176 citations · 382 across the 20 of their papers we have counts for
20 papers · 1 filter
Towards Practical Learned Indexing
Mihail Stoian, Andreas Kipf, Ryan Marcus +1
Latest research proposes to replace existing index structures with learned models. However, current learned indexes tend to have many hyperparameters, often do not provide any erro…
When Are Learned Models Better Than Hash Functions?
Ibrahim Sabek, Kapil Vaidya, Dominik Horn +2
In this work, we aim to study when learned models are better hash functions, particular for hash-maps. We use lightweight piece-wise linear models to replace the hash functions as…
LEA: A Learned Encoding Advisor for Column Stores
Lujing Cen, Andreas Kipf, Ryan Marcus +1
Data warehouses organize data in a columnar format to enable faster scans and better compression. Modern systems offer a variety of column encodings that can reduce storage footpri…
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…
Learned Indexes for a Google-scale Disk-based Database
Hussam Abu-Libdeh, Deniz Altınbüken, Alex Beutel +7
There is great excitement about learned index structures, but understandable skepticism about the practicality of a new method uprooting decades of research on B-Trees. In this pap…
Cortex: Harnessing Correlations to Boost Query Performance
Vikram Nathan, Jialin Ding, Tim Kraska +1
Databases employ indexes to filter out irrelevant records, which reduces scan overhead and speeds up query execution. However, this optimization is only available to queries that f…