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US Patent 11921719 Automated query selectivity predictions using query graphs

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Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
0
Patent Number
119217190
Patent Inventor Names
Vincent Corvinelli0
Calisto Zuzarte0
Mohammed Fahd Alhamid0
Date of Patent
March 5, 2024
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Patent Application Number
179319630
Date Filed
September 14, 2022
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Patent Citations
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US Patent 10942923 Deep learning for optimizer cardinality estimation
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US Patent 11030521 Estimating cardinality selectivity utilizing artificial neural networks
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US Patent 11416487 Data-driven checkpoint selector
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US Patent 11755576 Data-driven task-execution scheduling using machine learning
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US Patent 11625398 Join cardinality estimation using machine learning and graph kernels
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US Patent 11853301 Sharing compiled code for executing queries across query engines
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US Patent 10303688 System and method for reducing data retrieval delays via prediction-based generation of data subgraphs
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US Patent 10643132 Cardinality estimation using artificial neural networks
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Patent Primary Examiner
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Merilyn P Nguyen
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CPC Code
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G06F 16/2246
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Patent abstract

Examples described herein provide a computer-implemented method that includes training a machine learning model. The model is trained by generating a set of training queries using at least one of a query workload and relationships between tables in a database, building a query graph for each of the set of training queries, computing, for each training query of the set of training queries, a selectivity based at least in part on the query graph, and building, based at least in part on the set of training queries, an initial join result distribution as a collection of query graphs.

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