Demonstrating DB-BERT: A Database Tuning Tool that "Reads" the Manual
Immanuel Trummer · Proceedings of the 2022 International Conference on Management of Data · 2022
DB-BERT is a database tuning tool that mines tuning hints from text documents, including the database manual. DB-BERT uses mined hints as a starting point for an iterative tuning approach, guided via reinforcement learning. This demonstration enables visitors to try out DB-BERT for tuning different database management systems, including Postgres and MySQL, on benchmarks such as TPC-C and TPC-H. Visitors can vary the input text to observe how mined hints influence DB-BERT's behavior. The demonstration interface allows tracing back configurations selected for trial runs to the text passages that motivated them. Finally, visitors may try to beat configurations proposed by DB-BERT with their own parameter settings. The code for this demo is publicly available at https://itrummer.github.io/dbbert/.