# Index Selection for NoSQL Database with Deep Reinforcement Learning

arXiv: https://arxiv.org/abs/2006.08842 · HTML: https://mlsanity.com/paper/2006.08842/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [AutoIndexer: A Reinforcement Learning-Enhanced Index Advisor Towards Scaling Workloads](https://mlsanity.com/paper/2507.23084/) (2025)

## Abstract (arXiv)

We propose a new approach of NoSQL database index selection. For different workloads, we select different indexes and their different parameters to optimize the database performance. The approach builds a deep reinforcement learning model to select an optimal index for a given fixed workload and adapts to a changing workload. Experimental results show that, Deep Reinforcement Learning Index Selection Approach (DRLISA) has improved performance to varying degrees according to traditional single index structures.