Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Temporal and Real-Time Databases: A Survey
IEEE Transactions on Knowledge and Data Engineering
A Foundation for Conventional and Temporal Query Optimization Addressing Duplicates and Ordering
IEEE Transactions on Knowledge and Data Engineering
Query Plans for Conventional and Temporal Queries Involving Duplicates and Ordering
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Chain: operator scheduling for memory minimization in data stream systems
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
The VLDB Journal — The International Journal on Very Large Data Bases
Punctuated data streams
Sliding window query processing over data streams
Sliding window query processing over data streams
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In this paper, we analyze how stream monotonicity classification can be adopted for the introduced developed model, which processes both temporal and negative events. As we show, information about stream monotonicity can be easily used to optimize individual stream operators as well as a full query plan. Comparing our stream engine with such engines as CEDR, STREAM and PIPES we demonstrate how a primary key constraint can be used in different types of the developed stream schemes. We implemented all of the above techniques in StreamAPAS.