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Found 9 papers, 6 papers with code
Lightweight Correlation-Aware Table Compression
The growing adoption of data lakes for managing relational data necessitates efficient, open storage formats that provide high scan performance and competitive compression ratios.
LSI: A Learned Secondary Index Structure
LSI works by building a learned index over a permutation vector, which allows binary search to performed on the unsorted base data using random access.
Bounding the Last Mile: Efficient Learned String Indexing
RSS achieves this by using the minimal string prefix to sufficiently distinguish the data unlike most learned approaches which index the entire string.
Towards Practical Learned Indexing
Latest research proposes to replace existing index structures with learned models.
The Case for Learned Spatial Indexes
This exponential growth in spatial data has led the research community to focus on building systems and applications that can process spatial data efficiently.
RadixSpline: A Single-Pass Learned Index
Recent research has shown that learned models can outperform state-of-the-art index structures in size and lookup performance.
SOSD: A Benchmark for Learned Indexes
A groundswell of recent work has focused on improving data management systems with learned components.
Estimating Cardinalities with Deep Sketches
We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries.
Databases
Learned Cardinalities: Estimating Correlated Joins with Deep Learning
We describe a new deep learning approach to cardinality estimation.
Databases
