Streaming Queries over Streaming Data

By Sirish Chandrasekaran, M. Franklin. Very Large Data Bases Conference, 2002

314 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b60a9e97a889a5056a362c5e3f4999dbb15fcb57

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In Signal Processing

Citations in the corpus

SINA: scalable incremental processing of continuous queries in spatio-temporal databases (2004, background): “Similar ideas of shared execution have been exploited in the NiagaraCQ [7] for web queries, PSoup [6], and [12] for streaming queries.”
SEA-CNN: scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases (2005, methodology): “, in NiagaraCQ [7] for web queries, in PSoup [5, 6] for streaming queries, and in SINA [19] for continuous spatio-temporal range queries.”
Approximate join processing over data streams (2003, background): “Adaptive query processing systems like Telegraph [18], NiagaraCQ [9], sensor database systems [5] and adaptive techniques as proposed in [7, 20, 24] aim at providing the best possible query performance in continuously changing environments like the Internet.”
Query Processing, Approximation, and Resource Management in a Data Stream Management System (2003, background): “In fact, several proposals for stream query languages automatically introduce windows in all joins, sometimes referred to as band joins , in order to bound the resource requirement, e.g., [5, 7, 12, 13, 20].”
Flux: an adaptive partitioning operator for continuous query systems (2003, background): “PSoup [6] extends CACQ to accommodate disconnected operation.”
Issues in data stream management (2003, methodology): “Two approaches have been proposed to execute similar continuous queries together: sharing query plans [17] and indexing query predicates [13, 52].”
Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams (2003, background): “TelegraphCQ [8] is a proposed extension of earlier efforts into adaptive query processing [4, 9, 21], where query plans are re-ordered throughout the lifetime of a continuous query in response to changes in the execution environment (e.”