A team consisting of CSE professor Vassilis Tsotras and student Christina Pavlopoulou, together with Prof. Michael J. Carey from UCI has received best paper runner-up at EDBT.

The paper is titled "Revisiting Runtime Dynamic Optimization for Join Queries in Big Data Management Systems".

This paper considers an old problem and an early solution within a very modern context. The topic of optimizing declarative queries has been studied since the early years of relational database systems. One approach that was proposed very early is runtime dynamic optimization, although most commercial systems display a preference for static cost-based optimization. This paper revives the idea of dynamic runtime query optimization within the context of a shared-nothing distributed big data system. The proposal eliminates the negative impact of errors in estimates in cost-based optimizers, which are exacerbated in big data systems due to the increased data size. It borrows ideas from cost-based optimizers by collecting statistics during materialization to assist in dynamic join order selection. The proposed approach is implemented within AsterixDB and demonstrates superior performance.

https://conferences.inf.ed.ac.uk/edbticdt2022/?contents=awards_bp_edbt.html