Neighborhood based fast graph search in large networks
Arijit Khan, Nan Li, et al.
SIGMOD 2011
In spite of the omnipresence of parallel (multi-core) systems, the predominant strategy to evaluate window-based stream joins is still strictly sequential, mostly just straightforward along the definition of the operation semantics. In this work we present handshake join, a way of describing and executing window-based stream joins that is highly amenable to parallelized execution. Handshake join naturally leverages available hardware parallelism, which we demonstrate with an implementation on a modern multi-core system and on top of field-programmable gate arrays (FPGAs), an emerging technology that has shown distinctive advantages for high-throughput data processing. On the practical side, we provide a join implementation that substantially outperforms CellJoin (the fastest published result) and that will directly turn any degree of parallelism into higher throughput or larger supported window sizes. On the semantic side, our work gives a new intuition of window semantics, which we believe could inspire other stream processing algorithms or ongoing standardization efforts for stream query languages. © 2011 ACM.
Arijit Khan, Nan Li, et al.
SIGMOD 2011
Tim Kaldewey, Guy Lohman, et al.
DaMoN 2012
Ioannis Koltsidas, Stratis D. Viglas
SIGMOD 2011
Ronald Barber, Christian Garcia-Arellano, et al.
CIDR 2017