US 12,222,938 B1
Systems and methods for query optimization
Mohamed Seck, Aubrey, TX (US); Pavlo Savchuk, Dublin, CA (US); Nikitha Kondapally, Frisco, TX (US); Chris Gallucci, Plano, TX (US); Prerna Kandhari, McKinney, TX (US); and Anand Annamalai, Glen Allen, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Dec. 22, 2023, as Appl. No. 18/394,493.
Int. Cl. G06F 16/00 (2019.01); G06F 11/34 (2006.01); G06F 16/242 (2019.01); G06F 16/2453 (2019.01); G06F 16/2455 (2019.01)
CPC G06F 16/24534 (2019.01) [G06F 11/3409 (2013.01); G06F 16/243 (2019.01); G06F 16/2455 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
capturing, by one or more processors, a proposed database query input into a user interface;
providing, by the one or more processors, the proposed database query to a machine-learning model, wherein the machine-learning model has been trained, using one or more gathered and/or simulated sets of query execution overhead data and one or more gathered and/or simulated sets of database queries, to determine a potential execution overhead of a database query and output a query execution score;
outputting, by the machine-learning model, the query execution score based on the proposed database query;
determining, by the one or more processors, that the query execution score exceeds a query execution score threshold; and
triggering, by the one or more processors, a corrective action based on the query execution score exceeding the query execution score threshold.