SIGMOD Santiago, Chile, 2024
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PODS 2024: Gems of PODS

Recent Increments in Incremental View Maintenance

Speaker: Dan Olteanu (University of Zurich)

Abstract

This talk overviews recent progress on the longstanding problem of incremental view maintenance (IVM), with a focus on the fine-grained complexity and optimality of IVM for classes of conjunctive queries. This theoretical progress guided the development of IVM engines that reported practical benefits in both academic papers and industrial settings. When taken in isolation, each of the reported advancements is but a small increment. Yet when taken together, these advancements may well pave the way to a deeper understanding of the IVM problem.

Bio

Dan Olteanu is a professor at the University of Zurich, where he leads the Data Systems and Theory group, and a computer scientist at RelationalAI, where he currently works on incremental view maintenance, cardinality estimation, and data science projects. He currently serves as chair of the ICDT council and as associate editor for TODS and VLDB Journal. He previously served as associate editor for PVLDB and the SIGMOD Record database principles column, as PC vice-chair for SIGMOD, and as PC chair for ICDT. He co-authored the book "Probabilistic Databases" (2011). He is the recipient of the ICDT 2022 Test of Time award for factorised databases, the ICDT 2019 best paper award for optimal maintenance of counting triangles in a graph, a PVLDB distinguished associate editor award, a SIGMOD distinguished PC member award, an ERC consolidator grant, a Google research faculty award, and an Oxford outstanding teaching award. Half a dozen of his works on in-database machine learning, maintenance for queries and analytics, and declarative probabilistic programming were invited to the special issues of the TODS and LMCS journals with the best papers at the ICDT and PODS conferences. More than a dozen of his BSc and MSc students received the prizes for the best thesis or best overall performance. His PhD student Max Schleich received an honorable mention to the 2021 SIGMOD Jim Gray doctoral dissertation award.

Credits
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