In this talk, Vasiliki Kalavri will give an overview of Apache Flink's Graph processing API, Gelly. Flink's iterative operators and other unique features make it a competitive alternative for large-scale graph processing. Graph analysis tasks can elegantly be expressed using common Flink operators, and different graph processing models, like vertex-centric and gather-sum-apply, can easily be mapped to Flink dataflows. Using Gelly, you can perform loading, transformation, filtering, graph creation and analysis, with a single program.
She will also share her recent work with KTH, Stockholm, on supporting single-pass graph streaming analytics on Apache Flink. She will introduce gelly-stream, a protoype that allows computing graph statistics, aggregates, sketches, as well as more complex algorithms, like connected components on streams of edges.
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Apache Flink's Graph processing API, Gelly (part 1)
Vasia Kalavri is a PhD candidate and a fellow of the Erasmus Mundus Joint Doctorate in Distributed Computing. Vasia's research focuses on distributed data processing, systems optimization, and large-scale graph analysis. She is a PMC member of Apache Flink and a core developer of its graph processing API, Gelly. Vasia has a MSc in Distributed Computing from KTH, Stockholm and UPC, Barcelona, and a diploma in Electrical and Computer Engineering from NTUA, Athens. During her PhD studies, she has been a visiting researcher at the Technical University of Berlin and she has interned at Telefonica Research and data Artisans.