LiLIS is a lightweight prototype that combines learned indices with spatial partitioning in distributed frameworks to support point, range, kNN, and join queries with reduced latency and construction cost.
Efficient k nearest neighbor queries on remote spatial databases using range estimation
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LiLIS: A Lightweight Distributed Learned Index Framework for Spatial Decision Analysis
LiLIS is a lightweight prototype that combines learned indices with spatial partitioning in distributed frameworks to support point, range, kNN, and join queries with reduced latency and construction cost.