Association algebra: a mathematical foundation for object-orienteddatabases

The application of the object-oriented (O-O) paradigm in the database management field has gained much attention in recent years. Several experimental and commercial O-O database management systems have become available. However, the existing O-O DBMSs still lack a solid mathematical foundation for the manipulation of O-O databases, the optimization of queries, and the design and selection of storage structures for supporting O-O database manipulations. This paper presents an association algebra (A-algebra) to serve as a mathematical foundation for processing O-O databases, which is analogous to the relational algebra used for processing relational databases. In this algebra, objects and their associations in an O-O database are uniformly represented by association patterns which are manipulated by a number of operators to produce other association patterns. Different from the relational algebra, in which set operations operate on relations with union-compatible structures, the A-algebra operators can operate on association patterns of homogeneous and heterogeneous structures. Different from the traditional record-based relational processing, the A-algebra allows very complex patterns of object associations to be directly manipulated. The pattern-based query formulation and the A-algebra operators are described. Some mathematical properties of the algebraic operators are presented together with their application in query decomposition and optimization. The completeness of the A-algebra is also defined and proven. The A-algebra has been used as the basis for the design and implementation of an object-oriented query language, OQL, which is the query language used in a prototype Knowledge Base Management System OSAM*.KBMS     

A pattern-based object calculus

Several object-oriented database management systems have been implemented without an accompanying theoretical foundation for constraint, query specification, and processing. The pattern-based object calculus presented in this article provides such a theoretical foundation for describing and processing objectoriented databases. We view an object-oriented database as a network of interrelated classes (i.e., the intension) and a collection of time-varying object association patterns (i.e., the extension). The object calculus is based on first-order logic. It provides the formalism for interpreting precisely and uniformly the semantics of queries and integrity constraints in object-oriented databases. The power of the object calculus is shown in four aspects. First, associations among objects are expressed explicitly in an object-oriented database. Second, the nonassociation operator is included in the object calculus. Third, set-oriented operations can be performed on both homogeneous and heterogeneous object association patterns. Fourth, our approach does not assume a specific form of database schema. A proposed formalism is also applied to the design of high-level object-oriented query and constraint languages.     

An Object Algebra Approach to Multidatabase Query Decomposition in Donají

This paper presents an approach to query decomposition in a multidatabase environment. The unique aspect of this approach is that it is based on performing transformations over an object algebra that can be used as the basis for a global query language. In the paper, we first present our multidatabase environment and semantic framework, where a global conceptual schema based on the Object Data Management Group standard encompasses the information from heterogeneous data sources that include relational databases as well as object-oriented databases and flat file sources. The meta-data about the global schema is enhanced with information about virtual classes as well as virtual relationships and inheritance hierarchies that exist between multiple sources. The AQUA object algebra is used as the formal foundation for manipulation of the query expression over the multidatabase. AQUA is enhanced with distribution operators for dealing with data distribution issues. During query decomposition we perform an extensive analysis of traversals for path expressions that involve virtual relationships and hierarchies for access to several heterogeneous sources. The distribution operators defined in algebraic terms enhance the global algebra expression with semantic information about the structure, distribution, and localization of the data sources relevant to the solution of the query. By using an object algebra as the basis for query processing, we are able to define algebraic transformations and exploit rewriting techniques during the decomposition phase. Our use of an object algebra also provides a formal and uniform representation for dealing with an object-oriented approach to multidatabase query processing. As part of our query processing discussion, we include an overview of a global object identification approach for relating semantically equivalent objects from diverse data sources, illustrating how knowledge about global object identity is used in the decomposition and assembly processes.     

Foundations for object-oriented query processing

A minimal framework for an object-oriented query language standard should (1) include a formal definition of a high-level data model and the syntax and semantics of associated query languages, (2) provide the functionality of relational query languages, and (3) support proofs of correctness of transformations for logical query optimization. In this paper, a high-level conceptual model for object-oriented query processing is discussed; the model includes widely-used structural abstractions such as the isa relationship, associations (properties) between complex objects and complex objects/values, and inheritance of properties. A formal, algebraic query language for the model, inspired by relational algebra, is presented. Operators of the algebra allow queries based on values, queries that manipulate entire objects, and queries that construct new objects from existing objects/values. All queries retain connections to existing database objects, providing logical access paths to data. Each query result is a class, so the algebra has the closure property. The intensional and extensional results of query operators are summarized. Two forms of logical query optimization supported by the query algebra are outlined: algebraic transformations and classifier-based optimizations (optimizations which employ inclusion and exclusion dependencies between classes).     

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.     

Object query optimization through detecting independent subqueries

The problem of query optimization in object-oriented databases is addressed. We follow the Stack-Based Approach to query languages, which employs the naming-scoping-binding paradigm of programming languages rather than traditional database concepts such as relational/object algebras or calculi. The classical environment stack is a semantic basis for definitions of object query operators, such as selection, projection/navigation, dependent join, and quantifiers. We describe a general object data model and define a formalized OQL-like query language SBQL. Optimization by rewriting concerns queries containing so-called independent subqueries. It consists in detecting them and then factoring outside loops implied by query operators. The idea is based on the formal static analysis of scoping rules and binding names occurring in a query. It is more general than the classical pushing selections/projections before joins.     

Identification- and Elimination-Based Parallel Query Processing Techniques for Object-Oriented Databases

The newly developed object-oriented database management systems provide rich facilities for the modeling and processing of structural as well as behavioral properties of complex application objects. However, due to their inherent generality, new functionalities to be added to these systems as they continue to evolve, and high performance demand in many application domains, efficient parallel algorithms and architectures would be needed to meet the performance requirement for processing large OODBs. In our previous work, we have shown that processing OODBs can be viewed as the manipulation of patterns of object associations. In this paper, we present several parallel, multiwavefront algorithms based on two approaches, i.e., identification and elimination approaches, to verify association patterns specified in queries. Both approaches allow more processors to operate concurrently on a query than the traditional tree-structured query processing approach, thus introducing a higher degree of parallelism in query processing. We present a graph model to transform the query processing problem into a graph problem. Based on the graph model, proofs of correctness of both approaches for tree-structured queries are given, and a combined approach for solving cyclic queries is also provided. We present a new data structure to represent associations between objects, parallel algorithms based on these approaches, and some evaluation results obtained from an actual implementation of these algorithms on an nCUBE 2 parallel computer.     

An object-oriented platform for distributed high-performance symbolic computation

We describe the distributed object-oriented threads system (DOTS), a programming environment designed to support object-oriented fork/join parallel programming in a heterogeneous distributed environment. A mixed network of Windows NT PCs and UNIX workstations is transformed by DOTS into a homogeneous pool of anonymous compute servers forming together a multicomputer. DOTS is a complete redesign of the distributed threads system (DTS) using the object-oriented paradigm both in its internal implementation and in the programming paradigm it supports. It has been used for the parallelization of applications in the field of computer algebra and in the field of computer graphics. We also give a brief account of applications in the domain of symbolic computation that were developed using DTS.     

面向对象数据库中基于有向图的联系代数

本文提出了基于基有向图的联系代数，并给出了一个优化联系代数表达的算法。本文所提出的改进较其原形式能 更精确地反映面向对象模型的实质，更有利于对象的查询处理与优化。     

TEMPOS: a platform for developing temporal applications on top of object DBMS

We present TEMPOS: a set of models and languages supporting the manipulation of temporal data on top of object DBMS. The proposed models exploit object-oriented technology to meet some important, yet traditionally neglected design criteria related to legacy code migration and representation independence. Two complementary ways for accessing temporal data are offered: a query language and a visual browser. The query language, namely TEMPOQL, is an extension of OQL supporting the manipulation of histories regardless of their representations, through fully composable functional operators. The visual browser offers operators that facilitate several time-related interactive navigation tasks, such as studying a snapshot of a collection of objects at a given instant, or detecting and examining changes within temporal attributes and relationships. TEMPOS models and languages have been formalized both at the syntactical and the semantical level and have been implemented on top of an object DBMS. The suitability of the proposals with regard to applications' requirements has been validated through concrete case studies.     

