一种改进的分布式数据库查询优化算法

分析和研究了传统的分布式数据库连接查询优化算法,利用数据划分和并行处理执行策略,提出了多连接属性划分的查询优化算法.实验证明,此算法可以提高查询的响应速度,减少查询的响应时间,在处理分布式数据 '库中海量信息查询和复杂查询方面具有实用价值.     

分布式数据库中查询处理的新方法研究

在分布式数据库系统中,由于数据的分布和冗余,使得分布式查询处理增加了许多新的内容和复杂性,通过分析现有分布式数据库查询处理技术,根据应用实际提出一种新的查询处理方法,该方法通过将常用查询结果存储在本地来减少查询时的数据传输量,从而缩短了响应时间.实验证明了该方法是有效的.     

一种分布式数据库多属性划分查询优化算法

简单阐述了分布式数据库中查询优化的查询目的,并简单介绍了直接连接优化算法中的Hash划分和Partition算法.通过分析,指出Partition算法的不足,并加以改进.在改进算法中提出了查询图划分方法,缩短查询操作的响应时间.     

半连接查询优化算法的研究

为了提高分布式数据库管理系统的查询效率,分析了分布式数据库管理系统的特点,找出了影响分布式数据库管理系统查询效率的关键因素,讨论了直接连接查询的常见策略和半连接查询的原理、实现方法以及所花费的传输代价,最后结合分布式数据库管理系统的具体实例提出了一种半连接查询策略。改进后的半连接查询策略优化了连接方案,降低了数据传输过程的成本,缩短了查询处理的响应时间,提高了查询操作的效率。     

无线传感器网络分布式数据库加密方法研究

传统方法在无线传感网络加密分布式数据库时,受到网络异构性的影响产生了大量异常数据,导致其存在加/解密速度慢、数据查询复杂度以及解密后数据准确性低的问题。为此,提出一种无线传感网络分布式数据库加密方法。首先通过密度峰值法对数据实施聚类处理,使用机器学习中的支持向量机分类法找出数据库中的异常数据并剔除。然后通过OPES算法对数据库内数据实施转换、桶划分等操作,再通过划分结果建立数据库的加密空间,实现对无线传感网络分布式数据库的加密。仿真分析结果表明：该加密方法提高了无线传感网络分布式数据库中,数据查询过程的复杂度和加/解密的速度,且应用该方法可使得解密后数据的准确性达到99.16%。     

在多元连接数据查询中最小生成树法的改进应用

本文对最小生成树法在分布式数据库多元连接中的应用进行了阐述和分析,并利用分布式数据库数据的分布性对最小生成树法进行了改进。提出了基于最小生成树法的连接图划分方法将连接图划分成多个子连接图,提高连接操作的并行性,从而使得响应时间得到减少。     

基于分布式数据库系统查询优化策略的研究

在分布式数据库系统中,由于数据的物理分布使得分布式查询处理增加了许多新的复杂性,不同的查询处理策略,其查询处理代价和复杂度是大不一样的。分布式数据库系统的查询优化和集中式数据库系统相比,显得更为重要。文章在充分讨论查询优化和策略的基础上,着重论述了一种分布式数据库系统查询优化策略是如何影响查询性能的。     

基于关系代数的分布式数据库查询优化

分布式数据库系统由于其数据的物理分布和冗余特性,使得对于分布式数据库的查询优化处理难度更大和复杂度更高,而分布式数据库查询优化处理一直是分布式数据库主要研究问题之一。本文主要概括地介绍分布式数据库查询过程、查询优化的策略和目标,重点阐述了基于关系代数等价变换的分布式数据库查询优化算法。     

基于分布式数据库的查询处理和优化算法

分布式查询处理和优化是用户与分布式数据库的接口,也是分布式数据库研究的主要问题之一。分布式数据库中数据的数据分散存放和冗余使得查询处理和优化更加复杂。文章分析了分布式查询处理过程．重点阐述了优化的各种策略和算法,分析了优缺点并给出了算法选择的方法。     

利用.NET技术构建分布式人口管理信息系统

本文在分析了人口数据信息特点的基础上,提出了采用分布式数据库技术实现人口数据管理系统的体系结构,并通过一实例阐述了使用ASP.NET、ADO.NET、链接数据库技术实现对分布式数据库的访问.为了实现查询优化,系统采用了C#下的多线程编程技术,实现对远程分布式数据库的并行访问,从而缩短了系统的响应时间.     

Query Processing in Distributed Database System

Query processing in a distributed system requires the transmission f data between computers in a network. The arrangement of data transmissions and local data processing is known as a distribution strategy for a query. Two cost measures, response time and total time are used to judge the quality of a distribution strategy. Simple algorithms are presented that derive distribution strategies which have minimal response time and minimal total time, for a special class of queries. These optimal algorithms are used as a basis to develop a general query processing algorithm. Distributed query examples are presented and the complexity of the general algorithm is analyzed. The integration of a query processing subsystem into a distributed database management system is discussed.     

