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.
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Thomas Neumann is a full professor in the Department of Computer Science
at the Technical University of Munich. After his PhD in Computer Science
at the University of Mannheim in 2005, he was Senior Researcher at the
Max-Planck Institute for Informatics in Saarbrücken until 2010. His
research interests are in the areas of database systems, query
processing, and query optimization. In 2020, he received the Gottfried
Wilhelm Leibniz Prize.