US 12,353,414 B2
Database query optimization based on analytics
Srikumar Venugopal, Dublin (IE); Alessandro Pomponio, Dublin (IE); Vasileios Vasileiadis, Dublin (IE); and Stefano Braghin, Dublin (IE)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on May 4, 2023, as Appl. No. 18/311,968.
Prior Publication US 2024/0370434 A1, Nov. 7, 2024
Int. Cl. G06F 16/245 (2019.01); G06F 11/34 (2006.01); G06F 16/2453 (2019.01)
CPC G06F 16/24545 (2019.01) [G06F 11/3419 (2013.01); G06F 16/24539 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for providing query management optimization, comprising:
receiving at least a query in a distributed management system having a multiple scale distribution that includes a plurality of execution environments;
analyzing the received query and obtaining any related information associated with the received query;
determining an application specific and/or a location specific distribution of datasets stored within the distributed management system;
dividing the received query into a plurality of subqueries, wherein said plurality of subqueries are performed in different execution environments such that the plurality of subqueries being distributed and run in parallel in the different execution environments;
determining that existing information in a database relating to previously executed queries being similar to the received query;
calculating and measuring effectiveness of query execution using a plurality of optimization techniques including running the plurality of subqueries in parallel executions through the determined application specific and/or location specific distribution of the datasets, and previous information associated with the plurality of subqueries, wherein the plurality of optimization techniques predict and formulate future optimizations of the received query based on a plurality of empirical data derived from any of the existing information in the database and other prior executions recorded relating to previously executed queries in the different execution environments;
formulating a query execution plan for the received query after analyzing the calculated and measured effectiveness using the plurality of optimization techniques, wherein the formulated query execution plan considers the determined application specific and/or location specific distribution of the datasets and includes merging together tasks and data gathered after the run in parallel in the different execution environments; and
executing the formulated query execution plan for the received query within the different execution environments.