Implementing a Graph Transformation Engine in Relational Databases

We present a novel approach to implement a graph transformation engine based on standard relational database management systems (RDBMSs). The essence of the approach is to create database views for each rule and to handle pattern matching by inner join operations while handling negative application conditions by left outer join operations. Furthermore, the model manipulation prescribed by the application of a graph transformation rule is also implemented using elementary data manipulation statements (such as insert, delete). As a result, we obtain a robust and fast transformation engine especially suitable for (1) extending modeling tools with an underlying RDBMS repository and (2) embedding model transformations into large distributed applications where models are frequently persisted in a relational database and transaction handling is required to handle large models consistently.     

A graph-oriented object database model

A graph-oriented object database model (GOOD) is introduced as a theoretical basis for database systems in which manipulation as well as conceptual representation of data is transparently graph-based. In the GOOD model, the scheme as well as the instance of an object database is represented by a graph, and the data manipulation is expressed by graph transformations. These graph transformations are described using five basic operations and a method construct, all with a natural semantics. The basic operations add and delete objects and edges as a function of the matchings of a pattern. The expressiveness of the model in terms of object-oriented modeling and data manipulation power is investigated     

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     

Spatial join processing using corner transformation

Spatial join finds pairs of spatial objects having a specific spatial relationship in spatial database systems. Since spatial join is a fairly expensive operation, we need an efficient algorithm taking advantage of the characteristics of available spatial access methods. In this paper, we propose a spatial join algorithm using corner transformation and show its excellence through experiments. To the extent of authors' knowledge, the spatial join processing using corner transformation is new. In corner transformation, two regions in one file joined with two adjacent regions in the other file share a large common area. The proposed algorithm utilizes this property in order to reduce the number of disk accesses for spatial join. Experimental results show that the performance of the algorithm is generally better than that of the R*-tree based algorithm proposed by Brinkhoff et al. (1993. 1994). This is a strong indication that corner transformation is a promising category of spatial access methods and that spatial operations can be performed better in the transform space than in the original space. This reverses the common belief that transformation will adversely effect the clustering. We also briefly mention that the join algorithm based on corner transformation has a nice property of being amenable to parallel processing. We believe that our result will provide a new insight towards transformation-based processing of spatial operations     

基于CouchDB的SPARQL查询引擎实现

传统的SPARQL查询引擎在处理查询时以三元组模式为基本单位做查询优化处理,在三元组模式较多时存在着过多的连接操作,开销比较大。文中基于文档数据库的存储和查询特点,提出一种利用主语分类的方式来存储RDF数据的方法,将不同的RDF三元组按主语分成不同的类,并存入文档数据库的文档中。在处理SPARQL查询时将三元组模式也按照主语分类,构成以主语相关块为单位的查询图,并提出一种基于属性相关性的选择度估计方法来优化查询执行计划。文中利用文档数据库CouchDB实现了新的SPARQL查询引擎,实验证明文中的方法能够提高SPARQL基本图模式查询的效率。     

Object configurations in software engineering databases

We consider the logical organization of database support for software engineering applications, which has to cope with such requirements as the adequate support of object composition and versioning, the derivation of (consistent) configurations, and the provision of application-specific transactions. A new approach to the organization, manipulation and management of multiversion objects in CASE databases is described and investigated, which clearly distinguishes four relevant concepts: documents, versions, configurations and databases. The approach is formally made precise using the concept ofAND/OR graphs, which renders it possible to cast operations on any of the concepts in terms of graph operations. The levels of abstraction distinguished and maintained throughout the exposition give rise to an appropriate transaction concept: transactions involve graph operations on specific types of objects only; conflicts between transactions can thus be easily identified, and consistency of objects is easily maintained.     

Taxonomy and formal properties of distributed joins

A general framework for studying the properties of joins between fragmented relations is presented. A join between fragmented relations can be performed as a set of partial joins between their fragments and can be represented as a join graph. A taxonomy of join graphs is developed. Rules are given for determining the class of a join graph from the properties of the fragmentation of relations and from semantic knowledge of different types of database dependencies. The fact that a join graph belongs to a given class is relevant for the efficiency of join execution; two typical application areas of these results are the design of distributed databases and the optimization of distributed queries.     

Page access scheduling in join processing

The join relational operation is one of the most expensive among database operations. In this study, we consider the problem of scheduling page accesses in join processing. This raises two interesting problems: (1) determining a page access sequence that uses the minimum number of buffer pages without any page reaccesses, and (2) determining a page access sequence that minimizes the number of page reaccesses for a given buffer size. We use a graph model to represent the pages from the relations that contain tuples to be joined, and present new heuristics for the two problems. Our experimental results show that the new heuristic performs well.     

