US 12,314,260 B2
Recommendations for changes in database query performance
Sheng Yan Sun, Beijing (CN); Peng Hui Jiang, Beijing (CN); Xiao Feng Meng, Beijing (CN); Xu Qin Zhao, Beijing (CN); and Ye Tao, Beijing (CN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Oct. 4, 2023, as Appl. No. 18/376,489.
Prior Publication US 2025/0117383 A1, Apr. 10, 2025
Int. Cl. G06F 16/24 (2019.01); G06F 16/242 (2019.01); G06F 16/2453 (2019.01)
CPC G06F 16/24542 (2019.01) [G06F 16/2423 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method, comprising:
analyzing, by a processor set, an incoming query for a database;
training, by the processor set, a query model using machine learning based on the analyzing the incoming query;
determining, by the processor set, a model result based on the trained query model;
extracting, by the processor set, a similar information query based on the model result;
generating, by the processor set, a recommendation for query tuning and a visual impact of the recommendation for the query tuning based on the extracting of the similar information query; and
outputting, by the processor set, the recommendation for the query tuning and the visual impact of the recommendation for the query tuning,
wherein the visual impact comprises a graphical user interface (GUI) which includes an index scan, an index name, and a part in a data path of the incoming query and a new index and another index scan of the recommendation for the query.