Search Results for author: Andreas Kipf

Found 8 papers, 5 papers with code

LSI: A Learned Secondary Index Structure

1 code implementation11 May 2022 Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska

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

no code implementations29 Nov 2021 Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska

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

1 code implementation11 Aug 2021 Mihail Stoian, Andreas Kipf, Ryan Marcus, Tim Kraska

Latest research proposes to replace existing index structures with learned models.

The Case for Learned Spatial Indexes

no code implementations24 Aug 2020 Varun Pandey, Alexander van Renen, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Alfons Kemper

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

no code implementations30 Apr 2020 Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann

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

1 code implementation29 Nov 2019 Andreas Kipf, Ryan Marcus, Alexander van Renen, Mihail Stoian, Alfons Kemper, Tim Kraska, Thomas Neumann

A groundswell of recent work has focused on improving data management systems with learned components.

Benchmarking Management

Estimating Cardinalities with Deep Sketches

1 code implementation17 Apr 2019 Andreas Kipf, Dimitri Vorona, Jonas Müller, Thomas Kipf, Bernhard Radke, Viktor Leis, Peter Boncz, Thomas Neumann, Alfons Kemper

We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries.

Databases

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