Fuzzy database query languages and their relational completenesstheorem

Two fuzzy database query languages are proposed. They are used to query fuzzy databases that are enhanced from relational databases in such a way that fuzzy sets are allowed in both attribute values and truth values. A fuzzy calculus query language is constructed based on the relational calculus, and a fuzzy algebra query language is also constructed based on the relational algebra. In addition, a fuzzy relational completeness theorem such that the languages have equivalent expressive power is proved     

Efficient recursive XML query processing using relational database systems

Recursive queries are quite important in the context of XML databases. In addition, several recent papers have investigated a relational approach to store XML data and there is growing evidence that schema-conscious approaches are a better option than schema-oblivious techniques as far as query performance is concerned. However, the issue of recursive XML queries for such approaches has not been dealt with satisfactorily. In this paper we argue that it is possible to design a schema-oblivious approach that outperforms schema-conscious approaches for certain types of recursive queries. To that end, we propose a novel schema-oblivious approach, called Sucxent++ (Schema Unconcious XML Enabled System), that outperforms existing schema-oblivious approaches such as XParent by up to 15 times and schema-conscious approaches (Shared-Inlining) by up to eight times for recursive query execution. Our approach has up to two times smaller storage requirements compared to existing schema-oblivious approaches and 10% less than schema-conscious techniques. In addition Sucxent++ performs marginally better than Shared-Inlining and is 5.7–47 times faster than XParent as far as insertion time is concerned.     

Object-oriented query language access to relational databases: A semantic framework for query translation

This research investigates and approach to query processing in a multidatabase system that uses an objectoriented model to capture the semantics of other data models. The object-oriented model is used to construct a global schema, defining an integrated view of the different schemas in the environment. The model is also used as a self-describing model to build a meta-database for storing information about the global schema. A unique aspect of this work is that the object-oriented model is used to describe the different data models of the multidatabase environment, thereby extending the meta database with semantic information about the local schemas. With the global and local schemas all represented in an object-oriented form, structural mappings between the global schema and each local schema are then easily supported. An object algebra then provides a query language for expressing global queries, using the structural mappings to translate object algebra queries into SQL queries over local relational schema. The advantage of using an object algebra is that the object-oriented database can be viewed as a blackboard for temporary storage of local data and for establishing relationships between different databases. The object algebra can be used to directly retrieve temporarily-stored data from the object-oriented database or to transparently retrieve data from local sources using the translation process described in this paper.     

Generalization of strategies for fuzzy query translation in classical relational databases

Users of information systems would like to express flexible queries over the data possibly retrieving imperfect items when the perfect ones, which exactly match the selection conditions, are not available. Most commercial DBMSs are still based on the SQL for querying. Therefore, providing some flexibility to SQL can help users to improve their interaction with the systems without requiring them to learn a completely novel language. Based on the fuzzy set theory and the α-cut operation of fuzzy number, this paper presents the generic fuzzy queries against classical relational databases and develops the translation of the fuzzy queries. The generic fuzzy queries mean that the query condition consists of complex fuzzy terms as the operands and complex fuzzy relations as the operators in a fuzzy query. With different thresholds that the user chooses for the fuzzy query, the user’s fuzzy queries can be translated into precise queries for classical relational databases.     

基于关系数据库的实时XML数据查询处理

力图用成熟的关系数据库查询机制处理符合DTD的XML文档。提出了一整套数据模型、转换规则和算法描述,可以将XML文档转换为关系元组,从而达到用XML实现基于关系数据库的实时数据一致性查询处理的目的。     

Building systems on relational database

Relational databases are becoming increasingly popular. They create an environment within which computer system developers can use high level tools to build application systems quickly. This article looks at one computer manufacturer, Microdata, which has built a whole product line around the use of relational database products.     

Sample-based quality estimation of query results in relational database environments

The quality of data in relational databases is often uncertain, and the relationship between the quality of the underlying base tables and the set of potential query results, a type of information product (IP), that could be produced from them has not been fully investigated. This paper provides a basis for the systematic analysis of the quality of such IPs. This research uses the relational algebra framework to develop estimates for the quality of query results based on the quality estimates of samples taken from the base tables. Our procedure requires an initial sample from the base tables; these samples are then used for all possible information IPs. Each specific query governs the quality assessment of the relevant samples. By using the same sample repeatedly, our approach is relatively cost effective. We introduce the reference-table procedure, which can be used for quality estimation in general. In addition, for each of the basic algebraic operators, we discuss simpler procedures that may be applicable. Special attention is devoted to the join operation. We examine various, relevant statistical issues, including how to deal with the impact on quality of missing rows in base tables. Finally, we address several implementation issues related to sampling.     

