High-Performance Dynamic Pattern Matching over Disordered Streams by Badrish Chandramouli, Jonathan Goldstein, and David Maier came to me by way of Jack Park.
From the abstract:
Current pattern-detection proposals for streaming data recognize the need to move beyond a simple regular-expression model over strictly ordered input. We continue in this direction, relaxing restrictions present in some models, removing the requirement for ordered input, and permitting stream revisions (modification of prior events). Further, recognizing that patterns of interest in modern applications may change frequently over the lifetime of a query, we support updating of a pattern specification without blocking input or restarting the operator.
In case you missed it, this is related to: Experience in Extending Query Engine for Continuous Analytics.
The algorithmic trading use case in this article made me think of Nikita Ogievetsky. For those of you who do not know Nikita, he is an XSLT/topic map maven, currently working in the finance industry.
Do trading interfaces allow user definition of subjects to be identified in data streams? And/or merged with subjects identified in other data streams? Or is that an upgrade from the basic service?