An object-based architecture for biomedical expert database systems

Objects play a major role in both database and artificial intelligence research. In this paper, we present a novel architecture for expert database systems that introduces an object-based interface between relational databases and expert systems. We exploit a semantic model of the database structure to map relations automatically into object templates, where each template can be a complex combination of join and projection operations. Moreover, we arrange the templates into object networks that represent different views of the same database. Separate processes instantiate those templates using data from the base relations, cache the resulting instances in main memory, navigate through a given network's objects, and update the database according to changes made at the object layer. In the context of an immunologic-research application, we demonstrate the capabilities of a prototype implementation of the architecture. The resulting model provides enhanced tools for database structuring and manipulation. In addition, this architecture supports efficient bidirectional communication between database and expert systems through the shared object layer.     

云环境下图数据库建模技术及其应用研究

针对云环境下传统关系型数据库在大数据库建模方面存在的诸多问题,描述了一种全新的能适应云计算环境建模的图数据库,定义了图数据库模型的基本概念,给出了图数据库建模元素及组织形式,在关系型数据库概念模型建模理论及方法的基础上提出了图数据库建模的若干规则和方法。以图数据库Neo4j为例,详细描述了现代物料入库管理图数据库的建模过程,并应用Cypher语言实现该系统模型的增加、删除、更改、查询及统计功能。实践结果表明：利用图数据库建模技术构造的模型具有语义表达更丰富、更具简易性和可扩展性等优点,对开发基于图模型的智能管理信息系统能够提供一定的参考依据。     

一种不确定图数据库上的相似性连接方法

在确定图上进行的相似性连接已有许多研究成果.然而,在实际应用中会有许多因素使得图结构数据变得不确定.研究了不确定图数据库上的相似性连接问题.采用联合概率分布表示法来描述图中边的不确定性,结合一种新的图的相似性度量方法,给出了不确定图数据库上的相似性连接的形式化定义,并设计了一组过滤策略来减少连接过程中候选图对的数量.大量的实验数据表明,所提出的方法具有较好的可行性和准确性.     

Similarity queries: their conceptual evaluation, transformations, and processing

Many application scenarios can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, for example join and selection, to be aware of data similarities, there has not been much study on the role and implementation of similarity-aware operations as first-class database operators. Furthermore, very little work has addressed the problem of evaluating and optimizing queries that combine several similarity operations. The focus of this paper is the study of similarity queries that contain one or multiple first-class similarity database operators such as Similarity Selection, Similarity Join, and Similarity Group-by. Particularly, we analyze the implementation techniques of several similarity operators, introduce a consistent and comprehensive conceptual evaluation model for similarity queries, and present a rich set of transformation rules to extend cost-based query optimization to the case of similarity queries.     

Performance analysis of parallel object-oriented query processing algorithms

Advanced application domains such as computer-aided design, computer-aided software engineering, and office automation are characterized by their need to store, retrieve, and manage large quantities of data having complex structures. A number of object-oriented database management systems (OODBMS) are currently available that can effectively capture and process the complex data. The existing implementations of OODBMS outperform relational systems by maintaining and querying cross-references among related objects. However, the existing OODBMS still do not meet the efficiency requirements of advanced applications that require the execution of complex queries involving the retrieval of a large number of data objects and relationships among them. Parallel execution can significantly improve the performance of complex OO queries. In this paper, we analyze the performance of parallel OO query processing algorithms for various benchmark application domains. The application domains are characterized by specific mixes of queries of different semantic complexities. The performance of the application domains has been analyzed for various system and data parameters by running parallel programs on a 32-node transputer based parallel machine developed at the IBM Research Center at Yorktown Heights. The parallel processing algorithms, data routing techniques, and query management and control strategies have been implemented to obtain accurate estimation of controlling and processing overheads. However, generation of large complex databases for the study was impractical. Hence, the data used in the simulation have been parameterized. The parallel OO query processing algorithms analyzed in this study are based on a query graph approach rather than the traditional query tree approach. Using the query graph approach, a query is processed by simultaneously initiating the execution at several object classes, thereby, improving the parallelism. During processing, the algorithms avoid the execution of time-consuming join operations by making use of the object references among the objects. Further, the algorithms do not generate any temporary data, thereby, reducing disk accesses. This is accomplished by marking the selected objects and by employing a two-phase query processing strategy.     

