162 citations · 186 across the 4 of their papers we have counts for
5 papers
Teach Your DBMS to LIKE Strings: Fast and General Pattern Matching for Wildcard Joins and Filters
Lam-Duy Nguyen, Pascal Ginter, Duc-Tam Nguyen +2
Nowadays, modern applications do more than just store text -- they need to derive meaningful insights from it. To do that, they usually rely on wildcard queries with LIKE predicate…
On the Impact of Memory Allocation on High-Performance Query Processing
Dominik Durner, Viktor Leis, Thomas Neumann
Somewhat surprisingly, the behavior of analytical query engines is crucially affected by the dynamic memory allocator used. Memory allocators highly influence performance, scalabil…
Estimating Cardinalities with Deep Sketches
Andreas Kipf, Dimitri Vorona, Jonas Müller +6
We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries. Deep Sketches are powered by a new deep learning approa…
Persistent Memory I/O Primitives
Alexander van Renen, Lukas Vogel, Viktor Leis +2
I/O latency and throughput is one of the major performance bottlenecks for disk-based database systems. Upcoming persistent memory (PMem) technologies, like Intel's Optane DC Persi…
Learned Cardinalities: Estimating Correlated Joins with Deep Learning
Andreas Kipf, Thomas Kipf, Bernhard Radke +3
We describe a new deep learning approach to cardinality estimation. MSCN is a multi-set convolutional network, tailored to representing relational query plans, that employs set sem…