Flux: An Adaptive Partitioning Operator for Continuous Query Systems (2002)
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| Venue: | In ICDE |
| Citations: | 99 - 5 self |
BibTeX
@INPROCEEDINGS{Shah02flux:an,
author = {Mehul A. Shah and Mehul A. Shah and Sirish Chandrasekaran and Joseph M. Hellerstein and Joseph M. Hellerstein and Sirish Ch and Sirish Ch and Michael J. Franklin and Michael J. Franklin},
title = {Flux: An Adaptive Partitioning Operator for Continuous Query Systems},
booktitle = {In ICDE},
year = {2002},
pages = {25--36}
}
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Abstract
The long-running nature of continuous queries poses new scalability challenges for dataflow processing. CQ systems execute pipelined dataflows that may be shared across multiple queries. The scalability of these dataflows is limited by their constituent, stateful operators -- e.g. windowed joins or grouping operators. To scale such operators, a natural solution is to partition them across a shared-nothing platform. But in the CQ context, traditional, static techniques for partitioned parallelism can exhibit detrimental imbalances as workload and runtime conditions evolve. Longrunning CQ dataflows must continue to function robustly in the face of these imbalances.
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