View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Exploiting Punctuation Semantics in Continuous Data Streams
IEEE Transactions on Knowledge and Data Engineering
Practical Lineage Tracing in Data Warehouses
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Gigascope: a stream database for network applications
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
Dynamic Load Distribution in the Borealis Stream Processor
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Flexible time management in data stream systems
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A heartbeat mechanism and its application in gigascope
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A Pipelined Framework for Online Cleaning of Sensor Data Streams
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Safety guarantee of continuous join queries over punctuated data streams
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A deferred cleansing method for RFID data analytics
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Frequent itemset mining of uncertain data streams using the damped window model
Proceedings of the 2011 ACM Symposium on Applied Computing
Frequent pattern mining from time-fading streams of uncertain data
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
A landmark-model based system for mining frequent patterns from uncertain data streams
Proceedings of the 15th Symposium on International Database Engineering & Applications
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Continuous queries enable alerts, predictions, and early warning in various domains such as health care, business process monitoring, financial applications, and environment protection. Currently, the consistency of the result cannot be assessed by the application, since only the query processor has enough internal information to determine when the output has reached a consistent state. To our knowledge, this is the first paper that addresses the problem of consistency under the assumptions and constraints of a continuous query model. In addition to defining an appropriate consistency notion, we propose techniques for guaranteeing consistency. We implemented the proposed techniques in our existing stream engine, and we report on the characteristics of the observed performance. As we show, these methods are practical as they impose only a small overhead on the system.