The case for NLP-enhanced database tuning

Volume: 14, Issue: 7, Pages: 1159 - 1165
Published: Mar 1, 2021
Abstract
A large body of knowledge on database tuning is available in the form of natural language text. We propose to leverage natural language processing (NLP) to make that knowledge accessible to automated tuning tools. We describe multiple avenues to exploit NLP for database tuning, and outline associated challenges and opportunities. As a proof of concept, we describe a simple prototype system that exploits recent NLP advances to mine tuning hints...
Paper Details
Title
The case for NLP-enhanced database tuning
Published Date
Mar 1, 2021
Volume
14
Issue
7
Pages
1159 - 1165
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