The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
A Data Model for Temporal XML Documents
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
XPath queries on streaming data
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Path sharing and predicate evaluation for high-performance XML filtering
ACM Transactions on Database Systems (TODS)
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
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ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2004
An Efficient XPath Query Processor for XML Streams
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The expressivity of XPath with transitive closure
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High-performance complex event processing over streams
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MonetDB/XQuery: a fast XQuery processor powered by a relational engine
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XMark: a benchmark for XML data management
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Navigational XPath: calculus and algebra
ACM SIGMOD Record
XPath, transitive closure logic, and nested tree walking automata
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ArchIS: an XML-based approach to transaction-time temporal database systems
The VLDB Journal — The International Journal on Very Large Data Bases
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DBKDA '09 Proceedings of the 2009 First International Conference on Advances in Databases, Knowledge, and Data Applications
The complexity of query containment in expressive fragments of XPath 2.0
Journal of the ACM (JACM)
Query Automata for Nested Words
MFCS '09 Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009
Distributed event stream processing with non-deterministic finite automata
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
Event-Oriented Data Models and Temporal Queries in Transaction-Time Databases
TIME '09 Proceedings of the 2009 16th International Symposium on Temporal Representation and Reasoning
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K*SQL: a unifying engine for sequence patterns and XML
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Proceedings of the VLDB Endowment
Queries on Xml streams with bounded delay and concurrency
Information and Computation
Streamable fragments of forward XPath
CIAA'11 Proceedings of the 16th international conference on Implementation and application of automata
Axiomatizing the logical core of XPath 2.0
ICDT'07 Proceedings of the 11th international conference on Database Theory
Adding nesting structure to words
DLT'06 Proceedings of the 10th international conference on Developments in Language Theory
High-performance complex event processing over XML streams
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Optimization of Massive Pattern Queries by Dynamic Configuration Morphing
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Complex pattern matching in complex structures: The XSeq approach
ICDE '13 Proceedings of the 2013 IEEE International Conference on Data Engineering (ICDE 2013)
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While Complex Event Processing (CEP) constitutes a considerable portion of the so-called Big Data analytics, current CEP systems can only process data having a simple structure, and are otherwise limited in their ability to efficiently support complex continuous queries on structured or semistructured information. However, XML-like streams represent a very popular form of data exchange, comprising large portions of social network and RSS feeds, financial feeds, configuration files, and similar applications requiring advanced CEP queries. In this article, we present the XSeq language and system that support CEP on XML streams, via an extension of XPath that is both powerful and amenable to an efficient implementation. Specifically, the XSeq language extends XPath with natural operators to express sequential and Kleene-* patterns over XML streams, while remaining highly amenable to efficient execution. In fact, XSeq is designed to take full advantage of the recently proposed Visibly Pushdown Automata (VPA), where higher expressive power can be achieved without compromising the computationally attractive properties of finite state automata. Besides the efficiency and expressivity benefits, the choice of VPA as the underlying model also enables XSeq to go beyond XML streams and be easily applicable to any data with both sequential and hierarchical structures, including JSON messages, RNA sequences, and software traces. Therefore, we illustrate the XSeq's power for CEP applications through examples from different domains and provide formal results on its expressiveness and complexity. Finally, we present several optimization techniques for XSeq queries. Our extensive experiments indicate that XSeq brings outstanding performance to CEP applications: two orders of magnitude improvement is obtained over the same queries executed in general-purpose XML engines.