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2008
ACM

Near-optimal algorithms for shared filter evaluation in data stream systems

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Near-optimal algorithms for shared filter evaluation in data stream systems
We consider the problem of evaluating multiple overlapping queries defined on data streams, where each query is a conjunction of multiple filters and each filter may be shared across multiple queries. Efficient support for overlapping queries is a critical issue in the emerging data stream systems, and this is particularly the case when filters are expensive in terms of their computational complexity and processing time. This problem generalizes other well-known problems such as pipelined filter ordering and set cover, and is not only NP-Hard but also hard to approximate within a factor of o(log n) from the optimum, where n is the number of queries. In this paper, we present two near-optimal approximation algorithms with provably-good performance guarantees for the evaluation of overlapping queries. We present an edge-coverage based Greedy algorithm which achieves an approximation ratio of (1 + log(n) + log()), where n is the number of queries and is the average number of filters in ...
Zhen Liu, Srinivasan Parthasarathy 0002, Anand Ran
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2008
Where SIGMOD
Authors Zhen Liu, Srinivasan Parthasarathy 0002, Anand Ranganathan, Hao Yang
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