The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Mar. 04, 2025
Filed:
Aug. 11, 2020
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Konstantinos Karanasos, San Francisco, CA (US);
Matteo Interlandi, Seattle, WA (US);
Fotios Psallidas, Bellevue, WA (US);
Rathijit Sen, Madison, WI (US);
Kwanghyun Park, Hudson, OH (US);
Ivan Popivanov, Redmond, WA (US);
Subramaniam Venkatraman Krishnan, Santa Clara, CA (US);
Markus Weimer, Kirkland, WA (US);
Yuan Yu, Cupertino, CA (US);
Raghunath Ramakrishnan, Bellevue, WA (US);
Carlo Aldo Curino, Woodinville, WA (US);
Doris Suiyi Xin, Berkeley, CA (US);
Karla Jean Saur, Seattle, WA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
The description relates to executing an inference query relative to a database management system, such as a relational database management system. In one example a trained machine learning model can be stored within the database management system. An inference query can be received that applies the trained machine learning model on data local to the database management system. Analysis can be performed on the inference query and the trained machine learning model to generate a unified intermediate representation of the inference query and the trained model. Cross optimization can be performed on the unified intermediate representation. Based upon the cross-optimization, a first portion of the unified intermediate representation to be executed by a database engine of the database management system can be determined, and, a second portion of the unified intermediate representation to be executed by a machine learning runtime can be determined.