What question did this study set out to answer?

This research aims to enhance cardinality estimation by accounting for correlations between join columns.

April 29, 2026Open Access

CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations

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CorrBound improves cardinality estimation accuracy in multi-join queries, suggesting better management of correlations.

This research aims to enhance cardinality estimation by accounting for correlations between join columns.
Introduced a cardinality estimator called CorrBound.
Utilized a linear program to optimally estimate cardinality.
Developed techniques to address high-dimensionality issues using degree vector sketches and low-rank decomposition.
CorrBound provides more accurate estimates than traditional and machine learning-based estimators.
Maintained low estimation times in evaluation against benchmarks.

Mayer et al. (2026) studied this question.

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April 29, 2026Open Access

View Full Paper

Ask AI

Bookmark

Authors

CorrBound improves cardinality estimation accuracy in multi-join queries, suggesting better management of correlations.

This research aims to enhance cardinality estimation by accounting for correlations between join columns.
Introduced a cardinality estimator called CorrBound.
Utilized a linear program to optimally estimate cardinality.
Developed techniques to address high-dimensionality issues using degree vector sketches and low-rank decomposition.
CorrBound provides more accurate estimates than traditional and machine learning-based estimators.
Maintained low estimation times in evaluation against benchmarks.

Mayer et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark