Vasiliki Kalavri gives a tutorial at BICOD in London

Vasiliki Kalavri gave the invited tutorial "Programming Models and Tools for Distributed Graph Processing" at the 31st British International Conference on Databases (BICOD) in London.


Graphs capture relationships between data items, such as interactions or dependencies, and their analysis can reveal valuable insights for machine learning tasks, anomaly detection, clustering, recommendations, social influence analysis, bioinformatics, and other application domains. This tutorial reviews the state of the art in high-level abstractions for distributed graph processing. First, we present six models that were developed specifically for distributed graph processing, namely vertex-centric, scatter-gather, gather-sum-apply-scatter, subgraph-centric, filter-process, and graph traversals. Then, we consider general-purpose distributed programming models that have been used for graph analysis, such as MapReduce, dataflow, linear algebra primitives, datalog, and shared partitioned tables. The tutorial aims at making a qualitative comparison of popular graph programming abstractions. We further consider performance limitations of some graph programming models and we summarize proposed extensions and optimizations.