MaD‐WiSe: a distributed stream management system for wireless sensor networks

Wireless sensor networks (WSN) are composed of several sensors having limited memory, processing power, communication bandwidth, and energy, which cooperate in performing a given task. The use of the database paradigm has emerged in the last few years as a viable solution to manage data in such a context. In this paper we present the MaD‐WiSe system, a distributed query processing framework that moves the processing of the query into the network. MaD‐WiSe reconsiders various aspects related to database system design and it reinterprets them according to the WSN constraints and requirements. In particular it considers the aspects related to the definition of a query language to formalize the queries, a stream model to manage data acquired by the sensors, a query algebra to define the operators that actually perform the query, and energy efficiency and query optimization strategies for saving energy. Copyright © 2010 John Wiley & Sons, Ltd.     

A Pictorial Query Language for Geographic Features in an Object-Oriented Environment

In this paper, a visual algebra and the relative pictorial query language (PQL) for geographic information systems (GIS) are proposed and discussed. The base data structure of the object oriented model for geographical data is defined and the symbolic features used in the PQL are described. The algebra operators are formally defined, besides their properties and applicability. The use of the symbolic features to express the queries is illustrated, as well as the possible pictorial operations are considered. The used interface is part of the Scenario GIS, developed using an object-oriented environment. This PQL makes easier the formulation of a complex query and simplifies user approach to the system, maintaining a strong expressive power. Finally, an example of query and its pictorial composition on the screen is shown.     

Query optimization and execution plan generation in object-orienteddata management systems

The generation of execution plans for object-oriented database queries is a new and challenging area of study. Unlike relational algebra, a common set of object algebra operators has not been defined. Similarly, a standardized object manager interface analogous to the storage manager interface of relational subsystems does not exist. We define the interface to an object manager whose operations are the executable elements of query execution plans. Parameters to the object manager interface are streams of tuples of object identifiers. The object manager can apply methods and simple predicates to the objects identified in a tuple. Two algorithms for generating such execution plans for queries expressed in an object algebra are presented. The first algorithm runs quickly but may produce inefficient plans. The second algorithm enumerates all possible execution plans and presents them in an efficient, compact representation     

Explicit graphs in a functional model for spatial databases

Observing that networks are ubiquitous in applications for spatial databases, we define a new data model and query language that especially supports graph structures. This model integrates concepts of functional data modeling with order-sorted algebra. Besides object and data type hierarchies, graphs are available as an explicit modeling tool, and graph operations are part of the query language. Graphs have three classes of components, namely, nodes, edges, and explicit paths. These are at the same time object types within the object type hierarchy and can be used like any other type. Explicit paths are useful because real-world objects often correspond to paths in a network. Furthermore, a dynamic generalization concept is introduced to handle heterogeneous collections of objects in a query. In connection with spatial data types, this leads to powerful modeling and querying capabilities for spatial databases, in particular for spatially embedded networks such as highways, rivers, public transport, and so forth. We use multilevel order-sorted algebra as a formal framework for the specification of our model. Roughly spoken, the first-level algebra defines types and operations of the query language, whereas the second-level algebra defines kinds (collections of types) and type constructors as functions between kinds, and so provides the types that can be used at the first level     

一个实现对象查询语言的形式化基础

在基于CORBA(common object request broker)的面向对象多数据库系统SCOPE/CIMS中，作者选择了对象数据库管理组ODMG(object database management group)提出的对象数据库标准ODMG-93的OQL(object query language)作为全局查询语言.为此，提出了一种实现OQL的形式化基础,包括适合建模OQL的一种对象演算和一种对象代数；对象演算的规范化规则和规范化步骤；对象演算与对象代数的等价映射规则及转换策略.     

An algebraic framework for temporal attribute characteristics

Most real-world database applications manage temporal data, i.e., data with associated time references that capture a temporal aspect of the data, typically either when the data is valid or when the data is known. Such applications abound in, e.g., the financial, medical, and scientific domains. In contrast to this, current database management systems offer preciously little built-in query language support for temporal data management. This situation persists although an active temporal database research community has demonstrated that application development can be simplified substantially by built-in temporal support. This paper's contribution is motivated by the observation that existing temporal data models and query languages generally make the same rigid assumption about the semantics of the association of data and time, namely that if a subset of the time domain is associated with some data then this implies the association of any further subset with the data. This paper offers a comprehensive, general framework where alternative semantics may co-exist. It supports so-called malleable and atomic temporal associations, in addition to the conventional ones mentioned above, which are termed constant. To demonstrate the utility of the framework, the paper defines a characteristics-enabled temporal algebra, termed CETA, which defines the traditional relational operators in the new framework. This contribution demonstrates that it is possible to provide built-in temporal support while making less rigid assumptions about the data and without jeopardizing the degree of the support. This moves temporal support closer to practical applications.     

