Model Reuse in Learned Spatial Indexes
Mayur S. Patil, Chinya V. Ravishankar · 2024
Learned database indexes use machine learning algorithms to directly predict the location of a query key within a sorted key array, thereby eliminating index search overhead. Prior work shows learned indexes outperforming traditional indexes in both space and query time for one-dimensional data, especially for read-intensive workloads. Usually, learned indexes linearize the multi-dimensional data with a space-filling curve before generating the index.