MultiCard: Multiple Attribute Cardinality Estimation via Deep Learning
Cardinality estimation is essential for query optimization, but most existing learned estimators focus on a single predicate type, such as string LIKE clauses or numerical range filters. In practice, analytical workloads often combine both types, while the accuracy of string estimators tends to decrease with longer patterns. We introduce MultiCard, a comprehensive learned cardinality estimator that unifies LIKE predicates and numerical filters within a single end-to-end architecture. By combining a Transformer for long-range sparse patterns with an LSTM for short, frequent patterns, MultiCard achieves robust pattern modeling. In parallel, a numerical encoder integrates catalog histograms ...
| Authors | Mobina Koochaknia, Maryam Ramezani, Mohammad Hasan Shafaat |
|---|---|
| Primary category | cs.DB |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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