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。     

关系数据库中基于EPTV的模糊查询

关系数据库中空值存在不同的语义,并且会影响模糊查询结果。针对该问题,提出用标号来区分空值的语义,并且在EPTV逻辑的基础上,对关系运算和一些复杂的嵌套查询进行扩展,给出相关定义和计算方法。通过实例说明,与常规模糊查询相比,该方法能较好地反映空值对模糊查询结果的影响。     

空值环境下关系数据库的更新Ⅱ：扩展关系模型及基本运算

本文从空值语义及更新操作的关系出发，提出了一种新的扩展关系模型，用以组织更新操作下的含有空值的关系数据库中的信息，同时，定义了这种模型下的基本关系代数运算，为实现空值环境下关系数据库的数据更新奠定了基础。     

空值环境下关系数据库的更新 Ⅰ：扩展关系模型及基本运算

本文从空值语义及更新操作的关系出发，提出了一种新的扩展关系模型，用以组织更新操作下的含有空值的关系数据库中的信息．同时，定义了这种模型下的基本关系代数运算．为实现空值环境下关系数据库的数据更新奠定了基础．     

含空值关系数据库中关系代数的实现

本文从空值的完全语义出发，依据空值环境下信息等价和信息相容的含义，全面定义了空值环境下运算结果完备的关系代数运算，并对空值环境下关系代数运算的有效性和完备性进行了讨论。     

关系数据库不可用空值的查询与处理

现有的基于关系数据模型的商业数据库采用空值对缺失信息进行建模与处理,然而,单一的空值解释无法体现空值本身的丰富语义。事实上,在相关研究中空值通常被解释为‘值未知’,‘值不可用’以及‘值不存在’等。文中主要研究不可用空值的查询与处理。通过仔细地观察和深刻地理解,分别在传统关系数据库查询和模糊数据库查询中讨论不同语义背景和查询条件下不可用空值的处理和分类。此外,还针对涉及不可用空值的传统关系数据库查询提出选择运算和差运算算法,这些算法使文中的研究更具实用性。     

糊糊空值环境下关系数据库的操作及查询处理

本文在经典关系数据库理论基础上引入模糊数学理论的基本思想和方法,对模糊空值环境下关系数据库的几种数学运算和基本关系操作进行了讨论,进而给出了查询处理中选择运算、差运算和连接运算的基本方法.     

知识库中的空值探讨

分析了空值环境下的三种类型的查询策略，以及Datalog查询求值的Semi-Naive算法，给出了一个从子目标关系空值特性导出头关系空值特性的一种方法，使改进后的Semi-Navie算法能在带空值的EDB数据库中对Datalog查询进行正确求值。     

一种基于语义的模糊关系数据库除操作

模糊信息的描述和处理只有符合自然语义才能反映事物本来面目，本文分析了传统关系数据库除操作，讨论了模糊关系数据库除操作的一般扩展形式和基于语义的运算方法－NQ扩展和运算，提出了除操作运算结果的个体活动满意度和团队活动满意度两种查询语义，并在此基础上给出了一种新的基于语义的模糊关系数据库除操作扩展和运算方法－PAT扩展和运算，通过实验测试和对比，结果表明PAT方法能使模糊信息的描述更逼近自然语义。     

关系模型中空值的引入与处理

随着数据库应用的不断扩展,对不完全信息的处理的需求日益突出出来,本文讨论了在数据库中引入空值的必要性和有关空值的若干语义问题,给出了一个增加了处理空值功能的扩充的关系模型,和若干现有的讨论文章相此,本模型力图最充分地表达空值本身的语义内涵,从这一基点出发,文章讨论了空值环境对若干关系操作的影响以及引入空值以后函数据关性的满足性问题,并且给出了在本文所提出的扩充关系模型下的某些新的定义。     

空值环境下含不确定及可能信息关系数据库的查询

本文以（１）中的扩展关系模型为基础在两种元组极的不完全信息－不确定及可能信息中引入属性级的不完全信息空值，使两种不同性质的不完全信息同时出现在同一关系中，为了能够查询到不同种类及不同确定程度的信息，文中制定了这种扩展关系模型上关系的查询策略，定义了能够体现这种策略的最小关系代数运算。     

