Semantics and evaluation techniques for window aggregates in data streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A data stream language and system designed for power and extensibility
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Extending XQuery with window functions
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Designing an inductive data stream management system: the stream mill experience
SSPS '08 Proceedings of the 2nd international workshop on Scalable stream processing system
SECRET: a model for analysis of the execution semantics of stream processing systems
Proceedings of the VLDB Endowment
Relational languages and data models for continuous queries on sequences and data streams
ACM Transactions on Database Systems (TODS)
Window specification over data streams
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
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Our implementation of the DEBS 2013 Challenge is based on a scalable, parallel, and extensible DSMS, which is capable of processing general continuous queries over high volume data streams with low delays. A mechanism to provide user defined incremental aggregate functions over sliding windows of data streams provide real-time processing by emitting results continuously with low delays. To further eliminate delays caused by time critical operations, the system is extensible so that functions can be easily written in some external programming language. The query language provides user defined parallelization primitives where the user can express queries specifying how high volume data streams are split and reduced into lower volume parallel data streams. This enables expensive queries over data streams to be executed in parallel based on application knowledge. Our OS-independent implementation was tested on several computers and achieves the real-time requirement of the challenge on a regular PC.