Extending C for Checking Shape Safety

The project Safe Pointers by Graph Transformation at the University of York has developed a method for specifying the shape of pointer-data structures by graph reduction, and a static checking algorithm for proving the shape safety of graph transformation rules modelling operations on pointer structures. In this paper, we outline how to apply this approach to the C programming language. We extend ANSI C with so-called transformers which model graph transformation rules, and with shape specifications for pointer structures. For the resulting language C-GRS, we present both a translation to C and and an abstraction to graph transformation. Our main result is that the abstraction of transformers to graph transformation rules is correct in that the C code implementing transformers is compatible with the semantics of graph transformation.     

Animation toolkit based on a database approach for reusing motions and models

As animations become more readily available, simultaneously the complexity of creating animations has also increased. In this paper, we address the issue by describing an animation toolkit based on a database approach for reusing geometric animation models and their motion sequences. The aim of our approach is to create a framework aimed for novice animators. Here, we use an alternative notion of a VRML scene graph to describe a geometric model, specifically intended for reuse. We represent this scene graph model as a relational database. A set of spatial, temporal, and motion operations are then used to manipulate the models and motions in an animation database. Spatial operations help in inserting/deleting geometric models in a new animation scene. Temporal and motion operations help in generating animation sequences in a variety of ways. For instance, motion information of one geometric model can be applied to another model or a motion sequence can be retargeted to meet additional constraints (e.g., wiping action on a table can be retargeted with constraints that reduce the size of the table). We present the design and implementation of this toolkit along with several interesting examples of animation sequences that can be generated using this toolkit.     

Towards an Integrated Graph Based Semantics for UML

Recently, we proposed an integrated formal semantics based on graph transformation for central aspects of UML class, object and state diagrams. In this paper, we explain the basic ideas of that approach and show how two more UML diagram types, sequence and collaboration diagrams, can be captured. For UML models consisting of a class diagram and particular state diagrams, a graph transformation system can be defined. Its graphs are associated with system states and its rules with operations in the class diagram and transitions in the state diagrams. Sequence and collaboration diagrams then characterize sequences of operation applications and therefore sequences of transformation rule applications. Thus valid sequence and collaboration diagrams correspond to derivations induced by the graph transformation system. Proceeding this way, it can be checked for example whether such an operation application sequence may be applied in a specific system state.     

Heuristic and randomized optimization for the join ordering problem

Recent developments in database technology, such as deductive database systems, have given rise to the demand for new, cost-effective optimization techniques for join expressions. In this paper many different algorithms that compute approximate solutions for optimizing join orders are studied since traditional dynamic programming techniques are not appropriate for complex problems. Two possible solution spaces, the space of left-deep and bushy processing trees, are evaluated from a statistical point of view. The result is that the common limitation to left-deep processing trees is only advisable for certain join graph types. Basically, optimizers from three classes are analysed: heuristic, randomized and genetic algorithms. Each one is extensively scrutinized with respect to its working principle and its fitness for the desired application. It turns out that randomized and genetic algorithms are well suited for optimizing join expressions. They generate solutions of high quality within a reasonable running time. The benefits of heuristic optimizers, namely the short running time, are often outweighed by merely moderate optimization performance.     

基于向量引用Platform-Oblivious内存连接优化技术

以MapD为代表的图分析数据库系统通过GPU、Phi等新型众核处理器来支持高性能分析处理,在面向复杂数据模式时连接操作仍然是重要的性能瓶颈.近年来,异构处理器逐渐成为高性能计算的主流平台,内存连接性能的研究从多核CPU平台扩展到新兴的众核处理器,但众多的研究成果并未系统地揭示连接算法性能、连接数据集大小、硬件架构之间的内在联系,难以为未来异构处理器平台的数据库提供连接平台优化选择策略.本文以面向多核CPU、Xeon Phi、GPU处理器平台的内存连接优化技术为目标,通过优化内存哈希表设计,实现以向量映射替代哈希映射操作,消除哈希代价对内存连接算法的影响,从而更加准确地测量内存连接算法在多核CPU的cache大小、Xeon Phi的cache大小、Xeon Phi的并发多线程、GPU的SIMT（单指令多线程）机制等硬件相关因素影响下的性能特征.实验结果表明,缓存与并发多线程机制是提高内存连接算法性能的重要影响因素.缓存机制对于满足cache大小的连接操作具有性能优势,而GPU的并发多线程机制则在较大表的连接操作中具有较高的性能,Xeon Phi则在满足其L2 cache大小的连接操作中具有最高性能.实验结果揭示了内存连接操作性能与异构处理器硬件特性的联系,为未来异构处理器平台内存数据库查询优化器提供了优化策略.     

区间值模糊图的分解性质

给出了区间值模糊图在笛卡尔积与合成运算下分解的充要条件,证明了区间值模糊图能够在并与联运算下分解。