{"ID":2878538,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.17931","arxiv_id":"2508.17931","title":"Join Cardinality Estimation with OmniSketches","abstract":"Join ordering is a key factor in query performance, yet traditional cost-based optimizers often produce sub-optimal plans due to inaccurate cardinality estimates in multi-predicate, multi-join queries. Existing alternatives such as learning-based optimizers and adaptive query processing improve accuracy but can suffer from high training costs, poor generalization, or integration challenges. We present an extension of OmniSketch - a probabilistic data structure combining count-min sketches and K-minwise hashing - to enable multi-join cardinality estimation without assuming uniformity and independence. Our approach introduces the OmniSketch join estimator, ensures sketch interoperability across tables, and provides an algorithm to process alpha-acyclic join graphs. Our experiments on SSB-skew and JOB-light show that OmniSketch-enhanced cost-based optimization can improve estimation accuracy and plan quality compared to DuckDB. For SSB-skew, we show intermediate result decreases up to 1,077x and execution time decreases up to 3.19x. For JOB-light, OmniSketch join cardinality estimation shows occasional individual improvements but largely suffers from a loss of witnesses due to unfavorable join graph shapes and large numbers of unique values in foreign key columns.","short_abstract":"Join ordering is a key factor in query performance, yet traditional cost-based optimizers often produce sub-optimal plans due to inaccurate cardinality estimates in multi-predicate, multi-join queries. Existing alternatives such as learning-based optimizers and adaptive query processing improve accuracy but can suffer...","url_abs":"https://arxiv.org/abs/2508.17931","url_pdf":"https://arxiv.org/pdf/2508.17931v1","authors":"[\"David Justen\",\"Matthias Boehm\"]","published":"2025-08-25T12:00:12Z","proceeding":"cs.DB","tasks":"[\"cs.DB\"]","methods":"[]","has_code":false}