Efficient pattern matching over event streams
Jagrati Agrawal,Yanlei Diao,Daniel Gyllstrom,Neil Immerman +3 more
- pp 147-160
TLDR
This paper presents a formal evaluation model that offers precise semantics for this new class of queries and a query evaluation framework permitting optimizations in a principled way and further analyzes the runtime complexity of query evaluation using this model and develops a suite of techniques that improve runtime efficiency by exploiting sharing in storage and processing.Abstract:
Pattern matching over event streams is increasingly being employed in many areas including financial services, RFIDbased inventory management, click stream analysis, and electronic health systems. While regular expression matching is well studied, pattern matching over streams presents two new challenges: Languages for pattern matching over streams are significantly richer than languages for regular expression matching. Furthermore, efficient evaluation of these pattern queries over streams requires new algorithms and optimizations: the conventional wisdom for stream query processing (i.e., using selection-join-aggregation) is inadequate.In this paper, we present a formal evaluation model that offers precise semantics for this new class of queries and a query evaluation framework permitting optimizations in a principled way. We further analyze the runtime complexity of query evaluation using this model and develop a suite of techniques that improve runtime efficiency by exploiting sharing in storage and processing. Our experimental results provide insights into the various factors on runtime performance and demonstrate the significant performance gains of our sharing techniques.read more
Citations
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TL;DR: The main techniques and state-of-the-art research efforts in IoT from data-centric perspectives are reviewed, including data stream processing, data storage models, complex event processing, and searching in IoT.
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TESLA: a formally defined event specification language
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ZStream: a cost-based query processor for adaptively detecting composite events
Yuan Mei,Samuel Madden +1 more
TL;DR: A cost model can accurately capture the actual runtime behavior of a plan, and that choosing the optimal plan can result in a factor of four or more speedup versus an NFA based approach, and a dynamic programming algorithm is described used in this cost model to efficiently search for an optimal query plan for a given pattern.
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