Multiclass query scheduling in real-time database systems

In recent years, a demand for real-time systems that can manipulate large amounts of shared data has led to the emergence of real-time database systems (RTDBS) as a research area. This paper focuses on the problem of scheduling queries in RTDBSs. We introduce and evaluate a new algorithm called Priority Adaptation Query Resource Scheduling (PAQRS) for handling both single class and multiclass query workloads. The performance objective of the algorithm is to minimize the number of missed deadlines, while at the same time ensuring that any deadline misses are scattered across the different classes according to an administratively-defined miss distribution. This objective is achieved by dynamically adapting the system's admission, memory allocation, and priority assignment policies according to its current resource configuration and workload characteristics. A series of experiments confirms that PAQRS is very effective for real-time query scheduling     

面向云数据库的属性基加密和查询转换中间件

针对云数据库租户隐私数据的加密和查询问题,提出并实现了一种面向云数据库的属性基加密（ABE）和查询转换服务中间件。首先,服务中间件的加解密部件对租户的对称密钥进行属性基加密,生成密文并保存;其次,服务中间件的查询转换部件对查询语句进行转换,使其可在加密后的数据库上正确执行;最后,租户的隐私数据经过对称加密后保存到云数据库。实验结果表明,与未加密数据库的数据写入和查询时间相比,加密数据库的写入时间与其相当,按照查询语句的复杂程度,查询时长增加10%~150%不等。理论分析表明,所采用的代理解密方案是安全的,与传统的基于密钥策略的属性基加密（CP-ABE）方案相比,代理解密方案在时间复杂度上更具优势。     

A Tree-structured Database Machine for large relational database systems

This paper proposes a Tree-structured Database Machine (TDM), which is designed forsupporting large relational database systems. The TDM aims at totally improving three levelperformance bottlenecks in relational database systems, i.e.(?) data transfer bottleneck, dataprocessing bottleneck, and multiquery optimization bottleneck. For reducing these bottlenecks,the TDM provides the approaches of data partition and data distribution upon data storages forconcurrent data accesses, the tree-structured multiprocessor architecture for parallel dataprocessing, the technique of tightly-coupled-shared-memory for decreasing data movement,the mechanisms of indices and dictionaries for reducing data transfer from the data storages tothe memory, and so on. These features show that the TDM not only improves the systemperformance, increases the parallelism and the data processing power, but also eliminates theperformance bottlenecks in relational database systems.     

Magnetic bubble memory structures for relational database management systems

Recently the concept of using magnetic bubble technology to store data and to perform logical operations has received considerable attention. By exploiting this hardware approach for relational database management systems, we introduce an efficient support for records permutation, sorting and searching for data. Actually these are substantial operations in relational data models.The organization of a relational data model in a magnetic bubbie memory is straightforward. In such systems the memory consists of loops, where each loop is capable of holding one record. Under the control of a switch, a loop can circulate the records or can hold them in position. However, as the number of switches in the memory system increases, the number of control lines becomes large and the model structure may lose its practical significance.In this investigation three different models of bubble memories are applied to a simple relational database example. The two basic operations of permuting records and searching for data are emphasized. For these models, some theoretical features, the essential characteristics and their applicability are pointed out.     

Embedding deductive capabilities in relational database systems

The basic idea of our work is to include deductive capabilities in a relational database system by fully using the operands of relational algebra and without using any theorem prover. We present a deductive database system where the user can formulate deduction laws as logical formulas, but which works on an underlying relational database system by fully using the data manipulation routines of such a system. Generally, it is not possible to express the deduction laws by means of expressions of relational algebra (see Ref. 1). In our system, a relational algebra expression is associated with every database deduction law. The result of its evaluation (with respect to an underlying database) is the set of all database entries that can be deduced from the database by applying the respective law once (Theorem 1). By successively applying all these relational expressions for all the database deduction laws it is possible to generate the whole extensional database (i.e. all tuples deducible from the database).     

