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.
The case for learned index structures
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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.