Invention Publication
- Patent Title: DATABASE GROUP-BY QUERY CARDINALITY ESTIMATION
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Application No.: US17979643Application Date: 2022-11-02
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Publication No.: US20240143586A1Publication Date: 2024-05-02
- Inventor: Kang Woo Choi , Daeun Lee , Dong Hun Lee
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Main IPC: G06F16/2453
- IPC: G06F16/2453

Abstract:
Mechanisms are disclosed for estimating cardinality of group-by queries. A probability of occurrence of values is obtained for columns that satisfy the query occurring in tables from a trained machine learning model. A range selectivity is calculated based on a conditional probability of occurrence of the values. A set of valid generated sample tuples is generated from the trained machine learning model. A group-by selectivity is calculated by keeping the conditional probability of occurrence to obtain probabilities that a result set will have specific group-by column values associated with the tables while proceeding with progressive sampling. A sampling probability is calculated by normalizing the group-by selectivity by dividing the group-by selectivity by the range selectivity. The samples are filtered such that the samples having a sampling probability below a sampling probability threshold are filtered out. A sampling-based estimator is applied to the filtered samples set to estimate the cardinality.
Public/Granted literature
- US12045233B2 Database group-by query cardinality estimation Public/Granted day:2024-07-23
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