BriskStream: Scaling Data Stream Processing on Shared-Memory Multicore Architectures
April 07, 2019 ยท Declared Dead ยท ๐ SIGMOD Conference
"No code URL or promise found in abstract"
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Authors
Shuhao Zhang, Jiong He, Amelie Chi Zhou, Bingsheng He
arXiv ID
1904.03604
Category
cs.DB: Databases
Citations
51
Venue
SIGMOD Conference
Last Checked
3 months ago
Abstract
We introduce BriskStream, an in-memory data stream processing system (DSPSs) specifically designed for modern shared-memory multicore architectures. BriskStream's key contribution is an execution plan optimization paradigm, namely RLAS, which takes relative-location (i.e., NUMA distance) of each pair of producer-consumer operators into consideration. We propose a branch and bound based approach with three heuristics to resolve the resulting nontrivial optimization problem. The experimental evaluations demonstrate that BriskStream yields much higher throughput and better scalability than existing DSPSs on multi-core architectures when processing different types of workloads.
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