Please note: This PhD seminar will be given online.
Anil Pacaci, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Tamer Özsu
Modern applications in many domains now operate on high-speed streaming graphs that continuously evolve at high rates. Efficient querying of these streaming graphs is a crucial task for applications that monitor complex patterns and relationships.
This talk will present our recent work on continuous query evaluation over streaming graphs within the context of the s-Graffito project. First, I will outline the common characteristics of applications that query and process streaming graphs and describe the requirements for a general-purpose streaming graph query processing framework. Next, I will introduce a streaming graph model and algebra that describes the precise semantics of persistent graph queries. Our Streaming Graph Algebra (SGA) constitutes the logical foundation for evaluation, planning and optimization of streaming graph queries. Finally, I will present our prototype implementation of a streaming graph query processor based on the proposed SGA. In particular, I will describe efficient physical implementations of SGA operators that utilize the temporal patterns of sliding window movements over streaming graphs. Our prototype implementation compiles streaming graph queries into dataflow computations consisting of SGA operators and demonstrates the feasibility and the performance of our algebraic approach for persistent query processing over streaming graphs.
To join this PhD seminar on Zoom, please go to https://us02web.zoom.us/j/83326411204?pwd=Z3dNVUxIK01PMXY3MTlXaHNVckJqdz09.
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