Estimating Cardinalities with Deep Sketches [article]

Andreas Kipf, Dimitri Vorona, Jonas Müller, Thomas Kipf, Bernhard Radke, Viktor Leis, Peter Boncz, Thomas Neumann, Alfons Kemper
2019 arXiv   pre-print
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 approach to cardinality estimation that can capture correlations between columns, even across tables. Our demonstration allows users to define such sketches on the TPC-H and IMDb datasets, monitor the training process, and run ad-hoc queries against trained sketches. We also estimate query cardinalities with HyPer and
more » ... eSQL to visualize the gains over traditional cardinality estimators.
arXiv:1904.08223v1 fatcat:7wkwfw4l2jcwrgyedsptsqj2ki