Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Flexible time management in data stream systems
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Semantics and evaluation techniques for window aggregates in data streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Towards a streaming SQL standard
Proceedings of the VLDB Endowment
Semantics and implementation of continuous sliding window queries over data streams
ACM Transactions on Database Systems (TODS)
Semantics of data streams and operators
ICDT'05 Proceedings of the 10th international conference on Database Theory
Window specification over data streams
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
How soccer players would do stream joins
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Revisiting formal ordering in data stream querying
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Transactional stream processing
Proceedings of the 15th International Conference on Extending Database Technology
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Chimera: a declarative language for streaming network traffic analysis
Security'12 Proceedings of the 21st USENIX conference on Security symposium
Anomaly management using complex event processing: extending data base technology paper
Proceedings of the 16th International Conference on Extending Database Technology
Proceedings of the 7th ACM international conference on Distributed event-based systems
Report on the first workshop on innovative querying of streams
ACM SIGMOD Record
Modeling the execution semantics of stream processing engines with SECRET
The VLDB Journal — The International Journal on Very Large Data Bases
A new operator for efficient stream-relation join processing in data streaming engines
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Realtime analysis of information diffusion in social media
Proceedings of the VLDB Endowment
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There are many academic and commercial stream processing engines (SPEs) today, each of them with its own execution semantics. This variation may lead to seemingly inexplicable differences in query results. In this paper, we present SECRET, a model of the behavior of SPEs. SECRET is a descriptive model that allows users to analyze the behavior of systems and understand the results of window-based queries for a broad range of heterogeneous SPEs. The model is the result of extensive analysis and experimentation with several commercial and academic engines. In the paper, we describe the types of heterogeneity found in existing engines, and show with experiments on real systems that our model can explain the key differences in windowing behavior.