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。     

多格式海量数据统一存取的索引结构

为提高多格式海量数据统一存取效率,提出了一种基于Hadoop的分布式数据读取模式。并通过对海量数据非主键索引结构的研究,结合统一存取的描述理念,提出了基于HDFS的一种可适用于B-树和R-树及其变种的层次索引结构,改变了原键—值存储在非主键索引结构中的劣势。通过提出Hadoop缓冲策略、基于随机读取的新数据传输模型以及相应的查询处理策略,进一步降低了数据传输开销。实验表明,该系列方法优化了统一存取中随机存取效率,减少了相应的查询响应时间和数据传输开销,提高了多格式海量数据统一存取的性能。     

An intelligent query processing for distributed ontologies

In this paper, we propose an intelligent distributed query processing method considering the characteristics of a distributed ontology environment. We suggest more general models of the distributed ontology query and the semantic mapping among distributed ontologies compared with the previous works. Our approach rewrites a distributed ontology query into multiple distributed ontology queries using the semantic mapping, and we can obtain the integrated answer through the execution of these queries. Furthermore, we propose a distributed ontology query processing algorithm with several query optimization techniques: pruning rules to remove unnecessary queries, a cost model considering site load balancing and caching, and a heuristic strategy for scheduling plans to be executed at a local site. Finally, experimental results show that our optimization techniques are effective to reduce the response time.     

Enhanced Schemes for Data Fragmentation,Allocation, and Replication in Distributed Database Systems

With the growth of information technology and computer networks, there is a vital need for optimal design of distributed databases with the aim of performance improvement in terms of minimizing the round-trip response time and query transmission and processing costs. To address this issue, new fragmentation, data allocation, and replication techniques are required. In this paper, we propose enhanced vertical fragmentation, allocation, and replication schemes to improve the performance of distributed database systems. The proposed fragmentation scheme clusters highly-bonded attributes (i.e., normally accessed together) into a single fragment in order to minimize the query processing cost. The allocation scheme is proposed to find an optimized allocation to minimize the round-trip response time. The replication scheme partially replicates the fragments to increase the local execution of queries in a way that minimizes the cost of transmitting replicas to the sites. Experimental results show that, on average, the proposed schemes reduce the round-trip response time of queries by 23% and query processing cost by 15%, as compared to the related work.     

Design of Distributed Databases on Local Computer Systems with a Multiaccess Network

Concurrency control, distribution design, and query processing are some of the important issues in the design of distributed databases. In this paper, we have studied these issues with respect to a relational database on a local computer system connected by a multiaccess broadcast bus. A broadcast bus allows information to be distributed efficiently, and hence simplifies the solutions to some of these issues. A transaction model that integrates the control strategies in concurrency control and query processing is proposed. In concurrency control, the lock, unlock, and update of data are achieved by a few broadcasts. A dynamic strategy is used in query processing, as less data are transferred when compared to a static strategy. The status information needed in dynamic query processing can be conveniently obtained by broadcasting. Lastly, some NP-hard file placement problems are found to be solvable in polynomial time when updates are broadcast.     

Improving network systems performance by clustering distributed database sites

Clustering network sites is a vital issue in parallel and distributed database systems DDBS. Grouping distributed database network sites into clusters is considered an efficient way to minimize the communication time required for query processing. However, clustering network sites is still an open research problem since its optimal solution is NP-complete. The main contribution in this field is to find a near optimal solution that groups distributed database network sites into disjoint clusters in order to minimize the communication time required for data allocation. Grouping a large number of network sites into a small number of clusters effectively increases the transaction response time, results in better data distribution, and improves the distributed database system performance. We present a novel algorithm for clustering distributed database network sites based on the communication time as database query processing is time dependent. Extensive experimental tests and simulations are conducted on this clustering algorithm. The experimental and simulation results show that a better network distribution is achieved with significant network servers load balance and network delay, a minor communication time between network sites is realized, and a higher distributed database system performance is recognized.     

基于MapReduce的Skyline查询处理算法

Skyline查询是一个典型的多目标优化查询,在多目标优化、数据挖掘等领域有着广泛的应用。现有的Skyline查询处理算法大都假定数据集存放在单一数据库服务器中,查询处理算法通常也被设计成针对单一服务器的串行算法。随着数据量的急剧增长,特别是在大数据背景下,传统的基于单机的串行Skyline算法已经远远不能满足用户的需求。基于流行的分布式并行编程框架MapReduce,研究了适用于大数据集的并行Skyline查询算法。针对影响MapReduce计算的因素,对现有基于角度的划分策略进行了改进,提出了Balanced Angular划分策略;同时,为了减少Reduce过程的计算量,提出了在Map端预先进行数据过滤的策略。实验结果显示所提出的Skyline查询算法能显著提升系统性能。     

分布式数据库系统的查询优化策略

简要的介绍了分布式数据库系统的概念和特点,并在分析比较分布式数据库系统和集中式数据库系统查询优化目标不同特点的基础上,归纳出分布式数据库系统的查询优化目标和代价分析,进而提出查询优化的策略,并在举例中重点讨论了操作执行顺序的不同对查询性能的影响。