Definition
The definition of an event processing network includes a relation to express un-modeled event processing logic between events.
The fact that events of type eT1 cause events of type eT2 is denoted by the relation causes(eT1,eT2).
In an EPN where E is the set of edges representing event streams, EC is the set of Event Channels, C is the set of Event Consumers and P is the set of Event Producers, the relation is evaluated to be true if events of type eT1 flow in an event stream e1(u,v): e1∈E, u∈EC, v∈C and events of type eT2 flow in an event stream e2(m,l): e2∈E, m∈P, l∈EC and there is some un-modeled event processing logic between events of type eT1 consumed by v∈e1 and events of type eT2 produced by m∈e2.
Key Points
The event processing intent defined by an event processing network may not cover the entire flow of events through systems as there may be cases where an event is handled by an event consumer, such as a software application, and as a result the application...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsRecommended Reading
Aiken A, Hellerstein JM, Widom J. Static analysis techniques for predicting the behavior of active database rules. ACM Trans Database Syst. 1995;20(1):3–41.
Bailey J, Poulovassilis A. Abstract interpretation for termination analysis in functional active databases. J Intell Inf Syst. 1999;12(2–3):243–73.
Baralis E, Ceri S, Paraboschi S. Compile-time and runtime analysis of active behaviors. IEEE Trans Knowl Data Eng. 1998;10(3):353–70.
Fisk M. A defence of the principle of event causality. Br J Philos Sci. 1967;18(2):89–108.
Pearl J. Causality: models, reasoning, and inference. New York: Cambridge University Press; 2000.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Sharon, G. (2018). Event Causality. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_572
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_572
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering