Join us for a talk by Professor Wolfgang Lehner, a leader in database technology and systems architecture at TU Dresden. As the head of the Database Technology Group, Prof. Lehner will present insights from his team’s work on improving query optimizers. He will discuss TONIC, a new approach to cardinality estimation-free query optimization, and FASTgres, a context-aware strategy for hint set prediction, both of which have shown promising performance improvements. Do not miss this opportunity to hear from an expert in the field.

Title: On Optimizing the Optimizer

Time: 03/19(Wed) 13:00-14:00 (UTC00:00)London

Speaker: Prof. Wolfgang Lehner

Location: 2SS 5F-Meeting Room 1 (14 pax)

External: https://app.huawei.com/wmeeting/join/97284648/RkY0TJkd6WSgy8VlqDebOsp1wK5jjTkmZ

Meeting ID: 97284648

Passcode: 223007

Registration: https://www.smartsurvey.co.uk/s/3N8U7J/

Abstract:

The traditional cost-based query optimizer approach enumerates different execution plans for each individual query, assesses each plan with costs, and selects the plan that promises the lowest costs for execution. However, – as we all know – the optimal execution plan is not always selected. To steer the optimizer in the right direction, many database systems provide optimizer hints. These hints can be set for workloads, individual queries or even for query fragments.

Within this talk, we first show the potential of optimizer hinting by presenting the results of a comprehensive and in-depth evaluation using three benchmarks and two different versions of the open-source database system PostgreSQL. Subsequently, we highlight that query optimizer hinting is a nontrivial challenge and show two potential solutions: On the one hand, we propose TONIC, a novel cardinality estimation-free extension for generic SPJ query optimizers. TONIC follows a learning-based approach and revises operator decisions for arbitrary join paths based on learned query feedback. To continuously capture and reuse optimal operator selections, we introduce a lightweight yet powerful Query Execution Plan Synopsis (QEP-S). On the other hand, we provide insights into FASTgres, a context-aware classification strategy for a more holistic hint set prediction. Both strategies show in the context of end-to-end evaluations significant reductions of benchmark runtimes.

Bio: 

Wolfgang Lehner is professor at TU Dresden, leading the database technology group as well as the institute of systems architecture. He is mostly interested in cross-cutting data management themes from complex analytical tasks and workflows to technologies pushing the envelope in compile and runtime of a data system. He serves the international database community in many ways (e.g. VLDB Endowment, PVLDB Management Editor, PC-CoChair/MetaReviewer/Reviewer activities). He is an appointed member of the German Council for the Sciences and Humanities as well as a member of the Academy of Europe. In this talk, he presents some of the research he and his research team has been conducting regarding optimizing the optimizer.

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