Abstract not found

Many computer-supported applications are of long duration and consist of multiple steps that are exe-cuted over possibly heterogeneous servers. Such activ-ities have weaker atomicity requirements than trans-actions. Previously, we illustrated how to organize the execution of such activities using triggers and transac-tions. In this paper, we describe an execution model in.which activities may consist recursively of steps that may be subactivities or transactions. The model defines precisely the semantics of activities: commu-nication between steps and the failure semantics of activities including compensation and exception han-dling. The model also supports querying the status of activities. We also propose an implementation of the model using recoverable queues for reliably chaining the steps according to the semantics of the model. 1

Integrating a production rules facility into a database system provides a uniform mechanism for a number of advanced database features including integrity constraint enforcement, derived data maintenance, triggers, alerters, protection, version control, and others. In addition, a database system with rule processing capabilities provides a useful platform for large and efficient knowledge-base and expert systems. Database systems with production rules are referred to as active database systems, and the field of active database systems has indeed been active. This chapter summarizes current work in active database systems; topics covered include active database rule models and languages, rule execution semantics, and implementation issues. 1 Introduction Conventional database systems are passive: they only execute queries or transactions explicitly submitted by a user or an application program. For many applications, however, it is important to monitor situations of interest, and to ...

Database researchers have recognized that integrating a production rules facility into a database system provides a uniform mechanism for a number of advanced database features including integrity constraint enforcement, derived data maintenance, triggers, protection, version control, and others. In addition, a database system with rule processing capabilities provides a useful platform for large and efficient knowledge-base and expert systems. Database systems with production rules are referred to as active database systems, and the field of active database systems has indeed been active. This paper summarizes current work in active database systems and suggests future research directions. Topics covered include database rule languages, rule processing semantics, and implementation issues. 1 Introduction Database systems provide persistent storage for massive amounts of data and powerful interfaces for querying and modifying this data. Even so, most database systems are passive, si...

This paper describes our development of the Starburst Rule System, an active database rules facility integrated into the Starburst extensible relational database system at the IBM Almaden Research Center. The Starburst rule language is based on arbitrary database state transitions rather than tuple- or statement-level changes, yielding a clear and flexible execution semantics. The rule system has been implemented completely. Its rapid implementation was facilitated by the extensibility features of Starburst, and rule management and rule processing is integrated into all aspects of database processing. Index terms: active database systems, database production rules, extensible database systems, expert database systems 1 Introduction Active database systems allow users to create rules---rules specify data manipulation operations to be executed automatically whenever certain events occur or conditions are met. Active database rules provide a general and powerful mechanism for traditiona...

Making a database system active entails not only the specification of expressive ECA (eventcondition -action) rules, algorithms for the detection of composite events, and rule management, but also a viable architecture for rule execution that extends a passive DBMS, and its implementation. In this paper, we propose an integrated active DBMS architecture for incorporating ECA rules using the Open OODB Toolkit (from Texas Instruments, Dallas). We then describe the implementation of the composite event detector, and rule execution using a nested transaction model for object-oriented active DBMS. Finally, the functionality supported by this architecture and its extensibility are analyzed along with the experiences gained. 1 Introduction During the last decade, database management systems (DBMSs) have evolved considerably to meet the requirements of emerging applications. ECA rules (or event-condition-action or situation-action rules) generalize the forms of monitoring supported earlier (e...

Change computation is an essential component in several capabilities of a deductive database, such as integrity constraints checking, materialized view maintenance and condition monitoring. In this paper, we present a general method for change computation, which is based on the use of transition and internal events rules. These rules explicitly define the insertions, deletions and modifications induced by a database update. Standard SLDNF resolution can be used to compute the induced changes, but other procedures could be used as well. Our method generalizes and extends previous work on change computation methods, and in some cases computes changes in a more efficient way. 1 Introduction Deductive databases generalize relational databases by including not only base predicates (or relations), but also derived predicates (or views). A derived predicate is defined by means of one or more deductive rules. In a deductive database, an update to base predicates may induce changes on one or ...

We introduce an active data mining paradigm that combines the recent work in data mining with the rich literature on active database systems. In this paradigm, data is continuously mined at a desired frequency. As rules are discovered, they are added to a rulebase, and if they already exist, the history of the statistical parameters associated with the rules is updated. When the history starts exhibiting certain trends, specified as shape queries in the user-speci ed triggers, the triggers are red and appropriate actions are initiated. To be able to specify shape queries, we describe the constructs for de ning shapes, and discuss how the shape predicates are used in a query construct to retrieve rules whose histories exhibit the desired trends. We describe how this query capability is integrated into a trigger system to realize an active mining system. The system presented here has been validated using two sets of customer data.

Making a database system active entails developing an expressive event specification language with well-defined semantics, algorithms for the detection of composite events, and an architecture for an event detector along with its implementation. This paper presents Snoop as the event specification language along with the semantics of composite events over a global event-history (or a global event-log). Parameter contexts are introduced for meaningfully restricting the detection of composite events. In addition, algorithms for the detection of composite events in various parameter contexts are presented. Finally, an architecture and implementation of a composite event detector is analyzed in the context of an object-oriented active DBMS. 1 Introduction Consensus is emerging in the database community about the structure of rules for supporting active functionality. A rule consists, primarily, of three components: an event, a condition, and an action. A rule consisting of these component...

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...