An efficient multiversion access structure

An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations-inserts, updates, and deletes-are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained     

SQL语言中的空值问题

结构化查询语言(SQL)是关系数据库中重要的查询语言，同时由于关系数据库中空值存在的必要性，因此在对不完全信息数据库进行SQL操作时，如何正确地处理空值是一个很重要的研究方向。文中简述了SQL语言标准中对空值的描述，从理论角度分析了引入空值后SQL语言的语义变化，同时从应用角度阐述了引入空值后所引发的一系列问题，最后介绍了下一代数据库语言标准SQL3对NULL处理方法的扩充。由于现实数据库信息的不完全性，文中对于如何正确地认识SOL语言中的空值问题具有很大的借鉴意义。     

Null values in fuzzy databases

Since in the real world, it often occurs that information is missing, database systems clearly need some facilities to deal with missing data. With respect to traditional database systems, the most commonly adopted approach to this problem is based on null values and three valued logic. This paper deals with the semantics and the use of null values in fuzzy databases. In dealing with missing information a distinction is made between incompleteness due to unavailability and incompleteness due to inapplicability. Both the database modelling and database querying aspects are described. With respect to attribute values, incompleteness due to unavailability is modelled by possibility distributions, which is a commonly used technique in the fuzzy databases. Domain specific null values, represented by a bottom symbol, are used to model incompleteness due to inapplicability. Extended possibilistic truth values are used to formalize the impact of data manipulation and (flexible) querying operations in the presence of these null values. The different cases of appearances of null values in the handling of selection conditions of flexible database queries are described in detail.     

演绎数据库中语义查询的动态优化算法

演绎数据库的语义查询优化是利用数据库中的完整性约束，将用户提交的查询转换为与原查询等价且执行效率更高的查询规则。该文提出的动态语义优化算法在查询计算过程中动态约去存在的空展开式，使得查询时间开销的节省可用所除去的空展开式规模大小衡量，较适用于含有大量空展开式的演绎数据库。     

A graph theoretical approach to determine a join reducer sequencein distributed query processing

Semijoin has traditionally been relied upon to reduce the cost of data transmission for distributed query processing. However, judiciously applying join operations as reducers can lead to further reduction in the amount of data transmission required. In view of this fact, we explore the approach of using join operations as reducers in distributed query processing. We first show that the problem of determining a sequence of join operations for a query can be transformed to that of finding a specific type of set of cuts to the corresponding query graph, where a cut to a graph is a partition of nodes in that graph. Then, in light of this concept, we prove that the problem of determining the optimal sequence of join operations for a given query graph is of exponential complexity, thus justifying the necessity of applying heuristic approaches to solve this problem. By mapping the problem of determining a sequence of join reducers into the one of finding a set of cuts, we develop (for tree and general query graphs, respectively) efficient heuristic algorithms to determine a join reducer sequence for distributed query processing. The algorithms developed are based on the concept of divide and conquer and are of polynomial time complexity. Simulation is performed to evaluate these algorithms     

传感器网络中一种支持多分辨率区域查询的数据存储方法

在传感器网络中,考虑到节点的通信开销在节点总能量开销中的比重大,以及用户由粗到细分辨率的不同查询需求,有必要在传感器网络中建立支持多分辨率的数据存储机制.首先提出了一种支持多分辨率的数据压缩存储策略 MDCS,节点基于 MDCS在网内产生多分辨率的近似结果;其次,给出了一种基于 MDCS的区域查询处理方法,根据用户给定的分辨率阈值去网内作区域查询处理,并将结果返回给用户.模拟实验表明,基于 MDCS的区域查询处理方法能够高效、低能耗地支持多分辨率的区域查询操作.     

Fuzzy query translation for relational database systems

The paper presents a new method for fuzzy query translation based on the alpha-cuts operations of fuzzy numbers. This proposed method allows the retrieval conditions of SQL queries to be described by fuzzy terms represented by fuzzy numbers. It emphasizes friendliness and flexibility for inexperienced users. The authors have implemented a fuzzy query translator to translate user's fuzzy queries into precise queries for relational database systems. Because the proposed method allows the user to construct his fuzzy queries intuitively and to choose different retrieval threshold values for fuzzy query translation, the existing relational database systems will be more friendly and more flexible to the users.