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| Category | Value | ||
| Available via | http://dbpubs.stanford.edu/pub/2003-8 | ||
| Previous version | 2002-55 | ||
| Submitted on | 13th of February 2003 | ||
| Author | Olston, Chris; Jiang, Jing; Widom, Jennifer | ||
| Title | Adaptive Filters for Continuous Queries over Distributed Data Streams | ||
| Date of publication | June 2003 | ||
| Published in | Proceedings of the ACM SIGMOD 2003 International Conference on Management of Data | ||
| Citation | Olston, Chris; Jiang, Jing; Widom, Jennifer. Adaptive Filters for Continuous Queries over Distributed Data Streams, Proceedings of the ACM SIGMOD 2003 International Conference on Management of Data | ||
| Number of pages | 12 | ||
| Language | English | ||
| Project | STREAM; TRAPP | ||
| Type | Conference or Journal Paper | ||
| Subject group | Data Streams; Distributed Systems | ||
| Abstract | We consider an environment where distributed data sources continuously stream updates to a centralized processor that monitors continuous queries over the distributed data. Significant communication overhead is incurred in the presence of rapid update streams, and we propose a new technique for reducing the overhead. Users register continuous queries with precision requirements at the central stream processor, which installs filters at remote data sources. The filters adapt to changing conditions to minimize stream rates while guaranteeing that all continuous queries still receive the updates necessary to provide answers of adequate precision at all times. Our approach enables applications to trade precision for communication overhead at a fine granularity by individually adjusting the precision constraints of continuous queries over streams in a multi-query workload. Through experiments performed on synthetic data simulations and a real network monitoring implementation, we demonstrate the effectiveness of our approach in achieving low communication overhead compared with alternate approaches. | ||
| Contact address | olston@db.stanford.edu | ||
| Sponsored by | This work was supported by the National Science Foundation under grants IIS-0118173 and IIS-9817799 and by a National Science Foundation graduate research fellowship. | ||
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| Management of the document by | siroker@db.stanford.edu
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