications of information systems need to integrate a large number of heterogeneous databases over computer networks. Answering a query in these applications usually involves selecting relevant information sources and generating a query plan to combine the data automatically. As significant progress has been made in source selection and plan generation, the critical issue has been shifting to query optimization. This paper presents a semantic query optimization (SQO) approach to optimizing query plans of heterogeneous multidatabase systems. This approach provides global optimization for query plans as well as local optimization for subqueries that retrieve data from individual database sources. An important feature of our local optimization algorithm is that we prove necessary and sufficient conditions to eliminate an unnecessary join in a conjunctive query of arbitrary join topology. This feature allows our optimizer to utilize more expressive relational rules to provide a wider range of possible optimizations than previous work in SQO. The local optimization algorithm also features a new data structure called AND-OR implication graphs to facilitate the search for optimal queries. These features allow the global optimization to effectively use semantic knowledge to reduce the data transmission cost. We have implemented this approach in the PESTO (Plan Enhancement by SemanTic Optimization) query plan optimizer as a part of the SIMS information mediator. Experimental results demonstrate that PESTO can provide significant savings in query execution cost over query plan execution without optimization