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We identify the precise conditions that any parallel implementation of production systems must fulfill in order to be semantically consistent. We present a mechanism that guarantees the semantic consistency of parallel execution, and prove its correctness. It is based on a novel locking mechanism that provides more parallelism than conventional 2-phase locking. Finally, we discuss the various factors that can affect the actual speed-up of a database production system."
Knowledge Base Systems are an integration of conventional database systems with Artificial Intelligence techniques. They provide inference capabilities to the database system by encapsulating the knowledge of the application domain within the database. Knowledge is the most valuable of all corporate resources that must be captured, stored, re-used and continuously improved, in much the same way as database systems were important in the previous decade. Flexible, extensible, and yet efficient Knowledge Base Systems are needed to capture the increasing demand for knowledge-based applications which will become a significant market in the next decade. Knowledge can be expressed in many static and dynamic forms; the most prominent being domain objects, their relationships, and their rules of evolution and transformation. It is important to express and seamlessly use all types of knowledge in a single Knowledge Base System. Parallel, Object-Oriented, and Active Knowledge Base Systems presents in detail features that a Knowledge Base System should have in order to fulfill the above requirements. Parallel, Object-Oriented, and Active Knowledge Base Systems covers in detail the following topics: Integration of deductive, production, and active rules in sequential database systems. Integration and inter-operation of multiple rule types into the same Knowledge Base System. Parallel rule matching and execution, for deductive, production, and active rules, in parallel Export, Knowledge Base, and Database Systems. In-depth description of a Parallel, Object-Oriented, and Active Knowledge Base System that integrates all rule paradigms into a single database system without hindering performance. Parallel, Object-Oriented, and Active Knowledge Base Systems is intended as a graduate-level text for a course on Knowledge Base Systems and as a reference for researchers and practitioners in the areas of database systems, knowledge base systems and Artificial Intelligence.
This book is the proceedings of a workshop held at Heriot-Watt University in Edinburgh in August 1993. The central theme of the workshop was rules in database systems, and the papers presented covered a range of different aspects of database rule systems. These aspects are reflected in the sessions of the workshop, which are the same as the sections in this proceedings: Active Databases Architectures Incorporating Temporal Rules Rules and Transactions Analysis and Debugging of Active Rules Integrating Graphs/Objects with Deduction Integrating Deductive and Active Rules Integrity Constraints Deductive Databases The incorporation of rules into database systems is an important area of research, as it is a major component in the integration of behavioural information with the structural data with which commercial databases have traditionally been associated. This integration of the behavioural aspects of an application with the data to which it applies in database systems leads to more straightforward application development and more efficient processing of data. Many novel applications seem to need database systems in which structural and behavioural information are fully integrated. Rules are only one means of expressing behavioural information, but it is clear that different types of rule can be used to capture directly different properties of an application which are cumbersome to support using conventional database architectures. In recent years there has been a surge of research activity focusing upon active database systems, and this volume opens with a collection of papers devoted specifically to this topic.
The latest techniques and principles of parallel and grid database processing The growth in grid databases, coupled with the utility of parallel query processing, presents an important opportunity to understand and utilize high-performance parallel database processing within a major database management system (DBMS). This important new book provides readers with a fundamental understanding of parallelism in data-intensive applications, and demonstrates how to develop faster capabilities to support them. It presents a balanced treatment of the theoretical and practical aspects of high-performance databases to demonstrate how parallel query is executed in a DBMS, including concepts, algorithms, analytical models, and grid transactions. High-Performance Parallel Database Processing and Grid Databases serves as a valuable resource for researchers working in parallel databases and for practitioners interested in building a high-performance database. It is also a much-needed, self-contained textbook for database courses at the advanced undergraduate and graduate levels.
Parallel processing technology in the next generation of Database Management Systems (DBMSs) make it possible to meet challenging new requirements. Database technology is rapidly expanding new application areas brings unique challenges such as increased functionality and efficient handling of very large heterogeneous databases. Abdelguerfi and Wong present the latest techniques in parallel relational databases illustrating high-performance achievements in parallel database systems. The text is st5ructured according to the overall architecture of a parallel database system presenting various techniques that may be adopted to the design of parallel database software and hardware execution environments. These techniques can directly or indirectly lead to high-performance parallel database implementation. The book's main focus follows the authors' engineering model: A survey of parallel query optimization techniques for requests involving multi-way joins A new technique for a join operation that can be adopted in the local optimization stage A framework for recovery in parallel database systems using the ACTA formalism The architectural details of NCR's new Petabyte multimedia database system A description of the Super Database Computer (SDC-II) A case study for a shared-nothing parallel database server that analyzes and compares the effectiveness of five data placement techniques
This monograph coherently presents a series of research results on concurrent production systems recently contributed by the author and several co-authors. Before going into the details of concurrent production systems the performance of a single system is discussed. Based on these considerations it is explained how to estimate the efficiency of production systems programs and how to automatically determine efficient join structures. Parallel systems, including algorithms for parallel rule firings, distributed systems under distributed control, and particularly multiagent production systems and the related control issues are investigated. Finally a meta-level control architecture is applied to the construction of the multiagent system CoCo for public telecommunication network control.
This text provides one of the broadest presentations of parallel processing available, including the structure of parallelprocessors and parallel algorithms. The emphasis is on mapping algorithms to highly parallel computers, with extensive coverage of array and multiprocessor architectures. Early chapters provide insightful coverage on the analysis of parallel algorithms and program transformations, effectively integrating a variety of material previously scattered throughout the literature. Theory and practice are well balanced across diverse topics in this concise presentation. For exceptional clarity and comprehension, the author presents complex material in geometric graphs as well as algebraic notation. Each chapter includes well-chosen examples, tables summarizing related key concepts and definitions, and a broad range of worked exercises. Overview of common hardware and theoretical models, including algorithm characteristics and impediments to fast performance Analysis of data dependencies and inherent parallelism through program examples, building from simple to complex Graphic and explanatory coverage of program transformations Easy-to-follow presentation of parallel processor structures and interconnection networks, including parallelizing and restructuring compilers Parallel synchronization methods and types of parallel operating systems Detailed descriptions of hypercube systems Specialized chapters on dataflow and on AI architectures
During the last few years, parallel object-relational database management systems have emerged as the leading data management technology on the market. These systems are extensible by user-defined data types and user-defined functionality for the data. This work focuses on the efficient parallel execution of user-defined functionality. The main contributions describe techniques to support data parallelism for user-defined scalar and aggregate functions and intra-function parallelism for the execution of a scalar function on a large object, and a new technology to provide extensibility with regard to new set-oriented database operations that can efficiently implement user-defined functionality in parallel object-relational database management systems.
Provides readers with a background knowledge of parallel database query processing and optimization and covers recent developments in the field. Subjects include design approaches, architecture of parallel database systems, parallel sorting, parallel processing of join, data skew and load balancing,