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.

Date of Patent:
Jul. 27, 2021

Filed:

Jun. 08, 2018
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Alekh Jindal, Kirkland, WA (US);

Hiren Patel, Bothell, WA (US);

Saeed Amizadeh, Seattle, WA (US);

Chenggang Wu, Berkeley, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/2453 (2019.01); G06N 3/08 (2006.01); G06N 5/00 (2006.01); G06N 5/02 (2006.01);
U.S. Cl.
CPC ...
G06F 16/24534 (2019.01); G06F 16/24545 (2019.01); G06N 3/08 (2013.01); G06N 5/003 (2013.01); G06N 5/022 (2013.01);
Abstract

Described herein is a system and method for training cardinality models in which workload data is analyzed to extract and compute features of subgraphs of queries. Using a machine learning algorithm, the cardinality models are trained based on the features and actual runtime statistics included in the workload data. The trained cardinality models are stored. Further described herein is a system and method of predicting cardinality of subgraphs of a query. Features for the subgraphs of the query are extracted and computed. Cardinality models are retrieved based on the features of the subgraphs of the query. Cardinalities of the subgraphs of the query are predicted using the retrieved cardinality models. One of the subgraphs of the query is selected to be utilized for execution of the query based on the predicted cardinalities.


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