Fuzzy rough set techniques for uncertainty processing in a relational database

This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an extension of the relational model of data: the fuzzy rough relational database, an approach which uses both fuzzy set and rough set theories for knowledge representation of imprecise data in a relational database model. The fuzzy rough relational database is formally defined, along with a fuzzy rough relational algebra for querying. Comparisons of theoretical properties of operators in this model with those in the standard relational model are discussed. An example application is used to illustrate other aspects of this model, including a fuzzy entity–relationship type diagram for database design, a fuzzy rough data definition language, and an SQL‐like query language supportive of the fuzzy rough relational database model. This example also illustrates the ease of use of the fuzzy rough relational database, which often produces results that are better than those of conventional databases since it more accurately models the uncertainty of real‐world enterprises than do conventional databases through the use of indiscernibility and fuzzy membership values. ©2000 John Wiley & Sons, Inc.     

An evaluation of buffer management strategies for relational database systems

In this paper we present a new algorithm, DBMIN, for managing the buffer pool of a relational database management system. DBMIN is based on a new model of relational query behavior, thequery locality set model (QLSM). Like the hot set model, the QLSM has an advantage over the stochastic models due to its ability to predict future reference behavior. However, the QLSM avoids the potential problems of the hot set model by separating the modeling of reference behavior from any particular buffer management algorithm. After introducing the QLSM and describing the DBMIN algorithm, we present a performance evaluation methodology for evaluating buffer management algorithms in a multiuser environment. This methodology employed a hybrid model that combines features of both trace-driven and distribution-driven simulation models. Using this model, the performance of the DBMIN algorithm in a multiuser environment is compared with that of the hot set algorithm and four more traditional buffer replacement algorithms.     

An evaluation of buffer management strategies for relational database systems

In this paper we present a new algorithm, DBMIN, for managing the buffer pool of a relational database management system. DBMIN is based on a new model of relational query behavior, thequery locality set model (QLSM). Like the hot set model, the QLSM has an advantage over the stochastic models due to its ability to predict future reference behavior. However, the QLSM avoids the potential problems of the hot set model by separating the modeling of reference behavior from any particular buffer management algorithm. After introducing the QLSM and describing the DBMIN algorithm, we present a performance evaluation methodology for evaluating buffer management algorithms in a multiuser environment. This methodology employed a hybrid model that combines features of both trace-driven and distribution-driven simulation models. Using this model, the performance of the DBMIN algorithm in a multiuser environment is compared with that of the hot set algorithm and four more traditional buffer replacement algorithms.This research was partially supported by the Department of Energy under Contract No. DE-AC02-81ER10920 and the National Science Foundation under grant MCS82-01870.     

Fuzzy orderings in flexible query answering systems

This paper describes the benefits of using fuzzy orderings in flexible query answering systems. We provide a brief overview of those results from the theory of fuzzy orderings that are necessary to couple fuzzy orderings with flexible querying in a meaningful synergistic way. As one case study, we discuss a simple and pragmatic variant of a flexible query answering system – the so-called Vague query system (VQS). The integration of fuzzy orderings into that system is provided in full detail along with examples.This work was supported by the K_plus Competence Center Program which is funded by the Austrian Government, the Province of Upper Austria, and the Chamber of Commerce of Upper Austria.     

自适应的数据库查询缓存

传统的缓存采取较为机械的管理方法,不能随数据库运行的动态信息调整自身参数以得到更优的性能。数据库语义缓存能够让数据库“理解”查询语义,可以为数据库的动态调节提供信息。而查询缓存是语义缓存的一种,在 SQL解析与查询执行之间,通过研究查询缓存的自主管理来提高数据库的查询性能。首先介绍了数据库常用的语义缓存与自主计算,然后对查询缓存进行了形式化定义,并提出了自适应的查询缓存模型。最后在MySQL的查询缓存上进行了实验,得到了较好的效果。     

Issues in query model design in object-oriented database systems

The provision of a powerful query system, including a declarative query language and the systems support for efficiently processing queries is essential for the success of object-oriented database technology. Designing a query system involves making a large number of decisions, further complicated by the lack of a universally accepted object-oriented object data model. In this paper, object data model and query model design decisions are enumerated, alternatives are identified, and the tradeoffs are specified.     

Time-based operators for relational algebra query languages

We present a new approach for historical relational algebra languages based upon generalized logic for Boolean and comparison operators and a temporal modification of the standard relational algebra operators. Historical versions of standard (snapshot) relational algebra operators based upon this generalized logic are presented. The temporal modification employs a logic that operates on sets of value/time-interval pairs and which can be applied to snapshot as well as historical databases. Our emphasis is that the generalized operators can be used to enrich existing historical query languages and to provide an easier and more natural time-based interface. Using the generalized operators, users can express their queries more naturally, succinctly and elegantly. Examples are presented which illustrate that the modified operators offer a good degree of flexibility in expressing different temporal requirements.