Adaptive Join Order Optimization Using Search Space Linearization
Abstract:
Join ordering is one of the core problems of query optimization, as differences in join order can affect the execution time of queries by orders of magnitudes. Unfortunately the problem is NP hard in general, and real world queries can join hundreds of relations, which makes exact solutions prohibitive expensive. In this talk we show how to tackle the join ordering problem by using a search space linearization technique.
This adaptive optimization mechanism allows for a smooth transition from guaranteed optimality to a more greedy approach, depending on the size of problem. In practice, a surprisingly large number of queries can be solved optimally or near optimally, with very low optimization times even for hundreds of relations.
Shortbio:
Thomas Neumann is Professor for Database Systems at TUM School of Computation, Information and Technology. He conducts research on database systems, focusing on query optimization (computing efficient query strategies) and query processing (efficient query execution).
Thomas Neumann studied business information systems at the University of Mannheim and received a doctorate in informatics from the same university in 2005. Before joining TUM (2010), he was a senior researcher at the Max Planck Institute for Informatics in Saarbrücken. He acquired his postdoctoral teaching qualification (habilitation) in informatics from Saarland University (2010).
external page https://db.in.tum.de/~neumann/call_made