Paper Info
Title
Continuously adaptive continuous queries over streams
Abstract
We present a continuously adaptive, continuous query (CACQ) implementation based on the eddy query processing framework. We show that our design provides significant performance benefits over existing approaches to evaluating continuous queries, not only because of its adaptivity, but also because of the aggressive cross-query sharing of work and space that it enables. By breaking the abstraction of shared relational algebra expressions, our Telegraph CACQ implementation is able to share physical operators --- both selections and join state --- at a very fine grain. We augment these features with a grouped-filter index to simultaneously evaluate multiple selection predicates. We include measurements of the performance of our core system, along with a comparison to existing continuous query approaches.
Year
DOI
Venue
2002
10.1145/564691.564698
SIGMOD Conference
Keywords
Field
DocType
aggressive cross-query sharing,significant performance benefit,multiple selection predicate,fine grain,continuous query,telegraph cacq implementation,grouped-filter index,continuous query approach,adaptive continuous query,core system,eddy query processing framework,relation algebra,indexation
Query optimization,Data mining,Web search query,Data stream management system,Query language,Query expansion,Computer science,Sargable,Web query classification,Theoretical computer science,Boolean conjunctive query,Database
Conference
ISBN
Citations 
PageRank 
1-58113-497-5
317
27.21
References 
Authors
29
4
Search Limit
100317
Name
Order
Citations
PageRank
Samuel Madden1161011176.38
Mehul A. Shah23547317.66
Joseph M. Hellerstein3140931651.14
Vijayshankar Raman42325239.92