One Model to Rule them All: Towards Zero-Shot Learning for Databases

• URL: http://arxiv.org/abs/2105.00642v1
• Date: Mon, 3 May 2021 06:18:47 GMT
• Title: One Model to Rule them All: Towards Zero-Shot Learning for Databases
• Authors: Benjamin Hilprecht and Carsten Binnig
• Abstract summary: Zero-shot learning for databases is a new learning approach for database components. We show the feasibility of zero-shot learning for the task of physical cost estimation. We discuss the core challenges related to zero-shot learning for databases and present a roadmap to extend zero-shot learning.
• Score: 18.46293613612346
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, we present our vision of so called zero-shot learning for databases which is a new learning approach for database components. Zero-shot learning for databases is inspired by recent advances in transfer learning of models such as GPT-3 and can support a new database out-of-the box without the need to train a new model. As a first concrete contribution in this paper, we show the feasibility of zero-shot learning for the task of physical cost estimation and present very promising initial results. Moreover, as a second contribution we discuss the core challenges related to zero-shot learning for databases and present a roadmap to extend zero-shot learning towards many other tasks beyond cost estimation or even beyond classical database systems and workloads.

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