A new, efficient selection predicate indexing scheme for active database systems is introduced. The selection predicate index proposed uses an interval index on an attribute of a relation or object collection when one or more rule condition clauses are defined on that attribute. The selection predicate index uses a new type of interval index called the interval skip list (IS-list). The IS-list is designed to allow efficient retrieval of all intervals that overlap a point, while allowing dynamic insertion and deletion of intervals. IS-list algorithms are described in detail. The IS-list allows efficient on-line searches, insertions, and deletions, yet is much simpler to implement than other comparable interval index data structures such as the priority search tree and balanced interval binary search tree (IBS-tree). IS-lists require only one third as much code to implement as balanced IBS-trees. The combination of simplicity, performance, and dynamic updateability of the IS-li...

This paper describes a model that integrates the execution of triggers with the evaluation of declarative constraints in SQL database systems. This model achieves full compatibility with the 1992 international standard for SQL (SQL92). It preserves the set semantics for declarative constraint evaluation while allowing the execution of powerful procedural triggers. It was implemented in DB2 for common servers and was recently accepted as the model for the emerging SQL standard (SQL3). 1 Introduction Active databases are taking a prominent role in commercial database applications [6, 30, 29, 13]. With client/server solutions, applications are being developed by small, autonomous groups of developers with narrow views of the overall enterprise; the enterprise information system is very vulnerable to integrity violations because it lacks strict enforcement of the enterprise business rules. Active data proactively monitors events and, without user intervention, protects its own integrity...

ing with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept, ACM Inc., 1515 Broadway, New York, NY 10036 USA, fax +1 (212) 869-0481, or permissions@acm.org. This is a preliminary release of an article accepted by ACM Transactions on Database Systems. The definitive version is currently in production at ACM and, when released, will supersede this version. 2 \Delta E. Baralis and J. Widom 1. INTRODUCTION An active database system is a conventional database system extended with a facility for managing active rules (or triggers). Incorporating active rules into a conventional database system has raised considerable interest both in the scientific community and in the commercial world: A number of prototypes that incorporate active rules into relational and object-oriented database system...

Rules in active database systems can be very difficult to program, due to the unstructured and unpredictable nature of rule processing. We provide static analysis techniques for predicting whether a given rule set is guaranteed to terminate, and whether rule execution is confluent (guaranteed to have a unique final state). Our methods are based on previous techniques for analyzing rules in active database systems. We improve considerably on the previous techniques by providing analysis criteria that are much less conservative: our methods often determine that a rule set will terminate or is confluent when previous methods could not make this determination. Our improved analysis is based on a "propagation" algorithm, which uses an extended relational algebra to accurately determine when the action of one rule can affect the condition of another, and to determine when rule actions commute. We consider both Condition-Action rules and Event-Condition-Action rules, making our approach widel...

This paper presents semantically-based explicit parallel structuring for rule-based programming systems. Explicit parallel structuring appears to be necessary since compile-time dependency analysis of sequential programs has not yielded large scale parallelism and run-time analysis for parallelism is restricted by the execution cost of the analysis. Simple language extensions specifying semantics of rules are used to define parallel execution behavior at the rule level. Type definitions for working memory elements are extended to include relationships within and among objects which define the parallelism allowed on instances of object types. The first result presented is that the algorithms implemented by commonly used benchmark rule-based programs contain scalable parallelism. The second result is that much of that parallelism can be captured by simple and modest extensions of rule-based languages which are analogies of models and constructs used for specification of parallel structur...

Set-oriented constructs for forward chaining rule-based systems are presented in this paper. These constructs allow arbitrary amounts of data to be matched and changed within the execution of a single rule. Second order tests on the data can be included in the match. The ability of a single rule to directly access all of the data to be manipulated eliminates the need for unwieldy control mechanisms and marking schemes. Adding this expressivity to rule-based languages enhances their value to expert system developers and their capabilities as database programming languages. Additionally, these set-oriented constructs can provide a basis for more efficient implementations of rule-based systems, for both the traditional memory-based systems and the emerging disk-based ones. The work described has been implemented using an extended version of the Rete network algorithm. AI Topic: Knowledge Representation, Rule-based systems. Language/Tool: OPS5. Effort: Proprietary Information. Impact: Set-oriented constructs in rule-based languages will enable fast prototyping of expert systems and provide new directions for integrating rule-based systems and database systems. 1.

F TP (Fuzzy Template Predicate) is proposed as a template to incorporate concept-based match into fuzzy production languages. A thesaurus augmented in F TP supports the conceptbased match, which is more sophisticated than previous fuzzy match mechanisms. Membership functions for fuzzy linguistic variables and fuzzy numbers are used as an interface to the thesaurus. F TP also has self refining facility to reformulate itself by exploiting user input or integrity constraints in Knowledge base. F TP is used mainly in the Left Hand Side (LHS) of a production rule to participate in matches made between patterns and fuzzy facts. For the seamless integration of the rule into a relational database, the structure of the fuzzy facts LHS refers to is conformed to the relational framework. We also develop a rule evaluation mechanism supporting the F TP construct. In the rule evaluation, a modified Rescher-Gaines translation rule is used for fuzzy implication rather than well-known composi...

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Current database trigger systems have extremely limited scalability. This paper proposes a way to develop a truly scalable trigger system. Scalability to large numbers of triggers is achieved with a trigger cache to use main memory effectively, and a memory-conserving selection predicate index based on the use of unique expression formats called expression signatures. A key observation is that if a very large number of triggers are created, many will have the same structure, except for the appearance of different constant values. When a trigger is created, tuples are added to special relations created for expression signatures to hold the trigger's constants. These tables can be augmented with a database index or main-memory index structure to serve as a predicate index. The design presented also uses a number of types of concurrency to achieve scalability, including token (tuple)-level, condition-level, rule action-level, and datalevel concurrency.

....................................................................................................................... ix CHAPTERS 1 INTRODUCTION ........................................................................................................... 1 2 RELATED WORK ......................................................................................................... 5 2.1 Active Databases ..................................................................................................... 5 2.1.1 Relational Active Database Systems .............................................................. 6 2.1.2 Object-Oriented Active Database Systems .................................................... 8 2.2 Temporal Database Systems ................................................................................. 10 2.3 Active Temporal Database Systems (ATDBMS).................................................. 12 2.4 The Basic Structure of a Typical Temporal Rule Processing (TRP) Syste...