IndexAI: AI Based Index Selection for NoSQL Databases (pre-print version)

Abstract (pre-print)

In the big data era, automated index selection and recommendation has been an important research problem to improve the data access efficiency. Previous efforts on artificial intelligence based database index selection have focused on relational databases. In this work, we consider the automated index selection for NoSQL databases and investigate the feasi- bility of supervised learning and reinforcement learning based solutions. The experiments conducted on the YCSB dataset show that reinforcement learning improves index selection per- formance as in relational databases, and supervised learning gives promising results and can be considered applicable under sufficient amount of training data.

Acknowledgement: This research received the support of EXA4MIND project, funded by a European Union ́s Horizon Europe Re- search and Innovation Programme, under Grant Agreement N° 101092944. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the granting authority can be held responsible for them.