Evaluating window joins over unbounded streams

By Jaewoo Kang, Jeffrey F. Naughton, Stratis Viglas. Proceedings / International Conference on Data Engineering, 2003

418 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Data Streams: Models and Algorithms (Advances in Database Systems) (2006, background): “[9] Aggarwal C. (2006) on Futuristic Query Processing in Data Streams.”
Load shedding for aggregation queries over data streams (2004, methodology): “For this reason, the techniques proposed in [9, 18] are not applicable to our problem setting, where there are no joins between streams and the metric being optimized is the accuracy of approximate answers to aggregate queries.”
Issues in data stream management (2003, background): “The symmetric hash join [69] and an analogous symmetric NLJ may be extended to operate over two [45] or more [38] sliding windows by periodically scanning the hash tables (or whole windows) and removing stale items.”
Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams (2003, background): “[20], who also introduce a per-unit-time cost model for insertion, invalidation, and join processing costs.”