Querying Multiple Data Sources via an Object-Oriented Spatial Query Interface and Framework

A spatial query interface has been designed and implemented in the object-oriented paradigm for heterogeneous data sets. The object-oriented approach presented is shown to be highly suitable for querying typical multiple heterogeneous sources of spatial data. The spatial query model takes into consideration two common components of spatial data: spatial location and attributes. Spatial location allows users to specify an area or a region of interest, also known as a spatial range query. Also, the spatial query allows users to query spatial orientation and relationships (geometric and topological relationships) among other spatial data within the selected area or region. Queries on the properties and values of attributes provide more detailed non-spatial characteristics of spatial data. A query model specific to spatial data involves exploitation of both spatial and attribute components. This paper presents a conceptual spatial query model of heterogeneous data sets based on the object-oriented data model used in the geospatial information distribution system (GIDS).     

Class Based Contextual Logic for DOOD

Cntextual logic provides a mechanism to reason about modules.In this paper,this theory of modules if modules is extended to a context theory of classes where class is in the true spirit of object-oriented databases.The logic,referred to as CLOG,is class-based.CLOG supports class,object identity,multiple role of object, monotonic and non-monotonic inheritance of data and method,method factoring,views,derived and query classes.Views and derived classes are queries in themselves.Objects are pure data terms representing the ground instances of facts in the class.Object identity is a first class term in the logic.Inheritance is handled through delegation.     

Performance analysis of parallel query processing algorithms forobject-oriented databases

Two types of parallel processing and optimization algorithms for processing object-oriented databases are the hybrid-hash pointer-based (HHP) algorithms and multi-wavefront (MWF) algorithms. We analyze these two algorithms and develop analytical formulas to capture their main performance features. We study their performance in three application environments, characterized by large databases having many object classes, each of which, respectively, (1) contains a large number of instances; (2) contains a relatively small number of instances; and (3) is of varying size. A horizontal data partitioning strategy is used in (1). A class-per-node assignment strategy is used in (2). In (3), object classes are partitioned horizontally and assigned to a varying number of processors depending on their different sizes. The MWF algorithm has three distinguishing features which contribute to its better performance: (a) a two-phase processing strategy, (b) vertical partitioning of horizontal segments, and (c) dynamic determination of the collision point in MWF propagations, which results in an optimized query execution plan. If these features are adopted by an HHP algorithm, its performance is comparable with that of the MWF algorithm because the difference in CPU time between them is negligible. The computing environment is a network of workstations having a shared-nothing architecture. The schema and some queries selected from the OO7 benchmark are used in the performance analyses and comparisons. The queries are modified slightly in different data environments in order to reflect the features of diverse database applications     

Using differential technlques to efficiently support transaction time

We present an architecture for query processing in the relational model extended with transaction time. The architecture integrates standard query optimization and computation techniques with new differential computation techniques. Differential computation computes a query incrementally or decrementally from the cahced and indexed results of previous computations. The use of differential computation techniques is essential in order to provide efficient processing of queries that access very large temporal relations. Alternative query plans are integrated into a state transition network, where the state space includes backlogs of base relations, cached results from previous computations, a cache index, and intermediate results; the transitions include standard relational algebra operators, operators for constructing differential files, operators for differential computation, and combined operators. A rule set is presented to prune away parts of state transition networks that are not promising, and dynamic programming techniques are used to identify the optimal plans from the remaining state transition networks. An extended logical access path serves as a structuring index on the cached results and contains, in addition, vital statistics for the query optimization process (including statistics about base relations, backlogs, and queries-previously computed and cached, previously computed, or just previously estimated).